Planning Persuasive Trajectories Based on a Leader-Follower Game Model

2025/07/29 by He, Chaozhe R., Dong, Yichen, Li, Nan
#FOS: Electrical engineering #Systems and Control (eess.SY) #electronic engineering #information engineering

paper · doi:10.48550/arxiv.2507.22022

Abstract

We propose a framework that enables autonomous vehicles (AVs) to proactively shape the intentions and behaviors of interacting human drivers. The framework employs a leader-follower game model with an adaptive role mechanism to predict human interaction intentions and behaviors. It then utilizes a branch model predictive control (MPC) algorithm to plan the AV trajectory, persuading the human to adopt the desired intention. The proposed framework is demonstrated in an intersection scenario. Simulation results illustrate the effectiveness of the framework for generating persuasive AV trajectories despite uncertainties.

Citations

• Eco-driving Accounting for Interactive Cut-in Vehicles
• Towards Proactive Safe Human-Robot Collaborations via Data-Efficient Conditional Behavior Prediction
• RILI: Robustly Influencing Latent Intent
• Interaction-Aware Trajectory Prediction and Planning for Autonomous Vehicles in Forced Merge Scenarios
• Learning Human Rewards by Inferring Their Latent Intelligence Levels in Multi-Agent Games: A Theory-of-Mind Approach with Application to Driving Data
• Game-theoretic Modeling of Traffic in Unsignalized Intersection Network for Autonomous Vehicle Control Verification and Validation
• Game-Theoretic Modeling of Multi-Vehicle Interactions at Uncontrolled Intersections
• Game-Theoretic Modeling of Driver and Vehicle Interactions for Verification and Validation of Autonomous Vehicle Control Systems

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