using value-of-time distributions in auto assignment to forecast effects of road pricing schemes...

Using value-of-time distributions in auto assignment to forecast effects of road pricing schemes with non-additive chargesLeonid Engelson & Dirk van Amelsfort

22nd Emme Users’ Conference, Portland 2011

Background

Road charges has been implemented in a dozen of cities

More cities consider

Typically designed as charge zone or charge cordon (set of links)

London, Milano, Valetta: pay as you drive or park in the zone

Singapore, Stockholm: pay each time you pass the cordon

Gothenburg (decided): pay as you pass any link of the set, once within 60 minutes (Multiple Passage Rule, MPR)

WSP Sweden was responsible for modelling in the design project of CC system for Gothenburg

How to model CC system with MPR?


Background


OSLO

MALMÖ

STOCKHOLM

Sweden’s second largest city500 000 inhabitantsFreight hubLand use low densityRiver with only 3 – 4 crossingsRailway station dead-end

Gothenburg suffers (some) congestion in morning peak


…and substantial air quality problems


Nitrogen dioxide 98-percentile in 2008

(Red = above the Environmental Quality Standards)

Politicians were inspired by success of the Congestion charging in Stockholm

Jan-July 2006 TrialSep 2006 Referendum showed: Most inhabitants of the Stockholm

commune are positive to the chargesAugust 2007 Permanent introduction

Cordon basedTime differentiated1,5-3 $ per passage

Delimited by water18 entry points sufficient

Bypass exempted from charging


Objectives…

100 million $ net revenue in 2015.

Reduction in congestion and air polluting emissions from traffic

Reduction of traffic through central Gothenburg

and constraints…Reasonable cost increase for travellers.

Fit under the existing legislation

Logical and easy to understand for the users.

ANPR technology from Stockholm

Tax to be paid 06.00 am – 18.30 pm.

Same fare for all non-exempted vehicles


First stage of the design :5 cordon types examined, 5 types of effects predictedSmall cordon chosen

Revenue

EnvironmentCongestion

Route choicesModal split


Second stage of the design:

Blue and Green – two small cordons evaluated in detail

Multiple passages => one charge


Modelling tool:

• SAMPERS – Swedish travel demand model

• 5 regions + long trips

• Four stages

• Multiclass auto assignment with generalized costs (Emme)

• Complication 1: Non-additive route cost: paying just once

• Complication 2: Discrete values of time• Too coarse representation of preferences

• Optimal discretization different for different OD-pairs

A B C

1 $ 1 $


Solution: Hierarchic route choice with VoT distribution

2 classes auto assignment: to H and to DModule 5.25, save paths

TimeH and TimeDDistH and DistD

Paying trip matrixNon-paying trip matrix

Define modes:H = whole road networkD = links without charges

Weigh together for CBA0

1

Value of time

F

Repeat until convergence (MSA)


Convergence with MSA applied to the demand

0.01

0.1

1

10

100

0 2 4 6 8 10 12

Iteration

Max

ab

s ch

ang

e n

um

ber

of

pay

ers


From new Swedish VoT study: Lognormal distributions (kr/h) ($1=6.3kr)

0

0.005

0.01

0.015

0.02

0.025

0.03

0 100 200 300 400 500 600 700

Private >100 km

Private <100 km

Commuting

Business and freight low

Business and freight high

Mean log STD log Median VoT Mean VoT Estimated by-0.20 1.29 49 113 SP

-0.89 1.17 25 49 SP-0.16 1.22 51 108 SP1.16 1.22 191 403 Judgement1.64 0.36 309 330 Judgement


Blue and Green – two small zones evaluated in detail

Multiple passages => one charge

Generally similar effectsBlue chosen

+ Stronger congestion releif+ Stronger effect on the air

quality


Flow changes with charges, the Blue scenario


Final scheme

Yellow sistemClosed ring+6 links

Improved Urban function and understandability compared to the blue system

(using the same method)


Advantages of the method

• Can be applied to some road user charge systems with discounts

• Allows arbitrary distributions of VoT

• Good convergence

Limitations

• If the user pays each time, needs 2N user classes, N=number of elements of the charging system (toll rings + separate toll links)

• For example, not possible to study effect of the multiple passage rule with continuous VoT distribution for the Yellow system


Unresolved issues

VoT for business trips and freight

Distance weight seems too high in the base scenario

• Distance weight = (gasoline and amortisation cost per km)/(median VoT)

• Too low VoT?

• The drivers don’t consider the whole distance related cost?

• In the last case (reduced distance cost), too strong (compared to the multiclass method) response to the charges

• Distangle distance cost from VoT?

Needed to further calibrate VoT and cost per km


Conclusions

Assignment method with continuous VoT distribution worked well in the application to Gothenburg

Manages cordon charge that is independent of the number of crossings

Warning: assignment with continuous VoT may give very different results compared to the assignment with discrete VoT.


Thank you for your attention

Questions?


Welcome to the Nordic Emme Users’ Conference 19-20 March 2012 in

Stockholm!


using value-of-time distributions in auto assignment to forecast effects of road pricing schemes...

Documents

nd emme users conference

cordon gothenburg

charge cordon

cordon types

background road charges

stockholm commune

stockholm tax

nonadditive route cost