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.
This research sought to evaluate the broad impacts that automated and connected vehicle technologies can have on both the motor carrier and rail industries. Since the development and adoption of these technologies are likely to be gradual, three phases were posited and analyzed. Depending on the degree of autonomy that is available, the motor carri
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Bao, K., & Mundy, R. A. (2018). Emerging Freight Truck Technologies : Effects on Relative Freight Costs. Midwest Transportation Center. https://rosap.ntl.bts.gov/view/dot/36218
Bao, Ken and Ray A. Mundy. Emerging Freight Truck Technologies : Effects on Relative Freight Costs. Midwest Transportation Center, 2018. https://rosap.ntl.bts.gov/view/dot/36218.
Bao, Ken, and Ray A. Mundy Emerging Freight Truck Technologies : Effects on Relative Freight Costs. Midwest Transportation Center, 2018, ROSA P. https://rosap.ntl.bts.gov/view/dot/36218.
Citation: Sinha, K.C. (2018). Charging mechanisms for road use: An interface between engineering and public policy, Keck Distinguished Lecture, April 12, 2018, University of Illinois Urbana Champaign, Urbana, IL.
Sinha, K. C. (2018). Charging Mechanisms for Road Use: An Interface between Engineering and Public Policy [Presentation]. Center for Connected and Automated Transportation. Purdue University. https://rosap.ntl.bts.gov/view/dot/73554
Sinha, Kumares C.. Charging Mechanisms for Road Use: An Interface between Engineering and Public Policy [Presentation]. Center for Connected and Automated Transportation. Purdue University, 2018. https://rosap.ntl.bts.gov/view/dot/73554.
Sinha, Kumares C. Charging Mechanisms for Road Use: An Interface between Engineering and Public Policy [Presentation]. Center for Connected and Automated Transportation. Purdue University, 2018, ROSA P. https://rosap.ntl.bts.gov/view/dot/73554.
This report describes the experiment on how to model impacts of connected and autonomous/automated vehicles (CAVs) and ride-hailing with an Activity-Based Model (ABM) and Dynamic Traffic Assignment (DTA) in the context of Exploratory Modeling and Analysis (EMA). EMA is a systematic approach to perform sensitivity analyses using models when users ca
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Stabler, B., Bradley, M., Morgan, D., Slavin, H., & Haque, K. (2018). Volume 2: Model Impacts of Connected and Autonomous/Automated Vehicles (CAVs) and Ride-Hailing with an Activity-Based Model (ABM) and Dynamic Traffic Assignment (DTA)-An Experiment (Report No. FHWA-HEP-18-081). United States. Federal Highway Administration. https://rosap.ntl.bts.gov/view/dot/55802
Stabler, Ben, Mark Bradley, Dan Morgan, Howard Slavin, and Khademul Haque. Volume 2: Model Impacts of Connected and Autonomous/Automated Vehicles (CAVs) and Ride-Hailing with an Activity-Based Model (ABM) and Dynamic Traffic Assignment (DTA)-An Experiment. Report no. FHWA-HEP-18-081. United States. Federal Highway Administration, 2018. https://rosap.ntl.bts.gov/view/dot/55802.
Stabler, Ben, et al. Volume 2: Model Impacts of Connected and Autonomous/Automated Vehicles (CAVs) and Ride-Hailing with an Activity-Based Model (ABM) and Dynamic Traffic Assignment (DTA)-An Experiment. United States. Federal Highway Administration, 2018, Report no. FHWA-HEP-18-081, ROSA P. https://rosap.ntl.bts.gov/view/dot/55802.
Automobiles are increasingly equipped with autonomous and semi-autonomous technologies such as adaptive cruise control and automated lane-keeping. It is apparent that increasing numbers of these smart vehicles will have a dramatic impact on network-level mobility factors such as traffic congestion and travel times. By enabling platooning of groups
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Pedarsani, R. (2018). Control and Management of Urban Traffic Networks With Mixed Autonomy (Report No. CA18-3140). California. Dept. of Transportation. Division of Research and Innovation. https://rosap.ntl.bts.gov/view/dot/63058
Pedarsani, Ramtin. Control and Management of Urban Traffic Networks With Mixed Autonomy. Report no. CA18-3140. California. Dept. of Transportation. Division of Research and Innovation, 2018. https://rosap.ntl.bts.gov/view/dot/63058.
Pedarsani, Ramtin Control and Management of Urban Traffic Networks With Mixed Autonomy. California. Dept. of Transportation. Division of Research and Innovation, 2018, Report no. CA18-3140, ROSA P. https://rosap.ntl.bts.gov/view/dot/63058.
Cooperative Adaptive Cruise Control (CACC) provides an intermediate step toward a longer-term vision of trucks operating in closely-coupled automated platoons. One distinction between CACC and automated truck platooning is with CACC, only truck speed control will be automated using Vehicle-to-Vehicle communication. The drivers will still be respons
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Shladover, S. E., Yun, X., Yang, L., Ramezani, H., Spring, J., Nowakowski, C. V., Nelson, D., Thompson, D., & Kailas, A. (2018). Cooperative Adaptive Cruise Control (CACC) For Partially Automated Truck Platooning (Report No. CA18-2623). California. Dept. of Transportation. Division of Research and Innovation. https://rosap.ntl.bts.gov/view/dot/43776
Shladover, Steven E., Xiao Yun, LuShiyan Yang, Hani Ramezani, John Spring, Christopher Vincent Nowakowski, David Nelson, Deborah Thompson, and Aravind Kailas. Cooperative Adaptive Cruise Control (CACC) For Partially Automated Truck Platooning. Report no. CA18-2623. California. Dept. of Transportation. Division of Research and Innovation, 2018. https://rosap.ntl.bts.gov/view/dot/43776.
Shladover, Steven E., et al. Cooperative Adaptive Cruise Control (CACC) For Partially Automated Truck Platooning. California. Dept. of Transportation. Division of Research and Innovation, 2018, Report no. CA18-2623, ROSA P. https://rosap.ntl.bts.gov/view/dot/43776.
This document summarizes positioning and timing related information from the three Connected Vehicle Pilot Deployment Sites (NYCDOT, Tampa/THEA, and WYDOT) as discussed during technical roundtables. Information is largely based on progress to date during Phase 2, and will be updated in the future once all sites have finalized their implementations.
Chang, J., & Fok, E. (2018). Connected Vehicle Pilot Positioning and Timing Report: Summary of Positioning and Timing Approaches in CV Pilot Sites (Report No. FHWA-JPO-18-638). United States. Department of Transportation. Intelligent Transportation Systems Joint Program Office. https://rosap.ntl.bts.gov/view/dot/35427
Chang, James and Edward Fok. Connected Vehicle Pilot Positioning and Timing Report: Summary of Positioning and Timing Approaches in CV Pilot Sites. Report no. FHWA-JPO-18-638. United States. Department of Transportation. Intelligent Transportation Systems Joint Program Office, 2018. https://rosap.ntl.bts.gov/view/dot/35427.
Chang, James, and Edward Fok Connected Vehicle Pilot Positioning and Timing Report: Summary of Positioning and Timing Approaches in CV Pilot Sites. United States. Department of Transportation. Intelligent Transportation Systems Joint Program Office, 2018, Report no. FHWA-JPO-18-638, ROSA P. https://rosap.ntl.bts.gov/view/dot/35427.
Connected and automated vehicles (CAV) are poised to transform surface transportationsystems in the United States. Near-term CAV technologies like cooperative adaptive cruisecontrol (CACC) have the potential to deliver energy efficiency and air quality benefits. Thisposter lays out a modeling framework for evaluating energy and tailpipe emission im
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Eilbert, A., Jackson, L., Noel, G., & Smith, S. (2018). A Framework for Evaluating Energy and Emissions of Connected and Automated Vehicles through Traffic Microsimulations. John A. Volpe National Transportation Systems Center (U.S.). https://rosap.ntl.bts.gov/view/dot/35986
Eilbert, Andrew, Lauren Jackson, George Noel, and Scott Smith. A Framework for Evaluating Energy and Emissions of Connected and Automated Vehicles through Traffic Microsimulations. John A. Volpe National Transportation Systems Center (U.S.), 2018. https://rosap.ntl.bts.gov/view/dot/35986.
Eilbert, Andrew, et al. A Framework for Evaluating Energy and Emissions of Connected and Automated Vehicles through Traffic Microsimulations. John A. Volpe National Transportation Systems Center (U.S.), 2018, ROSA P. https://rosap.ntl.bts.gov/view/dot/35986.
This research develops heuristics to manage mandatory network capacity reductions to better serve the network flows. The main application discussed relates to transportation networks, and flow cost relates to travel cost of users of the network. Temporary mandatory capacity reductions are required by maintenance activities. The objective of managin
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Mirchandani, Pitu B., and Dening Peng Scheduling Work Zones in Multi-Modal Networks. SOLARIS Consortium, 2018, ROSA P. https://rosap.ntl.bts.gov/view/dot/37385.
Road travel in light-duty vehicles, while of great economic value to private consumers and society, also generates a range of social costs. These include environmental damage from localized and global emissions, energy security concerns from petroleum use, external accident risk, and road congestion. These social costs are addressed only partially
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Rubin, J., & Noblet, C. (2017). Automated Vehicles: Economic Incentives for Environmental Benefits and Safety (Report No. UMER25-37). New England University Transportation Center. https://rosap.ntl.bts.gov/view/dot/43930
Rubin, Jonathan and Caroline Noblet. Automated Vehicles: Economic Incentives for Environmental Benefits and Safety. Report no. UMER25-37. New England University Transportation Center, 2017. https://rosap.ntl.bts.gov/view/dot/43930.
Rubin, Jonathan, and Caroline Noblet Automated Vehicles: Economic Incentives for Environmental Benefits and Safety. New England University Transportation Center, 2017, Report no. UMER25-37, ROSA P. https://rosap.ntl.bts.gov/view/dot/43930.
Connected and automated vehicles (CAVs) must be tested extensively before they can be deployed and accepted by the general public. Currently, CAV testing and evaluation are primarily conducted in two ways: on public roads and in closed test facilities. There are two significant limitations of public road testing. First, safety is a critical issue b
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University of Michigan, Central State University, Purdue, University of Akron, University of Illinois at Urbana-Champaign, & Washtenaw Community College (2017). Augmented Reality and Connected Automated Vehicles. United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology. https://doi.org/10.21949/1528836
University of Michigan, Central State University, Purdue, University of Akron, University of Illinois at Urbana-Champaign, and Washtenaw Community College. Augmented Reality and Connected Automated Vehicles. United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology, 2017. https://doi.org/10.21949/1528836.
University of Michigan, et al. Augmented Reality and Connected Automated Vehicles. United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology, 2017, ROSA P. https://doi.org/10.21949/1528836.
This report investigates using detailed simulation models to help regional and state agencies plan for the effects of connected vehicle (CV) and autonomous vehicle (AV) technologies in long-range planning. The research integrates the DaySim activity-based travel demand model with the TransModeler dynamic traffic simulation model for Jacksonville, F
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Bradley, M., Stabler, B., Haque, K., Slavin, H., & Morgan, D. (2017). Volume 1: Integrated ABM-DTA Methods to Model Impacts of Disruptive Technology on the Regional Surface Transportation System - A Feasibility Study (Report No. FHWA-HEP-18-082). United States. Federal Highway Administration. https://rosap.ntl.bts.gov/view/dot/55801
Bradley, Mark, Ben Stabler, Khademul Haque, Howard Slavin, and Dan Morgan. Volume 1: Integrated ABM-DTA Methods to Model Impacts of Disruptive Technology on the Regional Surface Transportation System - A Feasibility Study. Report no. FHWA-HEP-18-082. United States. Federal Highway Administration, 2017. https://rosap.ntl.bts.gov/view/dot/55801.
Bradley, Mark, et al. Volume 1: Integrated ABM-DTA Methods to Model Impacts of Disruptive Technology on the Regional Surface Transportation System - A Feasibility Study. United States. Federal Highway Administration, 2017, Report no. FHWA-HEP-18-082, ROSA P. https://rosap.ntl.bts.gov/view/dot/55801.
This summary report provides a high-level overview of four experiments that investigated human factors issues surrounding cooperative adaptive cruise control (CACC). CACC combines three driver assist systems: (1) conventional cruise control, which automatically maintains the speed a driver has set, (2) adaptive cruise control, which uses radar or l
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Inman, V. W., Balk, S. A., Jackson, S., & Philips, B. H. (2017). Summary Report : Cooperative Adaptive Cruise Control Human Factors Study (Report No. FHWA-HRT-17-025). United States. Department of Transportation. Federal Highway Administration. Office of Safety. https://rosap.ntl.bts.gov/view/dot/37823
Inman, Vaughan W., Stacy A. Balk, Steven Jackson, and Brian H. Philips. Summary Report : Cooperative Adaptive Cruise Control Human Factors Study. Report no. FHWA-HRT-17-025. United States. Department of Transportation. Federal Highway Administration. Office of Safety, 2017. https://rosap.ntl.bts.gov/view/dot/37823.
Inman, Vaughan W., et al. Summary Report : Cooperative Adaptive Cruise Control Human Factors Study. United States. Department of Transportation. Federal Highway Administration. Office of Safety, 2017, Report no. FHWA-HRT-17-025, ROSA P. https://rosap.ntl.bts.gov/view/dot/37823.
The Federal Highway Administration (FHWA) has adapted the Transportation Systems Management and Operations (TSMO) Capability Maturity Model (CMM) to describe the operational maturity of Infrastructure Owner-Operator (IOO) agencies across a range of important dimensions. Agencies can use the CMM to develop action plans to move agencies capabilities
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Gettman, D., Burgess, L., Haase, D., Flanigan, E., & Lockwood, S. (2017). Guidelines for Applying the Capability Maturity Model Analysis to Connected and Automated Vehicle Deployment (Report No. FHWA-JPO-18-629). United States. Department of Transportation. Intelligent Transportation Systems Joint Program Office. https://rosap.ntl.bts.gov/view/dot/34398
Gettman, Douglas, Lisa Burgess, Deanna Haase, Erin Flanigan, and Steve Lockwood. Guidelines for Applying the Capability Maturity Model Analysis to Connected and Automated Vehicle Deployment. Report no. FHWA-JPO-18-629. United States. Department of Transportation. Intelligent Transportation Systems Joint Program Office, 2017. https://rosap.ntl.bts.gov/view/dot/34398.
Gettman, Douglas, et al. Guidelines for Applying the Capability Maturity Model Analysis to Connected and Automated Vehicle Deployment. United States. Department of Transportation. Intelligent Transportation Systems Joint Program Office, 2017, Report no. FHWA-JPO-18-629, ROSA P. https://rosap.ntl.bts.gov/view/dot/34398.
Connected and automated vehicles (CAV) may deliver energy efficiency and air quality benefits by reducing traffic congestion and facilitating smoother driving behavior. This paper proposes a three-layered modeling framework for assessing the energy and emission impacts of first generation CAV technologies, such as cooperative adaptive cruise contro
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Eilbert, A., Jackson, L., Noel, G., & Smith, S. (2017). A Framework for Evaluating Energy and Emissions of Connected and Automated Vehicles through Traffic Microsimulations [Paper]. John A. Volpe National Transportation Systems Center (U.S.). https://rosap.ntl.bts.gov/view/dot/43934
Eilbert, Andrew, Lauren Jackson, George Noel, and Scott Smith. A Framework for Evaluating Energy and Emissions of Connected and Automated Vehicles through Traffic Microsimulations [Paper]. John A. Volpe National Transportation Systems Center (U.S.), 2017. https://rosap.ntl.bts.gov/view/dot/43934.
Eilbert, Andrew, et al. A Framework for Evaluating Energy and Emissions of Connected and Automated Vehicles through Traffic Microsimulations [Paper]. John A. Volpe National Transportation Systems Center (U.S.), 2017, ROSA P. https://rosap.ntl.bts.gov/view/dot/43934.
The Center for Connected Multimodal Mobility (C2M2), headquartered at Clemson University, began conducting research in 2016 by utilizing and enhancing the functionalities of the Clemson University Connected Vehicle Testbed (CU-CVT). CU-CVT includes heterogeneous wireless communication technologies and data infrastructure for real-time connected veh
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Center for Connected Multimodal Mobility, Clemson University, Benedict College, The Citadel, South Carolina State University, & University of South Carolina (2017). New Frontiers in Connected Vehicle Technologies: A Testbed for Validating Connectivity, Data Analytics, Cybersecurity, and Automation. United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology. https://doi.org/10.21949/1528837
Center for Connected Multimodal Mobility, Clemson University, Benedict College, The Citadel, South Carolina State University, and University of South Carolina. New Frontiers in Connected Vehicle Technologies: A Testbed for Validating Connectivity, Data Analytics, Cybersecurity, and Automation. United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology, 2017. https://doi.org/10.21949/1528837.
Center for Connected Multimodal Mobility, et al. New Frontiers in Connected Vehicle Technologies: A Testbed for Validating Connectivity, Data Analytics, Cybersecurity, and Automation. United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology, 2017, ROSA P. https://doi.org/10.21949/1528837.
The goal of this project is to develop decision-making tools that enhance our understanding of the intricate relationship between vehicle autonomy, traffic operations and congestion externalities. A detailed traffic simulation tool was used to investigate the relationship between vehicle autonomy, travel demand attributes (e.g., driver behavior), a
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Osorio, C. (2017). Optimal Road Traffic Operations for an Increasingly Autonomous and Connected Vehicle Fleet (Report No. MITR25-11). New England University Transportation Center. https://rosap.ntl.bts.gov/view/dot/43885
Osorio, Carolina. Optimal Road Traffic Operations for an Increasingly Autonomous and Connected Vehicle Fleet. Report no. MITR25-11. New England University Transportation Center, 2017. https://rosap.ntl.bts.gov/view/dot/43885.
Osorio, Carolina Optimal Road Traffic Operations for an Increasingly Autonomous and Connected Vehicle Fleet. New England University Transportation Center, 2017, Report no. MITR25-11, ROSA P. https://rosap.ntl.bts.gov/view/dot/43885.
LIDAR has become one of the major enabling technologies for autonomous vehicles. LIDAR sensors generate 3D point cloud data around the instrumented vehicle. These data enable detailed localization of both fixed and moving objects in the surrounding environment. In this project, various aspects of LIDAR data processing are studied with an emphasis o
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Cetin, M., Sazara, C., & Vatani, R. N. (2017). Exploring the Use of Lidar Data From Autonomous Cars for Estimating Traffic Flow Parameters and Vehicle Trajectories. Mid-Atlantic Transportation Sustainability University Transportation Center. https://rosap.ntl.bts.gov/view/dot/36619
Cetin, Mecit, Cem Sazara, and Reza Nezafat Vatani. Exploring the Use of Lidar Data From Autonomous Cars for Estimating Traffic Flow Parameters and Vehicle Trajectories. Mid-Atlantic Transportation Sustainability University Transportation Center, 2017. https://rosap.ntl.bts.gov/view/dot/36619.
Cetin, Mecit, et al. Exploring the Use of Lidar Data From Autonomous Cars for Estimating Traffic Flow Parameters and Vehicle Trajectories. Mid-Atlantic Transportation Sustainability University Transportation Center, 2017, ROSA P. https://rosap.ntl.bts.gov/view/dot/36619.
This report documents the work completed by the Crash Avoidance Metrics Partners LLC (CAMP) Vehicle to Infrastructure (V2I) Consortium during the third year of the “Development of Vehicle-to-Infrastructure Applications (V2I) Program.” Participating companies in the V2I Consortium during this period were Ford, General Motors, Hyundai-Kia, Honda, Maz
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Shulman, M., & Geisler, S. (2017). Development of Vehicle-to-Infrastructure Applications Program Third Annual Report (Report No. FHWA-JPO-18-618). United States. Department of Transportation. Intelligent Transportation Systems Joint Program Office. https://rosap.ntl.bts.gov/view/dot/37213
Shulman, Michael and Scott Geisler. Development of Vehicle-to-Infrastructure Applications Program Third Annual Report. Report no. FHWA-JPO-18-618. United States. Department of Transportation. Intelligent Transportation Systems Joint Program Office, 2017. https://rosap.ntl.bts.gov/view/dot/37213.
Shulman, Michael, and Scott Geisler Development of Vehicle-to-Infrastructure Applications Program Third Annual Report. United States. Department of Transportation. Intelligent Transportation Systems Joint Program Office, 2017, Report no. FHWA-JPO-18-618, ROSA P. https://rosap.ntl.bts.gov/view/dot/37213.
Through this project, the Texas Department of Transportation (TxDOT) funded the creation of a comprehensive truck platooning demonstration in Texas, serving as a proactive effort in assessing innovative operational strategies to position TxDOT as a leader in this research area and the overall transportation systems management and operation using co
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Kuhn, B., Lukuc, M., Poorsartep, M., Wagner, J., Balke, K. N., Middleton, D., Songchitruksa, P., Wood, N., & Moran, M. (2017). Commercial Truck Platooning Demonstration in Texas – Level 2 Automation (Report No. FHWA/TX-17/0-6836-1). Texas Department of Transportation. Research and Technology Implementation Office. https://rosap.ntl.bts.gov/view/dot/32611
Kuhn, Beverly, Mike Lukuc, Mo Poorsartep, Jason Wagner, Kevin N. Balke, Dan Middleton, Praprut Songchitruksa, Nick Wood, and Maarit Moran. Commercial Truck Platooning Demonstration in Texas – Level 2 Automation. Report no. FHWA/TX-17/0-6836-1. Texas Department of Transportation. Research and Technology Implementation Office, 2017. https://rosap.ntl.bts.gov/view/dot/32611.
Kuhn, Beverly, et al. Commercial Truck Platooning Demonstration in Texas – Level 2 Automation. Texas Department of Transportation. Research and Technology Implementation Office, 2017, Report no. FHWA/TX-17/0-6836-1, ROSA P. https://rosap.ntl.bts.gov/view/dot/32611.
This research is intended to provide a technical analysis of the potential impacts of automated vehicles (AVs) on current light-duty vehicle miles traveled (VMT) and parking decisions, the economic desirability of widespread deployment of partially automated technologies, and methods for existing roadways to transition to connected and automated ve
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Samaras, C., Henrickson, C., & Harper, C. (2017). Transitioning Roadways to Accommodate Connected and Automated Vehicles: A Pennsylvania Case Study. Technologies for Safe and Efficient Transportation. University Transportation Center. https://rosap.ntl.bts.gov/view/dot/63303
Samaras, Costa, Chris Henrickson, and Corey Harper. Transitioning Roadways to Accommodate Connected and Automated Vehicles: A Pennsylvania Case Study. Technologies for Safe and Efficient Transportation. University Transportation Center, 2017. https://rosap.ntl.bts.gov/view/dot/63303.
Samaras, Costa, et al. Transitioning Roadways to Accommodate Connected and Automated Vehicles: A Pennsylvania Case Study. Technologies for Safe and Efficient Transportation. University Transportation Center, 2017, ROSA P. https://rosap.ntl.bts.gov/view/dot/63303.
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