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Autonomous Vehicles

rosaP Repository & Open Science Access Portal

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 101 - 120 of 867 results
  • 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 ...
  • 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 ...
  • 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 ...
  • 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 ...
  • 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 ...
  • 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 ...
  • A Statistical and Machine Learning Approach to Assess Contextual Complexity of the Driving Environment Using Autonomous Vehicle Data Technology Transfer Activities
    A Statistical and Machine Learning Approach to Assess Contextual Complexity of the Driving Environment Using Autonomous Vehicle Data— Technology Transfer Activities
    Ogle, Jennifer H ;
    Bendigeri, Vijay
    2024-05-01 | PDF
    Traditional road safety assessment methodologies rely heavily on AADT (Annual Average Daily Traffic) data estimates to account for variability in traffic operations. Unfortunately, this approach does not consider the driving environment's fast-changing dynamics, which can influence contextual complexity and risk. This research report presents a met ...
  • Heterogeneous Preferences for Activities While Traveling in Autonomous Vehicles Relationships with Travel Contexts and Attitudes
    Heterogeneous Preferences for Activities While Traveling in Autonomous Vehicles: Relationships with Travel Contexts and Attitudes
    Kim, Ilsu ;
    Lee, Yongsung
    2024-05-01 | PDF
    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 ...
  • Experiences With Autonomous Vehicle in US Cities
    Experiences With Autonomous Vehicle in U.S. Cities
    D’Agostino, Mollie Cohen ;
    Cooper, Elliott Michael
    2024-05-01 | PDF
    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 ...
  • Assessment of Contextual Complexity and Risk Using Unsupervised Clustering Approaches with Dynamic Traffic Condition Data Obtained from Autonomous Vehicles
    Assessment of Contextual Complexity and Risk Using Unsupervised Clustering Approaches with Dynamic Traffic Condition Data Obtained from Autonomous Vehicles
    Ogle, Jennifer H ;
    Bendigeri, Vijay
    2024-05-01 | PDF
    Traditional road safety assessment methodologies rely heavily on AADT (Annual Average Daily Traffic) data estimates to account for variability in traffic operations. Unfortunately, this approach does not consider the driving environment's fast-changing dynamics, which can influence contextual complexity and risk. This research report presents a met ...
  • 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.
  • Third Generation Simulation Data TGSIM A Closer Look at The Impacts of Automated Driving Systems on Human Behavior
    Third Generation Simulation Data (TGSIM): A Closer Look at The Impacts of Automated Driving Systems on Human Behavior
    Talebpour, Alireza ;
    Mahmassani, Hani S.
    2024-05-01 | PDF
    This study collected and processed accurate trajectory datasets capable of characterizing human-automated vehicle interactions under a diverse set of scenarios in highway and city environments. Multiple methods were utilized to collect data: fixed location aerial videography, moving aerial videography, and infrastructure-based videography. Fixed lo ...
  • State of the Practice of Crash Reporting in the US and Implications for CAV Safety Assessment Research Brief
    State of the Practice of Crash Reporting in the U.S. and Implications for CAV Safety Assessment [Research Brief]
    Mekker, Michelle ;
    Acharya, Sailesh
    2024-05-01 | PDF
    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 ...
  • 2022 CDA Annual Report
    2022 CDA Annual Report
    Balse, Animesh ;
    Bellamkonda, Mitali
    2024-04-01 | PDF
    The Cooperative Driving Automation (CDA) Annual Report highlights the achievements of the CDA program and discusses the use cases that were created and researched to further overall CDA program objectives to enable a cooperative, safe, efficient, and sustainable transportation system for all users. This report also details engagement activities wit ...
  • Development of an Immersive Training Platform for Roadway Construction Workers using Virtual Reality Technologies Policy Brief
    Development of an Immersive Training Platform for Roadway Construction Workers using Virtual Reality Technologies [Policy Brief]
    Wang, Zhenyu ;
    Lin, Pei-Sung
    2024-03-31 | PDF
    Workforce education is crucial to ensuring the safety and equality of the work environment. Immersive virtual reality (VR) training is revolutionizing workforce education, providing practical on-the-job training within a safe simulated environment. The project aimed to develop an immersive training platform using state-of-the-art VR technologies an ...
  • Securing Deep Learning Against Adversarial Attacks for Connected and Automated Vehicles
    Securing Deep Learning Against Adversarial Attacks for Connected and Automated Vehicles
    Pisu, Pierluigi ;
    Comert, Gurcan
    2024-03-01 | PDF
    Intelligent mobile robots, including autonomous agents, highly rely on the correctness of surrounding environment perception. Recently, Deep Learning-based perception models have been shown to be vulnerable to adversarial attacks through one kind of well-designed input called adversarial examples. Existing defenses include mainly adversarial traini ...
101 - 120 / 867