高速场景下自动驾驶系统测试数据生成方法研究

Research on Test Data Generation Method of Automatic Driving System in High-speed Scenario

自动驾驶系统的应用范围随人工智能等领域的发展逐渐广泛,当前对于自动驾驶系统的研究多以十字路口场景为基础,缺少基于高速路段场景的研究,由于高速公路是车辆行驶道路上较为特殊且事故发生概率最高的路段之一,本文基于此提出了一种在高速场景下的自动驾驶系统测试数据生成方法。对选定的高速公路场景进行Petri网建模,并应用自适应的遗传算法生成测试数据,旨在使自动驾驶系统的测试覆盖路段更加全面,并能够更加安全的应用。

With the development of artificial intelligence and other fields,the application range of automatic driving system is gradually expanding.Currently,most of the researches on automatic driving system are based on the scene of intersections,and there is a lack of researches based on the scene of high-speed sections.Because the highway is one of the special sections on the road where vehicles travel and the probability of accidents is highest,based on this,this paper proposes a test data generation method for automatic driving system in high-speed scenario.Petri net modeling is carried out on selected highway scenes,and adaptive genetic algorithm is applied to generate test data,which aims to make the test coverage of automatic driving system more comprehensive and more secure application.