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.
Fatal traffic crashes have increased significantly, largely due to human error, which automated vehicle technology aims to reduce. However, challenges such as driver fatigue and the need for quick intervention in case of system failures must be urgently addressed to ensure safety. This study aims to develop a driver fatigue monitoring system to det
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This report aims to investigate and expand on five essential research areas related to connected and autonomous vehicle (CAV) testbeds and their contribution to enhancing road safety, especially for vulnerable road users. These areas include validating LiDAR data with CCTV systems, investigating CAV testbeds across the country, real-time communicat
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In recent years, there has been a notable increase in the development of autonomous vehicle (AV) technologies aimed at improving safety in transportation systems. While AVs have been deployed in the real-world to some extent, a full-scale deployment requires AVs to robustly navigate through challenges like heavy rain, snow, low lighting, constructi
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Most light-duty vehicle (LDV) crashes occur due to human error. The National Highway Safety Administration (NHTSA) reports that eight percent of fatal crashes in 2018 were distraction-affected crashes, while close to ninety-four percent of all crashes occur in part due to human error. Crash avoidance features could reduce both the frequency and sev
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The current approach to connected and autonomous driving function development and evaluation uses model-in-the-loop (MIL) simulation, hardware-in-the-loop (HIL) simulation and limited proving ground use, followed by public road deployment of the beta version of software and technology. The rest of the road users are involuntarily forced into taking
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Autonomous ground vehicles must safely operate in highly interactive environments with human uncertainties. Safe actions depend on context, interactions, and absolute (mathematical measures for safety) may differ from how humans perceive as safe and reliable behaviors. However, producing context-dependent and interaction-aware safe actions is non-t
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In this project, we proposed a CBF-inspired risk assessment toolbox, measuring the aggregated risk faced by individual agents due to multi-agent interactions, to help empower the ego robot with a comprehensive understanding of the dynamic environment it is in. We also demonstrate two complementary methodologies of embedding the resulting risk asses
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Developing an automated driving system capable of navigating complex traffic environments remains a formidable challenge. Unlike rule-based or supervised learning-based methods, Deep Reinforcement Learning (DRL) based controllers eliminate the need for domain-specific knowledge and datasets, thus providing adaptability to various scenarios. Nonethe
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Despite maturing road tests and limited commercial mobility services with autonomous vehicles (AVs), the existing behavioral research, surveys, and polls suggest that, to date, the public is largely reluctant or neutral to accept this emerging technology due to potential lurking failures and malfunctions in unexpected weather/road conditions and cy
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Vehicle headway, defined as the time elapsed between two successive vehicles passing a roadway point, is a key mesoscopic-scale measure in traffic flow theory with safety-critical transportation applications, such as preemptive collision avoidance warning systems as well as connected and autonomous vehicle (CAV) platoon control. Hence, it is crucia
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Pavement marking style and patterns have largely been designed based on human vision. MnDOT is completing a human factors study on pavement marking variations, A field study included data collected through various methods from test corridors in Minnesota and Texas during daytime and nighttime driving. A closed course at Texas A&M University allowed
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The North Carolina Department of Transportation (NCDOT) partnered with the University of North Carolina at Charlotte (UNC Charlotte) and Beep, Inc. (Beep) to bring a novel-design, all-electric, low-speed automated shuttle to UNC Charlotte’s campus for a 23-week pilot through the Connected Autonomous Shuttle Supporting Innovation (CASSI) program. Be
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In fall 2022, a first-of-its-kind connected and automated vehicle (CAV) pilot program called goMARTI (Minnesota’s Autonomous Rural Transit Initiative) was launched as a collaborative effort between numerous partners. The 18-month pilot offers free, on-demand rides to area residents and visitors using five autonomous shuttle vans (including three wh
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Work zone safety has been a major concern for many stakeholders, including the state Departments of Transportation (DOTs). To prevent DOT workers, especially truck mounted attenuator (TMA) drivers, from injuries, the Autonomous Truck Mounted Attenuator (ATMA) technology was developed. To understand the current testing and deployment status of ATMA,
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New technologies are being added to vehicles at a growing rate to assist drivers and even fully take over the driving task in some situations. These technologies are generally camera-based and typically rely on pavement markings to maintain vehicle position and navigate the roadway. As drivers become more reliant on these systems, and for these sys
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This study evaluated connected and autonomous vehicle (CAV) crash reporting practices across the United States, emphasizing the importance of standardized reporting and legislation for the safe deployment of CAVs on public roads. Through a survey of state transportation officials and a review of current practices and legislation, the study identifi
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The objective of this project was to identify the user perspective about autonomous ride-sharing services for adults 50 years of age and older in Lake Nona, Port St. Lucie, and The Villages, and to solicit responses pertaining to the adoption and acceptance of these services.
This research focuses on evaluating current CAV crash reporting practices across the United States, identifying inconsistencies and gaps, and proposing recommendations for standardized reporting and legislation to ensure safe and effective deployment of CAVs on public roads. Researchers assessed CAV crash reporting practices across the United State
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Although the literature on autonomous vehicles (AVs) has been growing with a focus on adoption, expected changes in travel behavior, and travel demand and land use in the future, few studies have analyzed envisioned activities in AVs, which will affect all those outcomes at the micro level. To address this gap, this study examines preferred activit
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This project convened a series of meetings and workshops to prioritize listening to multi-sector stakeholders from local government, advocacy, and industry in US cities where autonomous vehicles are operating. The objective was to listen and learn from all stakeholders, raise issues surrounding accessibility and equity, and to solicit responses. Ke
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