Collective Decision-Making Mechanisms in Urban Traffic

This project aims at exploring possible applications of methods from Computational Social Choice for traffic management. Computational Social Choice is a field of study at the interface of Social Choice Theory and Computer Science. On the one hand, methods from Computer Science such as complexity analysis are applied to constructs from Social Choice Theory such as voting systems; on the other hand, concepts from Social Choice Theory are applied to Computer Science.

Research in Social Choice investigates collective decision-making mechanisms, i.e. methods aiming at creating a common decision for a group with differing preferences/decisions which takes all individual preferences/decisions into account.

Previously considered applications of collective decision-making mechanisms in urban traffic will be taken into account when searching for further possible applications. Applications already considered are auction-based procedures for intersection management [VO09] and auction-based procedures for decision on which transport to use for travel to work [GLBG12]. The first application to be investigated is the formation and decision making of tour groups in the sense of share-taxi passenger groups, where the decision making is based on the individual preferences for points of interest (POIs) and each tour group agrees on a set of POIs to visit.

It is planned to conduct the evaluation of the methods via agent-based simulation, where human and automated actors are modelled by means of a multi-agent system. Different collective decision-making mechanisms will be compared - on the one hand, simulatively evaluating satisfaction of the group members, travel time, waiting time, air pollution and noise pollution - and on the other hand, evaluating theoretical properties.

[VO09] - Vasirani, M., & Ossowski, S. (2009). A market-inspired approach to reservation-based urban road traffic management. In Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems-Volume 1 (pp. 617-624). International Foundation for Autonomous Agents and Multiagent Systems.

[GLBG12] - Grimaldo, F., Lozano, M., Barber, F., & Guerra-Hernández, A. (2012). Towards a model for urban mobility social simulation. Progress in Artificial Intelligence, 1(2), 149-156.