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A smart market for passenger road transport (SMPRT) congestion: An application of computational mechanism design

Markose, Sheri and Alentorn, Amadeo and Koesrindartoto, Deddy and Allen, Peter and Blythe, Phil and Grosso, Sergio (2007) 'A smart market for passenger road transport (SMPRT) congestion: An application of computational mechanism design.' Journal of Economic Dynamics and Control, 31 (6). pp. 2001-2032. ISSN 0165-1889

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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. © 2007 Elsevier B.V. All rights reserved.

Item Type: Article
Uncontrolled Keywords: congestion charging; negative externalities; agent-based computational auction design; 'cap' and trade smart market; willingness to pay; cross-sectional demand analysis
Subjects: H Social Sciences > HB Economic Theory
Divisions: Faculty of Social Sciences
Faculty of Social Sciences > Economics, Department of
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 16 Aug 2012 13:46
Last Modified: 18 Aug 2022 10:42

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