Impact of Connected and Autonomous Vehicles on Nontraditional Intersection Design: Superstreets

Fan, Wei (David); Liu, Shaojie

i

Impact of Connected and Autonomous Vehicles on Nontraditional Intersection Design: Superstreets

2021-09-01
By Fan, Wei (David) ; Liu, Shaojie

File Language:

English

Details

Creators:

Fan, Wei (David) ; Liu, Shaojie
Corporate Creators:

University of North Carolina at Charlotte. Center for Advanced Multimodal Mobility Solutions and Education
Corporate Contributors:

United States. Department of Transportation. University Transportation Centers (UTC) Program
Subject/TRT Terms:

Autonomous Vehicles Connected Vehicles Highway Capacity Highway Design Highway Safety Impacts Intersections Market Penetration Methodology Mobility Traffic Congestion Traffic Simulation
Publication/ Report Number:

2020 Project 03;CAMMSE-UNCC-2020-UTC-Project-03
Resource Type:

Tech Report
Geographical Coverage:

United States
Corporate Publisher:

University of North Carolina at Charlotte. Center for Advanced Multimodal Mobility Solutions and Education
Abstract:

Congestion has been becoming a critical issue for transportation professionals as it increases travel time, energy use and pollutant emissions. Thanks to recent technology development of wireless communication and artificial intelligence, connected and autonomous vehicles (CAVs) become a promising and practical approach to increasing road capacity. As many studies have been done to explore the potential application and impact of CAVs in various transportation environment and scenarios, such as freeway segments (Liu and Fan 2020), signalized intersections (Han et al., 2020), unsignalized intersections (Sharon and Stone, 2017), roundabouts (Anagnostopoulos and Kehagia, 2020) and on/off ramps (Rios-Torres and Malikopoulos, 2016), the operational performance of CAVs at innovative intersections had received relatively less attention. This research aims to mitigate the research gaps by conducting simulation-based research to explore the impact of CAVs on the operational performances in the environment of superstreets.
Format:

PDF
Funding:

69A3551747133
Collection(s):

University Transportation Centers US Transportation Collection Autonomous Vehicles
Main Document Checksum:

urn:sha-512:b234cbe9725fb8c726e95dabd4fc9236ec6c447ffb66814fd6f7592e5148a5becedc2d39069b7d6513b2c7b83055f9d58dc02fe0f0e121c6dffadba86af164e8
Download URL:

https://rosap.ntl.bts.gov/view/dot/58262/dot_58262_DS1.pdf
File Type:

[PDF - 1.57 MB ]

File Language:

English

ON THIS PAGE

Details

ROSA P serves as an archival repository of USDOT-published products including scientific findings, journal articles, guidelines, recommendations, or other information authored or co-authored by USDOT or funded partners. As a repository, ROSA P retains documents in their original published format to ensure public access to scientific information.