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.
As the population of older drivers continues to grow, there is an increasing need to enhance their awareness and understanding of Connected and Automated Vehicles (CAVs). This study utilized an education program aimed at improving the knowledge and awareness of older drivers about CAVs, thereby preparing them to utilize the safety features of these
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This project focuses on experimental tests of the performance characteristics of autonomous vehicles (AVs) on highways and local roads in Minnesota. The project provides detailed data characterizing AV performance, which in turn can be used to inform the transportation community on implications for infrastructure maintenance, winter road maintenanc
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Development of connected and automated vehicles (CAVs) holds promise for reducing traffic crashes and maintaining mobility among older adults. Challenges remain, however, in ensuring that CAVs are accessible, acceptable, affordable, and otherwise inclusive for older adults. The objective of this project was to increase graduate students’ awareness
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To standardize definitions and guide the design, regulation, and policy related to automated transportation, the Society of Automotive Engineers (SAE) has established a taxonomy consisting of six levels of vehicle automation. The SAE taxonomy defines each level based on the capabilities of the automated system. It does not fully consider the infras
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This funding augmented maintenance and operations of the Ann Arbor Connected Environment. The Ann Arbor Connected Environment is one of the largest operational, real-world deployment of DSRC connected vehicles and infrastructure in the world. In 2017, it was expanded to encompass the entire City of Ann Arbor – 29 square miles. It has 70 infrastruct
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The effectiveness of the human–machine interface (HMI) in a driving automation system during takeover situations is based, in part, on its design. Past research has indicated that modality, specificity, and timing of the HMI have an impact on driver behavior. The objective of this study was to examine the effectiveness of two HMIs, which vary by mo
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Texas has become a major hub for autonomous trucking activity, with companies operating routes daily and continuing to expand operations onto new roadways. Equipped with high-definition cameras and sensor suites, autonomous trucks present a new data opportunity for the Texas Department of Transportation (TxDOT) to improve its routine maintenance op
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This project aimed to implement the advances in new technologies to develop a robotic-based autonomous inspection system for underground pipelines. The new technology is based on the combination of intelligent powerful portable software and the newly advancement in mapping techniques. The system can scan and reconstruct the 3D profile of a pipeline
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This paper proposes an alternative strategy that could meet the needs of both connected vehicles and Wi-Fi 6 by allowing them to share spectrum under an appropriate set of coexistence rules. This could be achieved through changes in spectrum regulations, modest changes in technology for those C-V2X devices that operate in the shared band, and no ch
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The accurate detection and prediction of actions by multiple traffic participants such as pedestrians, vehicles, cyclists and others is a critical prerequisite for enabling self-driving vehicles to make autonomous decisions. Current approaches to teach an autonomous vehicle how to drive use reinforcement learning which is essentially relies on alre
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As the demand for curb parking increases and new types of curb space users compete for space, the need to more efficiently manage how vehicles interact with the curb becomes more apparent. One solution is to allow curb space users to submit a reservation ahead of their arrival that can be centrally managed and scheduled if the resources are availab
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Advanced Driver Assistance Systems (ADAS) support drivers with some driving tasks. However, drivers may lack appropriate knowledge about ADAS (referred to as their mental model), which can translate to drivers misusing or mistrusting the technologies, especially in situations beyond the capability of the system (i.e., edge cases). Past research sug
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The consideration of cooperative driving automation (CDA) in the transportation system management and operations (TSM&O ) processes has the potential for improving system performance in terms of safety, mobility, environmental impacts, and user satisfaction and acceptance. The goal of this project is to provide recommendations regarding the incorpo
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Autonomous, or self-driving, vehicles have the capability to either fully or partially replace a human driver in the navigation to a destination. To better understand how receptive society will be to these types of vehicles, this study focused on the perceived level of trust in autonomous vehicles (AVs) by rural drivers and passengers. An online su
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At roadway ecosystems with frequent movement conflicts among vehicles, pedestrians, and other road users, a road user entering the location immediately triggers a vibrant exchange of informal or formal cues with other road users and the traffic environment to ensure safe and efficient movement for all the road users at that location and at that tim
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Connected, automated, shared, and electric (CASE) technologies have invoked Mobility 4.0—a connected, digitized, multimodal, and autonomous system of systems. This project established a flexible and adaptable blueprint that would streamline multidisciplinary and multistakeholder efforts as well as leverage available resources to prepare the Illinoi
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Given the importance of mental models towards safe interaction with Advanced Driver Assistance Systems (ADAS) and the various human factors challenges regarding ADAS such as mis-calibrated trust and the effect on workload, it is important to understand how different types of driving experiences and exposures affect drivers’ mental models about ADAS
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Automated vehicles (AVs) present significant potential; yet, their technological maturity and performance remain to be proven. With several deployments underway in the state, it is critical for the Texas Department of Transportation (TxDOT) to provide the public with assurances that the AVs are performing safely in their intended operational enviro
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This project focuses on experimental tests of the performance characteristics of autonomous vehicles (AVs) on highways and local roads in Minnesota. The project provides detailed data characterizing AV performance, which in turn can be used to inform the transportation community on implications for infrastructure maintenance, winter road maintenanc
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In September 2015, the U.S. Department of Transportation (USDOT) Intelligent Transportation Systems (ITS) Joint Program Office (JPO) awarded three deployment sites under the Connected Vehicle (CV) Pilot Deployment Program to: the New York City Department of Transportation (NYCDOT); the Tampa Hillsborough Expressway Authority (THEA); and the Wyoming
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