With the growing rate of automated vehicles(AVs)at the lower level of automation,the experimental tests are also in progress with vehicles at higher levels.In the absence of extended digital infrastructures and deploy...With the growing rate of automated vehicles(AVs)at the lower level of automation,the experimental tests are also in progress with vehicles at higher levels.In the absence of extended digital infrastructures and deployment of level 5 full automated vehicles,the physical infrastructure is required to maintain a fundamental role to enable their introduction in public roads.This paper focuses on lane support system(LSS)whose operational design domain(ODD)is strongly connected to the road characteristics and conditions.An experimental test was carried out with a state of the art,and LSS and advanced technologies were used for road monitoring on different roads under various environmental conditions including dry,wet pavements and rain.We applied the generalized estimation equation for logistic regression to account within-cluster homogeneity which is induced by repeated measures on the same road sections.Statistical models allow the identification of variables that are significant for the LSS fault probability among various effects of road features including marking,pavement distress,weather conditions,horizontal curvature,and cross section.Results pointed out the relevance of the wet retro-reflection of marking(RLw)and the horizontal curvature in the definition of ODD for LSS.Threshold values have been proposed for the tested LSS.Wet pavement doesn’t affect the LSS performance when compared to the dry condition.Rain was shown to be critical even with very good road characteristics.展开更多
To improve the ride comfort and safety of a traditional adaptive cruise control(ACC)system when the preceding vehicle changes lanes,it proposes a target vehicle selection algorithm based on the prediction of the lane-...To improve the ride comfort and safety of a traditional adaptive cruise control(ACC)system when the preceding vehicle changes lanes,it proposes a target vehicle selection algorithm based on the prediction of the lane-changing intention for the preceding vehicle.First,the Next Generation Simulation dataset is used to train a lane-changing intention prediction algorithm based on a sliding window support vector machine,and the lane-changing intention of the preceding vehicle in the current lane is identified by lateral position offset.Second,according to the lane-changing intention and collision threat of the preceding vehicle,the target vehicle selection algorithm is studied under three different conditions:safe lane-changing,dangerous lane-changing,and lane-changing cancellation.Finally,the effectiveness of the proposed algorithm is verified in a co-simulation platform.The simulation results show that the target vehicle selection algorithm can ensure the smooth transfer of the target vehicle and effectively reduce the longitudinal acceleration fluctuation of the subject vehicle when the preceding vehicle changes lanes safely or cancels their lane change maneuver.In the case of a dangerous lane change,the target vehicle selection algorithm proposed in this paper can respond more rapidly to a dangerous lane change than the target vehicle selection method of the traditional ACC system;thus,it can effectively avoid collisions and improve the safety of the subject vehicle.展开更多
基金partially financed by“Astro Database”Project of the University of Catania
文摘With the growing rate of automated vehicles(AVs)at the lower level of automation,the experimental tests are also in progress with vehicles at higher levels.In the absence of extended digital infrastructures and deployment of level 5 full automated vehicles,the physical infrastructure is required to maintain a fundamental role to enable their introduction in public roads.This paper focuses on lane support system(LSS)whose operational design domain(ODD)is strongly connected to the road characteristics and conditions.An experimental test was carried out with a state of the art,and LSS and advanced technologies were used for road monitoring on different roads under various environmental conditions including dry,wet pavements and rain.We applied the generalized estimation equation for logistic regression to account within-cluster homogeneity which is induced by repeated measures on the same road sections.Statistical models allow the identification of variables that are significant for the LSS fault probability among various effects of road features including marking,pavement distress,weather conditions,horizontal curvature,and cross section.Results pointed out the relevance of the wet retro-reflection of marking(RLw)and the horizontal curvature in the definition of ODD for LSS.Threshold values have been proposed for the tested LSS.Wet pavement doesn’t affect the LSS performance when compared to the dry condition.Rain was shown to be critical even with very good road characteristics.
基金Supported by National Key Research and Development Program(Grant No.2017YFB0102601)National Natural Science Foundation of China(Grant Nos.51775236,U1564214).
文摘To improve the ride comfort and safety of a traditional adaptive cruise control(ACC)system when the preceding vehicle changes lanes,it proposes a target vehicle selection algorithm based on the prediction of the lane-changing intention for the preceding vehicle.First,the Next Generation Simulation dataset is used to train a lane-changing intention prediction algorithm based on a sliding window support vector machine,and the lane-changing intention of the preceding vehicle in the current lane is identified by lateral position offset.Second,according to the lane-changing intention and collision threat of the preceding vehicle,the target vehicle selection algorithm is studied under three different conditions:safe lane-changing,dangerous lane-changing,and lane-changing cancellation.Finally,the effectiveness of the proposed algorithm is verified in a co-simulation platform.The simulation results show that the target vehicle selection algorithm can ensure the smooth transfer of the target vehicle and effectively reduce the longitudinal acceleration fluctuation of the subject vehicle when the preceding vehicle changes lanes safely or cancels their lane change maneuver.In the case of a dangerous lane change,the target vehicle selection algorithm proposed in this paper can respond more rapidly to a dangerous lane change than the target vehicle selection method of the traditional ACC system;thus,it can effectively avoid collisions and improve the safety of the subject vehicle.
