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 of 2021, there were 18,696 small towns in the US with a population of less than 50,000. These communities typically have a low population density, few public transport services, and limited accessibility to daily services. This can pose significant challenges for residents trying to fulfill essential travel needs and access healthcare. Autonomou
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Taking advantage of the rapid development of vehicle control and communication technologies, many studies have suggested that operating vehicles in platoons in the future would help improve the safety and efficiency of the transportation system. Although vehicles in a platoon can share data from V2/V communication, a platoon model built on proper c
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This study introduces a unified end-to-end framework for analyzing network traffic equilibrium. The framework learns supply and demand components directly from traffic data, using computational graphs to parameterize unknown elements. It enforces user equilibrium through variational inequalities and can incorporate various modeling approaches, incl
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The number of automated features in surface vehicles is increasing as new vehicles are released each year. Some features allow drivers to temporarily take their attention off the road to engage in other tasks. However, sometimes it is important for drivers to immediately take control of the vehicle. To take control safely, drivers must understand w
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Truck platooning—wirelessly linking two or more trucks to travel in a closely spaced convoy—is federally promoted to save fuel, improve the environment, and improve traffic operations. Platooning places trucks much closer than current design codes anticipate. While this strategy can provide higher fuel efficiency, it also can potentially overload s
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We will apply our results from neuroscience and safe control to improve driver-assistance technology as follows. First, we will study the use of visual attention information to detect risks early, before the failure to detect risk-critical obstacles can be identified from the drivers' control action and vehicle states. Second, we will find safer co
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This paper focuses on assessing the transportation system and sub-population level impacts of different congestion pricing policies for shared AV services in Seattle. While the conclusions of this research are meant to be generalizable, we focus our study on Seattle, Washington because it’s a diverse city with known inequalities among income, race,
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There are numerous applications of the Autonomous Maintenance Technology (AMT) that have yet to be fully utilized or widely shared. There are many slow-moving operations conducted by Departments of Transportation (DOTs) with an attenuator (e.g., work zone set up, operations, take down, repairs, mowing, sweeping), platooning of two or more vehicles
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Roadway intersections are among the major causes of traffic congestion besides lane reduction bottlenecks. When a major road intersects a minor road at an unsignalized intersection without the control of a traffic signal, the mainline vehicles are given priority over the minor road vehicles to go through the intersection, and the latter can only en
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High precision road maps are a crucial component to facilitating autonomous driving techniques. Autonomous vehicles (AVs) are experiencing exponential growth. According to the latest forecast from IHS Markit, over 33 million AVs will be on the road globally by 2040, posing a higher requirement to ensure AVs’ driving safety. Although current AVs rel
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The research team aims to investigate how networked autonomous mobility, such as self-driving taxis or delivery robots, will reshape our understanding of privacy and explore technical tools for privacy-preserving operation on the individual level and group level. The team will conduct comprehensive and realistic analysis using public datasets colle
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This report lays the theoretical groundwork for participatory traffic control that integrates traditional infrastructure like traffic signals with connected and automated vehicles (CAVs) acting as mobile actuators. The study is divided into two main parts. First, we introduce a robust traffic state estimation method that leverages real-time data fr
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A significant majority of state-of-the-art autonomous sensing and navigation technologies rely on good lane markings or detailed 3D maps of the environment, making them more suited for urban communities. Conversely, many rural roads in the U.S. do not have lane markings and have irregular boundaries. These challenges are common to many small and ru
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With the arrival of new technologies like connected and self-driving autonomous vehicles (AVs), the workload of regional dispatchers will increase. To this end, the CADS (Congestion Alerting Decision Support) tool was developed to support strategic transportation planning (on the order of weeks to months) and tactical transportation planning (on th
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Electric vehicles, autonomous or manual, provide a valuable opportunity to address issues of environmental pollution, climate change, and national security. In recognition of the synergies between vehicle electrification and autonomy, this study addresses the facilitation of vehicle electrification in the prospective future era where autonomous veh
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The aim of Project 0-7129 was to demonstrate that AV trucking data can be effectively ingested and reported to TxDOT maintenance personnel, improving operational efficiency. Texas leads the nation in AV testing and deployment, with significant stakeholder support for the IRMF’s potential to reduce reporting latency and improve geographical and seve
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The authors will apply their results from neuroscience and safe control to improve driver-assistance technology as follows. First, the authors will study the use of visual attention information to detect risks early, before the failure to detect risk-critical obstacles can be identified from the drivers' control action and vehicle states. Second, t
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According to studies done by Pew Research, PAVE, and AAA [2], [5], [3], people are quite apprehensive about being passengers in self-driving vehicles. They are concerned about the ethical choices that AV systems might make and how AV manufacturers prioritize pedestrians, passengers, or other drivers in an unavoidable accident. Drivers worry whether
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This project will explore several potential applications of image processing, including NN/deep learning technologies, to the analysis of traffic scenes involving passenger and transit vehicles. The project team outlines three potential applications below- the exact distribution of effort and topics addressed will depend on the availability of stud
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Vehicle-pedestrian interactions in shared spaces represents a complex safety problem. Ideally, the vehicle must react safely to any pedestrian behavior, while the pedestrian behavior itself can be very complex and unpredictable. To emphasize this safety problem, in a 2019 Traffic Safety Facts report by the National Highway Traffic Safety Administra
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