[2603.20234] Emergency Lane-Change Simulation: A Behavioral Guidance Approach for Risky Scenario Generation

Computer Science > Robotics arXiv:2603.20234 (cs) [Submitted on 8 Mar 2026] Title:Emergency Lane-Change Simulation: A Behavioral Guidance Approach for Risky Scenario Generation Authors:Chen Xiong, Cheng Wang, Yuhang Liu, Zirui Wu, Ye Tian View a PDF of the paper titled Emergency Lane-Change Simulation: A Behavioral Guidance Approach for Risky Scenario Generation, by Chen Xiong and 4 other authors View PDF HTML (experimental) Abstract:In contemporary autonomous driving testing, virtual simulation has become an important approach due to its efficiency and cost effectiveness. However, existing methods usually rely on reinforcement learning to generate risky scenarios, making it difficult to efficiently learn realistic emergency behaviors. To address this issue, we propose a behavior guided method for generating high risk lane change scenarios. First, a behavior learning module based on an optimized sequence generative adversarial network is developed to learn emergency lane change behaviors from an extracted dataset. This design alleviates the limitations of existing datasets and improves learning from relatively few samples. Then, the opposing vehicle is modeled as an agent, and the road environment together with surrounding vehicles is incorporated into the operating environment. Based on the Recursive Proximal Policy Optimization strategy, the generated trajectories are used to guide the vehicle toward dangerous behaviors for more effective risk scenario exploration. Final...