Abstract
Traffic light-free intersection control is envisioned to alleviate congestion and manage vehicles intelligently. With the help of vehicle-to-infrastructure (V2I) communication and edge computing (EC), vehicles are instructed to cross the intersection with high vehicle safety and traffic efficiency without traffic lights. However, unstable channel conditions can lead to the reduction of traveling safety. In this paper, we propose a robust autonomous intersection control (AIC) approach with global optimization scheduling, which protects connected autonomous vehicles from collision under any channel conditions while achieving decent traffic efficiency. In particular, we propose an AIC model that gives vehicles certain autonomy under centralized control to ensure the traveling safety in case of some emergencies. By conducting an interference graph, we simplify the AIC problem as a weighted maximal clique problem with restriction. To improve the fairness and efficiency in terms of vehicle passage, multiple factors such as travel delay, traffic of the current lane and passengers' desired speed are considered. Furthermore, we propose a heuristic algorithm to search the solution space. For further optimization, a particle swarm optimization algorithm is proposed, achieving a near-optimal result with adjustable overhead. Finally, we build the simulation model and conduct a comparative performance evaluation. Simulation results demonstrate the superiority of our proposed scheme.
Highlights
Known as a bottleneck of traffic, intersections are the area that causes many accidents and traffic congestion [1]
Our autonomous intersection control (AIC) solution considers the influence of unstable channel conditions and external disturbances to ensure its robustness while presenting near-optimal performance in terms of traffic efficiency
We propose an AIC algorithm using a tabu search algorithm, which is based on solving the weighted maximum clique (WMC) problem
Summary
Known as a bottleneck of traffic, intersections are the area that causes many accidents and traffic congestion [1]. Researchers have proposed many ways to improve the performance of traffic lights, it still has its limitations [15]–[18]. Considering the above properties, in this paper, we propose an robust reservation-based AIC scheme for autonomous vehicles. The main contributions of this paper are summarized as follows: 1) We propose an edge-assisted traffic control architecture for CAVs. We divide intersection into multiple collision areas, and define the trajectories that vehicles in different motion (turning left, turning right or going straight) pass through for model simplification. All the possible collisions are predicted, and are abstracted with a weighted interference graph Multiple characteristics such as travel delay, current lane traffic and passengers’ desired speed are taken into account for system fairness and traffic efficiency consideration.
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