This paper extends a real-time, Connected Vehicle-based traffic signal control algorithm at
isolated intersections to balance between two competing intersection objectives: efficiency …

Vehicular travel is increasing throughout the world, particularly in large urban areas.
Therefore the need arises for simulating and optimizing traffic control algorithms to better …

Optimal traffic light control is a multi-agent decision problem, for which we propose to use
reinforcement learning algorithms. Our algorithm learns the expected waiting times of cars …

Traffic conflict points (eg, intersections, work-zones) cause travel delay, stop-and-go traffic,
and excessive energy consumption. Efforts have been taken to improve traffic conflict point …

In junction traffic operations, vehicle delay is one of the most essential performance
measures of effectiveness. It allows traffic engineers to assess the performance of a traffic …

This work investigated stochastic distribution control theory-based traffic signal optimization
to achieve a smooth and uniform flow of vehicles through signalized intersections. In this …

Traffic jams can be avoided by controlling traffic signals according to quickly building
congestion with steep gradients on short temporal and small spatial scales. With the rising …

This chapter provides an in-depth overview of the state of the art on traffic light control and
optimization. Several classical control systems, methods, concepts, tools, and strategies are …

What if traffic lights gave you a break after you've spent a long time waiting in traffic
elsewhere? In this paper we examine a variety of multi-agent traffic light controllers which …

This paper presents an application of diverse soft-computing techniques to adaptive traffic
light controls. The proposed methodology consists of two main phases: off-line and on-line …