Traffic Signal Control Methods: Current Status, Challenges, and Emerging Trends

Traffic signal control is an important and challenging real-world problem that has recently received a large amount of interest from both transportation and computer science communities. In this survey, we focus on investigating the recent advances in using reinforcement learning (RL) techniques to solve the traffic signal control problem. We classify the known approaches based on the RL techniques they use and provide a review of existing models with analysis on their advantages and disadvantages. Moreover, we give an overview of the simulation environments and experimental settings that have been developed to evaluate the traffic signal control methods. Finally, we explore future directions in the area of RLbased traffic signal control methods. We hope this survey could provide insights to researchers dealing with real-world applications in intelligent transportation systems

Download Full-text

A Systematic Literature Review of Researches on Urban Traffic Strategy Development

International Research Journal of Electronics and Computer Engineering ◽

10.24178/irjece.2017.3.1.14 ◽

2017 ◽

Vol 3 (1) ◽

pp. 14

Author(s):

Zhang Lin ◽

Cheng Wei ◽

Wang Wei ◽

Li Yinan ◽

Xiao Haochen

Keyword(s):

Traffic Signal ◽

Urban Traffic ◽

Current Status ◽

Signal Control ◽

Traffic Signal Control ◽

Traffic Network ◽

Optimization Strategy ◽

Advantages And Disadvantages ◽

Research Perspectives ◽

Traffic Optimization

Abstract—With the advancement of computer science and the development of urban economy, the interest of human research on urban traffic strategy has been promoted. Number of vehicles in urban traffic network in a sharp increase, in order to solve the current status of China's traffic congestion, we hope to reduce urban vehicles greenhouse gas emissions and to reduce waiting time is a serious problem currently facing the city traffic. In order to solve this problem, it can be from two aspects. On the one hand, traffic signal control of traffic network, the other is to optimize the route of the vehicle. This paper respectively from tells the development of the traffic signal control strategy and vehicle routing process, and compares their advantages and disadvantages. The paper summarizes the urban traffic strategy and traffic optimization strategy in recent years, and systematically summarizes the present situation and existing problems of urban traffic optimization strategies at home and abroad, summarizes the development prospects of urban traffic optimization strategies, and provides the strategies for traffic optimization. In order to provide the strategy of scholars engaged in the transportation of new research perspectives and research data.

Download Full-text

A survey of model predictive control methods for traffic signal control

IEEE/CAA Journal of Automatica Sinica ◽

10.1109/jas.2019.1911471 ◽

2019 ◽

Vol 6 (3) ◽

pp. 623-640 ◽

Cited By ~ 8

Author(s):

Bao-Lin Ye ◽

Weimin Wu ◽

Keyu Ruan ◽

Lingxi Li ◽

Tehuan Chen ◽

...

Keyword(s):

Model Predictive Control ◽

Predictive Control ◽

Traffic Signal ◽

Signal Control ◽

Traffic Signal Control ◽

Control Methods

Download Full-text

A Scientometric-Based Review of Traffic Signal Control Methods and Experiments Based on Connected Vehicles and Floating Car Data (FCD)

Applied Sciences ◽

10.3390/app11125547 ◽

2021 ◽

Vol 11 (12) ◽

pp. 5547

Author(s):

Vittorio Astarita ◽

Vincenzo Pasquale Giofrè ◽

Giuseppe Guido ◽

Alessandro Vitale

Keyword(s):

New Technologies ◽

State Of The Art ◽

Traffic Signal ◽

The State ◽

Signal Control ◽

Traffic Signal Control ◽

Connected Vehicles ◽

City Management ◽

Control Methods ◽

Floating Car Data

This paper reviews the state of the art in traffic signal control methods that are based on data coming from onboard smartphones or connected vehicles. The review of the state of the art is carried out by applying analytical scientometric tools (topic visualization, co-citation analysis to establish influential journals and references, country analysis based on coauthorship, trending-topics analysis carried out by overlay visualization). The introduction of autonomous and connected vehicles will allow city management organizations to introduce new intersection management systems that rely on real-time positional data coming from instrumented vehicles. Traditional vehicles also could benefit from these new technologies by profiting from better-regulated intersections. This paper using a scientometric approach frames all the scientific contributions aimed at the field of traffic signal methods and experiments based on connected vehicles and floating car data. The applied scientometric approach reveals trending ideas and concepts and identifies the relevant documents that can be consulted in order for scientists and professionals to develop further this field with the implementation of new traffic signal control systems that can “give the green light” to drivers.

Download Full-text