The electrification of vehicle helps to improve its operation efficiency and safety. Due to fast development of network, sensors, as well as computing technology, it becomes realizable to have vehicles driving autonomously. To achieve autonomous driving, several steps, including environment perception, path-planning, and dynamic control, need to be done. However, vehicles equipped with on-board sensors still have limitations in acquiring necessary environmental data for optimal driving decisions. Intelligent and connected vehicles (ICV) cloud control system (CCS) has been introduced as a new concept as it is a potentially synthetic solution for high level automated driving to improve safety and optimize traffic flow in intelligent transportation. This paper systematically investigated the concept of cloud control system from cloud related applications on ICVs, and cloud control system architecture design, as well as its core technologies development. Based on the analysis, the challenges and suggestions on cloud control system development have been addressed.
Intelligent and Connected Vehicle (ICV) technology is considered to be a solution to improve the traffic performance. Through the information exchange in real-time among the vehicles, the roadside infrastructures, and the cloud platform, the sensing of the vehicles can be enhanced. This also enables coordinated driving decisions, which can improve traffic operations, especially at bottleneck locations. This paper addresses the problem of coordinating the vehicles near the bottleneck locations to help the vehicles passing the area quickly and smoothly. A lane advisory algorithm is designed to reduce conflicts by encouraging early lane changes. A coordinated vehicle movement planning algorithm is proposed to achieve a smooth longitudinal reference speed profiles for vehicles in the subject area. The algorithm can open enough headway for vehicles to change the lane and continue their trips. The effectiveness of the algorithm is evaluated using SUMO (Simulation of Urban MObility) as the simulation tool with no communication between vehicles as the benchmark case as well as the case where the vehicular traffic follows the so-called First-in-First-Out (FIFO) principle. The results of the evaluation summarize and indicate that the Coordinated Control Algorithm (CCA) proposed in this paper can improve traffic performance in terms of the average speed, the waiting time, the total travel time, and the traffic flow rate under different levels of service. INDEX TERMS Coordinated control, coordinated movement planning, intelligent and connected vehicles, lane advisory, non-recurrent bottlenecks.
Intelligent and connected vehicles are believed to be the future solution to traffic management, especially in highly challenging areas such as intersections. In this paper, a priority tree based coordination method is proposed for intelligent and connected vehicles at unsignalized intersections. First, a dynamic scheduling method is used to generate the crossing order of the vehicles, considering the conflicting relationship, waiting time, and arrival time of the vehicles. Then a conflict resolution method is presented to handle the spatial and temporal conflicts among the vehicles inside the intersection. And the simulation results show that the method can generate collision-free traffic flows as well as improving the traffic performance.
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