CPS-oriented Modeling and Control of Traffic Signals Using Adaptive Back Pressure
Wanli Chang1,a, Debayan Roy2, Shuai Zhao1,b, Anuradha Annaswamy3 and Samarjit Chakraborty4
1University of York, UK
awanli.chang@york.ac.uk
bshuai.zhao@york.ac.uk
2Technical University of Munich, Germany
debayan.roy@tum.de
3Massachusetts Institute of Technology, USA
aanna@mit.edu
4University of North Carolina at Chapel Hill, USA
samarjit@cs.unc.edu
ABSTRACT
Modeling and design of automotive systems from a cyber-physical system (CPS) perspective have lately attracted extensive attention. As the trend towards automated driving and connectivity accelerates, strong interactions between vehicles and the infrastructure are expected. This requires modeling and control of the traffic network in a similarly formal manner. Modeling of such networks involves a tradeoff between expressivity of the appropriate features and tractability of the control problem. Back-pressure control of traffic signals is gaining ground due to its decentralized implementation, low computational complexity, and no requirements on prior traffic information. It guarantees maximum stability under idealistic assumptions. However, when deployed in real traffic intersections, the existing back-pressure control algorithms may result in poor junction utilization due to (i) fixed-length control phases; (ii) stability as the only objective; and (iii) obliviousness to finite road capacities and empty roads. In this paper, we propose a CPS-oriented model of traffic intersections and control of traffic signals, aiming to address the utilization issue of the back-pressure algorithms. We consider a more realistic model with transition phases and dedicated turning lanes, the latter influencing computation of the pressure and subsequently the utilization. The main technical contribution is an adaptive controller that enables varying-length control phases and considers both stability and utilization, while taking both cases of full roads and empty roads into account. We implement a mechanism to prevent frequent changes of control phases and thus limit the number of transition phases, which have negative impact on the junction utilization. Microscopic simulation results with SUMO on a 3 × 3 traffic network under various traffic patterns show that the proposed algorithm is at least about 13% better in performance than the existing fixed-length backpressure control algorithms reported in previous works. This is a significant improvement in the context of traffic signal control.
