2019/12/13 by Charlotte Roman, Paolo Turrini, Roman, Charlotte +1
Economics, Econometrics and Finance · Engineering · Social Sciences · #Artificial Intelligence (cs.AI) #Computer Science and Game Theory (cs.GT) #FOS: Computer and information sciences #Game Theory and Voting Systems #Multiagent Systems (cs.MA) #Transportation Planning and Optimization #Transportation and Mobility Innovations
paper · pdf · doi:10.48550/arxiv.1912.06513
openalex publication_date 2019/12/13 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Traffic congestion games abstract away from the costs of junctions in transport networks, yet, in urban environments, these often impact journey times significantly. In this paper we equip congestion games with traffic lights, modelled as junction-based waiting cycles, therefore enabling more realistic route planning strategies. Using the SUMO simulator, we show that our modelling choices coincide with realistic routing behaviours, in particular, that drivers' decisions about route choices are based on the proportion of red light time for their direction of travel. Drawing upon the experimental results, we show that the effects of the notorious Braess' paradox can be avoided in theory and significantly reduced in practice, by allocating the appropriate traffic light cycles along a transport network.