A Graph-based Conflict-free Cooperation Method for Intelligent Electric Vehicles at Unsignalized Intersections

TL;DR

This paper introduces a graph-based approach for conflict-free scheduling of intelligent electric vehicles at unsignalized intersections, improving traffic flow and safety through optimized algorithms.

Contribution

It proposes novel graph-based methods for conflict-free vehicle scheduling, including a depth-first spanning tree and maximum matching algorithm, with proven effectiveness.

Findings

Algorithms effectively improve vehicle passing order

Simulation results validate the proposed methods

Complexity analysis supports practical application

Abstract

Electric, intelligent, and network are the most important future development directions of automobiles. Intelligent electric vehicles have shown great potentials to improve traffic mobility and reduce emissions, especially at unsignalized intersections. Previous research has shown that vehicle passing order is the key factor in traffic mobility improvement. In this paper, we propose a graph-based cooperation method to formalize the conflict-free scheduling problem at unsignalized intersections. Firstly, conflict directed graphs and coexisting undirected graphs are built to describe the conflict relationship of the vehicles. Then, two graph-based methods are introduced to solve the vehicle passing order. One method is an optimized depth-first spanning tree method which aims to find the local optimal passing order for each vehicle. The other method is a maximum matching algorithm that solves the global optimal problem. The computational complexity of both methods is also derived. Numerical simulation results demonstrate the effectiveness of the proposed algorithms.