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.
New York City is piloting connected vehicle (CV) technology to support the Vision Zero initiative and help eliminate injuries and fatalities caused by crashes. As a part of the USDOT CV Pilot Deployment Program, a Mobile Accessible Pedestrian Signal System (PED-SIG) was developed. The PED-SIG application provides audio alerts and haptic prompts to
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Emerging automated vehicles (AV) may be able to provide advanced information about the surrounding information with video cameras, radar sensors, lidar sensors, etc. Such information will enable estimating and predicting transportation system states on mobility, energy, and emissions. In this study, a physical informed neural network is developed t
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United States. Committee on the Marine Transportation System (CMTS)
2021-12-01
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The U.S. Committee on the Marine Transportation System (CMTS) in partnership with the Transportation Research Board (TRB) held the Sixth Biennial Marine Innovative Science and Technology Conference, “Advancing the Maritime Transportation System through Automation and Autonomous Technology: Trends, Applications, and Challenges,” virtually on March 1
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Connected and Autonomous Vehicle (CAV) technologies enable communication among vehicles, and vehicles and infrastructure, paving the way for multiple safety and operational applications. This research developed and tested traffic signal control algorithms and control programs which utilized CAV-equipped heavy trucks and traffic signals. The focus o
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A solar-powered automated transportation network (ATN) connecting the North and South campuses of San José State University with three passenger stations was designed, visualized, and analyzed in terms of its energy usage, carbon offset, and cost. The study’s methodology included the use of tools and software such as ArcGIS, SketchUp, Infraworks, S
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SAE Level 5 autonomy requires the autonomous vehicle to be able to accurately sense the environment and detect obstacles in all weather and visibility conditions. This sensing problem becomes significantly challenging in weather conditions that include such events as sudden change in lighting, smoke, fog, snow, and rain. There is no standalone sens
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Driverless vehicles must be self-aware to make learned and ethical decisions to avoid crashes in multimodal and diverse settings. This proposed effort will develop an Infrastructure Safety Support System by embedding vehicle-to-infrastructure (V2I) enabled sensor networks into the transportation infrastructure to provide autonomous vehicles and hum
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This project develops the main modules and algorithm models for the digital twin platform for a smart mobility testing ground currently under construction. LiDAR (Line Detection And Ranging)-sensor-based object detection and 3D infrastructure modeling modules are developed and tested in the project. The developed digital twin model is pilot tested
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Leveraging recent advancements in distributed optimization and reinforcement learning, and the growing connectivity and computational capability of vehicles and infrastructure, we propose to advance real-time adaptive signal control via distributed control and optimization. This report consists of three parts. Part 1 develops distributed algorithms
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Recently, 2D detection in images has made significant progress owing to the emergence of a convolutional neural network (CNN), which can extract high-level features from the images. However, detecting objects in 3D instead of 2D space is an essential topic when building perception systems for autonomous driving. An autonomous vehicle (AV) needs to
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Rapidly evolving technology is changing the how and why of travel. The Alaska Department of Transportation and Public Facilities (DOT&PF) is preparing for these changes by developing a Connected and Automated Vehicle (CAV) Strategic Plan for the established Working Group, made up of stakeholders across Alaska. The CAV Strategic Plan centers on the
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This brief summarizes an evaluation of the Federal Highway Administration's (FHWA's) investment in the truck platooning research project titled "Assessing the Feasibility of Deploying Partial Automation for Truck Platooning." This research project included two complementary subprojects, titled "Partial Automation for Truck Platooning" (PATP) and "D
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Autonomous vehicles (AV) and advanced driver-assistance systems (ADAS) offer multiple safety benefits for drivers and road agencies. However, maintaining the lateral position of an AV or a vehicle with ADAS within a lane is a challenge, especially in adverse weather conditions when lane markings are occluded. For significant penetration of AV witho
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Automated Vehicles have been one of the most sought-after concepts to make transportation more effective and safer. No-occupant vehicles with automated driving systems (ADS) make up one such class of vehicles. These are primarily intended for goods transportation services. This vehicle class presents a body structure different than that of a passen
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This project proposes a modeling framework to integrate ride-sourcing services and connected/automated vehicles with transit to serve different users in an urban area. Multiple travel modes are considered for morning commute: single ride and shared ride in ride-sourcing, and integrated ride-sourcing (either single ride or shared ride) and transit.
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Recent development of autonomous and connected trucks (ACT) has provided the freight industry with the option of using truck platooning to improve fuel efficiency, traffic throughput, and safety. However, closely spaced and longitudinally aligned trucks impose frequent and concentrated loading on pavements, which often accelerates pavement deterior
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As part of the City of Riverside’s Smart-City initiative, UC Riverside researchers have developed an Innovation Corridor testbed for enabling shared electric connected and automated transportation research. This Innovation Corridor testbed is located in Riverside California, and consists of a six-mile section of University Avenue between the UC Riv
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We sought to better understand how autonomous vehicle (AV) communication strategies impact human road users’ perceptions and behaviors. More specifically, we explored the impact of different external human-machine interface (eHMI) designs on understanding, task load, comfort, trust, acceptance, and reaction time. To accomplish this, we created virt
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We sought to better understand how autonomous vehicle (AV) communication strategies impact human road users’ perceptions and behaviors. More specifically, we explored the impact of different external human-machine interface (eHMI) designs on understanding, task load, comfort, trust, acceptance, and reaction time. To accomplish this, we created virt
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This study helps understand how the anticipated emergence of autonomous vehicles will affect various aspects of society and transportation, including travel demand, vehicle miles traveled, energy consumption, and emissions of greenhouse gases and other pollutants. The study begins with a literature review on connected and automated vehicle (CAV) te
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