无人驾驶规则的自动提取方法研究

Research on Automatic Extraction Method of Driverless Rules

无人驾驶汽车的测试技术主要是通过虚拟测试和场地测试的方法来检测无人驾驶汽车的智能化水平,通过不断的学习和总结经验来提高无人驾驶的安全性,这种方法耗费大量的人力物力以及时间。为此,从文本的角度出发,利用驾驶行为相关文本,通过NLP技术和基于规则的方法构建一个无人驾驶规则库,依据这个规则库来辅助测试无人驾驶汽车能否满足道路安全要求。实验结果表明,对《中华人民共和国道路交通安全法实施条例》处理后规则提取的正确率为89.85%,驾考题库文本的正确率为87.33%。

Nowadays,the test technology of driverless vehicle mainly tests the intelligent level of driverless vehicle by means of virtual test and field test,and improves the safety of driverless vehicle by continuous learning and summarizing experience.This method consumes a lot of manpower,material resources and time.Therefore,from the perspective of text,this paper uses the driving behavior related text,through NLP technology and rule-based method to build an driverless rule base,according to which to help test whether the driverless vehicle can meet the requirements of road safety.The experimental results show that the accuracy rate of rule extraction is 89.85%and the accuracy rate of driving test database text is 87.33%.