Implementation of Understanding the Impact of Autonomous Vehicles on Long-Distance Travel Mode and Destination Choice in Texas [Project Summary]

Kockelman, Kara; Vellimana, Maithreyi; Paithankar, Priyanka; Mori, Kentaro; University of Texas at Austin. Center for Transportation Research

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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.

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Implementation of Understanding the Impact of Autonomous Vehicles on Long-Distance Travel Mode and Destination Choice in Texas [Project Summary]

2023-12-31
By Kockelman, Kara ; Vellimana, Maithreyi ; Paithankar, Priyanka ; ...

English

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Details:

Creators:

Kockelman, Kara ; Vellimana, Maithreyi ; Paithankar, Priyanka ; Mori, Kentaro

Kockelman, Kara ; Vellimana, Maithreyi ; Paithankar, Priyanka ; Mori, Kentaro Less -
Corporate Creators:

University of Texas at Austin. Center for Transportation Research
Corporate Contributors:

Texas. Dept. of Transportation. Research and Technology Implementation Office ; United States. Department of Transportation. Federal Highway Administration

Texas. Dept. of Transportation. Research and Technology Implementation Office ; United States. Department of Transportation. Federal Highway Administration Less -
Subject/TRT Terms:

[+]

Autonomous Vehicles Choice Models Distance Forecasting Freight Transportation Market Penetration Mode Choice Travel Demand Vehicle Sharing
Publication/ Report Number:

5-7081-01
Resource Type:

Brief
Geographical Coverage:

Texas ; United States

Texas ; United States Less -
Edition:

Project Summary Report
Corporate Publisher:

University of Texas at Austin. Center for Transportation Research
Abstract:

As privately owned and shared autonomous vehicles (AVs and SAVs) and automated trucks (ATrucks) become available, TxDOT and partner agencies must anticipate their travel, trade, emissions, cost, and other implications. Introducing these modes can significantly alter mode choices for passenger travel and freight and impact traffic volumes and congestion throughout the network. The researchers significantly modified TxDOT’s Statewide Analysis Model (SAM) to predict travel and traffic impacts of AVs, SAVs, and ATrucks on passenger and freight flows across Texas.
Format:

PDF
Collection(s):

US Transportation Collection
Main Document Checksum:

[+]

urn:sha-512:bb3cd3c99a814dfb6b727e1298e0577f71adee000ba16a6011c5213ef6b95bd9d97227a3fa495026afe88beb7e3176085ccfbd7379bc5dfc2226a785d90f0ee8
Download URL:

https://rosap.ntl.bts.gov/view/dot/76658/dot_76658_DS1.pdf
File Type:

[PDF-385.24 KB]