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

ArXi:2603.20234v1 Announce Type: cross 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.