Intelligent Infrastructure Futures OFFICE OF SCIENCE AND TECHNOLOGY FORESIGHT 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

Intelligent Infrastructure Futures Foresight 2 OST Purpose 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

Intelligent Infrastructure Futures Foresight 3 OST 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

Intelligent Infrastructure Futures Foresight 4 OST Important to Note 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.

Intelligent Infrastructure Futures Foresight 5 OST 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 fall- off in the road network performance – different road authorities with have different judgements as to where this point occurs

Intelligent Infrastructure Futures Foresight 6 OST 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.

Intelligent Infrastructure Futures Foresight 7 OST The actual Central Gateshead Congestion ‘Hotspot’

Intelligent Infrastructure Futures Foresight 8 OST Simulation VISSIM

Intelligent Infrastructure Futures Foresight 9 OST 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): PCUs

Intelligent Infrastructure Futures Foresight 10 OST Analysis of spatial/temporal modelling options * Gateshead Council’s model *

Intelligent Infrastructure Futures Foresight 11 OST Setting the CAP & marginal social cost OST Intelligent Infrastructure Futures Foresight

Intelligent Infrastructure Futures Foresight 12 OST Demand Analysis For the bid function it is necessary to have information on:  Commuters origins and destinations  Socio-economic groups  Income distribution

Intelligent Infrastructure Futures Foresight 13 OST Routes that cross Central Gateshead: South to North North to South

Intelligent Infrastructure Futures Foresight 14 OST Income Distributions of Commuters in the North East: The professional status of Commuters in an out of Tyne and Wear 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

Intelligent Infrastructure Futures Foresight 15 OST The income distribution of car drivers traversing Gateshead cordon area (i.e. commuters with income greater than £10,500) (Mean annual income is £ ) Car user income distribution

Intelligent Infrastructure Futures Foresight 16 OST Winners of auction: Market 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

Intelligent Infrastructure Futures Foresight 17 OST Price determination in uniform Dutch Auction

Intelligent Infrastructure Futures Foresight 18 OST

Intelligent Infrastructure Futures Foresight 19 OST Current Demand 10%reduction in travel slots 20% reduction in travel slots 30% reduction in travel slots Winners and losers OST

Intelligent Infrastructure Futures Foresight 20 OST A New Tool: 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.

Intelligent Infrastructure Futures Foresight 21 OST 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

Intelligent Infrastructure Futures Foresight 22 OST 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…..

Intelligent Infrastructure Futures Foresight 23 OST Fully Executable SMPRT Simulator Smart Market for Congestion - Robustness Analysis - Simulator to study the auction design for a congestion charge model:Smart Market for CongestionRobustness Analysis Full Reports on the IIS Smart Market For Road Congestion can be found at: Project team contacts:  CCFEA:  TORG: or  CSMC: