No abstract

No abstract

No abstract

To control and price negative externalities in passenger road transport, we develop an innovative and integrated computational agent based economics (ACE) model to simulate a market oriented "cap" and trade system. (i) First, there is a computational assessment of a digitized road network model of the real world congestion hot spot to determine the "cap" of the system in terms of vehicle volumes at which traffic efficiency deteriorates and the environmental externalities take off exponentially. (ii) Road users submit bids with the market clearing price at the fixed "cap" supply of travel slots in a given time slice (peak hour) being determined by an electronic sealed bid uniform price Dutch auction. (iii) Cross-sectional demand data on car users who traverse the cordon area is used to model and calibrate the heterogeneous bid submission behaviour in order to construct the inverse demand function and demand elasticities. (iv) The willingness to pay approach with heterogeneous value of time is contrasted with the generalized cost approach to pricing congestion with homogenous value of travel time. JEL Classification: R41, R48, C99, D44, H41Keywords: Congestion charging; Negative externalities; Agent based computational auction design; "Cap" and trade smart market; Willingness to pay; Cross sectional demand analysis *Tel.: +44 1206 872742; fax: +44 (0)1206 872724 E-mail address: scher@essex.ac.uk Acknowledgements:We are grateful to Foresight Directorate of the UK Office of Science and Technology in the Department of Trade and Industry (DTI) for financing this project and to Miles Yarrington for project management. We also thank the Gateshead Metropolitan Borough Council for the use of their micro transport model for central Gateshead. This has been used entirely for purposes of research. We are grateful to Frank Kelly, John Urry and Andrew Scurry for their comments. Our particular thanks go to the referee, John Ledyard, for his significant technical corrections and high calibre input. We remain responsible for all errors.

No abstract