Toward Intelligent Traffic Light Control with Quality-of-Service Provisioning

TL;DR

This paper investigates how traffic light scheduling impacts worst-case wait times, deriving theoretical bounds and proposing a controller that outperforms fixed-cycle systems in simulations.

Contribution

It introduces a theoretical analysis of worst-case wait times and proposes a new traffic light controller based on these insights.

Findings

Theoretical bounds for best-case and worst-case wait times at intersections.

The proposed controller significantly reduces wait times compared to fixed-cycle systems.

Effective in both light and heavy traffic scenarios.

Abstract

Today's fixed-cycle traffic signaling is highly suboptimal and aggravates traffic congestion and waste of energy in urban areas. In addition, it offers no quality-of-service guarantee and makes travel time prediction extremely hard. While existing traffic light control research primarily focuses on improving the average wait time of cars, we study in this paper how traffic light scheduling affects the worst-case wait time. In particular, we derive the time a car spends at an intersection in the best-case and the worst-case, respectively. Using the theoretical results, we propose a simple but effective controller and run simulation to verify its performance. The result shows that it works much better than fixed-cycle controllers in both light and heavy traffic scenarios.