FORESIGHT
Intelligent Infrastructure Futures
OFFICE OF SCIENCE AND TECHNOLOGY
Intelligent Charging: Smart Market
Protocols for Road Transport
Sheri M. Markose Amadeo Alentorn and Deddy Koesrindartoto, CCFEA, Essex,
Phil Blythe, Sergio Grosso, Anett Ehlert and Dilum Dissanayake, TORG, Newcastle
&
Peter Allen, CSMC, Cranfield
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Purpose
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 Smart Markets could bring intelligence into the
road transport network to address congestion
 A Smart Market is an on-line auction:
 Potential users submit bids
 Auction determines the price and ‘winners’
 Infrastructure operators pre-set the limits (slots)
 We explored a road pricing regime which fixes
(Cap) the number of vehicles able to use the roads
at peak time
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Roadmap: ‘CAP’ and TRADE: Smart Market for Congestion
 Rationale : ‘CAP’’ and trade
 Application to a typical congestion ‘hotspot’ in
Gateshead
 How to ‘cap’ or determine optimal congestion?
TORG /Vissim Traffic Micro Simulator
 Cross Sectional demand analysis : Bid
Submission (from individuals)
 SMPRT Algorithm for Price Determination
 Winners and losers
 Robustness analysis of SMPRT
 Future research
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Important to Note
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 We are grateful to
Gateshead MBC for
allowing us to use their
traffic model.
 Their network is used
purely for research
investigation purposes
 Gateshead MBC has not
expressed an interest,
either publicly or privately
in introducing any form of
road user charging.
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Cap and Trade Rationale
 Negative externalities (congestion and pollution)
are internalised.
 The method has been proven in the field of trading
pollution licences.
 Establish the limit (Cap) that is consistent with
efficient use of resources
 In this case the road network capacity and the number
of vehicles wishing to use the infrastructure
 In this case it is the load at which there is significant falloff in the road network performance – different road
authorities with have different judgements as to where
this point occurs
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Stages of the Research
 Develop prototype Gateshead Vissim Traffic Model
which could be used under varying loads:
 Average speed and travel time
 Number of vehicles in network and per link
 Emissions and pollutants
 In parallel the commuter origins/destinations,
socio-economic groups and demand trends were
analysed for this model
 Smart Market simulator was developed in order to
generate the pattern of bid submissions.
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The actual Central Gateshead Congestion ‘Hotspot’
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Simulation
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VISSIM
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TORG /Vissim Traffic Micro Simulation Results
The cap is
• the maximum number of road users permitted to use the road during
a time slice in terms of the criteria.
 Based on the ‘production function’ of traffic, the cap is:
 maximum total distance travelled in the time slice;
 begins to drop with incremental growth in vehicle volumes; and
 the point at which vehicular emissions grow exponentially.
 The PCU volumes are scaled from base-line demands in the
transport model from between 10% and 170% of current demand
 The cap is given as X# passenger car units (PCUs): 11720 PCUs
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Analysis of spatial/temporal
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modelling options
*
* Gateshead Council’s model
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Setting the CAP & marginal
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social cost
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Demand Analysis
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 For the bid function it is necessary to have
information on:
 Commuters origins and destinations
 Socio-economic groups
 Income distribution
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Routes that cross Central Gateshead:
South to North
North to South
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Income Distributions of Commuters
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in the North East: Foresight
The professional status of Commuters in an out of Tyne and Wear
Tyne & Wear
higher managerial & professional
lower managerial & professional
intermediate
small employers & own account
lower supervisory & technical
semi-routine
routine
% In
% Out
16%
32%
16%
3%
11%
11%
9%
15%
30%
11%
3%
15%
10%
12%
We also know the income distributions for different classes of
Professionals for the North East:
This enables us to calculate the sensitivity to
Road User Charges from the different commuters
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Car user income
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distribution
The income distribution of 16740 car drivers traversing Gateshead cordon
area (i.e. commuters with income greater than £10,500) (Mean annual
income is £ 21990.39)
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Number Car Drivers
160
140
120
100
80
60
40
20
0
£10k £14k £18k £22k £26k £30k £34k £38k £42k £46k £50k £54k More
Income
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Winners of auction: Market
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Clearing Price
 SMPRT based on a uniform sealed bid Dutch
Auction Design where the X* highest bid that
clears the market for X* travel slots applies to all
bidders who bid above this. SMPRT price
algorithm can also adjust for environmental
externality costs
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Price
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uniform Dutch Auction
Bids ranked
from high
to low
X* highest bid on
the bid schedule
B(V(X*))
P*
X*
X
Quantity
Figure 1 Price Determination in uniform
Dutch Auction with Fixed supply of X*
travel slots
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Distribution of winners across socio-economic groups for various ‘cap’ travel slots
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Winners and losers
20% reduction in
travel slots
Current
Demand
(a)
(c)
30% reduction in
travel slots
10%reduction
in travel slots
(b)
(d)
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A New Tool:
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 CCFEA, TORG and the CSMC have developed a new tool
 Could be applied to any road network that is suffering
congestion and apply SMART Market protocols
 Urban Centres are obvious candidates, but could be
applied to larger network
 Challenge to explore how to test modelled-system with
‘real’ users
 Approach could be extended to price other transport
networks, such as the railways, ports etc.
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Concluding Remarks
 An innovative approach
 Integrated - full cross sectional demand analysis
of different socio-economic groups
 Identifies ‘winners and losers’
 Give a better understanding for transport
provision
 Could be used to integrate pricing for vehicular
use externalities
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Method for Foresight:
 Potential application - multi-agent models to investigate
infrastructure needs and look at the co-evolution of
demography, spatial structure and flows
 Model new patterns of residential and professional locations,
and the nature of key interactions
 Future developments may include:
 Beyond extrapolation of current trends; eg include “causalities” of
travel….
 Wider range of multi-agent (age cohort, household type, skill and
knowledge quality), spatial modelling with distributed knowledge,
responses and learning
 Include measure of Quality of Life…..
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Fully Executable SMPRT Simulator
 Smart Market for Congestion - Robustness
Analysis - Simulator to study the auction design for
a congestion charge model:
http://privatewww.essex.ac.uk/~aalent/
 Full Reports on the IIS Smart Market For
Road Congestion can be found at:
www.foresight.gov.uk
 Project team contacts:
 CCFEA: [email protected]
 TORG: [email protected] or [email protected]
 CSMC: [email protected]
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