Autonomous and Connected Intersection Crossing Traffic Management using Discrete-Time Occupancies Trajectory

TL;DR

This paper introduces an algorithm for safe, efficient intersection crossing management for autonomous and connected vehicles, demonstrating deadlock and starvation freedom, and improving computational efficiency through enhancements validated by simulations.

Contribution

The paper proposes the Discrete-time Occupancies Trajectory based Intersection traffic Coordination Algorithm (DICA), with proven deadlock/starvation freedom and enhanced efficiency over the basic version.

Findings

The basic DICA is deadlock and starvation free.

Enhanced DICA reduces computational complexity from O(n^2 L_m^3) to O(n^2 L_m log L_m).

Simulation shows improved throughput and efficiency compared to traffic lights.

Abstract

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.