Examining the feasibility of current spiral curve design controls for LiDAR‐based automated vehicles - Shuyi Wang; Chengyang Mao; Yang Ma; Jinzhou Liu; Bin Yu (IET Intelligent Transport Systems, 2023)
Abstract Enabling large‐scale deployment of automated vehicles (AVs) in the near future requires answering the question firstly: whether AVs could safely adapt to as‐built road geometry? This study aims to examine the feasibility of current spiral curve design controls for LiDAR‐based AVs (LAVs) from the perspective of the available sight distance (ASD). A series of tests featuring the design speed (Vd), lengths of tangent (LT) and spiral (LS), circular curve radii (R), and point thresholds for detection (NT) were simulated in PreScan/MATLAB/Simulink co‐simulation platform. The ASDs affected by those parameters’ combined effects were analyzed and compared with required stopping sight distances (RSDs) of human‐driven vehicles (HVs) and level 3 to 5 (L3–L5) LAVs followed by proposing the ASD‐oriented safe speeds and the corresponding speed limits. The results indicate that: (1) the combination of the tangent‐spiral curve‐circular curve causes a shorter ASD than that without the spiral curve; (2) a longer spiral curve causes a shorter ASD; and (3) only a low‐type combination of R, LS, Vd conditions is feasible for L3 LAVs while L4 or L5 LAVs have difficulties in dealing with high‐type conditions. These findings help understand the ASD for AVs and provide safety‐critical speed references for administrators.