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Autonomous Vehicles

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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.

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Showing 81 - 100 of 852 results
  • Evaluating Autonomous Vehicles Safety Benefits in Mixed Autonomy Scenarios
    Evaluating Autonomous Vehicles’ Safety Benefits in Mixed Autonomy Scenarios
    Joe-Wong, Carlee ;
    Yağan, Osman
    2024-08-01 | PDF
    Connected autonomous vehicles (CAVs) are gradually advancing towards widespread deployments. CAVs promise to improve transportation safety by operating more efficiently and avoiding incidents like crashes due to human driver error. However, they may cause crashes or other safety incidents themselves, especially when interacting with humans. Our wor ...
  • Development of a Monitoring System for Driver Readiness in Prolonged Automated Driving
    Development of a Monitoring System for Driver Readiness in Prolonged Automated Driving
    Deb, Shuchisnigdha ;
    Kan, Chen
    2024-08-01 | PDF
    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 ...
  • Development of a CAV Testbedenhanced Smart Campus at Morgan State University Phase 1
    Development of a CAV Testbed-enhanced Smart Campus at Morgan State University – Phase 1
    Jeihani, Mansoureh ;
    Yang, Di
    2024-08-01 | PDF
    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 ...
  • ContextVLM ZeroShot and FewShot Context Understanding for Autonomous Driving using Vision Language Models
    ContextVLM: Zero-Shot and Few-Shot Context Understanding for Autonomous Driving using Vision Language Models
    Sural, Shounak ;
    Ramakrishnan, Naren
    2024-08-01 | PDF
    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 ...
  • Connected Vehicle Identification System for Cooperative Control of Connected Automated Vehicles [supporting dataset]
    Park, B. Brian ;
    Mu, Zeyu
    2024-08-01 | ZIP
    Connected preceding vehicle identification is crucial for establishing cooperative platooning. This paper presents the development of a prototype preceding vehicle identification system (PVIS) and its field evaluation for the assessment of commercial viability. We designed and assembled a prototype consisting of a processing unit (Jetson Nano board ...
    Dataset
  • Estimating the Effects of Vehicle Automation and Vehicle Weight and Size on Crash Frequency and Severity Phase 1
    Estimating the Effects of Vehicle Automation and Vehicle Weight and Size on Crash Frequency and Severity: Phase 1
    Harper, Corey ;
    Hendrickson, Chris
    2024-07-31 | PDF
    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 ...
  • VehicleinVirtualEnvironment VVE Method for Developing and Evaluating VRU Safety of Connected and Autonomous Driving
    Vehicle-in-Virtual-Environment (VVE) Method for Developing and Evaluating VRU Safety of Connected and Autonomous Driving
    Chen, Haochong ;
    Cao, Xincheng
    2024-07-31 | PDF
    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 ...
  • Safe DecisionMaking in Interactive Environments
    Safe Decision-Making in Interactive Environments
    Nakahira, Yorie ;
    Hoshino, Hiraku
    2024-07-31 | PDF
    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 ...
  • Risk Aware Warning and Control for Interactive Traffic Safety
    Risk Aware Warning and Control for Interactive Traffic Safety
    Dolan, John M ;
    Lyu, Yiwei
    2024-07-31 | PDF
    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 ...
  • Reinforcement Learning
    Reinforcement Learning
    Redmill, Keith ;
    Zhang, Zhihao
    2024-07-31 | PDF
    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 ...
  • On the Role of Perceived Safety Concerns on Public Acceptance Behavior of Autonomous Vehicles
    On the Role of Perceived Safety Concerns on Public Acceptance Behavior of Autonomous Vehicles
    Nazari, Fatemeh ;
    Noruzoliaee, Mohamadhossein
    2024-07-30 | PDF
    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 ...
  • Enhancing Traffic Safety and Connectivity A DataDriven MultiStepAhead Vehicle Headway Prediction Leveraging HighResolution Vehicular Trajectories
    Enhancing Traffic Safety and Connectivity: A Data-Driven Multi-Step-Ahead Vehicle Headway Prediction Leveraging High-Resolution Vehicular Trajectories
    Noruzoliaee, Mohamadhossein ;
    Nazari, Fatemeh
    2024-07-30 | PDF
    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 ...
  • Pavement Markings To Support Automated Vehicles Research Summary
    Pavement Markings To Support Automated Vehicles [Research Summary]
    Peterson, Ethan ;
    Pike, Adam
    2024-07-01 | PDF
    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 ...
  • Connected Autonomous Shuttle Supporting Innovation CASSI at UNC Charlotte
    Connected Autonomous Shuttle Supporting Innovation (CASSI) at UNC Charlotte
    Searcy, Sarah ;
    Lape, Doug
    2024-07-01 | PDF
    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 ...
  • The Grand Iron Range CAV Initiative History Partnerships and Community Engagement
    The Grand Iron Range CAV Initiative: History, Partnerships, and Community Engagement
    Douma, Frank ;
    Weiner, Evelyn
    2024-07-01 | PDF
    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 ...
  • Impacts of Autonomous TruckMounted Attenuator ATMA on INDOT Work Zone Safety Mobility and Worker Productivity
    Impacts of Autonomous Truck-Mounted Attenuator (ATMA) on INDOT Work Zone Safety, Mobility, and Worker Productivity
    Tian, Chi ;
    Feng, Yiheng
    2024-07-01 | PDF
    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, ...
  • Scan and Review of Autonomous Shuttle Operation and Other Personal Transportation Options Affecting Autonomous Transit Viability
    Scan and Review of Autonomous Shuttle Operation and Other Personal Transportation Options Affecting Autonomous Transit Viability
    Elefteriadou, Lily ;
    Yan, Jacob
    2024-07-01 | PDF
    At the state and national levels, there is continued interest in AV technologies and in providing a broad set of transportation options. Furthermore, technologies such as mobility on demand, ridesharing, and micromobility provide alternative options. Research is needed to understand how AV shuttles and other advanced technology-based options may of ...
  • Assessing Pavement Markings for Automated Vehicle Readiness
    Assessing Pavement Markings for Automated Vehicle Readiness
    Pike, Adam ;
    Shirinzad, Maryam
    2024-06-01 | PDF
    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 ...
  • State of the Practice of Crash Reporting in the US and Implications for CAV Safety Assessment
    State of the Practice of Crash Reporting in the U.S. and Implications for CAV Safety Assessment
    Acharya, Sailesh ;
    Rahman, Md Ashikur
    2024-05-01 | PDF
    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 ...
  • Assessing Safety and Mobility Benefits of Autonomous Ride Sharing Services Summary
    Assessing Safety and Mobility Benefits of Autonomous Ride Sharing Services [Summary]
    Holley, Gail M. ;
    Classen, Sherrilene
    2024-05-01 | PDF
    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.
81 - 100 / 852