Autonomous and Connected Intersection Crossing Traffic Management using Discrete-Time Occupancies Trajectory
This addresses traffic management for autonomous vehicles at intersections, but it appears incremental as it builds on existing coordination methods with computational optimizations.
The paper tackles the problem of safe and efficient intersection crossing for autonomous and connected ground traffic by proposing the Discrete-time occupancies trajectory based Intersection traffic Coordination Algorithm (DICA), which is proven deadlock-free and starvation-free, with computational complexity improved from O(n^2 L_m^3) to O(n^2 L_m log_2 L_m) through enhancements validated via simulation.
In this paper, we address a problem of safe and efficient intersection crossing traffic management of autonomous and connected ground traffic. Toward this objective, we propose an algorithm that is called the Discrete-time occupancies trajectory based Intersection traffic Coordination Algorithm (DICA). We first prove that the basic DICA is deadlock free and also starvation free. Then, we show that the basic DICA has a computational complexity of $\mathcal{O}(n^2 L_m^3)$ where $n$ is the number of vehicles granted to cross an intersection and $L_m$ is the maximum length of intersection crossing routes. To improve the overall computational efficiency of the algorithm, the basic DICA is enhanced by several computational approaches that are proposed in this paper. The enhanced algorithm has the computational complexity of $\mathcal{O}(n^2 L_m \log_2 L_m)$. The improved computational efficiency of the enhanced algorithm is validated through simulation using an open source traffic simulator, called the Simulation of Urban MObility (SUMO). The overall throughput as well as the computational efficiency of the enhanced algorithm are also compared with those of an optimized traffic light control.