Assessing the Impact of Automated and Connected Automated Vehicles on Virginia Freeways

This study assesses the impact of the introduction of connected and automated vehicles on Virginia freeway corridors. Three vehicle types: legacy vehicles (LV), automated vehicles (AV), and connected automated vehicles (CAV), were considered in mixed traffic scenarios. Previous relevant studies were reviewed and the proper operating parameters for LV, AV, and CAV identified. AV and CAV driving behavior models were developed in the VISSIM environment. According to the basic freeway test network results, AV and CAV increase road capacity by 29% and 91%. In the merging freeway test network, AV and CAV increase road capacity by 48% and 60% compared with LV, respectively. A model with diverse LV, AV, and CAV market penetration and diverse traffic demand was tested on I-95 in Virginia, where the research team tested the speed and throughput. Under the current traffic demand, the average speed was higher when there were more AV and no CAV in the traffic flow. However, the average speed of CAV in a congested segment is higher than LV. In the case of throughput, CAV shows poor performance under current traffic demand. With increased traffic demand, high penetrations of AV and CAV present better performance because of their short headway and homogeneity. Therefore, the study predicts that in the future, as the traffic demand grows, AV and CAV can reduce traffic congestion.

• Record URL:
  https://doi.org/10.1177/03611981211004979
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/03611981
• Supplemental Notes:
  • © National Academy of Sciences: Transportation Research Board 2021.
• Authors:
  • Kim, Bumsik
  • Heaslip, Kevin P
  • Aad, Mirla Abi
  • Fuentes, Antonio
  • Goodall, Noah
• Publication Date: 2021-9

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 870-884
• Serial:
  • Transportation Research Record: Journal of the Transportation Research Board
  • Volume: 2675
  • Issue Number: 9
  • Publisher: Sage Publications, Incorporated
  • ISSN: 0361-1981
  • EISSN: 2169-4052
  • Serial URL: http://journals.sagepub.com/home/trr

Subject/Index Terms

• TRT Terms: Connected vehicles; Freeways; Highway capacity; Intelligent vehicles; Merging area; Motor vehicles; Traffic congestion; Traffic speed; Travel demand
• Geographic Terms: Virginia
• Subject Areas: Highways; Operations and Traffic Management;

Filing Info

• Accession Number: 01769402
• Record Type: Publication
• Files: TRIS, TRB, ATRI
• Created Date: Apr 13 2021 4:42PM