Kockelman, Kara; Boyles, Stephen; Stone, Peter; Fagnant, Dan; Patel, Rahul; Levin, Michael W.; Sharon, Guni; Simoni, Michele; Albert, Michael; Fritz, Hagen; Hutchinson, Rebecca; Bansal, Prateek; Domnenko, Gleb; Bujanovic, Pavle; Kim, Bumsik; Pourrahmani, Elham; Agrawal, Sudesh; Li, Tianxin; Hanna, Josiah; Nichols, Aqshems; Li, Jia
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A research team based out of the University of Texas-Austin's Center for Transportation Research sought to provide a systematic synthesis of contemporary smart driving technologies, such as connected and autonomous vehicles (CAVs), including their technological maturity and their potential crash, congestion and other impacts in Texas at various levels of market penetration. The project designed and disseminated a Texas-wide survey with 1,364 completed responses to analyze and gain an understanding of the U.S. general public’s perception towards and willingness to adopt such technologies. Additionally, the research team studied the effects of rising CAV ownership on transit ridership, CAV repositioning trips, and total personal-vehicle demand using the traditional four-step planning process for static traffic assignment, and how dynamic traffic flow models can represent capacity increases from using CAVs and their effects on congestion and travel times. The study also analyzed how shared (and connected) autonomous vehicles (SAVs) may perform relative to privately held CAVs. To assess potential benefits to the transportation system and its users stemming from CAVs, a benefit-cost analysis was also performed focusing on congestion and crashes assuming CAV elasticities with respect to studied metrics that are consistent with the literature.

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Other Reference Number
Report No. FHWA/TX-17/0-6847-1
Publication Sort Date
Prepared by the Center for Transportation Research at the University of Texas at Austin for TDOT
Result Type
An Assessment of Autonomous Vehicles: Traffic Impacts and Infrastructure Needs-Final Report
Project Category
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