Ill-managed intersections are the primary reasons behind the increasing traffic problem in urban areas, leading to nonoptimal traffic-flow and unnecessary deadlocks. In this paper, we propose an automated intersection management system that extracts data from a well-defined grid of sensors and optimizes traffic flow by controlling traffic signals. The data extraction mechanism is independent of the optimization algorithm and this paper primarily emphasizes the later one. We have used MiniZinc modeling language to define our system as a constraint satisfaction problem which can be solved using any off-the-shelf solver. The proposed system performs much better than the systems currently in use. Our system reduces the mean waiting time and standard deviation of the waiting time of vehicles and avoids deadlocks.
LIDSA: Cognitive Arbitration for Signal-Free Autonomous Intersection Management
Department of Computer and Network Engineering, United Arab Emirates University, UAE（计算机与网络工程系，阿联酋大学）；Research Institute for Digital Future, Khalifa University, UAE（未来数字研究院，哈利法大学）
DSIP: A Dynamic Coordination Planner for Signal-Free Intersections using Diffusion-Model-Based Multi-Agent Motion Planning
Global Institute of Future Technology, Shanghai Jiao Tong University（上海交通大学全球未来技术学院）；School of Automation and Intelligent Sensing, Shanghai Jiao Tong University（上海交通大学自动化与智能感知学院）；Department of Electrical Engineering, The University of Texas at Arlington（德克萨斯大学阿灵顿分校电气工程系）
A Multi-intersection Vehicular Cooperative Control based on End-Edge-Cloud Computing
Beijing University of Posts and Telecommunications（北京邮电大学）；Beijing Information Science and Technology University（北京信息科技大学）；University of Technology Sydney（悉尼科技大学）
Towards Multi-agent Reinforcement Learning based Traffic Signal Control through Spatio-temporal Hypergraphs
School of Computer Science and Artificial Intelligence, Wuhan University of Technology（武汉理工大学计算机科学与人工智能学院）；College of Electronics and Information Engineering, Tongji University（同济大学电子与信息工程学院）；School of Computer Science and Technology, Tongji University（同济大学计算机科学与技术学院）
Ground Plane Projection for Improved Traffic Analytics at Intersections
Center of Vision Research (CVR) and Centre for AI & Society (CAIS) at York University（约克大学视觉研究中心（CVR）和人工智能与社会研究中心（CAIS））；Vector Institute for Artificial Intelligence（人工智能向量研究所）；Region of York（约克地区）；York University（约克大学）；University of Toronto（多伦多大学）
Traffic control using intelligent timing of traffic lights with reinforcement learning technique and real-time processing of surveillance camera images
