Algorithm for optimal winner determination in combinatorial auctions
Artificial Intelligence
Multi-Agent Reinforcement Leraning for Traffic Light Control
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Solving Combinatorial Auctions Using Stochastic Local Search
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
An Algorithm for Multi-Unit Combinatorial Auctions
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Social Structure in Artificial Agent Societies: Implications for Autonomous Problem-Solving Agents
ATAL '98 Proceedings of the 5th International Workshop on Intelligent Agents V, Agent Theories, Architectures, and Languages
The price of anarchy is independent of the network topology
Journal of Computer and System Sciences - STOC 2002
The computation of market equilibria
ACM SIGACT News
Dealing with non-stationary environments using context detection
ICML '06 Proceedings of the 23rd international conference on Machine learning
Evaluating the performance of DCOP algorithms in a real world, dynamic problem
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2
Agent-Based Traffic Control Using Auctions
CIA '07 Proceedings of the 11th international workshop on Cooperative Information Agents XI
A market-inspired approach to reservation-based urban road traffic management
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
Multi-Agent Systems for Traffic and Transportation Engineering
Multi-Agent Systems for Traffic and Transportation Engineering
A multiagent approach to autonomous intersection management
Journal of Artificial Intelligence Research
Market-based control of computational systems: introduction to the special issue
Autonomous Agents and Multi-Agent Systems
Cooperative, hybrid agent architecture for real-time traffic signal control
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Vehicle-to-vehicle wireless communication protocols for enhancing highway traffic safety
IEEE Communications Magazine
A Computational Market for Distributed Control of Urban Road Traffic Systems
IEEE Transactions on Intelligent Transportation Systems
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Traffic congestion in urban road networks is a costly problem that affects all 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 a network, (ii) to reduce the demand, restricting the access to urban areas at specific hours or to specific vehicles, or (iii) to improve the efficiency of the existing network, by means of a widespread use of so-called Intelligent Transportation Systems (ITS). In line with the recent advances in smart transportation management infrastructures, ITS has turned out to be a promising field of application for artificial intelligence techniques. In particular, multiagent systems seem to be the ideal candidates for the design and implementation of ITS. In fact, drivers can be naturally modelled as autonomous agents that interact with the transportation management infrastructure, thereby generating a large-scale, open, agent-based system. To regulate such a system and maintain a smooth and efficient flow of traffic, decentralised mechanisms for the management of the transportation infrastructure are needed. In this article we propose a distributed, market-inspired, mechanism for the management of a future urban road network, where intelligent autonomous vehicles, operated by software agents on behalf of their human owners, interact with the infrastructure in order to travel safely and efficiently through the road network. Building on the reservationbased intersection control model proposed by Dresner and Stone, we consider two different scenarios: one with a single intersection and one with a network of intersections. In the former, we analyse the performance of a novel policy based on combinatorial auctions for the allocation of reservations. In the latter, we analyse the impact that a traffic assignment strategy inspired by competitive markets has on the drivers' route choices. Finally we propose an adaptive management mechanism that integrates the auction-based traffic control policy with the competitive traffic assignment strategy.