TxDOT Research Library - Publication Details

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Title:

Travel Modeling in an Era of Connected and Automated Transportation Systems: An Investigation in the Dallas-Fort Worth Area

Report No.:

DSTOP/2017/122

Authors:

James Kuhr [and six others (CTR)]; Thomas Bamonte, Arash Mirzaei, Hong Zheng (NCTCOG); Research Supervisor: Chandra Bhat

Published:

2017

Austin, Texas

University of Texas at Austin. Data-Supported Transportation Operations & Planning Center (DSTOP)

Series:

Technical Report (D-STOP)

Type:

Online document

1 PDF (61 pages)

Online Access:

https://ctr.utexas.edu/wp-content/uploads/122.pdf

Access Note:

1.7 MB

Summary

The North Central Texas Council of Governments (NCTCOG) engaged D-STOP to conduct a planned four-year study to analyze the status and progress of connected/autonomous vehicle (CAV) development, determine what the wide-ranging effects of the technology's adoption in North Central Texas, and, ultimately, begin constructing scenarios and methods to account for these effects in long range planning.

Part I begins by examining the state of technology for both AVs and CVs and provides evidence that the discrete technologies to enable both vehicle capabilities are nearing market readiness. The paper also draws a contrast between the two technologies as they are each being developed in response to distinct factors. Finally, Part I examines certain policy, privacy, and security questions. Part II looks at CAV adoption and finds that there will likely be decades of mixed use between AVs and human-driven vehicles. In addition, this section discusses existing adoption predictions from private consultants and academics, provides adoption estimates of CAVs based on adoption rates of similar technologies in the past, and proposes assumptions for three planning scenarios. Although the implementation timeline is highly uncertain, the market is susceptible to certain disruptors (such as ridesharing) that could significantly affect AV adoption. Finally, Part III describes the approach followed in order to propose 112 potential planning scenarios to reflect the wide range of potential CAV impacts. The proposed scenarios are built based on the analysis of possible adoption timelines for vehicle automation and connectivity, and consider the impact of additional behavioral and technological factors, using existent regional planning methodologies. The limitations of traditional modeling tools may limit the observed impacts of CAVs, which can motivate the exploration of more advanced tools such as activity-based models and dynamic traffic assignment.

Publ. Place

Austin, Texas

Contents

Executive Summary --
Part I: The State of CAV Technology --
Introduction --
Autonomous Vehicle Technology --
Vehicle and Infrastructure Communication --
Policy and Societal Concerns --
Overall Conclusions --
Part II: Adoption Scenarios --
Introduction --
Adoption of Connected Vehicles --
Adoption of Autonomous Vehicles --
Current Applications of Autonomous Vehicle Technology --
Summary --
Part III: Development of Planning Scenarios to Assess the Impacts of Autonomous and Connected Vehicles --
Introduction --
Relevant Factors to be Considered in a Comprehensive Assessment of CAVs’ Impact --
Proposed Planning Scenarios --
Future Research --
References --
Appendix A. Industry Car Formulas

Notes

"February 2017"

Study Sponsor

Contract No.

DTRT13-G-UTC58

Print Copy

Collection:

CTR (Misc) Online Only

Call Number:

DSTOP Report 122

More Like This

Topics

Intelligent vehicles
Mobile communication systems
Automated vehicle control
Intelligent transportation systems
Transportation planning
Technology assessment
Technological innovations
Vehicle to infrastructure communications
Vehicle to vehicle communications

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Contributors

Kuhr, James
Ruiz Juri, Natalia
Bhat, Chandra R. (Chandrasekhar R. ), 1964-
Archer, Jackson L.
Duthie, Jennifer Clare
Varela, Edgar A.
Zalawadia, Maitri
Bamonte, Thomas J.
Mirzai, Arash
Zheng, Hong

Center for Transportation Research (CTR)
North Central Texas Council of Governments (NCTCOG)

Updated

12/20/2021 10:34:04

Cataloged

February 20, 2017 11:35:22

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