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Traffic congestion in urban road networks is a costly problem that affectsall major cities in developed countries. To tackle this problem, it is possible(i) to act on the supply side, increasing the number of roads or lanes in anetwork, (ii) to reduce the demand, restricting the access to urban areas atspecific hours or to specific vehicles, or (iii) to improve the efficiency ofthe existing network, by means of a widespread use of so-called IntelligentTransportation Systems (ITS). In line with the recent advances in smarttransportation management infrastructures, ITS has turned out to be a promisingfield of application for artificial intelligence techniques. In particular,multiagent systems seem to be the ideal candidates for the design andimplementation of ITS. In fact, drivers can be naturally modelled as autonomousagents that interact with the transportation management infrastructure, therebygenerating a large-scale, open, agent-based system. To regulate such a systemand maintain a smooth and efficient flow of traffic, decentralised mechanismsfor the management of the transportation infrastructure are needed.  In this article we propose a distributed, market-inspired, mechanism for themanagement of a future urban road network, where intelligent autonomousvehicles, operated by software agents on behalf of their human owners, interactwith the infrastructure in order to travel safely and efficiently through theroad network. Building on the reservation-based intersection control modelproposed by Dresner and Stone, we consider two different scenarios: one with asingle intersection and one with a network of intersections. In the former, weanalyse the performance of a novel policy based on combinatorial auctions forthe allocation of reservations. In the latter, we analyse the impact that atraffic assignment strategy inspired by competitive markets has on the driversroute choices. Finally we propose an adaptive management mechanism thatintegrates the auction-based traffic control policy with the competitivetraffic assignment strategy.

A Market-Inspired Approach for Intersection Management in Urban Road Traffic Networks