Traffic-adaptive Signal Control and Vehicle Routing Using a Decentralized Back-pressure Method
Paper in proceedings, 2015
The problem of controlling traffic lights under adaptive
routing of vehicles in urban road networks is considered.
Multi-commodity back-pressured algorithms, originally
developed for routing and scheduling in communication
networks, are applied to road networks to control traffic
lights and adaptively reroute vehicles. The performance of
the algorithms is analyzed using a microscopic traffic
simulator. The results demonstrate that the proposed signal
control and adaptive routing algorithms can provide
significant improvement over a fixed schedule and a
single-commodity back-pressure signal controllers, in terms
of various performance metrics, including queue-length,
trips completed, and travel times.