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

Mayar Nour, Atrisha Sarkar, Mohamed H. Zaki

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.

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

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.
Paper Structure (15 sections, 7 equations, 5 figures, 3 tables)

This paper contains 15 sections, 7 equations, 5 figures, 3 tables.

Table of Contents

  1. Introduction
  2. Related Work
  3. Work Zone Safety and AVs Impact
  4. Trajectory Planning in AVs
  5. Game Theory Approaches
  6. Methodology
  7. Simulation Environment and Traffic Model
  8. Vehicle Modelling and Traffic Dynamics
  9. Game-Theoretic Lane Change Framework
  10. Interaction Pairing
  11. Game Formulation and Trajectory Sampling
  12. Receding Horizon Execution and Re-planning
  13. Results And Analysis
  14. Conclusion
  15. Acknowledgement

Figures (5)

  • Figure 1: SUMO representation of the 7 km M50 motorway segment in Dublin, Ireland, highlighting the work zone study area.
  • Figure 2: The Game-Theoretic Framework architecture.
  • Figure 3: Fig a: Game-theoretic control reduces lateral conflict frequency under L2 automation across simulation seeds. Fig b: The 5th percentile of TTC values is higher under Game-theoretic control.
  • Figure 4: Under L2, the proposed framework shifts the TTC distribution toward higher values, reducing the probability of high-risk interactions ($TTC < 2$ s) compared to the baseline scenario. Risk regions are defined as high risk ($< 2$ s), moderate risk (2–3 s), and safe ($> 3$ s).
  • Figure 5: Under L4, the proposed framework produces a slight rightward shift in the TTC distribution. Risk regions are defined as high risk ($< 2$ s), moderate risk (2–3 s), and safe ($> 3$ s).