Impact of Connected and Autonomous Vehicles on Nontraditional Intersection Design: Superstreets
Connected and autonomous vehicle (CAV) is an emerging technology that has the potential to improve operations, safety, and environment of the existing transportation system. Being able to travel on the roads with shorter headways, CAV is expected to yield a larger capacity compared with human-driven vehicles (HDVs). Accidents caused by human improper driving behaviors can also be reduced by the introduction of such technology. In addition, since CAVs can travel on the roads with fewer speed fluctuations, CAVs may as well contribute significantly to the emission reduction and improve the environmental condition of the current transportation system. Many studies have been conducted to explore the potential benefits of CAV technologies on the performances of conventional intersections. Improvement on the operational performances has been confirmed when the market penetration of CAVs reaches to a certain rate. Innovative intersections distinguish themselves usually by creating minor intersections that are hundreds of feet ahead of the main intersection for turning movements. Superstreets are one of the innovative intersection designs which have been implemented in numerous states. However, how CAVs would affect the performances of superstreets has not been explored, even to a minimum extent. To be specific, the following questions need to be answered: 1) at what market penetration rate would CAVs bring benefits towards operational performances; 2) at what extent would CAVs bring benefits towards operational performances of superstreets; 3) at what market penetration rate would CAVs bring benefits towards safety performances; 4) at what extent would CAVs bring benefits towards operational performances of superstreets. This study will fill this gap by conducting several simulation-based experiments to identify the potential impact of CAVs on superstreets regarding operational and safety performances. This study will also provide a better understanding of the impacts of CAVs on innovative intersections.
Language
- English
Project
- Status: Completed
- Funding: $90006
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Contract Numbers:
69A3551747133
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Sponsor Organizations:
Center for Advanced Multimodal Mobility Solutions and Education
University of North Carolina, Charlotte
Charlotte, NC United States 28223Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC United States 20590 -
Managing Organizations:
University of North Carolina - Charlotte
9201 University City Blvd
Charlotte, North Carolina United States 28223-0001 -
Project Managers:
Fan, Wei
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Performing Organizations:
Center for Advanced Multimodal Mobility Solutions and Education
University of North Carolina, Charlotte
Charlotte, NC United States 28223 -
Principal Investigators:
Fan, Wei
- Start Date: 20191001
- Expected Completion Date: 20210930
- Actual Completion Date: 20210930
Subject/Index Terms
- TRT Terms: Autonomous vehicles; Connected vehicles; Highway capacity; Highway design; Highway safety; Impacts; Intersections; Market penetration; Methodology; Mobility; Traffic congestion; Traffic simulation
- Identifier Terms: VISSIM (Computer model)
- Subject Areas: Highways; Operations and Traffic Management; Planning and Forecasting; Vehicles and Equipment;
Filing Info
- Accession Number: 01724142
- Record Type: Research project
- Source Agency: Center for Advanced Multimodal Mobility Solutions and Education
- Contract Numbers: 69A3551747133
- Files: UTC, RIP
- Created Date: Dec 1 2019 10:29AM