Using Reinforcement Learning With Partial Vehicle Detection for Intelligent Traffic Signal Control

Reinforcement Learning For Adaptive Traffic Signal Control

By 2050, two-thirds of the world’s 9.6 billion people will live in urban areas [2]. In many cities, opportunities to expand urban road networks are limited, so existing roads will need to more efficiently accommodate higher volumes of traffic. Consequently, there is a pressing need for technologically viable, low-cost solutions that can work with existing infrastructure to help alleviate increa...

Using a Deep Reinforcement Learning Agent for Traffic Signal Control

Ensuring transportation systems are efficient is a priority for modern society. Technological advances have made it possible for transportation systems to collect large volumes of varied data on an unprecedented scale. We propose a traffic signal control system which takes advantage of this new, high quality data, with minimal abstraction compared to other proposed systems. We apply modern deep...

Reinforcement learning in neurofuzzy traffic signal control

A reinforcement learning based traffic signal control algorithm in a connected vehicle environment

The emerging vehicle technologies, i.e. connected vehicle technology and autonomous driving technology, can be beneficial for traffic control and operations. They not only serve as new source of information, but also enable us to control and modify the trajectory of vehicles. Reinforcement learning is widely used to design intelligent control algorithms in various disciplines. This paper provid...

Multiobjective Reinforcement Learning for Traffic Signal Control Using Vehicular Ad Hoc Network

We propose a newmultiobjective control algorithm based on reinforcement learning for urban traffic signal control, namedmultiRL. A multiagent structure is used to describe the traffic system. A vehicular ad hoc network is used for the data exchange among agents. A reinforcement learning algorithm is applied to predict the overall value of the optimization objective given vehicles’ states. The p...