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Title:

Modeling the Impact of Shared Autonomous Vehicles on Travel Behaviors

Accession Number:

01764075

Record Type:

Component

Abstract:

Autonomous Vehicles (AVs) have the potential to offer benefits and flexibility in travel, which can lead to significant reductions in the generalized travel cost, and possibly more demand. The combination of the AV technology with Mobility as a Service (MaaS) creates a new disruptive transportation mode – Shared Autonomous Vehicles (SAVs) that have the promise to re-define the transportation landscape by improving mobility and competing with conventional transportation modes. While it is foreseen that SAVs could potentially be on the market in the near future, the long-range transportation planning process has yet to account for their impact. The authors fill this gap by presenting a framework of modeling SAVs to seamlessly integrate them into the four-step travel demand models that are widely used by transportation agencies. Using the Wasatch Front region in the State of Utah as a case study, this paper presents such modeling effort for the year 2040 forecast horizon. Delineated by different combinations of trip growth rates and SAV market attractiveness, the designed scenarios revealed that SAVs could increase the total number of trips by 1% to 7%. SAVs could shift travel away from conventional transportation modes. It is estimated that SAVs will increase daily Vehicle Miles Traveled (VMT) by 4% to 9% across designed scenarios due to improved mobility of underserved populations and additional repositioning trips. The results will assist public agencies in understanding the impacts of SAVs on travel patterns to further consider the special needs of AV technology in long-range cost estimates and programming processes.

Supplemental Notes:

This paper was sponsored by TRB committee AEP15 Standing Committee on Transportation Planning Analysis and Application.

Report/Paper Numbers:

TRBAM-21-03018

Language:

English

Corporate Authors:

Transportation Research Board

Authors:

Haghighi, Nima
Liu, Xiaoyue Cathy
Yi, Zhiyan

Pagination:

21p

Publication Date:

2021

Conference:

Transportation Research Board 100th Annual Meeting

Location: Washington DC, United States
Date: 2021-1-5 to 2021-1-29
Sponsors: Transportation Research Board; Transportation Research Board

Media Type:

Digital/other

Features:

Figures; References; Tables

Identifier Terms:

Mobility-as-a-Service (MaaS)

Geographic Terms:

Wasatch Front (Utah)

Subject Areas:

Data and Information Technology; Highways; Planning and Forecasting; Vehicles and Equipment

Source Data:

Transportation Research Board Annual Meeting 2021 Paper #TRBAM-21-03018

Files:

TRIS, TRB, ATRI

Created Date:

Dec 23 2020 11:19AM