Back-Pressure Traffic Signal Control With Fixed and Adaptive Routing for Urban Vehicular Networks

Abstract

City-wide control and coordination of traffic flow can improve efficiency, fuel consumption, and safety. We consider the problem of controlling traffic lights under fixed and adaptive routing of vehicles in urban road networks. Multicommodity back-pressure 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 multi-commodity and adaptive routing algorithms provide significant improvement over a fixed schedule controller and a single-commodity back-pressure controller, in terms of various performance metrics, including queue-length, trips completed, travel times, and fair traffic distribution.

Novel Applications of High Altitude Stratospheric Platforms for Traffic Management and Control

“…Traffic congestion causes many problems such as loss of time, missed opportunities, and frustration [6][7][8]. One solution to this problem is to adapt the time duration of the traffic signals at the intersections where it can be done manually or automatically.…”

Blue phase: Optimal network traffic control for legacy and autonomous vehicles

“…Starting from the seminal work of Smith [30], several efforts have also attempted to model the impact of traffic signal optimization on route choice [42,12,41]. Other studies used bi-level optimization for signal timings that assume a user equilibrium behavior [40,31].…”

“…A policy is a function π : X → M that chooses a service matrix α(t) ∈ M for every state x(t). We use the concept of strong stability to characterize the proposed stochastic queuing process [15,38,41]: Definition 4. A stochastic queue evolution process is strongly stable under policy π if and only if there exists K < ∞ such that the network state x(t) verifies:…”

Utility optimization framework for a distributed traffic control of urban road networks

“…Further the backpressure policy can incorporate and route multicommodity flows provided a separate queue is maintained for each commodity, such a system was first proposed by Tassiulas and Ephremides (1992) . With some loss of stability, can be adapted to traffic control mechanisms which are agnostic to the commodities used, see Bui et al (2009) and Zaidi et al (2016) .…”