V2V-Based Collision-Avoidance Decision Strategy for Autonomous Vehicles Interacting with Fully Occluded Pedestrians at Midblock on Multilane Roadways
Pedestrian occlusion is challenging for autonomous vehicles (AVs) at midblock locations on multilane roadways because an AV cannot detect crossing pedestrians that are fully occluded by downstream vehicles in adjacent lanes. This paper tests the capability of vehicle-to-vehicle (V2V) communication between an AV and its downstream vehicles to share midblock pedestrian crossing information. The researchers developed a V2V-based collision-avoidance decision strategy and compared it to a base scenario (i.e., decision strategy without the utilization of V2V). Simulation results showed that for the base scenario, the near-zero time-to-collision (TTC) indicated no time for the AV to take appropriate action and resulted in dramatic braking followed by collisions. But the V2V-based collision-avoidance decision strategy allowed for a proportional braking approach to increase the TTC allowing the pedestrian to cross safely. To conclude, the V2V-based collision-avoidance decision strategy has higher safety benefits for an AV interacting with fully occluded pedestrians at midblock locations on multilane roadways.
- Record URL:
-
Availability:
- Find a library where document is available. Order URL: http://worldcat.org/isbn/9780784484876
-
Supplemental Notes:
- © 2023 American Society of Civil Engineers.
-
Corporate Authors:
American Society of Civil Engineers
1801 Alexander Bell Drive
Reston, VA United States 20191-4400 -
Authors:
- Zou, Fengjiao
- Deng, Hsien-Wen
-
0000-0001-9964-4356
- Iunn, Tsing-Un
- Ogle, Jennifer Harper
- Jin, Weimin
-
Conference:
- International Conference on Transportation and Development 2023
- Location: Austin Texas, United States
- Date: 2023-6-14 to 2023-6-17
- Publication Date: 2023
Language
- English
Media Info
- Media Type: Web
- Features: References;
- Pagination: pp 180-193
- Monograph Title: International Conference on Transportation and Development 2023: Transportation Safety and Emerging Technologies
Subject/Index Terms
- TRT Terms: Autonomous vehicles; Crash avoidance systems; Midblock crossings; Multilane highways; Pedestrian vehicle crashes; Vehicle to vehicle communications
- Subject Areas: Data and Information Technology; Highways; Pedestrians and Bicyclists; Safety and Human Factors; Vehicles and Equipment;
Filing Info
- Accession Number: 01902016
- Record Type: Publication
- ISBN: 9780784484876
- Files: TRIS, ASCE
- Created Date: Dec 12 2023 2:00PM