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Abstract:
Emerging automated vehicle (AV) technology is being deployed on as-built roadways due to its promising safety improvements. However, realistic problems concerning whether and how perception sensor-based AVs can safely adapt to the existing roadway infrastructures remain to be well addressed due to a lack of consideration of the sensor's angular resolution and detection threshold. In this study, we aim to assess whether LiDAR-based AVs (LAVs) could safely adapt to as-built horizontal curved roads from the perspective of available sight distances (ASDs) through virtual simulations. In specific, i) numerous driving scenarios featuring the design speed (V-d: 40 similar to 100 km/h), circular curve radius (R: limited minimum radius similar to common minimum radius), LAV (with LiDAR technical parameters, e.g., number of channels, N-c: 32, 64, 128), and the front target vehicle were simulated in PreScan/MATLAB/Simulink co-simulation platform; ii) an ASD extraction algorithm was proposed considering the point threshold for detection (N-T); iii) effects of V-d, R, N-c, and N-T on the ASD were analyzed and polynomial models were adopted to capture relationships between the ASD, V-d, R at different N-c and N-T; iv) the minimum speed against as-built sight obstructions along the roadside and the maximum speed against inadequate sight distance were proposed by comparing the ASD with the required stopping sight distance of human-driven vehicles and LAVs (level 3 similar to 5), respectively; and v) speed limits (V-L) against inadequate sight distances for level 3 similar to 5 LAVs were proposed. The results indicate that: i) a larger R or V-d, fewer N-c, or a higher N-T would cause a shorter ASD in general; ii) attention should be paid to the occlusion imposed by as-built roadside infrastructures even with more N-c or/and a lower N-T, particularly to curved roads with more rigorous geometric design controls (e.g., small V-d); and iii) level 3 LAVs struggle to adapt to as-built horizontal curved roads, and level 4 or 5 LAVs cannot assure adequate ASDs on high-type curved roads (e.g., large V-d). These findings shall help road administrators make decisions on speed limits for LAVs on as-built curved roads.
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ACCIDENT ANALYSIS AND PREVENTION
ISSN: 0001-4575
Year: 2022
Volume: 174
5 . 9
JCR@2022
5 . 7 0 0
JCR@2023
ESI Discipline: SOCIAL SCIENCES, GENERAL;
ESI HC Threshold:36
JCR Journal Grade:1
CAS Journal Grade:1
Cited Count:
WoS CC Cited Count: 4
SCOPUS Cited Count: 6
ESI Highly Cited Papers on the List: 0 Unfold All
WanFang Cited Count:
Chinese Cited Count:
30 Days PV: 0
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