By leveraging advanced technologies, Autonomous Vehicles (AVs) hold the potential to increase transportation safety and efficiency. This collection showcases USDOT-funded research and data concerning AVs. Bookmark this collection: https://rosap.ntl.bts.gov/collection_avs OR https://doi.org/10.21949/1x81-qs91.
Connected Autonomous Vehicles (CAVs) and advanced propulsion systems, like battery-electric vehicles, could significantly impact transportation infrastructure investments. These changes require a reevaluation of how infrastructure projects are planned, focusing on both direct and indirect economic, social, and environmental effects. A key overlooke
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Manion, P. T., & Durango-Cohen, P. L. (2025). Optimizing Investments in Design, Maintenance, and Operations of Transportation Infrastructure to Capitalize on the Promise of Connected Autonomous Vehicles (Report No. CCAT-NU-2025-2). University of Michigan. Center for Connected and Automated Transportation. https://rosap.ntl.bts.gov/view/dot/83800
Manion, Pablo Teixeira and Pablo L. Durango-Cohen. Optimizing Investments in Design, Maintenance, and Operations of Transportation Infrastructure to Capitalize on the Promise of Connected Autonomous Vehicles. Report no. CCAT-NU-2025-2. University of Michigan. Center for Connected and Automated Transportation, 2025. https://rosap.ntl.bts.gov/view/dot/83800.
Manion, Pablo Teixeira, and Pablo L. Durango-Cohen Optimizing Investments in Design, Maintenance, and Operations of Transportation Infrastructure to Capitalize on the Promise of Connected Autonomous Vehicles. University of Michigan. Center for Connected and Automated Transportation, 2025, Report no. CCAT-NU-2025-2, ROSA P. https://rosap.ntl.bts.gov/view/dot/83800.
The rapid deployment of automated vehicles (AVs) presents both opportunities and challenges, especially for first responders tasked with ensuring public safety during emergencies. This project addressed critical needs and strategies for interactions between first responders and AVs. The project sought to identify the needs and strategies for Texas
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Trefz, B., Ivie, R., Guzman, I., Merritt, J., Hwang, W., Le, M., Perez, M., Stoeltje, G., Speed, J., Warner, J., Zhou, H., Crow, R., Avolio, M., McCollum, S., & Miller, B. (2025). 0-7199: Identification of Needs and Strategies for First Responder Interactions with Automated Vehicles [Summary]. Texas A&M Transportation Institute. https://rosap.ntl.bts.gov/view/dot/83537
Trefz, Bradley, Ray Ivie, Itzel Guzman, Jack Merritt, William Hwang, Minh Le, and Marcy Perez, et al.. 0-7199: Identification of Needs and Strategies for First Responder Interactions with Automated Vehicles [Summary]. Texas A&M Transportation Institute, 2025. https://rosap.ntl.bts.gov/view/dot/83537.
Trefz, Bradley, et al. 0-7199: Identification of Needs and Strategies for First Responder Interactions with Automated Vehicles [Summary]. Texas A&M Transportation Institute, 2025, ROSA P. https://rosap.ntl.bts.gov/view/dot/83537.
This study envisions a jointly designed transit system comprised of a fixed-route (FR) service and a paratransit (PT) service. The integration of the two services is inspired by the potential application of modular autonomous vehicles, or pods, in transit. Constrained by a fixed budget, the operator of the joint system aims to minimize the total us
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Nie, Y. (., Yan, X., Zheng, H., & Dai, T. (2025). Impact of Modularized Autonomous Vehicles on Transit System Design and Operations (Report No. CCAT-NU-2025-1). University of Michigan. Center for Connected and Automated Transportation. https://doi.org/10.5281/zenodo.15499559
Nie, Yu (Marco), Xiaoyu Yan, Hongyu Zheng, and Tianxing Dai. Impact of Modularized Autonomous Vehicles on Transit System Design and Operations. Report no. CCAT-NU-2025-1. University of Michigan. Center for Connected and Automated Transportation, 2025. https://doi.org/10.5281/zenodo.15499559.
Nie, Yu (Marco), et al. Impact of Modularized Autonomous Vehicles on Transit System Design and Operations. University of Michigan. Center for Connected and Automated Transportation, 2025, Report no. CCAT-NU-2025-1, ROSA P. https://doi.org/10.5281/zenodo.15499559.
This study envisions a jointly designed transit system comprised of a fixed-route (FR) service and a para- transit (PT) service. The integration of the two services is inspired by the potential application of modular autonomous vehicles, or pods, in transit. Constrained by a fixed budget, the operator of the joint system aims to minimize the total
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Yan, X., Zheng, H., Dai, T., & Nie, Y. (. (2025). Joint Design of Fixed-Route and Paratransit Services with Autonomous Pods. University of Michigan. Center for Connected and Automated Transportation. https://rosap.ntl.bts.gov/view/dot/83834
Yan, Xiaoyu, Hongyu Zheng, Tianxing Dai, and Yu (Marco) Nie. Joint Design of Fixed-Route and Paratransit Services with Autonomous Pods. University of Michigan. Center for Connected and Automated Transportation, 2025. https://rosap.ntl.bts.gov/view/dot/83834.
Yan, Xiaoyu, et al. Joint Design of Fixed-Route and Paratransit Services with Autonomous Pods. University of Michigan. Center for Connected and Automated Transportation, 2025, ROSA P. https://rosap.ntl.bts.gov/view/dot/83834.
In this report, the Tennessee Department of Transportation (TDOT) has developed a Connected and Automated Vehicle (CAV) Readiness Action Plan to guide the implementation, operation, and maintenance of CAV technologies at traffic signals and along roadways across the state. Through this action plan, TDOT aims to position Tennessee as a leader in CAV
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Toth, C., Perry, F., & Keshmiri, A. (2025). Connected and Autonomous Vehicle Readiness Action Plan (Report No. RES2023-29). Tennessee. Department of Transportation. https://rosap.ntl.bts.gov/view/dot/82913
Toth, Chris, Frank Perry, and Armon Keshmiri. Connected and Autonomous Vehicle Readiness Action Plan. Report no. RES2023-29. Tennessee. Department of Transportation, 2025. https://rosap.ntl.bts.gov/view/dot/82913.
Toth, Chris, et al. Connected and Autonomous Vehicle Readiness Action Plan. Tennessee. Department of Transportation, 2025, Report no. RES2023-29, ROSA P. https://rosap.ntl.bts.gov/view/dot/82913.
This project assesses how Texas roadway and parking infrastructure should evolve as connected and automated vehicles (CAVs) gain market share, using behavioral-diffusion insights to frame adoption scenarios. Researchers combined literature synthesis with expert questionnaires/interviews, analysis of AV disengagement reports, and PTV Vissim microsim
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Kumar, A., Weissmann, J., Sharif, H., & Dessouky, S. (2025). 0-7080 Develop Roadway and Parking Design Criteria to Accommodate Automated and Autonomous Vehicles [Summary]. Texas Department of Transportation. Research and Technology Implementation Office. https://rosap.ntl.bts.gov/view/dot/84676
Kumar, Amit, Jose Weissmann, Hatim Sharif, and Samer Dessouky. 0-7080 Develop Roadway and Parking Design Criteria to Accommodate Automated and Autonomous Vehicles [Summary]. Texas Department of Transportation. Research and Technology Implementation Office, 2025. https://rosap.ntl.bts.gov/view/dot/84676.
Kumar, Amit, et al. 0-7080 Develop Roadway and Parking Design Criteria to Accommodate Automated and Autonomous Vehicles [Summary]. Texas Department of Transportation. Research and Technology Implementation Office, 2025, ROSA P. https://rosap.ntl.bts.gov/view/dot/84676.
Motor vehicle crashes are a prominent and distressing cause of fatalities in the United States and globally. Addressing this issue, the integration of Partially Automated in-vehicle technologies, notably Advanced Driver Assistance Systems (ADAS), emerged as a promising avenue for enhancing safety on highways. These systems become even more critical
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Kidando, E., Owusu-Danquah, J. S., & Ngereza, A. S. (2025). Examine the Impact of Vehicle Automation Levels on Road Safety in Rural Areas. Rural Safe Efficient Advanced Transportation (R-SEAT) Center. https://rosap.ntl.bts.gov/view/dot/94078
Kidando, Emmanuel, Josiah S. Owusu-Danquah, and Abdul S. Ngereza. Examine the Impact of Vehicle Automation Levels on Road Safety in Rural Areas. Rural Safe Efficient Advanced Transportation (R-SEAT) Center, 2025. https://rosap.ntl.bts.gov/view/dot/94078.
Kidando, Emmanuel, et al. Examine the Impact of Vehicle Automation Levels on Road Safety in Rural Areas. Rural Safe Efficient Advanced Transportation (R-SEAT) Center, 2025, ROSA P. https://rosap.ntl.bts.gov/view/dot/94078.
Pedestrian trajectory prediction constitutes a critical component of motion planning in autonomous vehicles (AVs), facilitating safe and efficient navigation. While recent advancements in deep learning have enabled near real-time prediction capabilities, ethical concerns have emerged within the artificial intelligence (AI) community regarding algor
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Xu, S., & Wang, C. (2025). Mitigating Out-of-Distribution Challenges in Connected Vehicle-Infrastructure-Pedestrian Systems for Promoting Pedestrian Safety at Intersections. Rural Safe Efficient Advanced Transportation (R-SEAT) Center. https://rosap.ntl.bts.gov/view/dot/94080
Xu, Susu and Chenguang Wang. Mitigating Out-of-Distribution Challenges in Connected Vehicle-Infrastructure-Pedestrian Systems for Promoting Pedestrian Safety at Intersections. Rural Safe Efficient Advanced Transportation (R-SEAT) Center, 2025. https://rosap.ntl.bts.gov/view/dot/94080.
Xu, Susu, and Chenguang Wang Mitigating Out-of-Distribution Challenges in Connected Vehicle-Infrastructure-Pedestrian Systems for Promoting Pedestrian Safety at Intersections. Rural Safe Efficient Advanced Transportation (R-SEAT) Center, 2025, ROSA P. https://rosap.ntl.bts.gov/view/dot/94080.
Autonomous vehicles are reshaping the car rental and ridesharing industries, potentially leading to a unified model of on-demand transportation suitable for both uncommon (e.g., business trips) and daily commuting. An exploratory study of human behavior towards autonomous vehicles can uncover the challenges and opportunities inherent in different l
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Meda, P., Contreras, A. V., Lo, W. H., Huang, G., & Luo, Y. (2025). Insights for the Future of Car Rental and Ridesharing: Driving Behavior Across Different Levels of Automation (Report No. 24-51). Mineta Transportation Institute. https://rosap.ntl.bts.gov/view/dot/80459
Meda, Pranav, Aubrey Victoria Contreras, Wei-Hsiang Lo, Gaojian Huang, and Yue Luo. Insights for the Future of Car Rental and Ridesharing: Driving Behavior Across Different Levels of Automation. Report no. 24-51. Mineta Transportation Institute, 2025. https://rosap.ntl.bts.gov/view/dot/80459.
Meda, Pranav, et al. Insights for the Future of Car Rental and Ridesharing: Driving Behavior Across Different Levels of Automation. Mineta Transportation Institute, 2025, Report no. 24-51, ROSA P. https://rosap.ntl.bts.gov/view/dot/80459.
This guide provides Texas first responders methods to safely and efficiently respond to a multitude of routine and adverse incident scenarios involving automated vehicles (AVs). It contains a catalog of 19 scenarios and best practices developed by the project team using first responder standards and industry practices.
Texas A&M Transportation Institute (2025). Texas First Responder Guide for Interactions with Automated Vehicles (AVs). Texas. Department of Transportation. https://rosap.ntl.bts.gov/view/dot/86022
Texas A&M Transportation Institute. Texas First Responder Guide for Interactions with Automated Vehicles (AVs). Texas. Department of Transportation, 2025. https://rosap.ntl.bts.gov/view/dot/86022.
Texas A&M Transportation Institute Texas First Responder Guide for Interactions with Automated Vehicles (AVs). Texas. Department of Transportation, 2025, ROSA P. https://rosap.ntl.bts.gov/view/dot/86022.
Autonomous vehicles are reshaping the car rental and ridesharing industries, potentially leading to a unified model of on-demand transportation suitable for both uncommon (e.g., business trips) and daily commuting. An exploratory study of human behavior towards autonomous vehicles can uncover the challenges and opportunities inherent in different l
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Meda, P., Contreras, A. V., Lo, W. H., Huang, G., & Luo, Y. (2025). Insights for the Future of Car Rental and Ridesharing: Driving Behavior Across Different Levels of Automation [Brief]. Mineta Transportation Institute. https://rosap.ntl.bts.gov/view/dot/80460
Meda, Pranav, Aubrey Victoria Contreras, Wei-Hsiang Lo, Gaojian Huang, and Yue Luo. Insights for the Future of Car Rental and Ridesharing: Driving Behavior Across Different Levels of Automation [Brief]. Mineta Transportation Institute, 2025. https://rosap.ntl.bts.gov/view/dot/80460.
Meda, Pranav, et al. Insights for the Future of Car Rental and Ridesharing: Driving Behavior Across Different Levels of Automation [Brief]. Mineta Transportation Institute, 2025, ROSA P. https://rosap.ntl.bts.gov/view/dot/80460.
This guide provides Texas first responders methods to safely and efficiently respond to a multitude of routine and adverse incident scenarios involving automated vehicles (AVs). It contains a catalog of 19 scenarios and best practices developed by the project team using first responder standards and industry practices. This guide is divided into si
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Texas A&M Transportation Institute (2025). Texas Automated Vehicle Recognition Guide for First Responders (Report No. 0-7199-P1). Texas. Department of Transportation. https://rosap.ntl.bts.gov/view/dot/86021
Texas A&M Transportation Institute. Texas Automated Vehicle Recognition Guide for First Responders. Report no. 0-7199-P1. Texas. Department of Transportation, 2025. https://rosap.ntl.bts.gov/view/dot/86021.
Texas A&M Transportation Institute Texas Automated Vehicle Recognition Guide for First Responders. Texas. Department of Transportation, 2025, Report no. 0-7199-P1, ROSA P. https://rosap.ntl.bts.gov/view/dot/86021.
We envisioned a project—a future—where the community is at the forefront of planning and implementation of new technology. Technologies are often developed by select companies and universities, and then tested in communities. Instead of leading with a solution, Community Driven CAV started by understanding community needs and assets, and then creat
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Minnesota. Department of Transportation (2025). Project Summary: Community Driven CAV. Minnesota. Department of Transportation. https://rosap.ntl.bts.gov/view/dot/82264
Minnesota. Department of Transportation. Project Summary: Community Driven CAV. Minnesota. Department of Transportation, 2025. https://rosap.ntl.bts.gov/view/dot/82264.
Minnesota. Department of Transportation Project Summary: Community Driven CAV. Minnesota. Department of Transportation, 2025, ROSA P. https://rosap.ntl.bts.gov/view/dot/82264.
Connected and autonomous vehicles (CAVs) enhance transportation efficiency, reduce costs, and improve safety through cooperative driving automation (CDA), which enables communication and cooperation among vehicles, infrastructure, and road users. However, the existing infrastructure is designed for conventional vehicles and human drivers. The "Infr
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Sargolzaei, A., Lin, P. S., Alemayehu, H., Okashita, M., Li, Q., Li, Y., Li, Z., Liang, Z., Li, H., Li, X., Hadi, M., & Mamun, M. M. H. (2025). Infrastructure Enablers for Reliable Cooperative Driving Automation (CDA) Phase I: Existing Infrastructure Evaluation (Report No. BED25-977-09). Florida Department of Transportation. https://rosap.ntl.bts.gov/view/dot/93275
Sargolzaei, Arman, Pei-Sung Lin, Hayleyesus Alemayehu, Matthew Okashita, Qianwen Li, Yang Li, and Zheng Li, et al.. Infrastructure Enablers for Reliable Cooperative Driving Automation (CDA) Phase I: Existing Infrastructure Evaluation. Report no. BED25-977-09. Florida Department of Transportation, 2025. https://rosap.ntl.bts.gov/view/dot/93275.
Sargolzaei, Arman, et al. Infrastructure Enablers for Reliable Cooperative Driving Automation (CDA) Phase I: Existing Infrastructure Evaluation. Florida Department of Transportation, 2025, Report no. BED25-977-09, ROSA P. https://rosap.ntl.bts.gov/view/dot/93275.
This study examines the benefits and implementation of autonomous pedestrian ferries in Washington State, aiming to understand which routes and terminals should be prioritized for their deployment. Correlation, principal component, and cluster analyses were performed to identify key factors influencing transportation and classify ferry terminals in
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Dillon, H., Walters, J. P., Kitali, A., Kalambay, P., Lipscomb, G., Weber, G. F., & Sanchez-Sossa, J. (2025). Autonomous Electric Ferries (Autoferry) - Efficient Connectors. Rural Safe Efficient Advanced Transportation (R-SEAT) Center. https://rosap.ntl.bts.gov/view/dot/94155
Dillon, Heather, Jeffrey P. Walters, Angela Kitali, Panick Kalambay, Grant Lipscomb, Gauge Frederick Weber, and Jose Sanchez-Sossa. Autonomous Electric Ferries (Autoferry) - Efficient Connectors. Rural Safe Efficient Advanced Transportation (R-SEAT) Center, 2025. https://rosap.ntl.bts.gov/view/dot/94155.
Dillon, Heather, et al. Autonomous Electric Ferries (Autoferry) - Efficient Connectors. Rural Safe Efficient Advanced Transportation (R-SEAT) Center, 2025, ROSA P. https://rosap.ntl.bts.gov/view/dot/94155.
This project examined how roadside inspections and other law enforcement interactions could be accomplished on ADS-equipped CMVs. This included research into: a) how automated CMVs can deliver necessary information to inspectors and b) how automated CMVs can recognize and respond to inspection locations and directions. These objectives were accompl
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Ma, J., Elminyawi, Y., Kehoe, N., Lantz, B., Zhou, F., & Goyal, R. (2025). Automated CMV Inspection Demonstrations and Evaluations (Report No. FMCSA-RRT-25-002). United States. Department of Transportation. Federal Motor Carrier Safety Administration. https://rosap.ntl.bts.gov/view/dot/79372
Ma, Jiaqi, Youssef Elminyawi, Nicholas Kehoe, Brenda Lantz, Fang Zhou, and Rohit Goyal. Automated CMV Inspection Demonstrations and Evaluations. Report no. FMCSA-RRT-25-002. United States. Department of Transportation. Federal Motor Carrier Safety Administration, 2025. https://rosap.ntl.bts.gov/view/dot/79372.
Ma, Jiaqi, et al. Automated CMV Inspection Demonstrations and Evaluations. United States. Department of Transportation. Federal Motor Carrier Safety Administration, 2025, Report no. FMCSA-RRT-25-002, ROSA P. https://rosap.ntl.bts.gov/view/dot/79372.
The Indiana Department of Transportation (INDOT) spends approximately $19 million annually on roadside mowing, which is a process that is time-consuming, costly, and poses safety risks. Automated mowing solutions have the potential to reduce costs and increase safety, but they will need to be extremely well tested before being deployed. In this wor
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Evans, J. T., Shaver, G., Mardikes, M. A., Sprague, N. C., Weigman, T. J., Supe, S., & Brown, E. M. (2025). Autonomous Mower Pilot Project (Report No. FHWA/IN/JTRP-2025/01). Purdue University. Joint Transportation Research Program. https://doi.org/10.5703/1288284317840
Evans, John T, Greg Shaver, Michael A Mardikes, Nathan C Sprague, Timothy J Weigman, Shreyas Supe, and Ethan M Brown. Autonomous Mower Pilot Project. Report no. FHWA/IN/JTRP-2025/01. Purdue University. Joint Transportation Research Program, 2025. https://doi.org/10.5703/1288284317840.
Evans, John T, et al. Autonomous Mower Pilot Project. Purdue University. Joint Transportation Research Program, 2025, Report no. FHWA/IN/JTRP-2025/01, ROSA P. https://doi.org/10.5703/1288284317840.
The primary goal of this project was to provide recommendations on incorporating CDA into FDOT’s Transportation System Management and Operations (TSM&O). Specific objectives included developing a Concept of Operations (ConOps) for incorporating CDA features in traffic management; formulating methods to test and evaluate infrastructure support for C
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Ponnaluri, R., & Hadi, M. (2025). Environment for Testing and Assessing Infrastructure Support of Connected Vehicle and Cooperative Highway Automation [Summary]. Florida. Department of Transportation. https://rosap.ntl.bts.gov/view/dot/80044
Ponnaluri, Raj and Mohammed Hadi. Environment for Testing and Assessing Infrastructure Support of Connected Vehicle and Cooperative Highway Automation [Summary]. Florida. Department of Transportation, 2025. https://rosap.ntl.bts.gov/view/dot/80044.
Ponnaluri, Raj, and Mohammed Hadi Environment for Testing and Assessing Infrastructure Support of Connected Vehicle and Cooperative Highway Automation [Summary]. Florida. Department of Transportation, 2025, ROSA P. https://rosap.ntl.bts.gov/view/dot/80044.
United States. Department of Transportation. Federal Motor Carrier Safety Administration
2025-01-01
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The Federal Motor Carrier Safety Administration (FMCSA) is researching how to safely use advanced driving technology in commercial motor vehicles (CMV). As part of FMCSA’s Automated Commercial Motor Vehicle Evaluation (ACE) program, this research is exploring topics that include systems that assist drivers, full driving automation, and the ability
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United States. Department of Transportation. Federal Motor Carrier Safety Administration (2025). Automated Commercial Motor Vehicle Inspection Demonstrations and Evaluations [Technology Brief] (Report No. FMCSA-RRT-25-002 (b)). United States. Department of Transportation. Federal Motor Carrier Safety Administration. https://rosap.ntl.bts.gov/view/dot/79373
United States. Department of Transportation. Federal Motor Carrier Safety Administration. Automated Commercial Motor Vehicle Inspection Demonstrations and Evaluations [Technology Brief]. Report no. FMCSA-RRT-25-002 (b). United States. Department of Transportation. Federal Motor Carrier Safety Administration, 2025. https://rosap.ntl.bts.gov/view/dot/79373.
United States. Department of Transportation. Federal Motor Carrier Safety Administration Automated Commercial Motor Vehicle Inspection Demonstrations and Evaluations [Technology Brief]. United States. Department of Transportation. Federal Motor Carrier Safety Administration, 2025, Report no. FMCSA-RRT-25-002 (b), ROSA P. https://rosap.ntl.bts.gov/view/dot/79373.
This project develops and tests the multiscale, multimodal signal-vehicle coupled control (M²SVCC) framework to jointly optimize traffic signal control and surrounding vehicles and other road users at urban intersections. Connected and automated vehicles and human-driven vehicles, with diverse energy types, are integrated, together with active road
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Ban, J., Kitali, A. E., & Naderian, S. (2025). Multimodal MultiScale Urban Traffic Control in Connected and Automated Cities. Connected Communities for Smart Mobility Toward Accessible and Resilient Transportation for Equitably Reducing Congestion (C2SMARTER) Tier-1 University Transportation Center (UTC). https://rosap.ntl.bts.gov/view/dot/86515
Ban, Jeff, Angela E Kitali, and Shakiba Naderian. Multimodal MultiScale Urban Traffic Control in Connected and Automated Cities. Connected Communities for Smart Mobility Toward Accessible and Resilient Transportation for Equitably Reducing Congestion (C2SMARTER) Tier-1 University Transportation Center (UTC), 2025. https://rosap.ntl.bts.gov/view/dot/86515.
Ban, Jeff, et al. Multimodal MultiScale Urban Traffic Control in Connected and Automated Cities. Connected Communities for Smart Mobility Toward Accessible and Resilient Transportation for Equitably Reducing Congestion (C2SMARTER) Tier-1 University Transportation Center (UTC), 2025, ROSA P. https://rosap.ntl.bts.gov/view/dot/86515.
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