100212 morpeth traffic model forecasting report rev1

Transportation

Northumberland County Council September 2011

Morpeth Traffic Model Forecasting Report

Prepared by: .................... Checked by: Gemma Paget Simon Fradgley Consultant Consultant

Approved by: Stuart McNaughton Principal Consultant Morpeth Traffic Model Forecasting Report

Rev No Comments Checked by Approved by

Date

1 Incorporating DfT queries SF SMcN 10/02/10

2 Best and Final Funding Bid SF SMcN 08/09/11 First Floor, One Trinity Gardens, Quayside, Newcastle upon Tyne, NE1 2HF Telephone: 0191 224 6500 Website: http://www.aecom.com Job No 60036225 Reference Rev01 Date Created September 2011 This document is confidential and the copyright of AECOM Limited. Any unauthorised reproduction or usage by any person other than the addressee is strictly prohibited. f:\projects\53101tnet morpeth northern bypass\dev pool modelling\reports\forecasting report\100212 morpeth traffic model forecasting report rev1.docx

1 Introduction ....................................................................................................................................................................... 1

1.1 Background ........................................................................................................................................................... 1

1.2 Report Structure .................................................................................................................................................... 1

2 Model Background ............................................................................................................................................................ 2

2.1 Modelled Time Periods .......................................................................................................................................... 2

2.2 Vehicle Types and Trip Purposes .......................................................................................................................... 2

2.3 Geographical Extent of Model ............................................................................................................................... 2

2.4 Zoning System ....................................................................................................................................................... 2

2.5 Network Description ............................................................................................................................................... 2

2.6 Model Validation .................................................................................................................................................... 3

2.7 Overview of Forecasting Methodology ................................................................................................................... 3

3 Future Year Highway Network ......................................................................................................................................... 4

3.1 Do-Minimum Highway Network ............................................................................................................................. 4

3.2 Do-Something Highway Network ........................................................................................................................... 4

4 Future Year Trip Matrix Development.............................................................................................................................. 5

4.1 Introduction ............................................................................................................................................................ 5

4.2 Background Growth ............................................................................................................................................... 5

4.3 Developments ........................................................................................................................................................ 6

4.4 Trip distribution .................................................................................................................................................... 10

4.5 Future Year Trip Matrix Production ...................................................................................................................... 10

5 Variable Demand Modelling ........................................................................................................................................... 13

5.1 Introduction .......................................................................................................................................................... 13

5.2 Methodology ........................................................................................................................................................ 13

5.3 Impact .................................................................................................................................................................. 18

5.4 Realism Testing ................................................................................................................................................... 19

6 Network Assignment Checks and Characteristics ....................................................................................................... 21

6.1 Generalised Cost Formulation ............................................................................................................................. 21

6.2 Model Convergence ............................................................................................................................................. 21

6.3 Network Wide Characteristics .............................................................................................................................. 24

7 Analysis of Traffic Forecasts ......................................................................................................................................... 25

7.1 Introduction .......................................................................................................................................................... 25

7.2 Analysis of Matrix Totals ...................................................................................................................................... 25

7.3 Analysis of Traffic Flow ........................................................................................................................................ 34

7.4 Analysis of Delay ................................................................................................................................................. 34

7.5 Analysis of Capacity ............................................................................................................................................ 40

7.6 Analysis of Speeds .............................................................................................................................................. 46

7.7 Summary ............................................................................................................................................................. 47

8 Sensitivity Testing .......................................................................................................................................................... 51

8.1 Introduction .......................................................................................................................................................... 51

8.2 Background Growth ............................................................................................................................................. 51

8.3 Uncertainty in Developments ............................................................................................................................... 52

8.4 Analysis of Matrices and Assignment .................................................................................................................. 56

9 Additional Testing ........................................................................................................................................................... 58

9.1 Introduction .......................................................................................................................................................... 58

9.2 Unconstrained Models ......................................................................................................................................... 58

9.3 Off-peak, Weekend and Bank Holiday Models .................................................................................................... 59

10 Summary .......................................................................................................................................................................... 63

10.1 Summary ............................................................................................................................................................. 63

Table of Contents

Appendix A – Scheme .................................................................................................................................................................... 65

Appendix B – Traffic Flow Diagrams ............................................................................................................................................... 66

Appendix C – Location Plan ........................................................................................................................................................... 67

Appendix D – Area Network Plan ................................................................................................................................................... 68

Appendix E – Morpeth Network Plan .............................................................................................................................................. 69

Table 1 - TEMPRO Growth Factors for the Northumberland Authority ......................................................................................5

Table 2 - NTM Growth Factors for North East region ..................................................................................................................5

Table 3 - Database of Proposed Developments ...........................................................................................................................6

Table 4 - Average Trip Rates ....................................................................................................................................................... 10

Table 5 – Volume Scaling Factors For peak periods ................................................................................................................. 15

Table 6: Public Transport Proportions ....................................................................................................................................... 15

Table 7 – Calculation for Value of Time ...................................................................................................................................... 16

Table 8 – Vehicle Occupancy ...................................................................................................................................................... 16

Table 9 – Calibrated Mode Choice Parameters .......................................................................................................................... 16

Table 10 – Calibrated Trip Distribution Parameters ................................................................................................................... 17

Table 11 – 2015 Matrix Totals Before and After the VADMA Process – Do Minimum and Preferred Scheme ...................... 18

Table 12 - 2030 Matrix Totals Before and After the VADMA Process – Do Minimum and Preferred Scheme ...................... 18

Table 13 – Matrix Elasticities ....................................................................................................................................................... 19

Table 14 –Output Fuel Cost Elasticities (network) ..................................................................................................................... 19

Table 15 – Fuel Cost Elasticity Relative to Trip Distribution Parameter .................................................................................. 20

Table 16 – Fuel Cost Elasticity Relative to Mode Choice Parameter ........................................................................................ 20

Table 17 - Highway Assignment Generalised Cost Parameters – 2015 ................................................................................... 21

Table 18 - Highway Assignment Generalised Cost Parameters – 2030 ................................................................................... 21

Table 19 - Summary of Convergence Criteria ............................................................................................................................ 22

Table 20 - Summary of Convergence Statistics – 2015 Do Minimum ....................................................................................... 22

Table 21 - Summary of Convergence Statistics – 2030 Do Minimum ....................................................................................... 23

Table 22 - Summary of Convergence Statistics – 2015 Preferred Scheme ............................................................................. 23

Table 23 - Summary of Convergence Statistics – 2030 Preferred Scheme ............................................................................. 23

Table 24 - Network Statistics – 2015 AM Peak ........................................................................................................................... 24

Table 25 - Network Statistics – 2030 AM Peak ........................................................................................................................... 24

Table 26 - Network Statistics – 2015 Inter-Peak ......................................................................................................................... 24

TAble 27 - Network Statistics – 2030 Inter Peak......................................................................................................................... 24

Table 28 - Network Statistics – 2015 PM Peak ........................................................................................................................... 24

Table 29 - Network Statistics – 2030 PM Peak ........................................................................................................................... 24

Table 30 - 2007 – 2015 Forecasting Process Matrix Totals ....................................................................................................... 26

Table 31 - 2007 – 2030 Forecasting Process Matrix Totals ....................................................................................................... 27

Table 32 - Sectored Growth ......................................................................................................................................................... 28






Table 38 - Forecast Traffic Flows – AM Peak Period ................................................................................................................. 48

Table 39 - Forecast Traffic Flows – Inter Peak Period ............................................................................................................... 49

Table 40 - Forecast Traffic Flows – PM Peak Period ................................................................................................................. 50

Table 41 - Pessimistic and Optimistic Growth Factors for the Castle Morpeth Authority ..................................................... 51

Table 42 – 2007-2030 Growth Rates ............................................................................................................................................ 52

Table 43 - Planned Developments in Modelled Area – Uncertainty Log ................................................................................. 52

Table 44 – 2015 Post-Variable Demand Sensitivity Totals ........................................................................................................ 56

Table 45 – 2030 Post-Variable Demand Sensitivity Totals ........................................................................................................ 57

Table 46: 2007-2015 TEMPRO/Development growth comparison (Castle Morpeth) ............................................................... 58

Table 47: 2007-2030 TEMPRO/Development growth comparison (Castle Morpeth) ............................................................... 59

Table 48: Proposed Methodology for Forecasting .................................................................................................................... 59

Table 49: Off-Peak, Weekend and Bank Holiday Factors .......................................................................................................... 61

Figure 1: Flow Diagram Detailing the Forecasting Process ..................................................................................................... 12

Figure 2 - Variable Demand Procedure ....................................................................................................................................... 14

Figure 3 – AM 2030 Do Minimum Delay ...................................................................................................................................... 35

Figure 4 – AM 2030 Do Something Delay ................................................................................................................................... 36

Figure 5 – IP 2030 Do Minimum Delay ........................................................................................................................................ 37

Figure 6 – IP 2030 Do Something Delay ...................................................................................................................................... 38

Figure 7 – PM 2030 Do Minimum Delay ...................................................................................................................................... 39

Figure 8 – PM 2030 Do Something Delay .................................................................................................................................... 40

Figure 9 – AM 2030 Do Minimum Capacity ................................................................................................................................. 41

Figure 10 – AM 2030 Do Something Capacity ............................................................................................................................ 42

Figure 11 – Inter-Peak 2030 Do Minimum Capacity ................................................................................................................... 43

Figure 12 – Inter-Peak 2030 Do Something Capacity ................................................................................................................ 44

Figure 13 – PM 2030 Do Minimum Capacity ............................................................................................................................... 45

Figure 14 – PM 2030 Do Something Capacity ............................................................................................................................ 46

Figure 15: Off-Peak, Weekend and Bank Holiday Forecasting Methodology .......................................................................... 62

AECOM Morpeth Traffic Model Forecasting Report 1

Capabilities on project:

Transportation

1.1 Background

Northumberland County Council (NCC) has long had a desire to see the construction of a link road between the A1 and

South East Northumberland having first appeared in local policy documents in the mid 1990’s. Following advice from

Government Office in 2001, the proposal was split into three parts; the A1-South East Northumberland Link Road-

Morpeth Northern Bypass (A1-SENSLR-MNB) is the only section still to be progressed.

The construction of the A1-SENSLR-MNB is expected to lead to the following benefits:

- Reduce congestion in Morpeth town centre;

- Improve accessibility to South East Northumberland;

- Facilitate development on land to the north of Morpeth.

This report summarises the methodology which has been adopted in order to assess the future impacts of the proposed

link road. The main objective of the Forecasting Report is to describe the development of the future year traffic model to

enable operational, economic and environmental evaluation of the proposed A1-SENSLR-MNB. This evaluation has

been undertaken through comparison of the Do Minimum reference case and the Do Something test case scenarios.

1.2 Report Structure

Following this introductory section, this report has been prepared with the following structure:

- Section 2 provides a background to the model and the approach to forecasting.

- Section 3 covers the future highway network conditions.

- Section 4 deals with the forecast trip matrix production.

- Section 5 provides details of the variable demand process.

- Section 6 covers characteristics of the network assignment and checks made on the assignments.

- Section 7 details an analysis of the forecasting results.

- Section 8 provides an explanation of the sensitivity testing.

- Section 10 provides information on additional models which have been constructed.

- Section 9 provides a summary to the report.

1 Introduction



Transportation

2.1 Modelled Time Periods

Three base year models have been developed representing a Monday to Thursday average for the following time

periods:

- 2007 Morning Peak (0800-0900);

- 2007 Inter-Peak (1000-1600) – a single inter-peak matrix represents an average hour; and

- 2007 Evening Peak (1700-1800)

This is discussed in greater detail in the Morpeth Traffic Model Local Model Validation Report, July 2011.

2.2 Vehicle Types and Trip Purposes

Demand matrices have been produced for 4 different user classes for input into the network. The first 3 consist of the

Car/LGV class spilt down into 3 journey purposes to reflect differing values of time and distance. The 4th and final user

class is for medium and heavy goods vehicles. The input matrix is split as follows:

- User class 1 (cars and light goods vehicles - commuting); and

- User class 2 (cars and light goods vehicles - business); and

- User class 3 (cars and light goods vehicles - other); and

- User class 4 (medium and heavy goods vehicles)

2.3 Geographical Extent of Model

The overall study area is sufficient to ensure an accurate representation of the longer distance journeys on major

strategic routes in the region although focuses on the town of Morpeth and the surrounding area. The study area, as

shown in Appendix C, Appendix D and Appendix E, is bounded by:

- A1/A1068 at Alnwick to the north

- the A1068 and A189 to the east

- the A19 south of Cramlington to the south

- A1 to the west

2.4 Zoning System

The zone system is in part defined by the level of detail provided within the network. The level of detail provided in the

network away from the main areas of interest determined the level of disaggregation required within the zoning system.

Within the core study area zones are defined by individual output area with aggregation of output area with distance from

the scheme. This resulted in a model with 81 zones.

The simulation junctions are divided into:

- 45 external nodes;

- 56 priority junctions;

- 10 roundabouts; and

- 1 traffic signal

More detail on the zoning system and extent of the model can be found in the Morpeth Traffic Model Local Model

Validation Report, July 2011.

2.5 Network Description

The model consists of both simulation (core) and buffer area. The simulation network is coded in considerable detail

using junction based data in addition to link based data. The simulation network is surrounded by the buffer network,

which is coded in less detail with data describing only the characteristics of the links.

2 Model Background



Transportation

The simulation area consists of the Morpeth town centre area, the A192 and A197 routes and the A196 and A1 to the

east and west of the town respectively. This enables major delays occurring within and around the town centre to be

reflected.

The remainder of the study area covers all major strategic routes into the greater zone of influence. This area has been

modelled in less detail and forms the buffer network.

2.6 Model Validation

The Morpeth Traffic Model Local Model Validation Report demonstrated that overall, the base year Morpeth model was a

sufficiently robust model that reproduces the existing situation and is suitable as a basis for forecasting.

Forecasts have therefore been produced to provide input into the following processes:

- Scheme design;

- Environmental assessment; and

- Economic cost benefit analysis

2.7 Overview of Forecasting Methodology

The forecasting work has been undertaken in accordance with current WebTAG guidance including a variable demand

assessment.

Networks and trip demand matrices were developed for the following forecast years:

- 2015 being the proposed year of opening for the A1-SENSLR-MNB; and

- 2030 being the proposed design year, 15 years after the opening of the A1-SENSLR-MNB.

To reflect future change in travel patterns, proposed employment and residential developments were incorporated into

the future year highway networks. No committed highway schemes have been identified and therefore the Do-Minimum

highway network remains unchanged.

The growth factors for future year demand were derived from TEMPRO and NTM. Account was also taken of local

developments at various stages of planning status.

The effect of induced/generated traffic was modelled using a freestanding variable demand modelling process that has

been developed by AECOM, and used in previous work with the approval of the DfT.



Transportation

3.1 Do-Minimum Highway Network

Officers from Northumberland County Council were consulted for information on any committed highway schemes likely

to impact on traffic patterns across the region. It was confirmed that there were no committed highway schemes of

significance in the area. As such, the Do-Minimum highway network was assumed to be the same as the base model.

3.2 Do-Something Highway Network

The Preferred Option involves the construction of a 3.7km length of 7.3m wide single carriageway between the A1 east

of Mitford and the A197 Pegswood Bypass. The scheme also incorporates a cycleway and footway for the full length of

the route. The new road will tie in as a fifth arm at the recently constructed Whorral Bank roundabout located west of

Pegswood. The scheme incorporates the construction of an all movements grade-separated junction onto the A1 at St

Leonard’s and the construction of two at-grade junctions on the St George’s Link section of the Bypass: the Northgate

roundabout will provide a junction with the A192 west of Fulbeck; and St George’s Roundabout, at a point north west of

St George’s hospital, will provide an access point to a future development (St George’s Phase 2 and Phase 3). The

scheme is detailed in Appendix A.

3 Future Year Highway Network



Transportation

4.1 Introduction

In order to predict traffic growth in future year scenarios, a number of different sources of data were used to provide

information on growth and development which would impact on traffic levels in the modelled area.

NCC provided information on proposed developments in the study area and the TRICS database (2011a) was used to

obtain appropriate production and attraction trip rate factors. TEMPRO, the National Trip End Model (NTEM) and NTM,

the Department for Transport’s Nation Transport Model, were used to produce background traffic growth forecasts as

follows:

- TEMPRO (version 6.2) was used to produce growth factors for car trip and light good vehicle demand matrices;

- NTM (2009) was used to produce growth factors for trips made by medium and heavy good vehicles.

4.2 Background Growth

4.2.1 Light Vehicles

TEMPRO and NTM factors have been used to calculate the background growth within the modelled area, for lights and

heavy vehicles respectively.

Local TEMPRO factors have been used for light traffic (User Classes 1, 2 and 3) growth, which takes into account local

demographic change, socioeconomic variation and changes in modes as well as other factors that affect the growth of

traffic within the locality.

Traffic growth factors for car trips were extracted from the TEMPRO database (version 6.2) for AM, inter-peak and PM

periods for the authority of Northumberland in the following time periods:

- 2007-2015

- 2007-2030

The results from TEMPRO are detailed in the below table:

Table 1 - TEMPRO Growth Factors for the Northumberland Authority

Time Period 2007-2015 2007-2030

Origin Destination Origin Destination

AM Peak 1.003 1.036 1.028 1.059 Inter-Peak 1.059 1.056 1.138 1.132

PM Peak 1.035 1.015 1.070 1.052

4.2.2 Heavy Vehicles

The base year heavy goods vehicle matrices have been growthed up for each of the future years using factors derived

from the 2009 forecast results from the DfT’s National Transport Model. The 2009 report supplies national growth factors

from a base year of 2003 to future years of 2015, 2025 and 2035 for heavy traffic.

Factors for the 2015 and 2030 forecast years were obtained by interpolating between 2003 and 2035. For both cases,

linear growth was assumed in order to calculate the years which were not specifically modelled within NTM.

The NTM growth forecasts are split into different regions and are universal across the day, hence the same factors have

been applied to all of the time periods within the model and the same value applied to both origin and destination. The

NTM growth factors used are supplied in Table 2 below:

Table 2 - NTM Growth Factors for North East region

NTM Period Calculated Factor

2007 – 2015 1.039

2007 - 2030 1.240

4 Future Year Trip Matrix

Development



Transportation

4.3 Developments

4.3.1 Development Data

A list of all proposed developments in the desired area which were forecast to be completed by 2030 was provided by

NCC. Each development was assigned a land use and trip rate and, using the TRICs software, factors for arrivals and

departures were calculated dependent on size of the development. It was not considered that future developments in

districts outside of the buffer network would have a significant impact on trip rates due to the wide area incorporated by

the buffer network. A list of the proposals included in the development database is shown in Table 3 below.

Table 3 - Database of Proposed Developments

Site No.

Site Name Proposed Land Use

Area (m2)

Size of Development

A (Retail) (sq.m)

B (Comm. >1000 (sq.m)

C - Residential D

Other (Sq.m) HA

No of Res. Units

1 Hadston Industrial Estate

Employment 2700

3039

2 Morpeth Fairmoor (Northgate)

Employment 100800

40800

3 Morpeth Fairmoor (Northgate)

Residential 101000

192

4 Longhorsely Land at East Road

Residential 3800

12

5 Morpeth Ex to Land Fairmoor

Employment 56000

22400

6 Morpeth Fairmoor Adj to A1

Employment 78800

31520

7 Morpeth Station Yard Employment 17400

6960

8 Stannington, part St. Mary's Hospital (mixed use)

Residential 283900

172

9 Stannington, part St. Mary's Hospital (mixed use)

Employment 283900

4924

10 Ellington Colliery (mixed Use)

Employment 146800

4185

11 Ellington Colliery (mixed Use)

Residential 146800

300

12 Lynemouth Colliery (mixed Use)

Residential 146300

200

13 Lynemouth Colliery (mixed Use)

Employment 146000

32700

14 Low Stanners Morpeth mixed development

Retail 22800 4560

15 Goose Hill Factory site/ Davidsons Garage Morpeth

Retail 1900 645

16 Goose Hill Factory site/ Davidsons Garage Morpeth

Residential 1900

60

17 Stobswood Brickworks Residential 75500

149



Transportation

Site No.


Area (m2)

Size of Development

A (Retail) (sq.m)

B (Comm. >1000 (sq.m)

C - Residential D

Other (Sq.m) HA

No of Res. Units

18 St Georges,Morpeth Phase 1

Residential 115000

246


Residential 319300

693


Residential 343500

241

21 Hepscott Park Employment 81800

32720

22 Hepscott Park Residential 81800

75

23 Park View, Hadston (Phase 3) West of A1068

Residential 28200

86

24 NCB Workshop site Ashington

Residential 96300

339

25 ASDA, Lintonville Terrace, Ashington

Retail 22000 6789

26 South of Wansbeck General Hospital, Ashington

Residential 547800

628

27 Ashwood Business Park, North Seaton

Employment 402400

3718

28 Wansbeck Business Park, Ashington

Employment 193300

21111

29 Lintonville Enterprise Park, Ashington

Employment 36000

6139

30 Former Ashington Hospital, Station Road

Residential 30200

139

31 Existing Northumberland College

Residential 79600

337

32 Ellington Colliery (site offices)

Employment 9500

951

33 Northumberland College (Hawthorne Annexe), Ashington

Residential 7900

47

34 South Loansdean, Morpeth (SHLAA-3007)

Residential 104300

240

35 NCC sites Fire Station, County Hall adjoining land

Residential 45900

150

36 Stobhill South Residential 114200

400

37 South Shore Links Road, Blyth

Residential 60300 229

38 Land at Wheatridge Park, Seaton Delaval


39 Land at area 2A Chase Farm Drive Blyth




Transportation

Site No.


Area (m2)

Size of Development

A (Retail) (sq.m)

B (Comm. >1000 (sq.m)

C - Residential D

Other (Sq.m) HA

No of Res. Units

40

Land at West Blyth accessed from Chase Farm Drive Blyth (Phases 1&2)


41

Land at West Blyth accessed from Chase Farm Drive Blyth (Phase 3)


42 Asda Stores Limited, Cowpen Road, Blyth

Retail 41300 1039

43 Tesco Supermarket Market Place Bedlington

Retail 23900 2338

44 Morrisons, Regent Street, Blyth

Retail 21300 2130

45 Narec Test Site, Albert Street, Blyth

Employment 10100 4040

46 Narec Test Site Albert Street, Blyth


47 Queen Street, Amble Residential 48900 46

48 Queen Street, Amble Retail 48900 2747

49 A1068 (land west of) and Marks Bridge (land south of) Amble


50 Coquet Enterprise Park, Amble

Employment 1700 700

51 Land at Crofton Mill Industrial Estate, Blyth


52 Crossland Park, Cramlington


53 Amble Boat Co. Amble - Residential


54 Amble Boat Co. Amble - Employment


55 Amble Boat Co. Amble - Retail

Retail 10900 1000

56 Land East of A189 and South of Lanercost Park, Cramlington

Hospital 213100 85240

57 West Hartford Business Park Cramlington


58 South West Sector Cramlington


59 Sanderson Arcade Morpeth

Retail 35200 8957



Transportation

Site No.


Area (m2)

Size of Development

A (Retail) (sq.m)

B (Comm. >1000 (sq.m)

C - Residential D

Other (Sq.m) HA

No of Res. Units

60 The Kylins, Morpeth Residential 24200 88

61 East Ashington SPD Area


62 East Ashington SPD Area

Retail 36100 2157

63 Jubilee Industrial Estate


64 North Seaton Industrial Estate


65 West Sleekburn Industrial Estate


66 Cambois Residential 526400 52.64

67 Welbeck Terrace Pegswood


68 The Mount, Morpeth Non-residential 6400 3644

69 Land east of Whorral Bank Roundabout Morpeth

Non-residential 13800 1044

70 Northgate Hospital (SHLAA 3079)


Each development was assigned to a particular zone in the network which matched the location of the site. Some of the

developments were in zones outside the detailed zoning system of Morpeth town centre and near to other urban areas.

In these cases, it was assumed that not all of the trips relating to these developments would be travelling through the

simulation network areas and, due to the larger zone coverage, there would be a significant amount of intrazonal trips.

To account for intrazonal trips, or trips which would not access the modelled network, where possible, information was

sought from detailed Transport Assessments for these developments. Zone 844, to the far east of the model contains

developments 10 to 13. The outline planning applications for these developments, the Lynmouth Outline Planning

Application and the Ellington Outline Planning Application, both February 2009 and produced by Entec, were available

and the agreed distribution from these documents suggests that no more than 10% of the potential traffic from these

developments should be entering the Morpeth modelled network.

A number of the developments identified in Table 3 are located in Ashington and Blyth. In order to account for trips from

these zones travelling to other areas or intrazonally, the number of trips was reduced to 25%. Where development sites

are located in Cramlington, the number of trips was reduced by 10%, which reflects the fact that trips to and from these

zones are unlikely to have been captured in the Roadside Interview Surveys.

As previously mentioned, trip rate figures were calculated separately for each development type. Vehicle trip rates were

calculated based on similar developments in the TRICS database (2011a).

Trip rates are listed in Table 4 below.



Transportation

Table 4 - Average Trip Rates

Land Use Sub Land Use

Trip Rate

Units AM Peak Inter Peak PM Peak

Arr. Dep. Arr. Dep. Arr. Dep. Employment Office 0.01 0.003 0.003 0.003 0.002 0.011 Trips per 100m

2 GFA

Employment Industrial Estate

0.005 0.002 0.003 0.003 0.001 0.004 Trips per 100m2 GFA

Employment Industrial Unit

0.003 0.001 0.002 0.002 0.000 0.003 Trips per 100m2 GFA

Hotel, Food & Drink

Hotel 0.005 0.006 0.003 0.003 0.004 0.003 Trips per 100m2 GFA

Residential Hospital 0.008 0.002 0.004 0.004 0.002 0.006 Trips per 100m2 GFA

Residential Houses Privately Owned

0.18 0.45 0.2 0.19 0.4 0.23 Trips per dwelling

Residential Houses Privately Owned

4.65 11.68 5.22 4.95 10.25 6.14 Trips per hectare

Leisure Mixed Leisure Complex

0.006 0.004 0.006 0.006 0.018 0.013 Trips per 100m2 GFA

Non-Residential

GP Surgery 0.028 0.010 0.013 0.013 0.015 0.026 Trips per 100m2 GFA

Non-Residential

Vets 0.028 0.013 0.029 0.024 0.035 0.040 Trips per 100m2 GFA

Retail Superstore 0.029 0.019 0.053 0.053 0.052 0.054 Trips per 100m2 GFA

Retail Shopping Centre

0.037 0.032 0.039 0.039 0.036 0.036 Trips per 100m2 GFA

The development database contains information on the size of each proposed development within the study area.

However, in most cases this was provided in the form of land available for development. It was assumed that some of

this available land will be designated for car parking or landscaping. Therefore it was estimated that the actual footprint

of the development buildings would be 40% of the total land area.

4.4 Trip distribution

For the majority of zones contained within the model, no developments were specified. In these cases, forecast year

distributions for future growth were based on the existing trip distributions for the zone.

For zones where developments were specified, existing base year distributions were assessed for applicability in terms

of land use. Where base year distributions would not reflect those associated with forecast year developments, the trip

distribution from an adjacent base year zone with a similar land-use was applied.

4.5 Future Year Trip Matrix Production

It is a requirement as stated in DMRB and WebTAG 3.15.2 that there is a need to control overall growth to TEMPRO.

Therefore, adjustment factors were calculated and applied such that the overall growth was constrained to local

TEMPRO factors. Origin and destination trip end totals were then balanced in order to enable the matrix furness

procedure to be carried out successfully.

Matrices were then furnessed to the revised row and column totals using the MX facility within the SATURN suite of

programs. Each future year matrix was then ready to be fed through the variable demand process as discussed in

Section 5.

The TEMPRO database takes into account potential for developments within each region but does not consider any

specific planned developments. Since the methodology for the scheme will include several actual developments in the



Transportation

area, the TEMPRO forecasts and specific development traffic will need to be combined whilst maintaining TEMPRO

growth to avoid double counting.

In order to constrain the growth of the matrices to the TEMPRO factors, a methodology from previous work undertaken

by AECOM has been applied. This methodology involves the following:

- Adding the base year 2007 row and column totals to the proposed development traffic (a)

- Factoring the base year 2007 row and column totals by the TEMPRO factors (b)

- Factoring the base year + development traffic by the TEMPRO factors (c)

- Dividing the total of (b) by the total of (c) and multiplying by (c)

The above method constrains the development traffic to the TEMPRO factored row and column totals for each year and

time period. Once the new row and column totals were calculated for each of the matrices, each matrix was furnessed

within the SATURN program and the final matrices output to be transferred in to the variable demand process. See

Chapter 5 for details

These final matrices for 2015 and 2030, AM, inter-peak and PM therefore contain both general background and specific

development growth constrained back to the approved TEMPRO overall growth rates for the region.

The forecasting process is illustrated in the following diagram.



Transportation

Figure 1: Flow Diagram Detailing the Forecasting Process



Transportation

5.1 Introduction

When a scheme is opened a range of responses by road users can take place, which can include all or some of the

following:

- Reassignment;

- Trip retiming;

- Trip redistribution;

- Mode switch;

- Change vehicle occupancy;

- Increase the frequency of some journeys;

- Trip Generation; and

- Change the pattern of land use.

A scheme which provides extra capacity on the road network can lead to traffic being induced through any of the above

responses.

In the same way, if there is a lack of capacity on the network (e.g. such as in the Do-Minimum when no scheme is

implemented), traffic can be suppressed.

To take account of the impacts of future year traffic conditions a full variable demand modelling (VDM) approach has

been taken in developing the future year matrices. This section describes the methodology adopted for the VDM and

describes the results of the approach by presenting a comparison of the demand matrices before and after the VDM was

applied.

5.2 Methodology

A freestanding variable demand modelling process has been developed for the Morpeth model.

This approach is fully compliant with the Department for Transport’s variable demand guidelines. The process used for

the Morpeth project has been based on a similar model developed previously by AECOM and approved by the

Department for Transport.

The process consists of a series of iterations during which the current demand matrices are assigned, skimmed cost

matrices are extracted and based on comparative travel costs the demand matrices are updated. The full process is

illustrated in Figure 2.

Key elements of the model

- Traffic assignments are carried out using SATURN, matrix manipulation and calculation is carried out in Emme/2

- Public transport costs are fixed within the process and have been assumed to remain constant across all scenarios

- All model parameters are based on the Webtag (Unit 3.10.3) Variable Demand Modelling advice (June 2006).

- Convergence of the model is measured by reference to changes in overall costs using the functions defined in

Webtag. (Unit 3.10.4)

- The model pivots on the base year assignment, so that all future year cost changes are compared against the base

year costs to determine changes in demand patterns.

- The following responses can be modelled:

o Mode Choice (car v public transport)

o Time Choice

o Distribution

o Trip frequency

o Responses are modelled separately for each trip purpose

5 Variable Demand Modelling



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Figure 2 - Variable Demand Procedure



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5.2.1 Input Matrices

The assignment matrices output from the initial future year growth process are peak hour matrices. For the purpose of

the demand model, the peak hours have been factored to periods and thus to an overall 12 hour matrix. The matrices

used in the process are origin – destination rather than production – attraction matrices.

Factors to produce the 12 hour matrix have been derived from ATC data as below in Table 5

Table 5 – Volume Scaling Factors For peak periods

The Morpeth model holds car demand matrices in the below three trip purposes:

- Commuting

- Business

- Other

For the purposes of the demand model it was necessary to break down the business and other trips into home based

and non home based matrices. This was done by applying global factors to the matrices in the assignment model.

On the basis of 2006 trip end data for the Morpeth area in Tempro, 65% of business trips were assumed to be home

based, and for other personal trip purposes 85% were assumed to be home based.

Intrazonal trips are not excluded from the process and there is the potential for trips to be interchanged between

intrazonal and interzonal as a result of the process. The intrazonal costs are calculated as half of the row minimum,

excluding zeros.

In this variable demand process external to external and external to internal trips have been frozen, and are thus not

affected by the variable demand process.

The following model zones are defined as external zones for this purpose.

823, 824, 825, 827, 831, 837, 850 - 854

Internal to external trips remain unfrozen.

5.2.2 Public Transport Trips

There were no public transport surveys, and no public transport model, included as a part of the Morpeth model.

To seed the mode choice model a baseline number of public transport trips were needed. Tempro 6.1 was used to

examine the number of public transport trips, as a proportion of all trips, in the Morpeth area. These proportions were

used to calculate the number of base year public transport trips from the numbers of car trips and are shown in Table 6

below.

Table 6: Public Transport Proportions

Peak Hour Peak Period Factor

0800 – 0900 0700 – 1000 2.824

Average inter peak 1000 – 1600 6.000

1700 – 1800 1600 – 1900 2.751

% PT Trips

Commuting 6.7%

Business 1.0%

Other 12.3%



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It was assumed that 50% of these public transport trips would have a car available for the journey. Base year public

transport times were globally assumed to be 25% greater than the equivalent highway journey times. All tests are based

on the difference between base and test journey times, and for all tests this was assumed to be zero.

5.2.3 Travel Cost Assumptions

Values of time used in the model are taken from WebTAG 3.5.6. The calculations used to adjust the 2002 based

WebTAG values to 2006 base year values are shown below in Table 7:

Table 7 – Calculation for Value of Time

WebTAG Value 2002 Change 2002 – 2006

Model input values

£/hr (2002) pence/min (2002) % pence/min (2006)

HBW 5.04 8.40 +8.56 9.12 HBEB 21.86 36.43 +10.77 40.36

HBO 4.46 7.43 +8.56 8.07 NHBEB 21.86 36.43 +10.77 40.36

NHBO 4.46 8.07 +8.56 8.07

National average values for vehicle occupancies have been used within the model. These have been derived from

applied from WebTAG 3.5.6 and are shown below in Table 8.

Table 8 – Vehicle Occupancy AM Peak Inter Peak PM Peak

HBW 1.114 1.096 1.104 HBEB 1.224 1.162 1.156

HBO 1.652 1.635 1.705 NHBEB 1.224 1.162 1.156

NHBO 1.652 1.635 1.705

WebTAG Table 4 corrected to 2006 values using WebTAG table 6

5.2.4 Final Car Trip Distribution Lambda Values

Fuel costs have been calculated using the fuel VOC formulae parameter values included in Table 10 of Unit 3.5.6. These

parameters have been used to calculate litres per kilometre. The fuel consumption has then been multiplied by the

average fuel costs included in Table 11 of Unit 3.5.6. Fuel costs for 2006 were used in the model, with non work trips

incurring the full cost, while in work trips incurred only the resource and duty costs. Within the model costs were then

reduced to take account of the fuel efficiency improvements included in Unit 3.5.6 Table 13.

5.2.5 Calibrated Parameter Values

The parameter values for the main mode choice model are shown below, together with the suggested values included in

WebTAG Unit 3.10.3. Table 9 below shows that for the non work purposes the calibrated values fall within the

recommended range. For the non home based employers business trip purpose there is little data available in WebTAG,

and no range is provided. A value lower than the single value contained in WebTAG range was found to produce a

better calibration.

Table 9 – Calibrated Mode Choice Parameters

Purpose WebTAG minimum

WebTAG maximum

Calibrated Values

HBW 0.50 0.83 0.50

HBEB 0.26 0.65 0.65 HBO 0.27 1.00 0.53

NHBEB 0.73 0.73 0.53 NHBO 0.62 1.00 0.71



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The parameter values for the trip distribution model are shown below, together with the suggested values included in

WebTAG Unit 3.10.3. Table 10 below shows that for the non work purposes the calibrated values fall within the

recommended range. For the in work trips parameter values slightly above the WebTAG range were found to produce a

better calibration.

Table 10 – Calibrated Trip Distribution Parameters Purpose WebTAG

minimum WebTAG maximum

Calibrated Values

HBW 0.054 0.113 0.100 HBEB 0.038 0.106 0.150

HBO 0.074 0.160 0.090

HNBEB 0.069 0.107 0.150 NHBO 0.073 0.105 0.080

5.2.6 Convergence Stability

The convergence of the variable demand process was measured using the approach outlined in WebTAG. This is based

on calculating the demand/supply gap using the following function on each iteration of the process.

Where:

Xijctm is the current flow vector or matrix from the model

C(Xijctm) is the generalised cost vector or matrix obtained by assigning that matrix

D(C(Xijctm)) is the flow vector or matrix output by the demand model, using the costs C(Xijctm) as input

ijctm represents origin i, destination j, demand segment/user class c, time period t and mode m

The process is assumed to have converged when the demand/supply gap falls below 0.15% for each user class in each

time period.

In addition, the convergence of each SATURN run during the process is measured. In each case the SATURN model is

run until the following levels of convergence are reached.

The target for convergence stability is 99% of link flows change by less than 5% on four consecutive iterations.

In the current version of the process, smoothing is applied to demand rather than costs.

The smoothing process begins after three iterations of the model. The function used to calculate the smoothed matrices

is:

Demandn = 2 * demandn + (n-3) * demandn-1 (n-1) (n-1)

Where:

Demandn is the demand matrix at the end of the nth iteration



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Convergence of the demand –supply model is measured by the criterion identified in WebTAG Unit 3.10.4. The model is

run until all trip purposes, in all time periods have a gap value lower than 0.05%. This is lower than the 1%

recommended in WebTAG, but is achievable in this case, due to the simple nature of the network.

5.2.7 Convergence Proximity

Delta values for each run are checked to ensure that they are less than 1%. In most cases delta is significantly lower,

typically around 0.15%.

5.3 Impact

In order to fully understand the impact of applying a variable demand modelling approach, the pre-VDM and post-VDM

matrices for Car trips have been compared for the Do Minimum and Do Something scheme scenarios. Only Car trips

have been considered as these are subject to the greatest change as a result of the variable demand process, with little

or no change affecting other user classes.

The results of this analysis are presented below, and are discussed along with a direct comparison between the variable

demand Do Minimum and Do Something Scheme models, which will show the effect of the variable demand process on

Car trips.

5.3.1 Comparison of Matrix Totals

Table 11 and 12 below, provide a summary of matrix totals for Car trips across the modelled network for all peak periods

in the opening year 2015 and design year 2030.

Table 11 – 2015 Matrix Totals Before and After the VADMA Process – Do Minimum and Preferred Scheme

Time Period 2015 Base Forecast

Do Minimum – 2015 (1) Preferred Scheme – 2015 (2) % Change between (2) & (1) Demand

% Change to Base

Demand % Change to

Base

AM Peak 21,240 21,401 0.76% 21,435 0.92% 0.16%

Inter Peak 10,924 11,125 1.84% 11,125 1.84% 0.00%

PM Peak 24,418 24,516 0.40% 24,603 0.76% 0.35%

Total 56,582 57,042 0.81% 57,163 1.03% 0.21%

Table 12 - 2030 Matrix Totals Before and After the VADMA Process – Do Minimum and Preferred Scheme

Time Period 2030 Base Forecast

Do Minimum – 2030 (1) Preferred Scheme – 2030 (2) % Change between (2) & (1) Demand

% Change to Base

Demand % Change to

Base

AM Peak 21,749 22,029 1.29% 22,121 1.71% 0.42%

Inter Peak 11,722 12,096 3.19% 12,133 3.51% 0.31%

PM Peak 25,276 25,491 0.85% 25,596 1.27% 0.41%

Total 58,747 59,616 1.48% 59,850 1.88% 0.39%

The results indicate that in 2015 the variable demand process is having the effect of increasing demand in both the Do

Minimum and Do Something Scheme variable demand models, compared with the Base forecast. This is due to the real

terms increases in earnings and decreases in vehicle operating costs between the base year and the forecast year.

These changes are introduced into the forecasts as a part of the variable demand model. Overall, both models

experience very similar changes in traffic with the % difference between the DS and DS increase being less than 1%.

The results show that in the 2030 future year scenario, both the Do Minimum and Do Something Scheme models exhibit

a noticeable increase in total car trips compared with the 2030 Base forecast. The variable demand process has the

effect of increasing demand by approx 1 to 2% in the AM and PM and approx 3% in the Inter Peak across both the Do

Minimum and Do Something Scenarios.



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Comparing both the Do Minimum post-VDM and Do Something Scheme post-VDM model results indicates that, in 2030,

the introduction of the scheme will induce additional car trips onto the network. The total number of trips induced by the

scheme remains relatively small with an increase in the Preferred Scheme of around 0.42% to 0.41%, in the AM and PM

peak periods.

5.4 Realism Testing

This section presents the results of the revised realism tests.

5.4.1 Fuel Cost

Fuel cost elasticities were determined by running the model with a 10% fuel cost increase. The results were obtained

from a fully converged model run. The matrix elasticities to a 10% increase in fuel costs produced by the model are

shown below.

Table 13 – Matrix Elasticities

Purpose

Car Fuel Cost Elasticities (matrix calculation)

Morning Peak Inter Peak Evening Peak 12-Hour

HBW -0.20 -0.41 -0.23 -0.25

HBEB -0.05 -0.11 -0.09 -0.09

HBO -0.29 -0.40 -0.20 -0.32

NHBEB -0.04 -0.13 -0.09 -0.10

NHBO -0.28 -0.40 -0.18 -0.32

Overall -0.22 -0.33 -0.20 -0.28

The current version of WebTAG 3.10.4 recommends that elasticity values should be expected to fall within the range -

0.1 to -0.4, with an overall elasticity of around 0.3. The discretionary trip purposes should be closer to -0.4 and business

trips closer to -0.1.

The results show that the weighted 12 hour results fall into the range identified within WebTAG.

The new consultation version of WebTAG narrows the recommended gap to a range of between -0.25 and -0.35. The

weighted 12 hour values for non work trips can be seen to also fall within this narrower band.

5.4.2 Network Based Fuel Cost

A set of network based fuel cost elasticities have also been calculated. These were obtained using the total network

vehicle kilometres on all links, excluding centroid connectors. As such, the calculations include the external to external

and external to internal trips which are not included in the variable demand model. As such, this calculation will tend to

underestimate the elasticities; however there was no readily available method of excluding these trips. It should be noted

that the assignment combines the home based and non home based matrices for the business and other trip purposes,

so combined elasticities are calculated for these purposes.

Table 14 –Output Fuel Cost Elasticities (network)

Purpose

Car Fuel Cost Elasticities (matrix calculation)

Morning Peak Inter Peak Evening Peak 12-Hour

Commute -0.11 -0.19 -0.12 -0.13

Business -0.03 -0.06 -0.05 -0.05

Other -0.18 -0.17 -0.09 -0.15

Overall -0.13 -0.14 -0.13 -0.13



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The results show the relative scales of the elasticity between trip purposes are retained. However, as would be predicted

the absolute values are lower than obtained for the matrix based calculation.

5.4.3 Journey time

Journey time elasticities were determined by running the model with a 10% increase in journey times. The results were

obtained from a single run of the demand model. The matrix elasticities to a 10% increase in highway journey time

produced by the model are shown below.

Table 27 – Output Journey Time Elasticities

WebTAG’s guidance on elasticity with respect to journey time suggests that that journey time elasticities will vary

considerably more than fuel cost elasticities and that there is no recommended range for response to journey time.

The results show that the elasticities are considerably lower than the value of 2.0 which is considered an upper limit in

WebTAG, and suggest that the model is relatively inelastic in its response to journey time changes.

5.4.4 Sensitivity of Fuel Cost Elasticities

This section reports on the sensitivity of the fuel cost elasticities to changes in the model parameters. The table shows

how the elasticities reported for the home based work trip purpose vary in response to changes in the trip distribution

parameter.

Table 15 – Fuel Cost Elasticity Relative to Trip Distribution Parameter

Parameter Value AM Peak Inter Peak PM Peak 12 Hour 0.07 -0.14 -0.29 -0.16 -0.19

0.08 -0.16 -0.33 -0.18 -0.20

0.09 -0.18 -.037 -0.20 -0.22

0.10 -0.20 -0.41 -0.23 -0.25

0.11 -0.23 -0.45 -0.25 -0.27

Table 16 – Fuel Cost Elasticity Relative to Mode Choice Parameter

Parameter Value AM Peak Inter Peak PM Peak 12 Hour 0.50 -0.20 -0.41 -0.23 -0.25

0.60 -0.21 -0.45 -0.24 -0.26

0.70 -0.21 -0.50 -0.26 -0.28 0.80 -0.22 -0.55 -0.27 -0.29

Purpose Journey Time Elasticities 12 hour average

HBW -0.24

HBEB -0.40

HBO -0.28

NHBEB -0.42

NHBO -0.27

Overall -0.30



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6.1 Generalised Cost Formulation

The highway assignment procedure builds and loads paths through the network based on a behavioural generalised

cost formulation. This is a linear combination of time and distance of the following form:

Parameter values PPM and PPK have been derived from WebTAG Unit 3.5.6 – Values of Time and Operating Costs.

This ensures maximum compatibility between the assignment process and any economic assessments that are carried

out at a later stage. The value of time data taken from WebTAG was for the peak/inter-peak periods and had a base

year of 2002. The desired values were then factored to get the relevant year and peak hour. The PPK or Value of

Distance was calculated using the cost of fuel as well as the non-fuel vehicle operating costs. Again, this was factored

up to the relevant year and time period. The generalised cost parameters are determined by assessment year, time

period and user class as shown in Table 17 and Table 18 below.

Table 17 - Highway Assignment Generalised Cost Parameters – 2015

Parameter User Class 1 User Class 2 User Class 3 User Class 4

AM PPM 10.95 59.29 14.21 19.08

PPK 8.72 9.81 8.72 34.51

IP PPM 10.85 57.86 14.79 19.08

PPK 8.72 9.81 8.72 34.51

PM PPM 10.66 57.11 15.14 19.08

PPK 8.72 9.81 8.72 34.51

Table 18 - Highway Assignment Generalised Cost Parameters – 2030

Parameter User Class 1 User Class 2 User Class 3 User Class 4

AM PPM 11.73 64.65 15.23 20.45

PPK 8.41 9.55 8.41 35.33

IP PPM 11.63 63.09 15.85 20.45

PPK 8.41 9.55 8.41 35.33

PM PPM 11.43 62.27 16.23 20.45

PPK 8.41 9.55 8.41 35.33

6.2 Model Convergence

SATURN loops between assignment and simulation until steady flows are obtained, at which point the model is deemed

to have reached convergence. A high degree of convergence is important for two reasons:

- If the link flows and their corresponding flow-delay curves are not reasonably consistent then there is no reason to

believe that the modelled link flows and costs will be realistic; and

- It gives us confidence that, when the A1-SENSLR-MNB strategy is tested, any difference in flow between the

converged base and the test network can be attributed to the efforts of the scheme as opposed to random noise

which would arise from a base model which had not reached convergence.

In terms of convergence criteria, the DMRB recognises two types of measure, proximity indicators and stability

indicators.

6 Network Assignment Checks

and Characteristics

Cost = PPM * Time (in min) + PPK * Distance (in km)

Where: PPM = Pence Per Minute

PPK = Pence Per Kilometre



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Proximity indicators are those things which measure the degree to which the assignment sub-model has achieved its

stated aim. In the case of equilibrium assignments this means the degree to which Wardrop equilibrium has been

achieved. The DMRB recommends Delta as the proximity measure for Wardrop equilibrium assignments and states that

it must be less than 1%.

Stability indicators measure the similarity of the results of the previous and current iterations and it is these that are of

particular relevance in terms of the assignment-simulation loop. The DMRB recommends measures which look at

absolute changes in individual link flows and measures which look at the percentage change in total user costs across

the network as a whole.

Table 19 below summarises the recommended convergence criteria.

Table 19 - Summary of Convergence Criteria

Indicator Measure of Convergence Acceptable Value(s)

Proximity Indicators

Assignment ‘Delta’ Value Less than 1% (or at least stable with convergence fully documented and all other criteria met)

Assignment ‘Gap’ Value Less than 1%

Stability Indicators

Percentage of links with flow change (P) < 5% Four consecutive iterations greater than 90%

The Absolute Average Difference in flow per link (AAD)

Less than 1

The Relative Absolute Average Difference in flow per link (RAAD)

Less than 1%

Although proximity and stability usually accompany each other, they both should be assessed separately, as each

relates to different aspects of the iterative process. In terms of achieving stable and robust assignment results the

convergence criteria for the assignment delta value and one of the stability indicators should be met. However, all

convergence measures should be reported.

Table 20 to Table 23 summarises the convergence results for each modelled hour.

Table 20 - Summary of Convergence Statistics – 2015 Do Minimum

Convergence Measure Acceptable Value(s) Convergence Statistics

AM Peak Inter-Peak PM Peak

Assignment ‘Delta’ Value Less than 1% 0.0160 0.0009 0.0147

Assignment ‘Gap’ Value Less than 1% 0.022 0.00068 0.0086

Percentage of links with flow change (P) < 5%

Four consecutive iterations greater than 90%

98.7 100 99.2


Less than 1 0.67 0.13 0.38


Less than 1% 0.20 0.06 0.11



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Table 21 - Summary of Convergence Statistics – 2030 Do Minimum







95.4 99.4 92.5


Less than 1 1.66 0.31 2.5


Less than 1% 0.47 0.12 0.68

Table 22 - Summary of Convergence Statistics – 2015 Preferred Scheme







99.2 99.4 99.9


Less than 1 0.33 0.18 0.24


Less than 1% 0.11 0.09 0.08

Table 23 - Summary of Convergence Statistics – 2030 Preferred Scheme







99.9 100 94.9


Less than 1 0.08 0.03 1.97


Less than 1% 0.03 0.01 0.60

As can be seen from Table 20 to Table 23 above, some of the stability indicators do not fall within the acceptable value.

However, it is outlined in the preceding paragraph that to achieve stable and robust assignment results, the convergence



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criteria for the assignment delta value and one of the stability indicators should be met. The results therefore meet these

criteria.

6.3 Network Wide Characteristics

In order to analyse the network wide impact of each scenario, statistics were extracted from the SATURN assignments

for each modelled time period and scenario. These include total travel distance, total travel time and average network

speed.

Results are summarised in Table 24 to Table 29 below and show that the introduction of the proposed bypass results in

a reduction in travel time and increased average vehicle speeds when compared to the Do-Minimum scenario.

However, an overall increase in vehicle kilometres is observed, primarily as a result of traffic from the south of Morpeth

using the bypass as opposed to travelling through the town centre which represents an increased journey length of

approximately 3km.

Table 24 - Network Statistics – 2015 AM Peak

Do-Minimum Preferred Scheme

Travel Distance (PCU km) 244553.5 244703.9

Travel Time (PCU hrs) 3656.6 3556.3

Network Speed (kph) 66.9 68.8

Table 25 - Network Statistics – 2030 AM Peak




Network Speed (kph) 66.1 68

Table 26 - Network Statistics – 2015 Inter-Peak


Travel Distance (PCU km) 167858.5 167941



TAble 27 - Network Statistics – 2030 Inter Peak





Table 28 - Network Statistics – 2015 PM Peak




Network Speed (kph) 66 67.5

Table 29 - Network Statistics – 2030 PM Peak







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7.1 Introduction

This section details an analysis of the post-variable demand matrices and subsequent assigned network conditions in

the future year scenarios. This will include analysis of the traffic growth in comparison with national averages, details of

future year traffic flows on key links, a discussion of any significant incidents of junction delay and details of

volume/capacity on the various key links. The analysis will cover both future years and compare the Do Minimum and Do

Something networks.

Flow diagrams summarising the modelled outputs for key links in each scenario are contained in Appendix B.

7.2 Analysis of Matrix Totals

The matrix totals post-variable demand are summarised in Tables 30 and 31 on the following pages. Although UC4 is

included in the diagram, it is worth noting that this represents HGV traffic and as such was growthed using an NTM

factor as opposed to TEMPRO. The variable demand matrices have also been sectored to show how growth varies

within the model between the base year and modelled years. The results of this are displayed in Tables 32 to 37.

7 Analysis of Traffic Forecasts



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Table 30 - 2007 – 2015 Forecasting Process Matrix Totals

AM 2007 IP 2007 PM 2007

UC1 UC2 UC3 UC4 UC1 UC2 UC3 UC4 UC1 UC2 UC3 UC4

Origin/Destination 10758 2714 7378 1181 Origin/Destination 1780 2654 5895 578 Origin/Destination 12059 3011 8748 950

AM 2015 TEMPRO + Developments IP 2015 TEMPRO + Developments PM 2015 TEMPRO + Developments


Origin 11244 2916 7869 1227 Origin 1971 3066 7113 601 Origin 13563 3117 9908 987

Destination 12270 2802 8286 1227 Destination 1969 3043 7110 601 Destination 12805 3196 9534 987

AM 2015 Constrained to TEMPRO IP 2015 Constrained to TEMPRO PM 2015 Constrained to TEMPRO




AM 2015 Balanced - Finished Pre-VaDMA IP 2015 Balanced - Finished Pre-VaDMA PM 2015 Balanced - Finished Pre-VaDMA



AM 2015 Post-VADMA DM IP 2015 Post-VADMA DM PM 2015 Post-VADMA DM



AM 2015 Post-VADMA DS IP 2015 Post-VADMA DS PM 2015 Post-VADMA DS





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Table 31 - 2007 – 2030 Forecasting Process Matrix Totals

AM 2007 IP 2007 PM 2007



AM 2030 TEMPRO + Developments IP 2030 TEMPRO + Developments PM 2030 TEMPRO + Developments




AM 2030 Constrained to TEMPRO IP 2030 Constrained to TEMPRO PM 2030 Constrained to TEMPRO




AM 2030 Balanced - Finished Pre-VaDMA IP 2030 Balanced - Finished Pre-VaDMA IP 2030 Balanced - Finished Pre-VaDMA



AM 2030 Post-VADMA DM IP 2030 Post-VADMA DM PM 2030 Post-VADMA DM



AM 2030 Post-VADMA DS IP 2030 Post-VADMA DS PM 2030 Post-VADMA DS





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Table 32 - Sectored Growth

TEMPRO AM 2007-2015

Origin Destination

Northumberland 1.003 1.035

GB Average 1.056 1.056

AM Base 1 2 3 4 5 6

1 596 356 324 125 1220 55 2 555 413 363 456 225 313 3 218 112 787 488 432 468 4 111 245 441 1211 512 852 5 623 74 686 377 317 757 6 70 135 580 877 1669 4987

2015 AM DM

1 2 3 4 5 6

1 586 356 376 201 1231 92 2 556 390 396 459 210 335 3 319 111 930 512 433 473 4 322 237 428 1138 502 891 5 615 67 693 373 369 730 6 175 132 607 890 1568 4924

2015 AM DS

1 2 3 4 5 6

1 514 319 282 164 1090 70 2 497 339 368 422 185 283 3 274 85 853 471 390 455 4 319 210 373 999 380 759 5 541 53 582 299 330 644 6 155 95 541 782 1386 4348

2015 AM DM Growth

1 2 3 4 5 6

1 0.98 1.00 1.16 1.61 1.01 1.67 2 1.00 0.94 1.09 1.01 0.93 1.07 3 1.46 0.99 1.18 1.05 1.00 1.01 4 2.91 0.96 0.97 0.94 0.98 1.05 5 0.99 0.91 1.01 0.99 1.17 0.96 6 2.49 0.97 1.05 1.02 0.94 0.99

2015 AM DS Growth

1 2 3 4 5 6

1 0.86 0.90 0.87 1.31 0.89 1.26 2 0.90 0.82 1.01 0.93 0.82 0.90 3 1.26 0.76 1.08 0.97 0.90 0.97 4 2.88 0.86 0.85 0.82 0.74 0.89 5 0.87 0.71 0.85 0.79 1.04 0.85 6 2.21 0.70 0.93 0.89 0.83 0.87



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TEMPRO IP 2007-2015

Origin Destination



IP Base 1 2 3 4 5 6

1 86 68 185 92 863 56 2 66 95 196 141 128 131 3 277 199 294 436 360 322 4 105 150 408 170 356 450 5 815 109 323 429 77 457 6 104 140 344 540 449 1482

2015 IP DM 1 2 3 4 5 6

1 80 63 291 118 856 68 2 63 88 203 148 129 145 3 412 207 438 468 380 377 4 125 166 443 173 383 532 5 772 100 338 426 90 444 6 114 150 394 616 430 1497

2015 IP DS 1 2 3 4 5 6

1 80 64 276 135 866 70 2 64 88 204 148 126 144 3 389 208 443 474 378 379 4 117 165 448 174 380 533 5 772 101 338 426 90 444 6 114 151 394 616 430 1497

2015 IP DM Growth

1 2 3 4 5 6

1 0.94 0.93 1.57 1.28 0.99 1.23 2 0.96 0.93 1.03 1.05 1.01 1.10 3 1.49 1.04 1.49 1.07 1.05 1.17 4 1.19 1.11 1.09 1.02 1.08 1.18 5 0.95 0.92 1.05 0.99 1.17 0.97 6 1.09 1.07 1.15 1.14 0.96 1.01

2015 IP DS Growth

1 2 3 4 5 6

1 0.94 0.93 1.49 1.46 1.00 1.26 2 0.97 0.93 1.04 1.04 0.99 1.10 3 1.40 1.05 1.50 1.09 1.05 1.18 4 1.11 1.10 1.10 1.02 1.07 1.18 5 0.95 0.92 1.04 0.99 1.16 0.97 6 1.09 1.07 1.15 1.14 0.96 1.01



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TEMPRO PM 2007-2015

Origin Destination



PM Base 1 2 3 4 5 6

1 704 658 276 89 616 108 2 407 476 136 302 112 179 3 336 298 1020 438 465 558 4 82 477 548 1428 403 996 5 1193 205 479 457 380 2772 6 108 262 467 825 1222 5285

2015 PM DM

1 2 3 4 5 6

1 683 638 425 219 642 223 2 395 454 132 305 111 181 3 435 355 1166 461 482 597 4 142 500 606 1369 429 1035 5 1162 183 495 444 421 2621 6 126 263 470 888 1144 5300

2015 PM DS

1 2 3 4 5 6

1 684 639 413 229 653 223 2 401 454 134 305 107 181 3 383 351 1206 468 497 633 4 149 494 620 1381 425 1033 5 1162 183 495 445 421 2620 6 128 264 474 891 1144 5299

2015 PM DM Growth

1 2 3 4 5 6

1 0.97 0.97 1.54 2.45 1.04 2.07 2 0.97 0.95 0.97 1.01 0.99 1.01 3 1.30 1.19 1.14 1.05 1.04 1.07 4 1.74 1.05 1.11 0.96 1.07 1.04 5 0.97 0.89 1.03 0.97 1.11 0.95 6 1.17 1.01 1.01 1.08 0.94 1.00

2015 PM DS Growth

1 2 3 4 5 6

1 0.97 0.97 1.50 2.57 1.06 2.06 2 0.99 0.95 0.98 1.01 0.96 1.01 3 1.14 1.18 1.18 1.07 1.07 1.14 4 1.82 1.04 1.13 0.97 1.06 1.04 5 0.97 0.89 1.03 0.97 1.11 0.95 6 1.18 1.01 1.01 1.08 0.94 1.00



Transportation


AM Base 1 2 3 4 5 6

1 596 356 324 125 1220 55 2 555 413 363 456 225 313 3 218 112 787 488 432 468 4 111 245 441 1211 512 852 5 623 74 686 377 317 757 6 70 135 580 877 1669 4987

2030 AM DM

1 2 3 4 5 6

1 594 391 387 247 1293 117 2 581 434 428 494 235 388 3 342 120 922 515 430 486 4 329 290 441 1133 522 931 5 637 74 701 373 370 753 6 179 151 617 897 1605 5085

2030 AM DS

1 2 3 4 5 6

1 593 401 369 277 1301 121 2 590 433 431 489 231 387 3 340 121 945 520 441 510 4 376 285 436 1116 517 916 5 636 74 702 374 370 753 6 175 152 619 898 1604 5083

2030 AM DM Growth

1 2 3 4 5 6

1 1.00 1.10 1.20 1.97 1.06 2.11 2 1.05 1.05 1.18 1.08 1.04 1.24 3 1.56 1.07 1.17 1.06 1.00 1.04 4 2.97 1.18 1.00 0.94 1.02 1.09 5 1.02 1.00 1.02 0.99 1.17 0.99 6 2.55 1.12 1.07 1.02 0.96 1.02

2030 AM DS Growth

1 2 3 4 5 6

1 1.00 1.13 1.14 2.21 1.07 2.19 2 1.06 1.05 1.19 1.07 1.03 1.24 3 1.56 1.09 1.20 1.07 1.02 1.09 4 3.40 1.16 0.99 0.92 1.01 1.07 5 1.02 1.00 1.02 0.99 1.17 0.99 6 2.51 1.12 1.07 1.02 0.96 1.02

TEMPRO AM 2007-2030

Origin Destination





Transportation


IP Base 1 2 3 4 5 6

1 86 68 185 92 863 56 2 66 95 196 141 128 131 3 277 199 294 436 360 322 4 105 150 408 170 356 450 5 815 109 323 429 77 457 6 104 140 344 540 449 1482

2030 IP DM 1 2 3 4 5 6

1 85 72 330 133 939 81 2 73 114 231 187 160 184 3 475 241 450 487 393 400 4 144 216 458 181 430 581 5 817 120 347 455 97 473 6 136 187 412 667 458 1601

2030 IP DS 1 2 3 4 5 6

1 85 72 315 154 951 83 2 74 114 234 187 159 184 3 457 243 456 494 397 405 4 144 216 463 181 428 581 5 818 120 347 455 97 473 6 137 187 413 667 458 1601

2030 IP DM

Growth 1 2 3 4 5 6

1 0.99 1.05 1.78 1.44 1.09 1.45 2 1.10 1.21 1.18 1.32 1.26 1.40 3 1.71 1.21 1.53 1.12 1.09 1.24 4 1.36 1.44 1.12 1.07 1.21 1.29 5 1.00 1.10 1.07 1.06 1.26 1.04 6 1.30 1.33 1.20 1.23 1.02 1.08

2030 IP DS

Growth 1 2 3 4 5 6

1 0.99 1.05 1.70 1.67 1.10 1.50 2 1.12 1.20 1.19 1.32 1.25 1.40 3 1.65 1.22 1.55 1.13 1.10 1.26 4 1.37 1.44 1.14 1.07 1.20 1.29 5 1.00 1.10 1.07 1.06 1.26 1.04 6 1.31 1.33 1.20 1.23 1.02 1.08

TEMPRO IP 2007-2015

Origin Destination





Transportation


TEMPRO PM 2007-2015

Origin Destination



PM Base 1 2 3 4 5 6

1 704 658 276 89 616 108 2 407 476 136 302 112 179 3 336 298 1020 438 465 558 4 82 477 548 1428 403 996 5 1193 205 479 457 380 2772 6 108 262 467 825 1222 5285

2030 PM DM

1 2 3 4 5 6

1 695 677 467 232 681 243 2 412 502 148 355 136 216 3 478 390 1158 467 489 624 4 203 540 619 1380 446 1064 5 1194 199 497 457 432 2695 6 150 300 490 922 1179 5532

2030 PM DS

1 2 3 4 5 6

1 695 678 453 249 686 247 2 418 502 149 354 134 217 3 425 385 1203 477 509 659 4 217 542 632 1385 443 1060 5 1194 199 497 457 432 2695 6 151 300 493 926 1179 5531

2030 PM DM Growth

1 2 3 4 5 6

1 0.99 1.03 1.69 2.60 1.10 2.25 2 1.01 1.06 1.08 1.18 1.21 1.21 3 1.42 1.31 1.14 1.07 1.05 1.12 4 2.47 1.13 1.13 0.97 1.11 1.07 5 1.00 0.97 1.04 1.00 1.13 0.97 6 1.39 1.15 1.05 1.12 0.97 1.05

2030 PM DS Growth

1 2 3 4 5 6

1 0.99 1.03 1.64 2.80 1.11 2.29 2 1.03 1.05 1.10 1.17 1.20 1.21 3 1.27 1.29 1.18 1.09 1.10 1.18 4 2.65 1.14 1.15 0.97 1.10 1.06 5 1.00 0.97 1.04 1.00 1.13 0.97 6 1.40 1.15 1.06 1.12 0.97 1.05



Transportation

Tables 32 to 37 on the preceding pages show how growth has varied across sector to sector movements for all peak

periods and modelled years; a comparison can also be made with the origin and destination factors extracted from

TEMPRO for both the local area and national average. What is notable from the results is that growth isn’t uniform

across all sector to sector movements as this will be dependent on the location of new developments. In some

instances there is also negative growth as zones within these sectors are affected when forecast traffic flows are

constrained back to TEMPRO.

The results show that there is significant growth in the sector 4 to sector 1 movement in the AM peak for both the 2015

and 2030 modelled years; this is reversed in the PM peak and is between sector 1 and sector 4. Analysis of the model

has shown that is as a result of a substantial development in the sector 1 area, Morpeth Fairmoor, which is generating a

lot of trips to and from the South East Northumberland area.

Overall, growth is generally greater than the local growth factor as this will be affected by the variable demand modelling.

Growth is however, much more comparable with the national average.

7.3 Analysis of Traffic Flow

The modelled traffic flows indicate that the addition of the A1-SENSLR-MNB to the network will attract vehicles away

from the town centre of Morpeth with a subsequent re-routing of vehicles to the A1 and the proposed bypass. Headline

statistics from the modelled scenarios can be summarised as follows:

- The introduction of the scheme results in increased traffic on the A1. For example, a 10.3% increase in 12 hour

AAWT flow is observed on the A1 northbound between Clifton and the new A1 junction, whilst a 12.2% increase is

observed southbound with the preferred scheme in place in 2030.

- The preferred scheme results in a significant reduction in volumes of traffic through the town centre of Morpeth. For

example:

o 2015 sees a 14.1% reduction northbound and a 8.7% reduction southbound in 12 hour AAWT flows on

the A192 Telford Bridge; a significant bottle neck in the town centre.

o Taking the A192 Peacock Gap, A197 Whorral Bank, A196 Dunces House, A192 Hepscott Park and A197

Clifton as a town centre cordon, the preferred scheme reduces 12 hour AAWT cordon flows by 16.2% in

2015 and 16.7% in 2030 (averaged for both directions).

o The A197 at Whorral experiences the greatest reduction in traffic across the network, with flow reductions

of 26% observed in 2030. This is primarily as a result of traffic diverting to the proposed A1-SENSLR-

MNB.

7.4 Analysis of Delay

The model results show that there are some junctions within the modelled area that experience very high junction delay

in the Do Minimum scenario. These junctions are predominantly, although not exclusively, within Morpeth town centre.

Analysis of the model in the Do Something scenario has shown that high junction delay is less of a problem as traffic

diverts away from Morpeth town centre to use the new A1 junction and the A1-SENSLR-MNB. The following section

summarises junctions with high delay for each of the peak periods for the future year 2030; this is considered to

represent a worst case scenario. For the purpose of this analysis, a value of 60 seconds was used to identify junctions

with high delay.



Transportation

Figure 3 – AM 2030 Do Minimum Delay

There are several junctions in the 2030 Do Minimum AM Peak which have a high level of delay; these are predominantly

in Morpeth town centre. It has already been outlined that there is a problem with congestion in Morpeth town centre and

the increase in traffic alongside no additional capacity only exacerbates this problem further. The delay ranges from 64-

227 seconds.

The A1 also experiences delay on the approach into Newcastle and this is reflective of conditions in the base year.



Transportation

Figure 4 – AM 2030 Do Something Delay

There is only one junction in Morpeth Town Centre which experiences a high level of delay in the 2030 Do Something

AM Peak. This is the Castle Bank/Goose Hill junction and is as a result of a reduction in traffic through this area as

people choose to use the bypass and the new A1 junction. Delay at this junction is 150 seconds which has reduced

from 202 seconds in the Do Minimum scenario.

Delay on the A1 approach into Newcastle is still present in the Do Something model as this is reflective of existing

conditions and will not be affected by the scheme.



Transportation

Figure 5 – IP 2030 Do Minimum Delay

Unlike the 2030 Do Minimum AM Peak, there are few junctions in the 2030 Do Minimum inter-peak which exhibit a high

level of delay. There is however, one exception.

A high level of delay is observed in the centre of Morpeth and is caused by right turning traffic on the minor road having

to give way to the mainline flow; the model shows 103 seconds of delay at this junction. This is considered

representative of the current situation.



Transportation

Figure 6 – IP 2030 Do Something Delay

The screen print above, taken from the 2030 IP Do Something SATURN model, illustrates that there are no junctions

which experience a high level of delay in this future year and time period.



Transportation

Figure 7 – PM 2030 Do Minimum Delay

In the 2030 Do Minimum PM Peak, there are several junctions which experience a high level of delay within the

modelled area. Similarly to the AM Peak, these junctions are, for the most part, in Morpeth town centre and are caused

by an increased level of traffic without any additional road capacity being provided. Delays range from 62-236 seconds.

Delay is also experienced on the A1 and A19 and is reflective of current conditions. Delay on the A697 is as a result of

the road approaching capacity.



Transportation

Figure 8 – PM 2030 Do Something Delay

Only one junction in Morpeth town centre exhibits a high level of delay in the 2030 Do Something PM Peak; Castle

Bank/Goose Hill junction. However, the delay at this junction is greatly reduced from the Do Minimum scenario. The

reduction in delay across the town centre is caused by a reduction in traffic flow as people choose to use the new A1

junction and bypass.

Delay is still experienced by vehicles using the A1, A19 and A697 as these links are unaffected by the scheme.

7.5 Analysis of Capacity

The model has been analysed to identify links that are at or above capacity in both the Do Minimum and Do Something

scenarios and ensure that this is reasonable. Similarly to the previous section, the problem is greatest in the Do

Minimum scenario with a number of links in Morpeth Town Centre being affected. This is analysed in greater detail in

the following section. For the purpose of this analysis a flow to capacity ratio of 85% was used to display links which are

at or above capacity.



Transportation

Figure 9 – AM 2030 Do Minimum Capacity

There are a number of links in the 2030 AM Do Minimum scenario which are at or above capacity. These are

predominantly links which are already recognised as being congested and therefore, as a result of an increase in traffic

flows, the problem is intensified.

Capacity issues on the northbound A192 approach to the Morpeth Fairmoor site access are as a result of development

traffic.

One link on the A1 is also approaching capacity at 91%. The A1 can become heavily congested in the AM peak and this

capacity issue is not considered unreasonable.



Transportation

Figure 10 – AM 2030 Do Something Capacity

In the 2030 Do Something AM Peak, the VoC for the eastbound approach and southbound approach to the Telford

Bridge remains a problem at 94% and 93% respectively. This however, is to a much lesser degree than in the Do

Minimum scenario when these links were operating above 100% capacity.



Transportation

Figure 11 – Inter-Peak 2030 Do Minimum Capacity

Similar to the AM peak, there are capacity issues at the Telford Bridge junction in the centre of Morpeth in the 2030

Inter-Peak model. This junction is recognised as being a highly constrained junction in the current year and it is

therefore not surprising that, without any highway improvements, this junction is exhibiting signs of congestion in the

future year 2030.



Transportation

Figure 12 – Inter-Peak 2030 Do Something Capacity

Figure 11 above shows that, with the inclusion of the A1-SENSLR-MNB, the capacity issues in the centre of Morpeth for

a standard inter-peak our disappear.



Transportation

Figure 13 – PM 2030 Do Minimum Capacity

There are several links in the centre of Morpeth where the volume to capacity ratio is above 85% in the 2030 PM peak.

Similarly to the AM Peak, these links have already been identified as suffering from congestion and therefore, as a result

of an increase in traffic flows without any additional road capacity, the problem is exacerbated.



Transportation

Figure 14 – PM 2030 Do Something Capacity

Similar to the AM peak, the Telford Bridge junction remains a problem in the 2030 PM peak with the inclusion of the A1-

SENSLR-MNB.

7.6 Analysis of Speeds

There are some areas of the model where very slow speeds are incurred by vehicles; these are mostly between origin

destination pairs within Morpeth Town Centre where the congestion problem is at its greatest. The problem is more

prevalent in the Do Minimum scenario as traffic diverts away from this area in the Do Something scenario. The following

section summarises some extreme examples of where very slow speeds are experienced in the 2030 model and the

reasons behind why these slow speeds have occurred. The 2030 model is considered to represent a worst case

scenario.

AM 2030 Do Minimum

926-931 (UC1)

Time (s) 408

Delay (s) 219

Dist (m) 490

Speed (kph) 4.32



Transportation

The average speed for this origin destination pair is low because vehicles experience a significant delay exiting from

zone 926 and giving way to traffic on the main flow. As the distance between the origin destination pair is small, vehicles

do not have time to increase their average speed.

The average speed for this origin destination pair is low because vehicles experience significant delay exiting the St

Mary’s Field/A197 junction and having to cross the main flow of traffic. As the distance between the origin destination

pair is small, vehicles do not have time to increase their average speed.

PM 2030 Do Minimum

AM 2030 Do Something

The average speed for this origin destination pair is low because it takes vehicles time to exit the St Mary’s Field/A197

junction. As the distance between the origin destination pair is small, vehicles do not have time to increase their average

speed.

PM 2030 Do Something

Similarly to the AM Peak, the average speed for this origin destination pair in the PM Peak is low because it takes

vehicles time to exit the St Mary’s Field/A197 junction. As the distance between the origin destination pair is small,

vehicles do not have time to increase their average speed.

7.7 Summary

The analysis has shown that there are some areas within the model that suffer from high delay, are over capacity or

have low speeds and is true of both the Do Minimum and Do Something scenarios. Investigation of these areas has

however shown that they are entirely reasonable and expected given the level of traffic in the model.

929-937 (UC1)

Time (s) 60

Delay (s) 26

Dist (m) 30

Speed (kph) 1.79

921-924 (UC1)

Time (s) 168

Delay (s) 160

Dist (m) 0

Speed (kph) 0

929-937 (UC1)

Time (s) 34

Delay (s) 9

Dist (m) 30

Speed (kph) 3.15

929-937 (UC1)

Time (s) 37

Delay (s) 8

Dist (m) 30

Speed (kph) 2.91



Transportation

Table 38 - Forecast Traffic Flows – AM Peak Period

Road Description Direction A Node B Node AM peak hour traffic flows (all traffic)

2015 DM 2015 DS % change 2030 DM 2030 DS % change

A1 North of A697 NB 211 209 666 679 1.84% 699 726 3.79%

SB 209 213 658 713 8.43% 715 765 7.07%

A1 A192 to A197 (Fairmoor) NB 111 115 786 935 18.94% 831 994 19.56%

SB 116 111 1402 1810 29.17% 1513 1917 26.69%

A1 Morpeth Bypass NB 108 107 786 906 15.30% 831 946 13.81%

SB 107 108 1402 1537 9.69% 1513 1674 10.64%

A1 South of A197 (Stannington) NB 144 143 1570 1615 2.86% 1621 1673 3.23%

SB 101 144 1997 2026 1.47% 2114 2169 2.60%

A192 Peacock Gap NB 138 173 748 363 -51.48% 760 402 -47.15%

SB 173 138 666 514 -22.80% 736 533 -27.60%

A193 Bridge Street EB 127 126 547 497 -9.13% 554 509 -8.14%

WB 126 127 630 428 -32.11% 636 434 -31.66%

A197 Whorral Bank EB 137 118 486 369 -23.97% 546 378 -30.84%

WB 118 137 916 686 -25.16% 919 727 -20.85%

A196 Dunce's House EB 119 708 357 352 -1.30% 360 363 0.80%

WB 708 119 444 303 -31.61% 501 319 -36.26%

A192 Hepscott Park EB 759 121 579 531 -8.17% 593 541 -8.75%

WB 121 759 412 417 1.13% 442 435 -1.58%

A192 Telford Bridge NB 158 126 1245 1008 -18.98% 1263 1024 -18.94%

SB 126 158 1161 1102 -5.05% 1164 1118 -3.97%

A197 Clifton EB 104 283 753 678 -9.98% 759 697 -8.21%

WB 283 104 545 440 -19.37% 551 446 -19.13%

A197 Pegswood Bypass EB 118 744 338 363 7.29% 392 420 7.17%

WB 744 118 533 686 28.62% 546 723 32.36%

MNB East of St George's

roundabout

EB 801 800 270 - 357 -

WB 800 801 481 - 520 -

MNB West of St George's

roundabout

EB 803 801 301 - 388 -

WB 801 803 509 - 551 -



Transportation

Table 39 - Forecast Traffic Flows – Inter Peak Period

Road Description Direction A Node B Node Interpeak hour traffic flows (all traffic)


A1 North of A697 NB 211 209 741 757 2.17% 799 829 3.72%

SB 209 213 700 741 5.83% 767 802 4.45%


SB 116 111 938 1165 24.24% 1063 1274 19.80%


SB 107 108 938 1042 11.10% 1063 1187 11.61%

A1 South of A197 (Stannington) NB 144 143 1240 1261 1.73% 1320 1348 2.10%

SB 101 144 1342 1372 2.25% 1484 1517 2.22%

A192 Peacock Gap NB 138 173 534 421 -21.17% 619 507 -18.18%

SB 173 138 432 313 -27.49% 491 357 -27.32%


WB 126 127 532 462 -13.18% 554 491 -11.34%

A197 Whorral Bank EB 137 118 579 504 -13.02% 641 550 -14.29%

WB 118 137 551 493 -10.64% 595 528 -11.26%

A196 Dunce's House EB 119 708 287 277 -3.52% 303 298 -1.76%

WB 708 119 261 230 -11.53% 283 246 -13.21%


WB 121 759 365 349 -4.32% 392 375 -4.44%


SB 126 158 1048 939 -10.41% 1096 976 -10.93%

A197 Clifton EB 104 283 340 288 -15.45% 352 297 -15.62%

WB 283 104 426 352 -17.22% 443 354 -20.19%


WB 744 118 311 339 8.98% 332 375 13.02%

MNB East of St George's roundabout EB 801 800 154 - 176 -

WB 800 801 142 - 179 -


roundabout

EB 803 801 177 - 200 -

WB 801 803 163 - 204 -



Transportation

Table 40 - Forecast Traffic Flows – PM Peak Period

Road Description Direction A Node B Node PM peak hour traffic flows (all traffic)


A1 North of A697 NB 211 209 527 474 -10.09% 551 477 -13.54%

SB 209 213 1348 1480 9.81% 1416 1564 10.44%


SB 116 111 888 1098 23.72% 1018 1168 14.69%


SB 107 108 281 344 22.39% 338 404 19.63%

A1 South of A197 (Stannington) NB 144 143 780 632 -18.99% 824 660 -19.90%

SB 101 144 409 370 -9.57% 435 397 -8.87%

A192 Peacock Gap NB 138 173 433 409 -5.73% 492 427 -13.09%

SB 173 138 604 530 -12.30% 562 536 -4.71%


WB 126 127 558 486 -12.94% 613 521 -15.01%

A197 Whorral Bank EB 137 118 534 446 -16.48% 602 449 -25.52%

WB 118 137 734 424 -42.23% 739 466 -36.94%

A196 Dunce's House EB 119 708 1952 1987 1.76% 1998 2074 3.85%

WB 708 119 1452 1556 7.15% 1608 1656 2.97%


WB 121 759 764 613 -19.71% 882 668 -24.34%


SB 126 158 579 614 6.09% 607 645 6.28%

A197 Clifton EB 104 283 566 475 -16.17% 541 478 -11.59%

WB 283 104 388 269 -30.75% 409 285 -30.13%


WB 744 118 532 519 -2.43% 515 535 3.90%

MNB East of St George's roundabout EB 801 800 368 - 405 -

WB 800 801 188 - 263 -


roundabout

EB 803 801 406 - 444 -

WB 801 803 219 - 300 -



Transportation

8.1 Introduction

In order to test uncertainty in future year forecasting, it is recommended in WebTAG unit 3.15.5 that a series of

proportional sensitivity tests are conducted in order to account for the possibility of forecasting error in the central

scenario. To this end 2 additional future year scenarios have been developed. The preceding chapters of this report has

focused in detail on the central scenario, this section will deal with the construction and analysis of the Pessimistic and

Optimistic scenarios. A description of the 3 scenarios is detailed below:

- Pessimistic, with low growth and only near certain developments

- Central, with medium growth and more than likely/near certain developments

- Optimistic, with high growth and all developments

8.2 Background Growth

The background growth for the central scenario was calculated as described in Chapter 4.2, to adjust this into high and

low growth variations an additional step is required. This section details the calculation used to either increase or

decrease the central TEMPRO and NTM growth factors. The guidance in WebTAG unit 3.15.5 sets out the process for

taking such uncertainty into consideration in modelling a highway scheme.

‘To deal with such uncertainty in highway models, it is expected that the analyst will explore scenarios using an

appropriate range about the central forecast of ±2.5% for traffic forecasts one year ahead, rising with the square root of

the number of years to ±15% for forecasts 36 years ahead.’

Optimistic and pessimistic growth factors were therefore calculated using the following formulas;

Pessimistic factor = -2.5*

Optimistic factor = +2.5*

The results from these calculations are detailed in the following table for the Northumberland authority;

Table 41 - Pessimistic and Optimistic Growth Factors for the Castle Morpeth Authority

Forecast Year

Time Period

Trip End TEMPRO Pessimistic

Uncertainty Optimistic

Uncertainty

Pessimistic Factor Optimistic Factor

Orig. Dest. Orig. Dest. Orig. Dest

2015

AM 1.003 1.035 93% 107% 0.933 0.962 1.073 1.107

IP 1.059 1.056 93% 107% 0.985 0.982 1.133 1.13

PM 1.035 1.015 93% 107% 0.963 0.944 1.108 1.086

2030

AM 1.028 1.059 88% 112% 0.904 0.931 1.151 1.186

IP 1.138 1.132 88% 112% 1.001 0.996 1.274 1.268

PM 1.070 1.052 88% 112% 0.942 0.926 1.198 1.179

As can been seen in the above Table 41, the pessimistic scenario results in growth factors that are less than 1, meaning

that there is actually a decrease in traffic between the base and future years. This is due to the comparatively low level

of growth contained within TEMPRO for the Northumberland authority. Table 42 below shows a comparison between the

2007-2030 growth rates between Northumberland, a typical authority in North Yorkshire and the GB national average.

8 Sensitivity Testing



Transportation

Table 42 – 2007-2030 Growth Rates

2007 to 2030

Northumberland North Yorkshire Great Britain

Orig Dest Orig Dest Orig Dest

AM 2.8% 5.9% 17.7% 19% 15.9% 15.9%

IP 13.8% 13.2% 24.3% 24.3% 22.7% 22.7%

PM 7% 5.2% 20% 19.1% 17% 17%

As Table 42 shows, in comparison to the Great Britain average and North Yorkshire growth factors, Castle Morpeth is

very low. Following the approved WebTAG method of accounting for uncertainty in TEMPRO growth we are left with

pessimistic matrices lower than the base year of 2007.

8.3 Uncertainty in Developments

As well as calculating low and high growth scenarios for the background growth we must also consider the status of the

planned developments within each of the three scenarios. To enable us to do this a planning status and uncertainty log

for each site was provided by the planning department at Northumberland County Council. The planning status comes

directly from the current status of each site within the planning department. This status was then used to assign each

site an uncertainty level from the below list (in increasingly levels of certainty) provided by WebTAG unit 3.15.5:

- Hypothetical

- Reasonably Foreseeable

- More than Likely

- Near Certain

The planning status of each development and subsequent uncertainty categorisation is listed in Table 43 below. The

tables also details within which of the scenarios each development is present.

Table 43 - Planned Developments in Modelled Area – Uncertainty Log

Site Proposed Land Use

Planning Status

Probability of Input (DfT Categories)

Future Year Scenarios

Likelihood of Site Completion %

OP CE PE

Hadston Industrial Estate

B2 Allocated site Reasonably foreseeable

OP 0 100

Morpeth Fairmoor (Northgate)

B1 Application awaiting a decision

More than likely OP CE 100 100

Morpeth Fairmoor (Northgate)

C3 Application awaiting a decision


Longhorsely Land at East Road

C3 Application approved but not yet started

Near Certain OP CE PE 100 100

Morpeth Ex to Land Fairmoor


OP 0 0

Morpeth Fairmoor Adj to A1


OP 0 100

Morpeth Station Yard

B1 Site complete Near Certain OP CE PE 100 100

Stannington, part St. Mary's Hospital (mixed use)



Stannington, part St. Mary's Hospital

B1 Application approved but




Transportation


Planning Status




OP CE PE

(mixed use) not yet started

Ellington Colliery(mixed Use)



Ellington Colliery(mixed Use)



Lynemouth Colliery(mixed Use)



Lynemouth Colliery(mixed Use)



Low Stanners Morpeth mixed development

A1 Application awaiting a decision


Goose Hill Factory site/ Davidsons Garage, Morpeth

A1 Application approved but not yet started


Goose Hill Factory site/ Davidsons Garage, Morpeth



Stobswood Brickworks



St Georges,Morpeth Phase 1

C3

Planning application expired but working with HCA



C3 Dependent on A1-SENSLR-MNB

Reasonably foreseeable

0 100


C3 Dependent on A1-SENSLR-MNB


0 100

Hepscott Park B1 No planning status

Hypothetical OP 0 0

Hepscott Park C3 No planning status

Hypothetical OP 0 0

Park View, Hadston (Phase 3) West of A1068



NCB Workshop site, Ashington

C3 Site under construction


ASDA, Lintonville Terrace, Ashington

A1 Site complete Near Certain OP CE PE 100 100

South of Wansbeck General Hospital, Ashington



Ashwood Business B1 Site under Near Certain OP CE PE 100 100



Transportation


Planning Status




OP CE PE

Park, North Seaton construction

Wansbeck Business Park, Ashington

B1 Site under construction


Lintonville Enterprise Park, Ashington

B1 Site under construction


Former Ashington Hospital, Station Road



Existing Northumberland College



Ellington Colliery (site offices)

B1 Application approved but not yet started


Northumberland College (Hawthorne Annexe), Ashington



South Loansdean, Morpeth (SHLAA-3007)

C3 SHLAA site Hypothetical OP 0 100

NCC sites Fire Station, County Hall adjoining land

C3 No planning status

Hypothetical OP 0 0

Stobhill South C3 SHLAA site Hypothetical OP 0 0

South Shore Links Road, Blyth



Land at Wheatridge Park, Seaton Delaval



Land at area 2A Chase Farm Drive, Blyth



Land at West Blyth accessed from Chase Farm Drive, Blyth (Phases 1&2)



Land at West Blyth accessed from Chase Farm Drive, Blyth (Phase 3)

C3 Application approved


Asda Stores Limited, Cowpen Road, Blyth

A1 Application approved




Transportation


Planning Status




OP CE PE

Tesco Supermarket, Market Place, Bedlington



Morrisons, Regent Street, Blyth



Narec Test Site, Albert Street, Blyth

B1 Application approved


Narec Test Site, Albert Street, Blyth



Queen Street, Amble



Queen Street, Amble



A1068 (land west of) and Marks Bridge (land south of), Amble



Coquet Enterprise Park, Amble



Land at Crofton Mill Industrial Estate, Blyth



Crossland Park, Cramlington



Amble Boat Co, Amble - Residential



Amble Boat Co, Amble - Employment



Amble Boat Co, Amble - Retail

A1 Application awaiting a decision


Land East of A189 and South of Lanercost Park, Cramlington



West Hartford Business Park, Cramlington



South West Sector, Cramlington

C3 Growth point site


OP 50 100

Sanderson Arcade, Morpeth

A1 Site completed Near Certain OP CE PE 100 100

The Kylins, Morpeth



East Ashington SPD Area


OP 0 100



Transportation


Planning Status




OP CE PE

East Ashington SPD Area

A1 Allocated site Reasonably foreseeable

OP 0 100

Jubilee Industrial Estate


OP 0 100

North Seaton Industrial Estate


OP 100 100

West Sleekburn Industrial Estate


OP 100 100

Cambois C3 Growth point site


OP 25 75

Welbeck Terrace, Pegswood



The Mount, Morpeth

D1 Application approved


Land east of Whorral Bank Roundabout, Morpeth

D1 Application awaiting a decision


Northgate Hospital (SHLAA 3079)

C3 Application submitted


*This development is conditional on the completion of the bypass and as such, it has not been included in the future year matrices since

this will not enable a like for like comparison between the Do Minimum and Do Something scenarios.

8.4 Analysis of Matrices and Assignment

This section details the resulting Pessimistic and Optimistic matrices from the above process and gives a description of

the future year assigned network in each scenario. As with the central scenario the matrices were put through a variable

demand assessment to get the final matrix totals. Tables 44 and 45 below details a comparison of the post-variable

demand matrix totals for all three growth scenarios in the two forecast years:

Table 44 – 2015 Post-Variable Demand Sensitivity Totals

2015 – Variable Demand Totals

Time Period

Scenario Pre VADMA

DM Post VADMA

Pre-Post % Change

DS Post VADMA

Pre-Post % Change

DS-DM % Change

AM

Pessimistic 20981 21143 0.77% 21141 0.76% -0.01%

Central 22468 22628 0.71% 22662 0.86% 0.15%

Optimistic 23955 24076 0.51% 24129 0.73% 0.22%

IP

Pessimistic 10759 10913 1.43% 10889 1.20% -0.22%

Central 11524 11725 1.75% 11726 1.75% 0.00%

Optimistic 12289 12496 1.69% 12501 1.73% 0.04%

PM

Pessimistic 23695 23822 0.54% 23838 0.60% 0.07%

Central 25404 25502 0.39% 25590 0.73% 0.34%

Optimistic 27113 27182 0.25% 27291 0.65% 0.40%



Transportation

Table 45 – 2030 Post-Variable Demand Sensitivity Totals

2030 – Variable Demand Totals

Time Period

Scenario Pre VADMA

DM Post VADMA

Pre-Post % Change

DS Post VADMA

Pre-Post % Change

DS-DM % Change

AM

Pessimistic 20604 20967 1.76% 20973 1.79% 0.03%

Central 23214 23494 1.21% 23586 1.60% 0.39%

Optimistic 25824 25916 0.36% 26096 1.05% 0.69%

IP

Pessimistic 11032 11387 3.22% 11374 3.10% -0.12%

Central 12439 12813 3.01% 12849 3.30% 0.28%

Optimistic 13845 14203 2.58% 14246 2.89% 0.30%

PM

Pessimistic 23419 23714 1.26% 23728 1.32% 0.06%

Central 26452 26668 0.81% 26774 1.22% 0.40%

Optimistic 29485 29591 0.36% 29763 0.94% 0.58%

As can been seen in the above tables the matrix totals follow a definite progression from Pessimistic to Central to

Optimistic in terms of the matrix size. The Pessimistic totals are still lower than the base year after the variable demand

process in the AM and PM time periods, despite there being a increase in the totals due to induced traffic. This stems

from the low growth present in TEMPRO for the Castle Morpeth region (as described in chapter 8.2) which results in a

very low Pessimistic matrix when all of the WebTAG guidance is followed to the letter.

Flow diagrams showing the forecast traffic on key links in included within Appendix B, as expected from the matrix

totals this shows an increase in traffic both along the bypass and through the town centre in Optimistic scenario. The

Pessimistic scenario, following on from the issues described above has a level of traffic lower than that of the 2007 base

in some areas and as such is relatively free flowing.



Transportation

9.1 Introduction

In order to best represent the value for money scheme of the A1-SENSLR-MNB, a number of additional models have

been created as summarised in this section of the report.

9.2 Unconstrained Models

The TEMPRO growth factors for Northumberland and Castle Morpeth are extremely low in comparison to similar

geographical areas and the Great Britain average. They are based on demographic forecasts that do not match the

Council’s vision for Morpeth and South East Northumberland once the A1-SENSLR-MNB has been completed. An

analysis of the planning data which underpins the TEMRPO growth factors has therefore been undertaken for the Castle

Morpeth area to show where any discrepancies may lie.

9.2.1 Employment - the planning data predicts almost no growth in jobs across Northumberland as a whole between 2010

and 2020 and a marginal decrease in jobs for Castle Morpeth. This contradicts the Economic Impact Report which

suggests that the completion of the bypass has the potential to trigger the development of around 5,000 jobs across

South East Northumberland. Additionally, a recent report prepared by David Lock Associates et al has identified that all

five "realistic" development scenarios for Morpeth generate between 1,700 and 3,000 jobs in Morpeth itself. This is

based on a job generation methodology produced on behalf of English Partnerships. The in TEMPRO is also

contradictory to the North East Economic Model which suggests an overall growth in the number of full time equivalent

jobs in Northumberland up between 2010 and 2030 of 2.56%; this figure is expected to be higher in Morpeth.

9.2.2 Households - the planning data predicts growth in households of 6-7% between 2010 and 2020 for Northumberland and

Castle Morpeth which is less than the predictions for, say Durham (9%) and Newcastle (10%). For planning purposes

the County Council still uses RSS housing figures for the County although, going forward, national planning policy is that

we should be seeking to increase provision above RSS levels. Housing provision will be addressed through the new

authority LDF Core Strategy but this is at a relatively early stage in plan preparation.

9.2.3 Population – the planning data suggests a significant reduction in working age population in Northumberland and a

major increase in the 65+ age group. Data comes from the ONS population projections to 2033 with the calculations

mainly being based on the last 5 years worth of historical data alongside 'expert advice' on future trends. Looking at the

data there is an increase in 65+ between 2003 and 2008 but it is difficult to see how this can be projected forward to

2033. The same applies to the predicted downturn in working age population (15-65). The delivery of the SENSLR is

about removing barriers to development and creating more sustainable communities through additional residential

provision and employment growth. This should change established demographics.

When the forecasted trip generation for each of the development sites is calculated for the Castle Morpeth area, the

percentage growth is significantly higher than the TEMPRO growth factor. This is highlighted in Tables 46 and 47

below.

Table 46: 2007-2015 TEMPRO/Development growth comparison (Castle Morpeth)

Time Period Base * TEMPRO 6.2 Base + Developments

AM average growth 1.55% 19.48%

Interpeak average growth 4.88% 23.68%

PM average growth 2.11% 19.27%

9 Additional Testing



Transportation

Table 47: 2007-2030 TEMPRO/Development growth comparison (Castle Morpeth)

Time Period Base * TEMPRO 6.2 Base + Developments

AM average growth 1.80% 22.73%

Interpeak average

growth 8.62% 27.08%

PM average growth 3.14% 22.33%

By constraining back to TEMPRO, the traffic conditions in the future years are being significantly underestimated. An

alternative methodology has therefore been developed and a full economic assessment for this carried out.

9.2.4 Methodology

In order to provide a more realistic representation of the forecast traffic growth in the Castle Morpeth area, traffic growth

in this area has not been constrained back to TEMPRO. Where developments have been specified, the development

traffic has been added to the base row and column total for this zone but has not be growthed by TEMPRO. Where no

developments are specified, the base row and column totals has been growthed to the future level using TEMPRO

growth factors to take account of background traffic growth.

In the wider modelled area, where zones represent greater spatial areas and the impact of development trips on traffic

levels in Castle Morpeth is less pronounced, the methodology outlined in WebTAG guidance has been adopted and all

zones in this area are constrained back to TEMPRO.

The new methodology is summarised in the Table 48 below.

Table 48: Proposed Methodology for Forecasting

Zone Methodology

Castle Morpeth zone – no

development

Base * Castle Morpeth TEMPRO

Castle Morpeth zone – with

development

Base + Development, no TEMPRO

Wider modelled area zone

– no development

Base * Northumberland TEMPRO, constrained back to wider

modelled area TEMPRO total

Wider modelled area zone

– with development

Base * Northumberland TEMPRO + Development, constrained back

to wider modelled area TEMPRO total

A full economic assessment has been carried out using the above methodology and is summarised in the A1-SENSLR-

MNB Economic Assessment Report.

9.3 Off-peak, Weekend and Bank Holiday Models

The Department for Transport have suggested that all economic assessment should be undertaken for a full year of

8760 hours. This would take account of not only AM, PM and inter-peak hours, but also of off-peak, weekend and bank

holiday traffic. In order to provide appropriate time, distance and demand skims for the economic assessment new

traffic models needed to be created to represent traffic conditions during these time periods. The methodology adopted

to undertake this process is summarised below.



Transportation

The TUBA methodology guidance states that in order to extend the annualisation to an hour which has not been

specifically modelled in the original scope of the scheme, it is preferable to use appropriate 24 hour traffic counts to

factor a demand matrix as opposed to actual TUBA cost data (e.g. journey time), as the relationship may not be linear.

Therefore, in order to account for all off-peak, weekend and bank holiday hours the demand matrices in the current

model have been factored by appropriate traffic counts and reassigned to the SATURN model to produce new journey

time costs. The inter-peak ‘other’ matrix and inter-peak HGV matrix have been used as a starting point for this analysis

as this time period best represents the journey purposes which would be observed.

The following section sets out the methodology in more detail using the off-peak time period as an example.

9.3.1 Methodology

The ‘other’ journey purpose demand matrix for the inter-peak model has been factored to the level of the average off-

peak hour. In order to adjust the inter-peak matrix to the off-peak level, the following factor has been used:

Factor = Average Off-Peak Hour / Average Inter-Peak Hour

As the demand matrix for the ‘other’ journey purpose is being used as the basis for the off-peak traffic, it was also

necessary to calculate the percentage of ‘other’ traffic which makes up the full demand matrix. An analysis of the light

vehicle matrix totals for all of the modelled years was therefore carried out.

The ‘other’ matrix needed to be factored up to represent a full inter-peak demand matrix and then factored down to

represent the off-peak period. This has been calculated as follows:

(1 / Percentage of ‘Other’ Traffic) * Inter-Peak to Off-Peak Factor

It was also necessary to take into account the HGV traffic and the proportion of the total traffic which is assigned to

HGVs. As the model includes a section of the A1, there will be a number of long haul HGV journeys present in the off-

peak period. There was no classified data available for the overnight time period and so the same calculation was used

for the inter-peak HGV demand matrix. It is logical to assume that the HGV traffic would not decrease to the same

amount as the light traffic due to the A1 overnight being a major route for goods vehicles. However, there is currently no

information to back this assumption up and so decreasing it by the same level can be considered a more robust

approach.

Once the matrices were formulated for all the required years and scenarios, they were assigned to the SATURN

networks and results extracted in the usual manner. The results from this SATURN run were then adapted into the

TUBA in the same way as the other time periods.

The flow chart in Figure 15 overleaf, shows the whole process from start to finish

The same methodology was adopted for weekend and bank holiday hours using appropriate ATC data. This is

summarised below.

Weekend and bank holiday annualisation was calculated as follows:

- Hours which were within 90% of an average weekday inter-peak hour were determined and flow weighted to

calculate the annualisation factor for the TUBA assessment. Within the TUBA assessment, the same journey

time/distance cost results from the inter-peak ‘other’ model and the demand matrix for the inter-peak ‘other’ journey

purpose were used and factored up to the full hourly demand;

- The average hourly flow for al other hours was calculated;

- A factor for reducing the inter-peak ‘other’ matrix to weekend or bank holiday levels was calculated;

- The ‘other’ demand matrix was increased to a full hour and then factored to an average weekend or bank holiday

hour;

- The inter-peak HGV matrix was factored down to reduce it to weekend or bank holiday levels;

- The matrices were assigned to the SATURN model and the outputs extracted in the usual manner.



Transportation

The following factors were used for reducing a full inter-peak ‘other’ matrix and an inter-peak HGV matrix to off-peak,

weekend and bank holiday levels.

Table 49: Off-Peak, Weekend and Bank Holiday Factors

Time Period Factor

Off-Peak Factor 0.193

Weekend Factor 0.329

Bank Holiday Factor 0.368



Transportation

Figure 15: Off-Peak, Weekend and Bank Holiday Forecasting Methodology

Extract the relevant model outputs and include in the

TUBA assessment

Run the matrices through current SATURN networks

setup for only 2 user classes

Stack the two matrices into a single off-peak

demand matrix

Factor the matrix to first increase it to the full

interpeak demand and then reduce it to off-peak

levels

Factor the matrix to reduce it to off-peak

levels

Extract the ‘HGV’ journey purpose demand matrix

Extract the ‘Other’ journey purpose demand matrix

2015 and 2030 DM inter-peak demand

matrices



Transportation

10.1 Summary

This report describes the methodology and assumptions that have underpinned the development of the future year

models that have produced the traffic forecasts used in the design, economic and environmental assessment of the of

the A1-South East Northumberland Strategic Link Road-Morpeth Northern Bypass (A1-SENSLR-MNB)

The production of the Base Year model is detailed in the Local Model Validation Report and this formed the basis for the

production of the forecast models.

There are no committed highway schemes of significance in the area therefore the Do-Minimum highway network was

assumed to be the same as the base situation in the future year scenarios.

The preferred option consists of the construction of a new bypass route between the A1 and the existing Pegswood

Bypass, with the construction of a new roundabout on the A1 at St Leonards.

Future year demand matrices were produced for the proposed opening year of 2015 and design year of 2030 based

upon growth predicted by the National Trip End Model (NTEM). Account was also taken of proposed local employment

and residential developments specifically with the total growth factors adjusted accordingly to keep them in line with

NTEM.

To take account of the impacts of future year traffic conditions a full variable demand modelling (VDM) approach has

been taken in developing the future year matrices. A freestanding variable demand modelling process has been

developed for the Morpeth model which is fully compliant with the Department for Transport’s variable demand

guidelines. The process used for the Morpeth project has been based on a similar model developed previously by

AECOM and approved by the Department for Transport.

The introduction of the proposed bypass results in a reduction in travel time and increased average vehicle speeds when

compared to the Do-Minimum scenario. However, an overall increase in vehicle kilometres is observed, primarily as a

result of traffic from the south of Morpeth using the bypass as opposed to travelling through the town centre which

represents an increased journey length of approximately 3km.

The modelled traffic flows indicate that the addition of the A1-SENSLR-MNB to the network will attract vehicles away

from the town of Morpeth with a subsequent re-routing of vehicles to the A1 and the proposed bypass.

10 Summary

Appendices

Appendix A – Scheme

Appendix B – Traffic Flow Diagrams

A1

256 N

127 1

150

23

A197

515 2

55 A192

117 13117 13

17 4 206

Mitford Rd A192 140 20 11 12 21 59 N

53 9 0 184

151 9 28 18

Coopies Lane 197 6 1 A192 231 19

53 27 A196 44 A197 559

193 11 312 83 22

15 288 11 202

274 28 33 37

52 81 407 14 341 225

99 21 61 298 78 25 20

20 10 122 101

30 114 264 172

13 19 80 16

352 6 16352 6 16

80 399

226 56 520

3 48 216 286 15 100 142 684 18

52 5 71 37 409 120

246 128 17 45 345

16 21 A192 48

4 223 A192 297

33 23 59

204 297

15 47 372 278 25

365 84 52

92

24 319 614 212 27

A1 23 103 31 197

A197 A196 53

114 26 193

29 51 15

Key Trip Purpose 76 274

1 52

Commute 198 99 28

Business 27 20

Other 76

HGV 18 A192

30

Client: Northumberland County CouncilAM 2015 Do Minimum Constrained Model Flows

A1

143 53

187 73 1 32 N

95 1

128

19

367 56 A197

176 2 57 1 31

52 A192

121 9121 9

8 5 132

Mitford Rd A192 148 32 11 12 21 28 N

42 11 2 174

149 9 6 18

Coopies Lane 206 6 1 A192 230 19

42 27 A196 44 A197 365

192 11 305 56 22

15 154 11 182

127 28 29 41

47 80 228 14 340 214

74 21 58 248 63 30 20

20 10 93 90

22 97 222 173

13 19 70 16

329 6 16

73 228

185 50 484

3 46 161 257 15 92 115 510 18

23 5 65 29 400 109

214 128 17 51 311

20 15 A192 39

4 218 A192 277

34 23 52

211 257

15 45 390 293 25

314 81 52

66

24 294 461 217 27

A1 28 98 25 206A1

A197 A196 42

125 26 192

29 54 15

Key TripPurpose 77 127

1 47

Commute 223 74 28

Business 34 20

Other 75

HGV 24 A192

30

Client: Northumberland County CouncilAM 2015 Do Something Constrained Model Flows

A1

322 N

128 1

184

27

A197

503 2

58 A192

140 13140 13

20 4 252

Mitford Rd A192 141 20 11 12 21 57 N

54 13 0 192

151 9 54 22

Coopies Lane 197 7 1 A192 230 19

54 27 A196 43 A197 532

191 11 308 84 22

25 327 14 209

294 28 39 47

55 85 401 14 314 224

103 25 66 312 81 33 20

24 10 153 98

36 117 276 166

13 23 75 19

351 6 16351 6 16

82 388

226 59 507

3 50 210 274 15 99 140 671 18

51 5 74 45 403 125

245 131 17 57 353

22 32 A192 57

4 246 A192 298

36 23 60

207 299

17 50 366 276 25

362 84 54

91

24 316 605 218 27

A1 31 107 37 197

A197 A196 54

115 26 191

29 52 25


2 55

Commute 212 103 28

Business 31 24

Other 79

HGV 22 A192

30

Client: Northumberland County CouncilAM 2030 Do Minimum Constrained Model Flows

A1

191 88

194 76 1 32 N

96 1

134

23

384 72 A197

181 2 62 1 31

54 A192

154 9154 9

9 5 141

Mitford Rd A192 142 32 11 12 21 23 N

49 12 2 171

158 9 5 21

Coopies Lane 196 7 1 A192 229 19

49 27 A196 39 A197 384

198 11 308 58 22

18 153 13 186

130 28 32 49

49 85 227 14 341 213

82 25 60 254 59 36 20

24 10 112 95

26 104 228 173

13 23 70 19

328 6 16

74 224

185 46 485

3 54 162 256 15 95 114 507 18

23 5 68 35 397 107

212 131 17 60 315

24 18 A192 47

4 225 A192 278

36 23 53

217 260

18 53 394 295 25

315 82 62

67

24 290 462 218 27

A1 34 96 30 196A1

A197 A196 49

139 26 198

29 56 18


1 49

Commute 227 82 28

Business 37 24

Other 80

HGV 29 A192

30

Client: Northumberland County CouncilAM 2030 Do Something Constrained Model Flows

A1

39 N

140 1

190

16

A197

58 2

142 A192

300 13300 13

11 12 104

Mitford Rd A192 41 5 18 12 21 116 N

59 5 0 314

149 9 10 23

Coopies Lane 43 19 0 A192 92 19

79 27 A196 90 A197 104

142 11 388 105 22

16 41 19 303

39 28 59 20

109 128 51 14 101 338

119 16 108 55 90 15 20

11 10 170 110

10 163 102 296

13 19 174 24

54 6 1654 6 16

76 89

186 156 163

3 12 66 62 15 259 230 133 18

90 5 92 13 570 206

235 245 17 43 497

18 22 A192 35

4 59 A192 80

77 23 113

196 268

14 21 114 370 25

96 175 37

137

24 346 96 366 27

A1 27 171 35 43

A197 A196 79

15 26 142

29 45 16


6 109

Commute 13 119 28

Business 37 11

Other 50

HGV 1 A192

30

Client: Northumberland County CouncilIP 2015 Do Minimum Constrained Model Flows

A1

27 56

30 71 0 32 N

98 1

171

9

24 61 A197

32 2 55 0 31

142 A192

250 9250 9

7 12 90

Mitford Rd A192 40 5 15 12 21 78 N

54 6 1 291

149 9 9 22

Coopies Lane 41 17 1 A192 86 19

73 27 A196 82 A197 94

142 11 361 86 22

15 33 19 274

32 28 51 19

60 116 28 14 97 332

106 16 92 41 82 15 20

11 10 132 77

7 128 91 263

13 13 142 18

42 6 16

66 71

156 143 142

3 12 48 56 15 226 189 105 18

70 5 88 11 534 183

203 238 17 37 441

15 21 A192 33

4 59 A192 68

67 23 102

195 236

12 21 113 365 25

78 156 33

116

24 316 83 342 27

A1 24 159 32 41A1

A197 A196 73

16 26 142

29 57 15


8 60

Commute 19 106 28

Business 41 11

Other 57

HGV 3 A192

30

Client: Northumberland County CouncilIP 2015 Do Something Constrained Model Flows

A1

45 N

148 1

230

16

A197

62 2

154 A192

365 13365 13

14 13 113

Mitford Rd A192 44 5 20 12 21 125 N

64 6 0 349

151 9 11 27

Coopies Lane 43 22 0 A192 98 19

84 27 A196 96 A197 110

142 11 413 113 22

19 45 22 325

42 28 64 23

124 136 56 14 100 346

126 19 115 67 95 18 20

14 10 205 116

13 189 108 304

13 20 182 26

57 6 1657 6 16

80 89

187 165 172

3 14 71 69 15 267 241 142 18

92 5 99 16 586 220

242 255 17 48 519

19 27 A192 43

4 64 A192 85

84 23 119

207 275

16 26 120 380 25

101 187 43

141

24 358 103 385 27

A1 30 183 41 43

A197 A196 84

18 26 142

29 48 19


9 124

Commute 15 126 28

Business 40 14

Other 56

HGV 1 A192

30

Client: Northumberland County CouncilIP 2030 Do Minimum Constrained Model Flows

A1

31 68

33 76 1 32 N

105 1

203

11

29 84 A197

36 2 64 1 31

151 A192

325 10325 10

9 13 96

Mitford Rd A192 43 5 17 12 21 84 N

59 7 1 316

155 9 8 27

Coopies Lane 45 20 2 A192 92 19

79 27 A196 88 A197 100

146 11 387 92 22

18 35 23 291

34 28 55 23

117 119 31 14 102 329

109 19 97 45 86 18 20

13 10 161 84

9 146 99 273

13 15 153 22

44 6 16

69 77

155 152 153

3 14 51 60 15 235 202 112 18

75 5 94 14 534 194

193 245 17 44 455

17 25 A192 39

4 64 A192 73

72 23 108

203 243

15 25 121 377 25

83 166 41

124

24 311 89 354 27

A1 28 169 39 45A1

A197 A196 79

17 26 146

29 62 18


9 117

Commute 21 109 28

Business 45 13

Other 67

HGV 3 A192

30

Client: Northumberland County CouncilIP 2030 Do Something Constrained Model Flows

A1

495 N

33 1

202

7

A197

311 2

126 A192

177 15177 15

7 8 452

Mitford Rd A192 283 18 12 12 21 68 N

19 6 0 236

69 9 14 12

Coopies Lane 224 8 2 A192 326 19

35 27 A196 69 A197 204

79 11 267 56 22

9 123 9 255

236 28 68 10

61 204 388 14 279 366

201 7 118 459 67 11 20

10 10 227 26

13 102 488 78

13 3 33 3

221 6 16221 6 16

60 233

278 89 740

3 4 262 191 15 219 101 543 18

55 5 55 9 339 164

191 227 17 15 557

9 9 A192 20

4 305 A192 494

69 23 121

120 300

7 11 656 229 25

365 87 17

60

24 216 368 383 27

A1 8 92 16 224

A197 A196 35

112 26 79

29 32 9


15 61

Commute 86 201 28

Business 28 10

Other 47

HGV 2 A192

30

Client: Northumberland County CouncilPM 2015 Do Minimum Constrained Model Flows

A1

259 68

228 39 1 32 N

30 1

198

5

81 55 A197

210 2 52 0 31

119 A192

159 15159 15

5 9 370

Mitford Rd A192 156 21 6 12 21 44 N

23 6 0 194

72 9 15 12

Coopies Lane 96 9 2 A192 319 19

41 27 A196 53 A197 162

84 11 264 36 22

9 114 9 229

183 28 54 10

49 188 286 14 249 309

183 7 98 257 48 10 20

9 10 153 38

11 93 354 120

13 3 51 3

163 6 16

50 203

255 71 628

3 4 258 187 15 197 109 473 18

49 5 47 8 342 128

148 216 17 16 511

9 8 A192 19

4 277 A192 434

66 23 106

133 277

7 11 519 257 25

381 99 17

64

24 183 356 358 27

A1 9 80 14 96A1

A197 A196 41

171 26 84

29 34 9


14 49

Commute 85 183 28

Business 30 9

Other 50

HGV 3 A192

30

Client: Northumberland County CouncilPM 2015 Do Something Constrained Model Flows

A1

456 N

34 1

253

8

A197

413 2

131 A192

191 16191 16

8 8 477

Mitford Rd A192 297 22 14 12 21 68 N

21 7 0 251

71 9 15 14

Coopies Lane 229 10 2 A192 320 19

37 27 A196 71 A197 260

82 11 266 57 22

11 130 11 262

238 28 71 12

63 217 433 14 280 383

210 9 121 409 55 13 20

12 10 235 39

15 119 430 88

13 3 38 3

215 6 16215 6 16

53 273

266 88 714

3 3 262 225 15 230 101 568 18

60 5 65 11 371 165

208 238 17 19 554

11 11 A192 24

4 271 A192 483

72 23 112

131 284

8 12 631 243 25

360 83 20

58

24 235 404 399 27

A1 10 95 19 229

A197 A196 37

170 26 82

29 44 11


19 63

Commute 88 210 28

Business 29 12

Other 50

HGV 4 A192

30

Client: Northumberland County CouncilPM 2030 Do Minimum Constrained Model Flows

A1

273 89

227 41 1 32 N

32 1

240

6

144 64 A197

247 2 54 0 31

125 A192

173 15173 15

6 10 387

Mitford Rd A192 165 20 6 12 21 45 N

25 6 1 199

75 9 15 14

Coopies Lane 97 10 2 A192 326 19

42 27 A196 55 A197 159

85 11 268 37 22

11 120 11 230

207 28 56 12

51 203 309 14 243 334

195 8 101 254 49 13 20

11 10 158 40

13 95 353 122

13 3 54 3

168 6 16

52 222

250 73 613

3 4 249 197 15 207 112 495 18

48 5 48 9 349 133

158 221 17 19 511

11 9 A192 23

4 279 A192 447

71 23 110

140 273

8 13 515 263 25

374 103 20

63

24 193 368 370 27

A1 11 81 17 97A1

A197 A196 42

183 26 85

29 36 11


17 51

Commute 96 195 28

Business 33 11

Other 53

HGV 5 A192

30

Client: Northumberland County CouncilPM 2030 Do Something Constrained Model Flows

A1

273 N

132 1

161

23

A197

511 2

58 A192

124 13124 13

16 5 222

Mitford Rd A192 147 22 12 12 21 65 N

54 9 0 204

160 9 30 18

Coopies Lane 207 6 1 A192 244 19

52 27 A196 42 A197 556

205 11 314 83 22

22 315 11 210

297 28 34 35

54 85 416 14 335 238

109 21 68 314 82 24 20

20 10 160 99

30 119 268 174

13 19 76 15

373 6 16373 6 16

80 397

236 56 515

3 40 222 287 15 105 141 699 18

53 5 71 38 426 122

259 136 17 42 366

14 28 A192 48

4 232 A192 315

36 23 60

214 313

15 40 371 294 25

379 84 44

92

24 332 629 225 27

A1 21 105 31 207

A197 A196 52

120 26 205

29 52 22


1 54

Commute 219 109 28

Business 27 20

Other 78

HGV 18 A192

30

Client: Northumberland County CouncilAM 2015 Do Minimum Unconstrained Model Flows

A1

148 56

199 77 0 32 N

97 1

137

0

379 58 A197

187 2 59 0 31

56 A192

135 10135 10

0 5 145

Mitford Rd A192 150 35 11 12 21 30 N

45 11 0 181

164 9 6 0

Coopies Lane 209 0 0 A192 241 19

43 27 A196 45 A197 383

209 11 309 56 22

0 160 0 190

135 28 29 0

49 85 244 14 350 227

106 0 62 263 60 0 20

0 10 116 96

0 106 231 174

13 0 70 0

349 6 16

73 239

194 46 497

3 0 169 270 15 100 116 538 18

24 5 65 0 424 112

225 136 17 0 327

0 0 A192 0

4 227 A192 294

36 23 52

226 272

0 0 401 314 25

330 84 0

66

24 309 488 226 27

A1 0 101 0 209A1

A197 A196 43

130 26 209

29 57 0


0 49

Commute 233 106 28

Business 34 0

Other 79

HGV 0 A192

30

Client: Northumberland County CouncilAM 2015 Do Something Unconstrained Model Flows

A1

335 N

127 1

193

27

A197

509 2

59 A192

150 14150 14

20 4 269

Mitford Rd A192 149 22 12 12 21 64 N

54 10 0 212

161 9 57 22

Coopies Lane 205 7 1 A192 239 19

52 27 A196 42 A197 537

202 11 307 83 22

34 334 14 215

310 28 41 47

54 88 418 14 323 229

111 25 68 319 84 34 20

25 10 184 92

36 119 278 170

13 22 69 16

367 6 16367 6 16

80 394

234 57 511

3 41 213 284 15 103 137 693 18

53 5 72 45 411 123

248 137 17 54 369

22 41 A192 58

4 257 A192 313

41 23 59

219 314

17 41 379 286 25

368 82 44

90

24 319 627 222 27

A1 30 106 37 205

A197 A196 52

120 26 202

29 53 34


2 54

Commute 207 111 28

Business 34 25

Other 88

HGV 22 A192

30

Client: Northumberland County CouncilAM 2030 Do Minimum Unconstrained Model Flows

A1

200 92

202 79 0 32 N

93 1

142

0

396 76 A197

196 2 63 0 31

56 A192

162 10162 10

0 5 157

Mitford Rd A192 143 33 12 12 21 24 N

51 11 0 185

165 9 6 0

Coopies Lane 198 0 0 A192 239 19

49 27 A196 39 A197 382

207 11 323 56 22

0 176 0 194

137 28 33 0

49 89 244 14 330 227

111 0 62 264 59 0 20

0 10 123 93

0 107 236 175

13 0 68 0

343 6 16

72 238

192 46 480

3 0 170 267 15 99 113 533 18

24 5 66 0 419 106

227 137 17 0 332

0 0 A192 0

4 237 A192 293

38 23 52

229 274

0 0 387 311 25

330 82 0

65

24 309 486 231 27

A1 0 96 0 198A1

A197 A196 49

146 26 207

29 58 0


0 49

Commute 215 111 28

Business 38 0

Other 82

HGV 0 A192

30

Client: Northumberland County CouncilAM 2030 Do Something Unconstrained Model Flows

A1

39 N

147 1

209

14

A197

60 2

155 A192

336 13336 13

11 13 107

Mitford Rd A192 42 5 21 12 21 125 N

64 6 0 354

157 9 11 23

Coopies Lane 42 19 0 A192 89 19

84 27 A196 96 A197 107

152 11 426 112 22

16 42 19 332

41 28 63 20

124 140 58 14 89 341

130 16 116 70 88 15 20

12 10 195 123

10 210 98 319

13 17 182 22

56 6 1656 6 16

80 78

206 157 164

3 12 69 65 15 252 243 136 18

94 5 98 13 631 219

261 269 17 40 550

15 22 A192 35

4 60 A192 83

83 23 121

217 299

15 21 115 408 25

98 187 37

144

24 387 99 404 27

A1 24 181 35 42

A197 A196 84

17 26 152

29 47 16


8 124

Commute 14 130 28

Business 39 12

Other 52

HGV 1 A192

30

Client: Northumberland County CouncilIP 2015 Do Minimum Unconstrained Model Flows

A1

27 58

30 74 0 32 N

105 1

191

0

25 64 A197

33 2 59 0 31

152 A192

283 9283 9

0 13 93

Mitford Rd A192 41 5 18 12 21 85 N

59 7 0 327

159 9 9 0

Coopies Lane 43 0 0 A192 88 19

79 27 A196 89 A197 96

153 11 404 92 22

0 34 0 302

33 28 54 0

108 128 29 14 89 345

117 0 96 51 88 0 20

0 10 150 84

0 166 95 318

13 0 153 0

44 6 16

70 65

174 149 146

3 0 50 57 15 252 203 107 18

76 5 93 0 597 193

227 262 17 0 492

0 0 A192 0

4 60 A192 71

72 23 110

217 264

0 0 115 409 25

81 167 0

125

24 354 86 383 27

A1 0 167 0 43A1

A197 A196 79

16 26 153

29 60 0


0 108

Commute 20 117 28

Business 43 0

Other 60

HGV 0 A192

30

Client: Northumberland County CouncilIP 2015 Do Something Unconstrained Model Flows

A1

43 N

139 1

243

16

A197

61 2

155 A192

386 14386 14

14 14 120

Mitford Rd A192 37 5 23 12 21 128 N

66 6 0 377

161 9 12 27

Coopies Lane 34 22 0 A192 92 19

87 27 A196 96 A197 109

153 11 432 119 22

19 46 22 353

42 28 66 23

126 148 60 14 83 348

136 19 119 74 98 17 20

14 10 233 108

13 229 101 312

13 20 172 26

58 6 1658 6 16

84 80

205 166 161

3 14 72 68 15 260 238 141 18

96 5 103 16 635 225

263 277 17 48 562

18 27 A192 43

4 64 A192 86

78 23 125

222 302

18 26 110 413 25

101 182 45

148

24 392 103 418 27

A1 28 186 41 34

A197 A196 87

19 26 153

29 57 19


9 126

Commute 15 136 28

Business 41 14

Other 59

HGV 1 A192

30

Client: Northumberland County CouncilIP 2030 Do Minimum Unconstrained Model Flows

A1

31 70

32 77 0 32 N

104 1

218

0

29 87 A197

35 2 66 0 31

152 A192

347 10347 10

0 14 96

Mitford Rd A192 43 5 19 12 21 88 N

61 7 0 346

161 9 9 0

Coopies Lane 45 0 0 A192 91 19

81 27 A196 92 A197 99

153 11 417 96 22

0 34 0 317

34 28 58 0

116 131 30 14 98 348

119 0 96 47 91 0 20

0 10 174 82

0 164 99 305

13 0 153 0

44 6 16

73 74

172 153 151

3 0 51 60 15 258 205 111 18

78 5 98 0 577 198

211 267 17 0 495

0 0 A192 0

4 64 A192 72

74 23 113

219 268

0 0 120 409 25

83 168 0

129

24 341 88 388 27

A1 0 172 0 45A1

A197 A196 81

17 26 153

29 64 0


0 116

Commute 21 119 28

Business 46 0

Other 69

HGV 0 A192

30

Client: Northumberland County CouncilIP 2030 Do Something Unconstrained Model Flows

A1

472 N

34 1

213

7

A197

329 2

132 A192

195 16195 16

7 8 466

Mitford Rd A192 291 21 13 12 21 67 N

19 6 0 254

71 9 16 12

Coopies Lane 231 8 2 A192 327 19

35 27 A196 69 A197 215

83 11 280 58 22

9 132 9 270

249 28 70 10

62 217 410 14 290 377

215 7 119 433 56 11 20

10 10 248 36

13 119 450 79

13 3 29 3

209 6 16209 6 16

53 243

273 86 727

3 3 277 225 15 228 91 553 18

57 5 66 9 356 161

205 261 17 15 585

9 10 A192 20

4 277 A192 484

69 23 108

130 293

7 10 637 242 25

372 77 17

50

24 223 405 429 27

A1 9 94 16 231

A197 A196 35

165 26 83

29 44 9


16 62

Commute 89 215 28

Business 29 10

Other 49

HGV 0 A192

30

Client: Northumberland County CouncilPM 2015 Do Minimum Unconstrained Model Flows

A1

267 72

240 41 0 32 N

31 1

212

0

84 58 A197

225 2 54 0 31

122 A192

177 15177 15

0 9 386

Mitford Rd A192 162 22 6 12 21 45 N

23 6 0 209

76 9 16 0

Coopies Lane 100 0 0 A192 328 19

40 27 A196 55 A197 170

89 11 278 37 22

0 122 0 242

216 28 55 0

50 201 314 14 275 341

197 0 103 258 55 0 20

0 10 186 36

0 104 343 111

13 0 46 0

172 6 16

52 208

270 72 640

3 0 265 196 15 208 108 496 18

45 5 48 0 358 132

156 229 17 0 547

0 0 A192 0

4 286 A192 458

70 23 108

141 296

0 0 540 275 25

392 99 0

60

24 193 377 386 27

A1 0 79 0 100A1

A197 A196 40

178 26 89

29 35 0


0 50

Commute 89 197 28

Business 34 0

Other 53

HGV 0 A192

30

Client: Northumberland County CouncilPM 2015 Do Something Unconstrained Model Flows

A1

457 N

34 1

264

8

A197

420 2

129 A192

200 16200 16

8 8 491

Mitford Rd A192 295 22 15 12 21 66 N

19 7 0 263

73 9 16 14

Coopies Lane 228 10 2 A192 323 19

36 27 A196 69 A197 271

84 11 269 58 22

11 138 11 272

250 28 72 12

65 228 454 14 283 391

222 9 116 415 54 13 20

12 10 255 38

15 130 426 87

13 4 32 3

187 6 16187 6 16

53 282

253 83 710

3 3 257 281 15 237 94 582 18

55 5 67 10 380 157

217 273 17 19 566

11 11 A192 23

4 274 A192 458

71 23 103

137 263

8 12 609 244 25

358 77 20

53

24 240 434 438 27

A1 10 95 20 228

A197 A196 36

216 26 84

29 46 11


19 65

Commute 91 222 28

Business 30 12

Other 52

HGV 4 A192

30

Client: Northumberland County CouncilPM 2030 Do Minimum Unconstrained Model Flows

A1

281 93

238 42 0 32 N

32 1

251

0

148 66 A197

256 2 55 0 31

122 A192

185 16185 16

0 10 399

Mitford Rd A192 169 21 7 12 21 45 N

23 6 0 210

79 9 16 0

Coopies Lane 102 0 0 A192 318 19

41 27 A196 55 A197 168

90 11 268 38 22

0 129 0 240

236 28 59 0

51 213 340 14 257 350

206 0 101 257 51 0 20

0 10 183 38

0 100 351 120

13 0 50 0

179 6 16

53 231

262 73 625

3 0 247 209 15 217 107 515 18

40 5 49 0 363 134

163 232 17 0 537

0 0 A192 0

4 290 A192 470

74 23 109

148 287

0 0 542 278 25

380 100 0

55

24 199 389 391 27

A1 0 77 0 102A1

A197 A196 41

186 26 90

29 36 0


0 51

Commute 99 206 28

Business 38 0

Other 55

HGV 0 A192

30

Client: Northumberland County CouncilPM 2030 Do Something Unconstrained Model Flows

Appendix C – Location Plan

A19

A1A9

A1068

A1

A197A192

A196

A196

A1068

A1147

A1

ASHINGTON

BEDLINGTON

BLYTH

NEWBIGGIN-BY-THE-SEA

MORPETH

A4

cm

Client:

Project:

Location Plan

A1-SENSLR-MNB

Title:

No. FIGURE 1

Design:

Chk'd:

Date:

Rev:

CAD:

App'd:

Scale:

LS

GP

July ’11

LS

SM

NTS

www.aecom.comFax: +44 (0) 191 224 6599Tel: +44 (0) 191 224 6500First Floor,

One Trinity Gardens, Quayside,NEWCASTLE UPON TYNE, NE1 2HF

Newcastle7 miles

Key:Morpeth NorthernBypass

Pegswood Bypass

Appendix D – Area Network Plan

A4

cm

Client:

Project:

Area Network Plan

A1-SENSLR-MNB

Title:

No. FIGURE 2

Design:

Chk'd:

Date:

Rev:

CAD:

App'd:

Scale:

LS

GP

July ’11

LS

SM

NTS



Appendix E – Morpeth Network Plan

A4

cm

Client: Project: Title:

No.Design:

Chk'd:

Date:

Rev:

CAD:

App'd:

Scale:

LS LS

SCALEJuly ’11 REVGP SM

A1-SENSLR-MNB

FIGURE 3

Morpeth Network Plan



100212 morpeth traffic model forecasting report rev1

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