基于多结点仿真的自动驾驶场景数据保护方法OA

High-quality testing scenarios significantly enhance the efficiency of simulation testing for autonomous vehicles and possess substantial data value.To address the issue of data leakage caused by the full exposure of scenario data to simulation engines or platforms in existing simulation testing processes,this paper conducts an in-depth analysis of the OpenSCENARIO format standard,semantic content,and mapping relationships,proposing a novel scenario data protection method based on multi-node simulation.This method divides a scenario into multiple sub-segments and distributes them to different computing nodes for simulation.This enables fragmented operation of the complete scenario within a distributed simulation framework,effectively preventing full exposure of the original data.Furthermore,obfuscation techniques are introduced to preprocess the textual content of the sub-scenario data,further weakening the correlations among segments and increasing the difficulty of the reconstructing the complete scenario.Experimental results demonstrate that the simulation of these generated sub-scenario segments shows minimal deviation from the original simulation,successfully completing the simulation tasks while avoiding scenario data leakage.