Portorož, Slovenia

•Alex WrightAlex Wright

•TRL Infrastructure DivisionTRL Infrastructure Division

•Group manager, Technology DevelopmentGroup manager, Technology Development

•mwright@trl.co.ukmwright@trl.co.uk

Developing the automatic measurement of surface condition on local roads

Portorož, Slovenia

Measuring condition at traffic-speed in the UK

o UK condition surveys measure• Longitudinal profile• Transverse profile• Texture profile• Cracking (automatic)• Geometry

o Annual coverage • TRACS: 40,000km motorway and trunk

roads • SCANNER: 80,000km local road network

o Surveys carried out to an end result specification

Portorož, Slovenia

“UK” Systems

• Accredited Systems:• Jacobs

– Ramboll RST26, RST27• WDM

– RAV1, RAV2, RAV3, RAV4• DCL

– Roadware ARAN1, ARAN2

Portorož, Slovenia

UK trunk roads - TRACS

Portorož, Slovenia

UK local roads (rural) - SCANNER

Portorož, Slovenia

UK local roads (urban) - SCANNER

Portorož, Slovenia

Use of the Data

o Local use• Parameters reported over 10m lengths for local use

o Network use• For trunk roads total length of poor values reported

• Single HA performance indicator (PI)

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Road category

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port

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Red

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• For local roads a Road Condition Index (RCI) is produced every 10m

• Reports “overall” condition score• Distribution of RCIs over the local

authority defines network condition (LA Indicator)

• Potential use in allocation of funding across authorities

Portorož, Slovenia

o Local roads differ from trunk roadso New methods required to maximise value of local road datao Research to improve the use of the survey data

• Measuring ride quality on local roads using shape data• Using texture to assess surface deterioration on local roads• Measuring edge deterioration on local roads

o Work concentrated on the use of shape datao Began with consultation to find out what users needed in

practice

Enhancing the use of data from local roads

Portorož, Slovenia

“Shape” data collected at traffic-speed

6566676869707172737475

Chainage (m)

Portorož, Slovenia

o Consultation with engineers found that• Little importance placed on longitudinal profile data• Key structural measure is cracking and rutting• Engineers desire a reliable assessment of general ride

quality (functionality)• But engineers key concern is defects giving rise to

bumps (user complaints)o Concluded that methods needed to

• Reliably identify lengths with poor ride quality• Identify general locations giving rise to bumps

Measuring ride quality on local roads - consultation

Portorož, Slovenia

Measuring ride quality - data collection

o A practical investigation to relate surface profile to user opinions on local roads

o Several routes surveyed, including sections known to be pooro Profile data provided by HARRIS1 profilometer

• Measurements in both wheel tracks (and across survey width)o User surveys:

• Car surveys• Motorbike survey• Utilising on-board data collection

with GPS referencing• Reported on ride and bumps• Repeat surveys for consistency

Portorož, Slovenia

Considering general ride quality

3m 5m0.000000001

0.000001

0.001

1

1000

1.00E-01 1.00E+00 1.00E+01 1.00E+02

Wavelength

Po

wer

100m lengths where dial >2100m lengths where dial <=2

0.37

5916

0.49

5487

0.65

3091

0.86

0827

1.13

4638

1.49

5543

1.97

1245

2.59

8258

3.42

471

4.51

4041

5.94

9865

7.84

2396

10.3

3690

2

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Wavelength (m)

Sit

e C

hai

nag

e (m

)

1.38-1.4

1.35-1.38

1.33-1.35

1.3-1.33

1.28-1.3

1.25-1.28

1.23-1.25

1.2-1.23

1.18-1.2

1.15-1.18

1.13-1.15

1.1-1.13

1.08-1.1

1.05-1.08

1.03-1.05

1-1.03

0.98-1

0.95-0.98

0.93-0.95

0.9-0.93

o Wavelet Decomposition

o PSD

1m – 5m

o IRI, Ride Number, Profile Indexo MA and enhanced varianceo Coefficient de planeiteo Waveband Energyo Standard Deviation

Portorož, Slovenia

General ride quality - wavelength response

o IRI

o 3m Variance

Portorož, Slovenia

Parameter for general ride quality

o Predicting general ride quality on local roads• 1-5m wavelength features cause the users most

discomfort. • 3m enhanced variance agreed best with user opinion of

underlying ride quality. Other measurements agreed no better with the user’s opinion.

• 10m enhanced variance showed some agreement (effects of longer wavelengths on truck drivers).

• Wavelengths over 20m - little or no agreement with usero Effect of measurement (line)

• Offside measurements contributed to 33% of agreement with user opinion.

• Multiple measurement lines around the wheelpath did not improve agreement

Portorož, Slovenia

Measuring “Bumps” on local roads

o User surveys recorded bumps using button presseso Wavelet analysis suggested wavelengths of interest lie

between 1 and 3m.o Existing measurements (variance, IRI etc) did not reliably

report the locations of the features causing this bump-like discomfort.

0.5m

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rmalised

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wer

Button press

No button press

Portorož, Slovenia

Measuring “Bumps” on local roads

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Chainage (m)

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val

ue

Cat4 3m enh var NSWT

Cat 4 3m enh var OSWT

Dial value

Bump

Portorož, Slovenia

A parameter for “Bumps” on local roads

o Considered many approaches, e.g.• 1.25m enhanced variance, change of vehicle acceleration,

derivative of longitudinal profile (features too small to impact on a car’s tyre)

o The Central Difference Method • Calculates a “derivative” for each point along the road (profile

measurements {yi}, taken at distances {xi} along the road):

• Similarly for F’’.• The maximum of these values is calculated over 1m lengths.• If max(F’) and max(F’’) both exceed set thresholds, then the

length contains a bump and a value of “1” is reported for that length. Otherwise “0” is reported.

11

11)('

ii

ii

xx

yyixF

Portorož, Slovenia

Measuring “Bumps” with the CDM – local roads

o Tests to review locations where the bump measure responded• Reported 84% of user button presses.• Potential high number of false positives.• Inspection of 3D profile and video showed features of note

where CDM responds, but users had not always pressed the button.

o Concluded • This is an appropriate method for identifying “bumps”.• We should use a combination of this and 3m enhanced

variance for assessing general ride and bump density on local roads

Portorož, Slovenia

Testing on trunk roadsEasting and Northing

152500

162500

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182500

465000 470000 475000 480000 485000 490000 495000 500000 505000 510000 515000

Easting

No

rth

ing

Portorož, Slovenia

Measuring “Bumps” – trunk roads

o Applied to whole of trunk road and motorway network.• 0.17% of network reported to contain bumps

o Subset inspected in closer detail:• Inspected 3D profile for 10% of locations• Visual inspection on site of 1% of locations

o Where 3D profile inspected:• 87% contained obvious bumps• Further 10% showed general unevenness

o Where site inspected,• 64% showed visible bumps on site• 24% were not “bumps”, but were poor bridge joints• 3% were bumps at surface change

Portorož, Slovenia

Measuring Edge deterioration - consultation

o Consultation with engineers found that • Edge deterioration universally considered an area for

concern• Key requirement for a measure to aid in defining

maintenance treatmento Features of interest

• Potholes in surface near edge• Overriding• Cracking of surface near edge• Edge supported or kerbed• Presence of patching

Portorož, Slovenia

Developing parameters for Edge Deterioration

o A fully automated measureo Utilising transverse profile

data • Firstly Identify the edge

strip o Edge Roughness

• Roughness within the edge strip

o Edge Stepping• Stepping at the

nearside of the edge strip

o Transverse Variance• Assessing roughness

across the pavement

Portorož, Slovenia

Edge deterioration parameters

Portorož, Slovenia

The Edge deterioration parameters

o Transverse edge roughness edge step unevenness

Portorož, Slovenia

Testing the Edge deterioration parameters

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mb

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of 1

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gth

s in

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xc

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din

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95th

pe

rcen

tile

lev

el

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Edge Step L2 Edge Step L1 CVI-B_ED

Portorož, Slovenia

An Indicator for Edge Condition

o Four parameters provide a complicated picture of condition• Better to report the general edge condition

o The ‘Edge Deterioration’ indicator• Combines all four SCANNER Initial Edge Deterioration

Parameters• Is a weighted combination of parameters after applying

thresholds and normalisation• Provides a single number to the engineer• Is based on the logic of the SCANNER RCI

Edge Det = Wryedge roughness + Wtvytrans variance + WE1yedge step 1 + WE2yedge step 2

Portorož, Slovenia

Testing the indicator for Edge Condition

o Comparison with site assessments

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Edge

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erio

ratio

n In

dica

tor

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CVI e

dge

dete

riora

tion

(y/n

?)

Edge deterioration seen on video Edge Deterioration Indicator CVI Edge

Portorož, Slovenia

Testing the indicator for Edge Condition

o Proportion of roads having significant edge deterioration by manual surveys and the Edge Deterioration Indicator

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Edge Condition indicator

CVI

Portorož, Slovenia

Conclusions

o Traffic-speed surveys have become widely applied in the UK on local roads under SCANNER (>100,000km/year)

o Local roads have particular defects o A research programme has developed a set of parameters for

reporting local road condition using data collected at traffic-speedo For ride quality

• Enhanced variance• A bump measure

o For edge deterioration• A set of edge deterioration parameters• An edge condition indicator

o These new parameters were introduced into SCANNER in 2007 for network level reporting