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. 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. 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. 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.

中文翻译：

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交通信号控制方法的最新回顾：挑战与机遇

由于每天的车辆数量激增，近年来缓解道路拥堵成为一项关键挑战。为了应付当前的交通情况并满足不断增长的交通需求，城市交通系统需要有效的解决方法。城市基础设施的变化将耗时数年，有时甚至不可行。因此，交通信号定时（TST）优化是减少交叉路口交通拥堵并改善城市网络交通流量的最快，最经济的方法之一。研究人员一直在努力使用各种方法以及利用技术来改善TST。本文旨在分析2015年1月至2020年1月之间发表的有关基于计算智能（CI）的仿真方法和基于CI的方法来优化TST和交通信号控制（TSC）系统的最新文献，提供见解，研究空白和可能的解决方案对该领域感兴趣的研究人员未来工作的方向。在分析交通流的复杂动态行为时，仿真工具占有重要地位。如今，微观仿真工具被广泛用于与TS​​T相关的研究中。因此，本文对一些广泛使用的微仿真软件包进行了严格的审查。我们的评论还显示，其中包括大约77％的论文都以某种形式利用了微仿真工具。因此，将评论，分类，与最常用的微仿真工具进行比较，以进行未来的工作。最后，我们提供有关这些领域研究未来的见解。