Reliable and efficient overtaking maneuvers are important and challenging for autonomous vehicles.Higher precision position information is thus required,rather than that traditional global navigation satellite systems...Reliable and efficient overtaking maneuvers are important and challenging for autonomous vehicles.Higher precision position information is thus required,rather than that traditional global navigation satellite systems can provide.In this paper,we try to perform reliable autonomous overtaking controls of vehicles,mainly based on the“relative”position information,including the distance,angle and velocity between vehicles,which can be achieved by on-board radars.To reduce the complexity of maneuvers,a fuzzy inference system is applied to analyze the driving behavior of the preceding vehicle based on the obtained consecutive relative position information.An output of“safe”or“dangerous”will be sent to the decision part based on reinforcement learning frameworks.Various overtaking maneuvers including“conservative”and“aggressive”can be obtained accordingly.Furthermore,we propose another overtaking strategy that vehicles can share their maneuver information during overtaking process via wireless links.Numeric results validate our analysis,and can provide meaningful performance benchmarks for practical system implementations.展开更多
基金supported by the Natural Science Foundation of China(under Grant No.91638204 and 61771159)Guangdong Natural Science Foundation under Grant No.2017A030313392Shenzhen Fundamental Research Project under Grant No.JCYJ20170811153639780。
文摘Reliable and efficient overtaking maneuvers are important and challenging for autonomous vehicles.Higher precision position information is thus required,rather than that traditional global navigation satellite systems can provide.In this paper,we try to perform reliable autonomous overtaking controls of vehicles,mainly based on the“relative”position information,including the distance,angle and velocity between vehicles,which can be achieved by on-board radars.To reduce the complexity of maneuvers,a fuzzy inference system is applied to analyze the driving behavior of the preceding vehicle based on the obtained consecutive relative position information.An output of“safe”or“dangerous”will be sent to the decision part based on reinforcement learning frameworks.Various overtaking maneuvers including“conservative”and“aggressive”can be obtained accordingly.Furthermore,we propose another overtaking strategy that vehicles can share their maneuver information during overtaking process via wireless links.Numeric results validate our analysis,and can provide meaningful performance benchmarks for practical system implementations.
