A priority tree based coordination method for intelligent and connected vehicles at unsignalized intersections

Abstract

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.

Research progress and prospect of energy-saving optimal control for intelligent and connected electric vehicles

“…With the continuous improvement of the coverage of intelligent transportation network and the efficiency of information acquisition, using the network of vehicles and infrastructure, vehicles and vehicles, vehicles and other objects (people, clouds, networks), we can obtain constantly changing navigation, high-precision maps and traffic environment information in real time, and comprehensively predict the impact of future traffic conditions on vehicle driving. The integration of modern communication and network technology can realize the exchange and sharing of intelligent information between vehicles, roads, people and clouds, and has the functions of complex environment perception, intelligent decision-making, collaborative control, etc., which can realize safe, efficient, comfortable and energy-saving driving, and finally realize a new generation of ICEV(Intelligent and Connected Electric Vehicles) operated instead of people [1].…”

A Decentralized Approach for Connected and Autonomous Vehicles Traffic Negotiation and Conflict Resolution

“…They are very complex and has several parameters that tries to replicate real world behavior that can be used to study urban mobility. These models can also be used as benchmark as demonstrated in the study by Dongxin et al (2021).…”

“…Finally, we use the metrics Average Travel Time, Average Speed, Average Waiting Time, Arrived Vehicles and Traffic Flow to evaluate our method and compare with SUMO and TLS methods. These metrics are widely used in several works in the literature (DONGXIN et al, 2021), (LEVIN; REY, 2017), (SCHEPPERLE; BöHM; FORSTER, 2007), (LISSAC; DJAHEL; HODGKISS, 2019) and (WANG; CAI; LU, 2020). As mentioned in the Section 1.1, our main goal is to enhance the flow of vehicles and reduce travel time.…”

“…The authors conclude that AIM* performs much better than AIM with FCFS policy. Dongxin et al (2021) proposed the coordination of passage at the non-signalized intersection using predefined trajectories coordinated through a priority tree based on a Dynamic Scheduling Algorithm and on an online formed priority tree. They also discretized the intersection center into sections used to calculate conflicts.…”

“…For each strategy, the trajectory is calculated for a given time interval and sampling time, and the trajectories represent "pre-defined" routes as pointed out by Chen and Englund (2016). As proposed by Dongxin et al (2021) and Levin and Rey (2017), once a trajectory is chosen it is no longer changed and overtaking is not considered either. In this way, the positions are calculated in continuous space, discretized time and a decision making is not changed.…”