Impacts of Shared Autonomous Vehicles on Traffic Operations (4.17)
As global demand for ride-hailing services rises, there is an increased urgency to study shared autonomous vehicles (SAV) fleets and their impacts on regional travel. According to Schaller (2018), the number of ride-sourcing vehicles and trips in New York City from 2013 to 2017 increased by 59% and 15%, respectively. In the same period, the number of idle vehicles increased by 81% and ride-sourcing drivers spent more than 40% of their time empty and cruising for passengers, which increased vehicle-miles travelled (VMT) by 36%. The same trends are expected to happen for ridesharing using SAVs if appropriate policies are not used to manage the empty VMT. For this reason, this proposed project aims to understand the impacts of ride-sharing, especially through shared autonomous vehicles on traffic operations and infrastructure durability (including the wear and tear of these vehicles on asphalt) in Connecticut. Investigating this impact requires the simulation of traffic for the entire population in the state under different ride-sharing scenarios. Traffic simulation tools require multiple datasets and calibrated models, which are different for each region. The research team plans to use a traffic simulator, such as POLARIS, which is an agent-based traffic simulation tool developed by Argonne National Laboratory, for SAV simulations. These tools allow for simulating multimodal traffic over large-scale transportation networks and requires multiple inputs and models calibrated for each specific region. Therefore, the research team will collect the required data and estimate models, including but not limited to activity generation, mode choice, and destination choice models, specific to Connecticut. The expected findings of this study could provide valuable insights into the impacts of autonomous vehicles and ride-sharing options provided by these vehicles on traffic operations including but not limited to VMT, empty VMT, and total travel time, as well as travel patterns in the state of Connecticut. These traffic operations and travel patterns will impact the deterioration of asphalt, which will be investigated in this study through the surface damage index.
Language
- English
Project
- Status: Active
- Funding: $80718
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Contract Numbers:
69A3551847101
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Sponsor Organizations:
Transportation Infrastructure Durability Center
University of Maine
Orono, ME United States 04469Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC United States 20590University of Connecticut, Storrs
Connecticut Transportation Institute
270 Middle Turnpike, Unit 5202
Storrs, CT United States 06269-5202 -
Managing Organizations:
Transportation Infrastructure Durability Center
University of Maine
Orono, ME United States 04469Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC United States 20590University of Connecticut, Storrs
Connecticut Transportation Institute
270 Middle Turnpike, Unit 5202
Storrs, CT United States 06269-5202 -
Project Managers:
Dunn, Denise
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Performing Organizations:
Transportation Infrastructure Durability Center
University of Maine
Orono, ME United States 04469University of Connecticut, Storrs
Connecticut Transportation Institute
270 Middle Turnpike, Unit 5202
Storrs, CT United States 06269-5202 -
Principal Investigators:
Fakhrmoosavi, Fatemeh
He, Suining
- Start Date: 20240301
- Expected Completion Date: 20250630
- Actual Completion Date: 0
- USDOT Program: University Transportation Centers Program
Subject/Index Terms
- TRT Terms: Autonomous vehicles; Pavement distress; Ridesharing; Ridesourcing; Traffic simulation; Travel time; Vehicle miles of travel; Vehicle sharing
- Geographic Terms: Connecticut
- Subject Areas: Highways; Maintenance and Preservation; Operations and Traffic Management; Planning and Forecasting; Vehicles and Equipment;
Filing Info
- Accession Number: 01917954
- Record Type: Research project
- Source Agency: Transportation Infrastructure Durability Center
- Contract Numbers: 69A3551847101
- Files: UTC, RIP
- Created Date: May 9 2024 3:15PM