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author:

Wang, Shuyi (Wang, Shuyi.) [1] | Ma, Yang (Ma, Yang.) [2] | Liu, Jinzhou (Liu, Jinzhou.) [3] | Yu, Bin (Yu, Bin.) [4] | Zhu, Feng (Zhu, Feng.) [5]

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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 (Vd: 40 ∼ 100 km/h), circular curve radius (R: limited minimum radius ∼ common minimum radius), LAV (with LiDAR technical parameters, e.g., number of channels, Nc: 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 (NT); iii) effects of Vd, R, Nc, and NT on the ASD were analyzed and polynomial models were adopted to capture relationships between the ASD, Vd, R at different Nc and NT; 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 ∼ 5), respectively; and v) speed limits (VL) against inadequate sight distances for level 3 ∼ 5 LAVs were proposed. The results indicate that: i) a larger R or Vd, fewer Nc, or a higher NT would cause a shorter ASD in general; ii) attention should be paid to the occlusion imposed by as-built roadside infrastructures even with more Nc or/and a lower NT, particularly to curved roads with more rigorous geometric design controls (e.g., small Vd); 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 Vd). These findings shall help road administrators make decisions on speed limits for LAVs on as-built curved roads. © 2022 Elsevier Ltd

Keyword:

Automation Motor transportation Optical radar Roadsides Simulation platform Speed Vehicles

Community:

  • [ 1 ] [Wang, Shuyi]School of Transportation, Southeast University, 211189, China
  • [ 2 ] [Wang, Shuyi]College of Civil Engineering, Fuzhou University, Fuzhou; 350116, China
  • [ 3 ] [Ma, Yang]School of Automotive and Transportation Engineering, Hefei University of Technology, Hefei; 230009, China
  • [ 4 ] [Liu, Jinzhou]School of Transportation, Southeast University, 211189, China
  • [ 5 ] [Yu, Bin]School of Transportation, Southeast University, 211189, China
  • [ 6 ] [Zhu, Feng]School of Civil and Environmental Engineering, Nanyang Technological University, Singapore; 639798, Singapore

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Source :

Accident Analysis and Prevention

ISSN: 0001-4575

Year: 2022

Volume: 174

5 . 9

JCR@2022

5 . 7 0 0

JCR@2023

ESI HC Threshold:36

JCR Journal Grade:1

CAS Journal Grade:1

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 2

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