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.
The National Highway Traffic Safety Administration (NHTSA) calls for fundamental research on “the driver performance profile over time in sustained and short-cycle automation … and driver-vehicle interface to allow safe operation and transition between automated and nonautomated vehicle operation.” The emerging level 3 autonomous vehicle (AV) has t
...
Dataset
Deng, M., Gluck, A., Menassa, C., Kamat, V., Li, D., & Brinkley, J. (2024). Predicting Driver Takeover Performance in Conditional Automation (Level 3) Through Physiological Sensing [supporting dataset] (Report No. CCAT Final Report #57). University of Michigan. Center for Connected and Automated Transportation. https://doi.org/10.7302/b312-3t56
Deng, Min, Aaron Gluck, Carol Menassa, Vineet Kamat, Da Li, and Julian Brinkley. Predicting Driver Takeover Performance in Conditional Automation (Level 3) Through Physiological Sensing [supporting dataset]. Report no. CCAT Final Report #57. University of Michigan. Center for Connected and Automated Transportation, 2024. https://doi.org/10.7302/b312-3t56.
Deng, Min, et al. Predicting Driver Takeover Performance in Conditional Automation (Level 3) Through Physiological Sensing [supporting dataset]. University of Michigan. Center for Connected and Automated Transportation, 2024, Report no. CCAT Final Report #57, ROSA P. https://doi.org/10.7302/b312-3t56.
High precision road maps are a crucial component to facilitating autonomous driving techniques. Although current Autonomous vehicles (AVs) rely on vehicular sensing techniques (e.g., camera, light detection and ranging [LiDAR], radar), studies have suggested that creating high-quality road maps with traffic control infrastructures (TCIs) (e.g., tra
...
Wu, J. (., Miller, M., Stoeltje, G., Le, M., Hwang, W., Huang, T., Hu, N., Zalila-Wenkstern, R., Torabi, B., & Li, X. (2024). Digitizing Traffic Control Infrastructure for Autonomous Vehicles (AV): Technical Report (Report No. FHWA/TX-23/0-7128-R1). Texas A&M Transportation Institute. https://rosap.ntl.bts.gov/view/dot/73234
Wu, Jason (Dayong), Matthew Miller, Gretchen Stoeltje, Minh Le, William Hwang, Tianchen Huang, Nanzhou Hu, Rym Zalila-Wenkstern, Behnam Torabi, and Xiao Li. Digitizing Traffic Control Infrastructure for Autonomous Vehicles (AV): Technical Report. Report no. FHWA/TX-23/0-7128-R1. Texas A&M Transportation Institute, 2024. https://rosap.ntl.bts.gov/view/dot/73234.
Wu, Jason (Dayong), et al. Digitizing Traffic Control Infrastructure for Autonomous Vehicles (AV): Technical Report. Texas A&M Transportation Institute, 2024, Report no. FHWA/TX-23/0-7128-R1, ROSA P. https://rosap.ntl.bts.gov/view/dot/73234.
Connected and autonomous vehicles (C/AV) present the opportunity for momentous and positive changes to most aspects of modern life. When described, the impact to mobility is imagined as safer and more efficient. This comes from the chance to build a self-driving and connected network of vehicles, infrastructure, and supporting data exchanges.... As
...
Blewett, B., Barham, M., Davis, R., Kuhr, J., Hwang, W., Stoeltje, G., Hansen, T., Geiselbrecht, T., Rodriguez, G., Shah, P., & Thompson, A. (2024). Tort Liability for TxDOT from C/AV Technologies (Report No. 0-7130-P7). Texas A&M Transportation Institute. https://rosap.ntl.bts.gov/view/dot/76671
Blewett, Becky, Misty Barham, Robert Davis, James Kuhr, William Hwang, Gretchen Stoeltje, and Todd Hansen, et al.. Tort Liability for TxDOT from C/AV Technologies. Report no. 0-7130-P7. Texas A&M Transportation Institute, 2024. https://rosap.ntl.bts.gov/view/dot/76671.
Blewett, Becky, et al. Tort Liability for TxDOT from C/AV Technologies. Texas A&M Transportation Institute, 2024, Report no. 0-7130-P7, ROSA P. https://rosap.ntl.bts.gov/view/dot/76671.
In recent years, camera-based 3D object detection has gained widespread attention for its ability to achieve high performance with low computational cost. However, the robustness of these methods to adversarial attacks has not been thoroughly examined, especially when considering their deployment in safety-critical domains like autonomous driving.
...
Xie, S., Li, Z., Wang, Z., & Xie, C. (2024). On the Adversarial Robustness of Camera-Based 3D Object Detection. University of California, Irvine. https://rosap.ntl.bts.gov/view/dot/73429
Xie, Shaoyuan, Zichao Li, Zeyu Wang, and Cihang Xie. On the Adversarial Robustness of Camera-Based 3D Object Detection. University of California, Irvine, 2024. https://rosap.ntl.bts.gov/view/dot/73429.
Xie, Shaoyuan, et al. On the Adversarial Robustness of Camera-Based 3D Object Detection. University of California, Irvine, 2024, ROSA P. https://rosap.ntl.bts.gov/view/dot/73429.
Intelligent road infrastructure consisting of sensors and communications is needed to deploy connected and automated vehicles (CAVs) on real highways. Such infrastructure can support the operation of CAVs (e.g., maneuver coordination and onboard energy management), and bridge the connectivity gap resulting from the currently low penetration of conn
...
Wang, H., & Orosz, G. (2024). Improving the Efficiency of Trucks via CV2X Connectivity on Highways (Report No. CCAT Final Report No. 20). University of Michigan. Center for Connected and Automated Transportation. https://dx.doi.org/10.7302/21946
Wang, Hao and Gabor Orosz. Improving the Efficiency of Trucks via CV2X Connectivity on Highways. Report no. CCAT Final Report No. 20. University of Michigan. Center for Connected and Automated Transportation, 2024. https://dx.doi.org/10.7302/21946.
Wang, Hao, and Gabor Orosz Improving the Efficiency of Trucks via CV2X Connectivity on Highways. University of Michigan. Center for Connected and Automated Transportation, 2024, Report no. CCAT Final Report No. 20, ROSA P. https://dx.doi.org/10.7302/21946.
This project is concerned with adapting land use and transportation infrastructure for automated driving. Autonomous vehicles will likely yield a transformation of urban form, its land use and mobility system. We propose to establish quantitative modeling frameworks to analyze these impacts and implications. The frameworks will provide a quantifiab
...
Yin, Y. (2024). Adapting Land Use and Infrastructure for Automated Driving: Part A (Report No. 8). University of Michigan. Center for Connected and Automated Transportation. https://dx.doi.org/10.7302/21950
Yin, Yafeng. Adapting Land Use and Infrastructure for Automated Driving: Part A. Report no. 8. University of Michigan. Center for Connected and Automated Transportation, 2024. https://dx.doi.org/10.7302/21950.
Yin, Yafeng Adapting Land Use and Infrastructure for Automated Driving: Part A. University of Michigan. Center for Connected and Automated Transportation, 2024, Report no. 8, ROSA P. https://dx.doi.org/10.7302/21950.
This study explored how children are restrained when traveling in ride-share vehicles. An observational survey was conducted from July to August 2022. The target population was children from birth to 12 years old transported in ride-share vehicles. About half of children observed were traveling unrestrained and the remainder were either using the v
...
De Leonardis, D., Levi, S., Benedick, A. K., Eisenhauer, E., Ferg, R., & Petraglia, E. (2024). Child Passenger Safety Perception and Practices in Ride-Sharing Vehicles (Report No. DOT HS 813 532). United States. Department of Transportation. National Highway Traffic Safety Administration. https://rosap.ntl.bts.gov/view/dot/72946
De Leonardis, Doreen, Sharon Levi, Amy K Benedick, Elizabeth Eisenhauer, Robyn Ferg, and Elizabeth Petraglia. Child Passenger Safety Perception and Practices in Ride-Sharing Vehicles. Report no. DOT HS 813 532. United States. Department of Transportation. National Highway Traffic Safety Administration, 2024. https://rosap.ntl.bts.gov/view/dot/72946.
De Leonardis, Doreen, et al. Child Passenger Safety Perception and Practices in Ride-Sharing Vehicles. United States. Department of Transportation. National Highway Traffic Safety Administration, 2024, Report no. DOT HS 813 532, ROSA P. https://rosap.ntl.bts.gov/view/dot/72946.
This edition of Traffic Tech briefly describes a full report that provides insight into how children are being restrained when traveling in ride-sharing vehicles such as Uber and Lyft. From July to August 2022 researchers observed children 12 and younger transported in ride-share vehicles in the Mid-Atlantic and Northeastern regions. About half of
...
Sifrit, K. J. (2024). Child Passenger Safety Perception and Practices in Ride-Sharing Vehicles [Traffic Tech] (Report No. DOT HS 813 533). United States. Department of Transportation. National Highway Traffic Safety Administration. https://rosap.ntl.bts.gov/view/dot/72945
Sifrit, Kathy J.. Child Passenger Safety Perception and Practices in Ride-Sharing Vehicles [Traffic Tech]. Report no. DOT HS 813 533. United States. Department of Transportation. National Highway Traffic Safety Administration, 2024. https://rosap.ntl.bts.gov/view/dot/72945.
Sifrit, Kathy J. Child Passenger Safety Perception and Practices in Ride-Sharing Vehicles [Traffic Tech]. United States. Department of Transportation. National Highway Traffic Safety Administration, 2024, Report no. DOT HS 813 533, ROSA P. https://rosap.ntl.bts.gov/view/dot/72945.
This paper proposes a novel physics-informed machine learning framework for motion planning and control of autonomous vehicles. By integrating longitudinal and lateral control, a nonlinear control problem is formulated using Model Predictive Control (MPC). To address computational challenges, a self-supervised framework, Recurrent Predictive Contro
...
Li, X., Wang, Y., Ozbay, K., & Jiang, Z. P. (2024). Physics-informed Machine Learning with Heuristic Feedback Control Layer for Autonomous Vehicle Control. 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/86348
Li, Xianning, Yebin Wang, Kaan Ozbay, and Zhong-Ping Jiang. Physics-informed Machine Learning with Heuristic Feedback Control Layer for Autonomous Vehicle Control. Connected Communities for Smart Mobility Toward Accessible and Resilient Transportation for Equitably Reducing Congestion (C2SMARTER) Tier-1 University Transportation Center (UTC), 2024. https://rosap.ntl.bts.gov/view/dot/86348.
Li, Xianning, et al. Physics-informed Machine Learning with Heuristic Feedback Control Layer for Autonomous Vehicle Control. Connected Communities for Smart Mobility Toward Accessible and Resilient Transportation for Equitably Reducing Congestion (C2SMARTER) Tier-1 University Transportation Center (UTC), 2024, ROSA P. https://rosap.ntl.bts.gov/view/dot/86348.
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 conges
...
Kockelman, K., Vellimana, M., Paithankar, P., & Mori, K. (2023). Implementation of Understanding the Impact of Autonomous Vehicles on Long-Distance Travel Mode and Destination Choice in Texas [Project Summary] (Report No. 5-7081-01). University of Texas at Austin. Center for Transportation Research. https://rosap.ntl.bts.gov/view/dot/76658
Kockelman, Kara, Maithreyi Vellimana, Priyanka Paithankar, and Kentaro Mori. Implementation of Understanding the Impact of Autonomous Vehicles on Long-Distance Travel Mode and Destination Choice in Texas [Project Summary]. Report no. 5-7081-01. University of Texas at Austin. Center for Transportation Research, 2023. https://rosap.ntl.bts.gov/view/dot/76658.
Kockelman, Kara, et al. Implementation of Understanding the Impact of Autonomous Vehicles on Long-Distance Travel Mode and Destination Choice in Texas [Project Summary]. University of Texas at Austin. Center for Transportation Research, 2023, Report no. 5-7081-01, ROSA P. https://rosap.ntl.bts.gov/view/dot/76658.
The data collected will be produced from the project, "Roundabout Connected Automated Vehicle Active Inference Control Strategies to Improve Safety for All Users". The purpose of the project is to implement roadside sensing and autonomous connected vehicle architecture that will perceive and broadcast sensor state estimates of Vulnerable Road Users
...
Morellas, V., & Morris, T. L. (2023). Roundabout Connected/Automated Vehicle Active Inference Control Strategies to Improve Safety for All Users: Phase-1 [data management plan]. University of Michigan. Center for Connected and Automated Transportation. https://rosap.ntl.bts.gov/view/dot/94090
Morellas, Vassilios and Ted L. Morris. Roundabout Connected/Automated Vehicle Active Inference Control Strategies to Improve Safety for All Users: Phase-1 [data management plan]. University of Michigan. Center for Connected and Automated Transportation, 2023. https://rosap.ntl.bts.gov/view/dot/94090.
Morellas, Vassilios, and Ted L. Morris Roundabout Connected/Automated Vehicle Active Inference Control Strategies to Improve Safety for All Users: Phase-1 [data management plan]. University of Michigan. Center for Connected and Automated Transportation, 2023, ROSA P. https://rosap.ntl.bts.gov/view/dot/94090.
Truck-Mounted Attenuators (TMAs) are energy-absorbing devices added to heavy shadow vehicles to provide a mobile barrier that protects work crews from errant vehicles entering active work zones. In mobile and short duration operations, drivers manually operate the TMA, keeping pace with the work zone as needed to function as a mobile barrier protec
...
Talledo Vilela, J. P., Mollenhauer, M. A., White, E. E., & Vaughan, E. W. (2023). Automated Truck Mounted Attenuator: Phase 2 Performance Measurement and Testing (Report No. VTTI-06-005). Safety through Disruption (Safe-D) University Transportation Center (UTC). https://rosap.ntl.bts.gov/view/dot/73294
Talledo Vilela, Jean Paul, Michael A Mollenhauer, Elizabeth E White, and Elijah W Vaughan. Automated Truck Mounted Attenuator: Phase 2 Performance Measurement and Testing. Report no. VTTI-06-005. Safety through Disruption (Safe-D) University Transportation Center (UTC), 2023. https://rosap.ntl.bts.gov/view/dot/73294.
Talledo Vilela, Jean Paul, et al. Automated Truck Mounted Attenuator: Phase 2 Performance Measurement and Testing. Safety through Disruption (Safe-D) University Transportation Center (UTC), 2023, Report no. VTTI-06-005, ROSA P. https://rosap.ntl.bts.gov/view/dot/73294.
Researchers focused on three research issues: 1) predicting and making recommendations for future evacuations under wildfire conditions using connected vehicle data, 2) driving behaviors in wildfire evacuations, and 3) autonomous vehicle perceptions in winter conditions. This research addresses the urgent need for enhanced emergency evacuation stra
...
Lu, P., Huang, Y., Ali, A., Ahmad, S., Yang, X., Ren, Y., & Ahmed, H. U. (2023). Regional Emergency Evacuation Analysis in Traffic With Connected and Autonomous Vehicles [Research Brief] (Report No. MPC 23-509 (project 685)). Mountain-Plains Consortium. https://rosap.ntl.bts.gov/view/dot/73133
Lu, Pan, Ying Huang, Asad Ali, Salman Ahmad, Xinyi Yang, Yihao Ren, and Hafiz Usman Ahmed. Regional Emergency Evacuation Analysis in Traffic With Connected and Autonomous Vehicles [Research Brief]. Report no. MPC 23-509 (project 685). Mountain-Plains Consortium, 2023. https://rosap.ntl.bts.gov/view/dot/73133.
Lu, Pan, et al. Regional Emergency Evacuation Analysis in Traffic With Connected and Autonomous Vehicles [Research Brief]. Mountain-Plains Consortium, 2023, Report no. MPC 23-509 (project 685), ROSA P. https://rosap.ntl.bts.gov/view/dot/73133.
This study compares the operational and policy-related data from 120 autonomous shuttle deployments worldwide. Additionally, an analysis was conducted to identify the strengths, weaknesses, opportunities, and threats associated with autonomous shuttle deployments. The study also comprehensively analyzes the perceptions of practitioners and industry
...
Diba, D. S., Gore, N., & Pulugurtha, S. S. (2023). Autonomous Shuttle Implementation and Best Practices [Research Brief] (Report No. 2321). Mineta Transportation Institute. https://rosap.ntl.bts.gov/view/dot/73206
Diba, Dil Samina, Ninad Gore, and Srinivas S. Pulugurtha. Autonomous Shuttle Implementation and Best Practices [Research Brief]. Report no. 2321. Mineta Transportation Institute, 2023. https://rosap.ntl.bts.gov/view/dot/73206.
Diba, Dil Samina, et al. Autonomous Shuttle Implementation and Best Practices [Research Brief]. Mineta Transportation Institute, 2023, Report no. 2321, ROSA P. https://rosap.ntl.bts.gov/view/dot/73206.
To help mitigate road fatalities due to human error, transportation stakeholders are turning to advanced driver assistance systems and autonomous vehicle (AV) development. However, the stakeholders continue to seek assurance of the safety performance of this new technology. This is often done using simulation testing of AV sensors and other platfor
...
Saka, Z. A., & Labi, S. (2023). Investigation of AV Operational Issues Using Simulation Equipment (Report No. Report No. 34). Center for Connected and Automated Transportation. Purdue University. http://dx.doi.org/10.5703/1288284317737
Saka, Zainab A and Samuel Labi. Investigation of AV Operational Issues Using Simulation Equipment. Report no. Report No. 34. Center for Connected and Automated Transportation. Purdue University, 2023. http://dx.doi.org/10.5703/1288284317737.
Saka, Zainab A, and Samuel Labi Investigation of AV Operational Issues Using Simulation Equipment. Center for Connected and Automated Transportation. Purdue University, 2023, Report no. Report No. 34, ROSA P. http://dx.doi.org/10.5703/1288284317737.
Most road fatalities are caused by human error. To help mitigate this issue and enhance overall transportation safety, companies are turning to advanced driver assistance systems and autonomous vehicle development. Perception, a key module of these systems, mostly uses light detection and ranging (LiDAR) sensors and enables object detection and env
...
In an ever-evolving world characterized by environmental challenges and technological advancements, the confluence of natural disasters, particularly increasing wildfire threats, and the role of connected and autonomous vehicles (CAVs) stands as a critical focal point for research and innovation. This study embarks on a comprehensive exploration of
...
Lu, P., Huang, Y., Ali, A., Ahmad, S., Yang, X., Ren, Y., & Ahmed, H. U. (2023). Regional Emergency Evacuation Analysis in Traffic With Connected and Autonomous Vehicles (Report No. MPC-685;MPC 23-509). Mountain-Plains Consortium. https://rosap.ntl.bts.gov/view/dot/73131
Lu, Pan, Ying Huang, Asad Ali, Salman Ahmad, Xinyi Yang, Yihao Ren, and Hafiz Usman Ahmed. Regional Emergency Evacuation Analysis in Traffic With Connected and Autonomous Vehicles. Report no. MPC-685;MPC 23-509. Mountain-Plains Consortium, 2023. https://rosap.ntl.bts.gov/view/dot/73131.
Lu, Pan, et al. Regional Emergency Evacuation Analysis in Traffic With Connected and Autonomous Vehicles. Mountain-Plains Consortium, 2023, Report no. MPC-685;MPC 23-509, ROSA P. https://rosap.ntl.bts.gov/view/dot/73131.
When, where, and how autonomous shuttles are deployed can have significant safety, economic, and policy impacts on their operation and performance. This research analyzes data related to 120 existing deployments of autonomous shuttles, looking at safety, operational, economic, and policy-related issues. Analysis shows that autonomous shuttles would
...
Diba, D. S., Gore, N., & Pulugurtha, S. S. (2023). Autonomous Shuttle Implementation and Best Practices (Report No. 23-33;CA-MTI-2321). Mineta Transportation Institute. https://doi.org/10.31979/mti.2023.2321
Diba, Dil Samina, Ninad Gore, and Srinivas S. Pulugurtha. Autonomous Shuttle Implementation and Best Practices. Report no. 23-33;CA-MTI-2321. Mineta Transportation Institute, 2023. https://doi.org/10.31979/mti.2023.2321.
Diba, Dil Samina, et al. Autonomous Shuttle Implementation and Best Practices. Mineta Transportation Institute, 2023, Report no. 23-33;CA-MTI-2321, ROSA P. https://doi.org/10.31979/mti.2023.2321.
When, where, and how autonomous shuttles are deployed can have significant safety, economic, and policy impacts on their operation and performance. This research analyzes data related to 120 existing deployments of autonomous shuttles, looking at safety, operational, economic, and policy-related issues. Analysis shows that autonomous shuttles would
...
Dataset
Diba, D. S., Gore, N., & Pulugurtha, S. S. (2023). Autonomous Shuttle Implementation and Best Practices [supporting dataset] (Report No. 23-33;CA-MTI-2321). Mineta Transportation Institute. https://doi.org/10.31979/mti.2023.2321
Diba, Dil Samina, Ninad Gore, and Srinivas S. Pulugurtha. Autonomous Shuttle Implementation and Best Practices [supporting dataset]. Report no. 23-33;CA-MTI-2321. Mineta Transportation Institute, 2023. https://doi.org/10.31979/mti.2023.2321.
Diba, Dil Samina, et al. Autonomous Shuttle Implementation and Best Practices [supporting dataset]. Mineta Transportation Institute, 2023, Report no. 23-33;CA-MTI-2321, ROSA P. https://doi.org/10.31979/mti.2023.2321.
United States. Department of Transportation. National Highway Traffic Safety Administration. Office of Behavioral Safety Research
2023-12-01
|
PDF
This PowerPoint slide was created to explore a new method to get summary information across to a non-technical audience. The slide is intended to be used in presentations on child restraint use when giving an overview of the topic.
United States. Department of Transportation. National Highway Traffic Safety Administration. Office of Behavioral Safety Research (2023). Child Passenger Safety Perception and Practices in Ride-Sharing Vehicles [PowerPoint Presentation]. United States. Department of Transportation. National Highway Traffic Safety Administration. https://rosap.ntl.bts.gov/view/dot/72944
United States. Department of Transportation. National Highway Traffic Safety Administration. Office of Behavioral Safety Research. Child Passenger Safety Perception and Practices in Ride-Sharing Vehicles [PowerPoint Presentation]. United States. Department of Transportation. National Highway Traffic Safety Administration, 2023. https://rosap.ntl.bts.gov/view/dot/72944.
United States. Department of Transportation. National Highway Traffic Safety Administration. Office of Behavioral Safety Research Child Passenger Safety Perception and Practices in Ride-Sharing Vehicles [PowerPoint Presentation]. United States. Department of Transportation. National Highway Traffic Safety Administration, 2023, ROSA P. https://rosap.ntl.bts.gov/view/dot/72944.
Links with this icon indicate that you are leaving a Bureau of Transportation
Statistics (BTS)/National Transportation Library (NTL)
Web-based service.
Thank you for visiting.
You are about to access a non-government link outside of
the U.S. Department of Transportation's National
Transportation Library.
Please note: While links to Web sites outside of DOT are
offered for your convenience, when you exit DOT Web sites,
Federal privacy policy and Section 508 of the Rehabilitation
Act (accessibility requirements) no longer apply. In
addition, DOT does not attest to the accuracy, relevance,
timeliness or completeness of information provided by linked
sites. Linking to a Web site does not constitute an
endorsement by DOT of the sponsors of the site or the
products presented on the site. For more information, please
view DOT's Web site linking policy.
To get back to the page you were previously viewing, click
your Cancel button.