State-of-art review of traffic signal control methods: challenges and opportunities

Abstract

Introduction Due to the menacing increase in the number of vehicles on a daily basis, abating road congestion is becoming a key challenge these years. To cope-up with the prevailing traffic scenarios and to meet the ever-increasing demand for traffic, the urban transportation system needs effective solution methodologies. Changes made in the urban infrastructure will take years, sometimes may not even be feasible. For this reason, traffic signal timing (TST) optimization is one of the fastest and most economical ways to curtail congestion at the intersections and improve traffic flow in the urban network. Purpose Researchers have been working on using a variety of approaches along with the exploitation of technology to improve TST. This article is intended to analyze the recent literature published between January 2015 and January 2020 for the computational intelligence (CI) based simulation approaches and CI-based approaches for optimizing TST and Traffic Signal Control (TSC) systems, provide insights, research gaps and possible directions for future work for researchers interested in the field. Methods In analyzing the complex dynamic behavior of traffic streams, simulation tools have a prominent place. Nowadays, microsimulation tools are frequently used in TST related researches. For this reason, a critical review of some of the widely used microsimulation packages is provided in this paper. Conclusion Our review also shows that approximately 77% of the papers included, utilizes a microsimulation tool in some form. Therefore, it seems useful to include a review, categorization, and comparison of the most commonly used microsimulation tools for future work. We conclude by providing insights into the future of research in these areas.

Evaluation and Analysis of CFI Schemes with Different Length of Displaced Left-Turn Lanes with Entropy Method

“…Besides, considering the settings of left-turn bays, two single-objective optimization models were developed for paired intersections with uncoordinated and coordinated signals [9]. A review article analyzed the current method of traffic signal timing and presented several directions for future research [10]. An unconventional leftturn waiting area design is also an innovative approach to mitigate traffic congestion at signalized intersections.…”

Traffic Signal Control: a Double Q-learning Approach

“…In [10], the authors presented an overview of widely acknowledged classical transportation approaches and the current state of research on the traffic signal control problem. In [11], the authors analyzed the literature for 2015-2020 on the topic of traffic management, reviewed approaches based on microsimulation and computational intelligence, presented research gaps and possible directions for future work. An overview of traffic control methods using data from autonomous and connected vehicles is presented in [12].…”

Group Formation in Shared Spaces

“…However, forming groups is not a trivial task in shared spaces. Firstly, shared spaces have no road markings such as zebra lines or lane markers, thus the location and number of groups should be decided, which is different from most area traffic management methods (Qadri et al, 2020;Ramadhan et al, 2020). Secondly, in shared spaces, the coming and leaving spots of road users may vary dramatically in different periods, therefore, a dynamic clustering algorithm for group formation is needed.…”