Planning Persuasive Trajectories Based on a Leader-Follower Game Model

Fuente: arXiv
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Main Authors: He, Chaozhe R., Dong, Yichen, Li, Nan
Format: Preprint
Published: 2025
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author He, Chaozhe R.
Dong, Yichen
Li, Nan
author_facet He, Chaozhe R.
Dong, Yichen
Li, Nan
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2507_22022
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Planning Persuasive Trajectories Based on a Leader-Follower Game Model
He, Chaozhe R.
Dong, Yichen
Li, Nan
Systems and Control
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.
title Planning Persuasive Trajectories Based on a Leader-Follower Game Model
topic Systems and Control
url https://arxiv.org/abs/2507.22022