Planning Autonomous Vehicle Maneuvering in Work Zones Through Game-Theoretic Trajectory Generation

TL;DR

This paper introduces a game-theoretic approach for autonomous vehicle trajectory planning in work zones, improving safety and reducing conflicts by modeling lane changes as strategic games between vehicles.

Contribution

It presents a novel non-cooperative game-theoretic framework for AV trajectory generation specifically designed for complex work zone environments.

Findings

Reduces conflict frequency by 35%

Decreases high-risk safety events

Enhances lane change safety in simulations

Abstract

Work zone navigation remains one of the most challenging manoeuvres for autonomous vehicles (AVs), where constrained geometries and unpredictable traffic patterns create a high-risk environment. Despite extensive research on AV trajectory planning, few studies address the decision-making required to navigate work zones safely. This paper proposes a novel game-theoretic framework for trajectory generation and control to enhance the safety of lane changes in a work zone environment. By modelling the lane change manoeuvre as a non-cooperative game between vehicles, we use a game-theoretic planner to generate trajectories that balance safety, progress, and traffic stability. The simulation results show that the proposed game-theoretic model reduces the frequency of conflicts by 35 percent and decreases the probability of high risk safety events compared to traditional vehicle behaviour planning models in safety-critical highway work-zone scenarios.