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author:

Wang, Shuyi (Wang, Shuyi.) [1] | Ma, Yang (Ma, Yang.) [2] | Easa, Said M. (Easa, Said M..) [3] | Zhou, Hao (Zhou, Hao.) [4] | Lai, Yuanwen (Lai, Yuanwen.) [5] | Chen, Weijie (Chen, Weijie.) [6]

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EI

Abstract:

Most existing road infrastructures were constructed before the emergence of automated vehicles (AVs) without considering their operational needs. Whether and how AVs could safely adapt to as-built highway geometry are questions that remain inconclusive, and a plausible concern is a challenge from vertical alignments. To fill this gap, this study uses a virtual simulation to investigate the available sight distance (ASD) of AVs on vertical alignments subject to the current highway geometric design specification and its implications for speed limits. According to the scenario generation framework, several scenarios featuring vertical geometric elements and lidar sensors were created and tested. Moreover, the maximum speed for adequate ASD is calculated to determine the AV speed limit, considering safe sight distance and speed consistency requirements. The results indicate that crest curves are not disadvantaged in ASD compared with either sag curves or tangent grades. Only equipped with multichannel lidar and advanced perception algorithms enabling a lower detection threshold would a level 4 AV be compatible with the as-built vertical alignment with a design speed (Vd) of 100 km/h. However, a level 3 AV can only adapt to the vertical profile with Vd = 60 km/h. The findings of this study should be of interest to the road-oriented operational design domain and support road administrators in regulating AV safe speeds. 1939-1390 © 2023 IEEE.

Keyword:

Alignment Automation Automobile drivers Curves (road) Geometry Highway planning Optical radar Variable speed drives

Community:

  • [ 1 ] [Wang, Shuyi]Fuzhou University, College of Civil Engineering, Fuzhou; 350108, China
  • [ 2 ] [Ma, Yang]Hefei University of Technology, School of Automotive and Transportation Engineering, Hefei; 230000, China
  • [ 3 ] [Easa, Said M.]Toronto Metropolitan University, Department of Civil Engineering, Toronto; ON; M5B 2K3, Canada
  • [ 4 ] [Zhou, Hao]University of South Florida, Department of Civil Engineering, Tampa; FL; 33620, United States
  • [ 5 ] [Lai, Yuanwen]Fuzhou University, College of Civil Engineering, Fuzhou; 350108, China
  • [ 6 ] [Chen, Weijie]Southeast University, School of Transportation, Nanjing; 211189, China

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Source :

IEEE Intelligent Transportation Systems Magazine

ISSN: 1939-1390

Year: 2024

Issue: 4

Volume: 16

Page: 45-61

4 . 3 0 0

JCR@2023

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ESI Highly Cited Papers on the List: 0 Unfold All

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30 Days PV: 3

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