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.
Testing and evaluation is a critical step in the development and deployment of connected and automated vehicle (CAV) technology. Testing standards for human-driven vehicles, such as Federal Motor Vehicle Safety Standards (FMVSS), were established a longtime ago. However, current standards cannot be applied to CAVs, because they often assume the pre
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Feng, Y., Bao, S., & Liu, H. (2023). Connected and Automated Vehicle (CAV) Testing Scenario Design and Implementation Using Naturalistic Driving Data and Augmented Reality (Report No. UMTRI-2023-6). University of Michigan. Center for Connected and Automated Transportation. https://rosap.ntl.bts.gov/view/dot/73486
Feng, Yiheng, Shan Bao, and Henry Liu. Connected and Automated Vehicle (CAV) Testing Scenario Design and Implementation Using Naturalistic Driving Data and Augmented Reality. Report no. UMTRI-2023-6. University of Michigan. Center for Connected and Automated Transportation, 2023. https://rosap.ntl.bts.gov/view/dot/73486.
Feng, Yiheng, et al. Connected and Automated Vehicle (CAV) Testing Scenario Design and Implementation Using Naturalistic Driving Data and Augmented Reality. University of Michigan. Center for Connected and Automated Transportation, 2023, Report no. UMTRI-2023-6, ROSA P. https://rosap.ntl.bts.gov/view/dot/73486.
Reliable, lane-level, absolute position determination for connected and automated vehicles (CAV’s) is near at hand due to advances in sensor and computing technology. These capabilities in conjunction with high-definition maps enable lane determination, per lane queue determination, and enhanced performance in applications. This project investigate
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Farrell, J. A., Wu, G., Hu, W., Oswald, D., & Hao, P. (2023). Lane-Level Localization and Map Matching for Advanced Connected and Automated Vehicle (CAV) Applications (Report No. NCST-UCR-RR-23-13). National Center for Sustainable Transportation (NCST) (UTC). https://doi.org/10.7922/G25T3HSS
Farrell, Jay A., Guoyuan Wu, Wang Hu, David Oswald, and Peng Hao. Lane-Level Localization and Map Matching for Advanced Connected and Automated Vehicle (CAV) Applications. Report no. NCST-UCR-RR-23-13. National Center for Sustainable Transportation (NCST) (UTC), 2023. https://doi.org/10.7922/G25T3HSS.
Farrell, Jay A., et al. Lane-Level Localization and Map Matching for Advanced Connected and Automated Vehicle (CAV) Applications. National Center for Sustainable Transportation (NCST) (UTC), 2023, Report no. NCST-UCR-RR-23-13, ROSA P. https://doi.org/10.7922/G25T3HSS.
Automated, connected, electric, and shared (ACES) technologies are rapidly evolving and will continue to impact the development of vehicles, infrastructure, communities, commerce, and the economy. Based on the Florida ACES transportation system roadmap for Florida developed in Phase I, this project aimed to engage with private industries to leverag
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Lin, P. S., Wang, Z., Li, Q., Lyu, H., Jackman, J., & Sipiora, A. M. (2023). Toward a Florida Automated, Connected, Electric, and Shared (ACES) Transportation System Roadmap: Phase II. Florida Department of Transportation. https://rosap.ntl.bts.gov/view/dot/74635
Lin, Pei-Sung, Zhenyu Wang, Qianwen Li, Huiqing Lyu, Jason Jackman, and Austin Marie Sipiora. Toward a Florida Automated, Connected, Electric, and Shared (ACES) Transportation System Roadmap: Phase II. Florida Department of Transportation, 2023. https://rosap.ntl.bts.gov/view/dot/74635.
Lin, Pei-Sung, et al. Toward a Florida Automated, Connected, Electric, and Shared (ACES) Transportation System Roadmap: Phase II. Florida Department of Transportation, 2023, ROSA P. https://rosap.ntl.bts.gov/view/dot/74635.
NEC developed a Video Analytics implementation for traffic intersections using 5G technology. This implementation included both hardware infrastructure and software applications supporting 5G communications, which allows low latency and secure communications. The Virginia Tech Transportation Institute (VTTI) worked with NEC to facilitate the usage
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Vilela, J. P. T., Mollenhauer, M. A., White, E. E., & Miller, M. (2023). Private 5G Technology and Implementation Testing (Report No. VTTI-06-006). Safety through Disruption (Safe-D) University Transportation Center (UTC). https://rosap.ntl.bts.gov/view/dot/67588
Vilela, Jean Paul Talledo, Michael A Mollenhauer, Elizabeth E White, and Marty Miller. Private 5G Technology and Implementation Testing. Report no. VTTI-06-006. Safety through Disruption (Safe-D) University Transportation Center (UTC), 2023. https://rosap.ntl.bts.gov/view/dot/67588.
Vilela, Jean Paul Talledo, et al. Private 5G Technology and Implementation Testing. Safety through Disruption (Safe-D) University Transportation Center (UTC), 2023, Report no. VTTI-06-006, ROSA P. https://rosap.ntl.bts.gov/view/dot/67588.
In this project, we developed an integrated solution for autonomous vehicle testing, in which the naturalistic driving environment (NDE) is combined with the augmented reality (AR) testing system. The integrated solution is implemented at American Center for Mobility (ACM). With the NDE, realistic virtual traffic flow can be generated in the testin
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Liu, H. (2023). Development of an Integrated Augmented Reality Testing Environment and Implementation at the American Center for Mobility (Report No. UMTRI-2023-2). University of Michigan. Center for Connected and Automated Transportation. https://doi.org/10.7302/7019
Liu, Henry. Development of an Integrated Augmented Reality Testing Environment and Implementation at the American Center for Mobility. Report no. UMTRI-2023-2. University of Michigan. Center for Connected and Automated Transportation, 2023. https://doi.org/10.7302/7019.
Liu, Henry Development of an Integrated Augmented Reality Testing Environment and Implementation at the American Center for Mobility. University of Michigan. Center for Connected and Automated Transportation, 2023, Report no. UMTRI-2023-2, ROSA P. https://doi.org/10.7302/7019.
The objective of this methodology is to refine the preliminary results from previous work (11% fuel savings for one vehicle, one intersection) to an entire corridor of SPaT signals, with different CV market penetration, and with driver awareness of fuel savings benefits. The research will proceed in three parts. First, several vehicles will be inst
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Levin, M. W., Sun, Z., Wang, S., Sun, W., He, S., Suh, B., Zhao, G., Margolis, J., & Zamanpour, M. (2023). Cost/Benefit Analysis of Fuel-Efficient Speed Control Using Signal Phasing and Timing (SPaT) Data: Evaluation for Future Connected Corridor Deployment (Report No. MN 2023-06). Minnesota. Department of Transportation. Office of Research & Innovation. https://rosap.ntl.bts.gov/view/dot/67145
Levin, Michael W., Zongxuan Sun, Shi’an Wang, Wenbo Sun, Suiyi He, Bohoon Suh, Gaonan Zhao, Jacob Margolis, and Maziar Zamanpour. Cost/Benefit Analysis of Fuel-Efficient Speed Control Using Signal Phasing and Timing (SPaT) Data: Evaluation for Future Connected Corridor Deployment. Report no. MN 2023-06. Minnesota. Department of Transportation. Office of Research & Innovation, 2023. https://rosap.ntl.bts.gov/view/dot/67145.
Levin, Michael W., et al. Cost/Benefit Analysis of Fuel-Efficient Speed Control Using Signal Phasing and Timing (SPaT) Data: Evaluation for Future Connected Corridor Deployment. Minnesota. Department of Transportation. Office of Research & Innovation, 2023, Report no. MN 2023-06, ROSA P. https://rosap.ntl.bts.gov/view/dot/67145.
The goal of this project was to explore the fuel efficiencies of SPaT broadcasts interacting with CVs to control speed along connected corridors. The findings from this investigation could then be used to inform possible future SPaT deployments.
Rowe, D., & Levin, M. W. (2023). Using Signal Phasing and Timing Data to Reduce Fuel Use [Technical Summary] (Report No. 2023-06). Minnesota. Department of Transportation. Office of Research & Innovation. https://rosap.ntl.bts.gov/view/dot/67167
Rowe, Daniel and Michael W. Levin. Using Signal Phasing and Timing Data to Reduce Fuel Use [Technical Summary]. Report no. 2023-06. Minnesota. Department of Transportation. Office of Research & Innovation, 2023. https://rosap.ntl.bts.gov/view/dot/67167.
Rowe, Daniel, and Michael W. Levin Using Signal Phasing and Timing Data to Reduce Fuel Use [Technical Summary]. Minnesota. Department of Transportation. Office of Research & Innovation, 2023, Report no. 2023-06, ROSA P. https://rosap.ntl.bts.gov/view/dot/67167.
Firstly, to guarantee stability and robustness in the face of parametric uncertainties, non-linearities, and modeling errors, we have proposed a data-driven optimal control algorithm to solve the lane-changing problem of AVs which is inspired by reinforcement learning and adaptive dynamic programming. Secondly, we have developed a lane change decis
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Jiang, Z. P., Ozbay, K., Chakraborty, S., & Cui, L. (2023). Automated Lane Change and Robust Safety. Connected Cities for Smart Mobility toward Accessible and Resilient Transportation Center (C2SMART). https://rosap.ntl.bts.gov/view/dot/67943
Jiang, Zhong-Ping, Kaan Ozbay, Sayantan Chakraborty, and Leilei Cui. Automated Lane Change and Robust Safety. Connected Cities for Smart Mobility toward Accessible and Resilient Transportation Center (C2SMART), 2023. https://rosap.ntl.bts.gov/view/dot/67943.
Jiang, Zhong-Ping, et al. Automated Lane Change and Robust Safety. Connected Cities for Smart Mobility toward Accessible and Resilient Transportation Center (C2SMART), 2023, ROSA P. https://rosap.ntl.bts.gov/view/dot/67943.
Surface transportation systems (e.g., arterial roadways with signalized intersections) are inherently inefficient, particularly at higher traffic volumes. In general, both the infrastructure (e.g., traffic signals) and the vehicles operate independently, with little coordination between them. Previous research has shown that implementing strategies
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Hao, P., Oswald, D., Wu, G., & Barth, M. J. (2023). Eco-friendly Cooperative Traffic Optimization at Signalized Intersections (Report No. NCST-UCR-RR-23-09). University of California, Riverside. Center for Environmental Research and Technology. https://rosap.ntl.bts.gov/view/dot/66750
Hao, Peng, David Oswald, Guoyuan Wu, and Matthew J. Barth. Eco-friendly Cooperative Traffic Optimization at Signalized Intersections. Report no. NCST-UCR-RR-23-09. University of California, Riverside. Center for Environmental Research and Technology, 2023. https://rosap.ntl.bts.gov/view/dot/66750.
Hao, Peng, et al. Eco-friendly Cooperative Traffic Optimization at Signalized Intersections. University of California, Riverside. Center for Environmental Research and Technology, 2023, Report no. NCST-UCR-RR-23-09, ROSA P. https://rosap.ntl.bts.gov/view/dot/66750.
Age-related macular degeneration is a leading cause of blindness worldwide and is one of many limitations to independent driving among old adults. Highly autonomous vehicles present a prospective solution for those who are no longer capable of driving due to low vision. However, accessibility issues must be addressed to create a safe and pleasant e
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Bynum, L., Parker, J., Lee, K., Nitschke, N., LaFlam, M., Marcussen, J., Taleb, J., Dogan, A., Molnar, L. J., & Zhou, F. (2023). Navigating in the Dark – Designing Autonomous Driving Features to Assist Old Adults with Visual Impairments. Association for Computing Machinery. https://doi.org/10.48550/arXiv.2302.00499
Bynum, Lashawnda, Jay Parker, Kristy Lee, Nia Nitschke, Melanie LaFlam, Jennifer Marcussen, Jana Taleb, Aleyna Dogan, Lisa J Molnar, and Feng Zhou. Navigating in the Dark – Designing Autonomous Driving Features to Assist Old Adults with Visual Impairments. Association for Computing Machinery, 2023. https://doi.org/10.48550/arXiv.2302.00499.
Bynum, Lashawnda, et al. Navigating in the Dark – Designing Autonomous Driving Features to Assist Old Adults with Visual Impairments. Association for Computing Machinery, 2023, ROSA P. https://doi.org/10.48550/arXiv.2302.00499.
The many potentially transformative changes to the transportation system, such as automated vehicles, electric vehicle adoption, increased telework, and new travel modes, are creating increasing uncertainties for the future. These uncertainties call for fast, flexible models. System dynamics (SD) is emerging as a research modeling focus area for ch
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Smith, S., Rakoff, H., Eilbert, A., Shaw, J., & Berg, I. (2023). System Dynamics Models of Automated Vehicle Impacts (Report No. FHWA-JPO-22-985;DOT-VNTSC-FHWA-23-02). United States. Department of Transportation. Intelligent Transportation Systems Joint Program Office. https://rosap.ntl.bts.gov/view/dot/66972
Smith, Scott, Hannah Rakoff, Andrew Eilbert, Jingsi Shaw, and Ian Berg. System Dynamics Models of Automated Vehicle Impacts. Report no. FHWA-JPO-22-985;DOT-VNTSC-FHWA-23-02. United States. Department of Transportation. Intelligent Transportation Systems Joint Program Office, 2023. https://rosap.ntl.bts.gov/view/dot/66972.
Smith, Scott, et al. System Dynamics Models of Automated Vehicle Impacts. United States. Department of Transportation. Intelligent Transportation Systems Joint Program Office, 2023, Report no. FHWA-JPO-22-985;DOT-VNTSC-FHWA-23-02, ROSA P. https://rosap.ntl.bts.gov/view/dot/66972.
"The Center for Transportation Research at the University of Texas-Austin recently completed a project that compared automated vehicle performance and human driving behavior in several virtual highway and urban environment scenarios. The research team then analyzed the safety, mobility, and human-factors results to draw conclusions and formulate te
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Supporting Files
Martin, D., West, K. D., Chin, K., & Ma, J. (2023). Defining Operational Design Domains for the Safe Blending of CAVs in the Traffic Stream: Project 0-7033 [Video]. University of Texas at Austin. Center for Transportation Research. https://rosap.ntl.bts.gov/view/dot/79819
Martin, David, Kelly D West, Kristie Chin, and Jianming Ma. Defining Operational Design Domains for the Safe Blending of CAVs in the Traffic Stream: Project 0-7033 [Video]. University of Texas at Austin. Center for Transportation Research, 2023. https://rosap.ntl.bts.gov/view/dot/79819.
Martin, David, et al. Defining Operational Design Domains for the Safe Blending of CAVs in the Traffic Stream: Project 0-7033 [Video]. University of Texas at Austin. Center for Transportation Research, 2023, ROSA P. https://rosap.ntl.bts.gov/view/dot/79819.
This project assesses how Texas roadway and parking infrastructure should evolve as connected and automated vehicles (CAVs) gain market share, using behavioral-diffusion insights to frame adoption scenarios. Researchers combined literature synthesis with expert questionnaires/interviews, analysis of AV disengagement reports, and PTV Vissim microsim
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Kumar, A., Dessouky, S., Sharif, H., Weissmann, J., Harinath, P. V., Bhandari, R., & Kalapurayil, H. K. M. (2023). Develop Roadway and Parking Design Criteria To Accommodate Automated and Autonomous Vehicles (Report No. FHWA/TX-23/0-7080-1). Texas Department of Transportation. Research and Technology Implementation Office. https://rosap.ntl.bts.gov/view/dot/84675
Kumar, Amit, Samer Dessouky, Hatim Sharif, Jose Weissmann, Pradeep Viyaluru Harinath, Royal Bhandari, and Hari Krishnan M Kalapurayil. Develop Roadway and Parking Design Criteria To Accommodate Automated and Autonomous Vehicles. Report no. FHWA/TX-23/0-7080-1. Texas Department of Transportation. Research and Technology Implementation Office, 2023. https://rosap.ntl.bts.gov/view/dot/84675.
Kumar, Amit, et al. Develop Roadway and Parking Design Criteria To Accommodate Automated and Autonomous Vehicles. Texas Department of Transportation. Research and Technology Implementation Office, 2023, Report no. FHWA/TX-23/0-7080-1, ROSA P. https://rosap.ntl.bts.gov/view/dot/84675.
With the expected arrival of autonomous vehicles, and the ever-increasing levels of automation in today’s human driven vehicles, road safety is changing at a rapid pace. This project aimed to address the need for an efficient and rapid method of safety evaluation and countermeasure identification via traffic encounters, specifically traffic conflic
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Tarko, A. P., Romero, M. A., Bandaru, V. K., & Shi, X. (2023). Guidelines for Evaluating Safety Using Traffic Encounters: Proactive Crash Estimation on Roadways with Conventional and Autonomous Vehicle Scenarios (Report No. FHWA/IN/JTRP-2023/02). Purdue University. Joint Transportation Research Program. https://doi.org/10.5703/1288284317587
Tarko, Andrew P., Mario A. Romero, Vamsi Krishna Bandaru, and Xueqian Shi. Guidelines for Evaluating Safety Using Traffic Encounters: Proactive Crash Estimation on Roadways with Conventional and Autonomous Vehicle Scenarios. Report no. FHWA/IN/JTRP-2023/02. Purdue University. Joint Transportation Research Program, 2023. https://doi.org/10.5703/1288284317587.
Tarko, Andrew P., et al. Guidelines for Evaluating Safety Using Traffic Encounters: Proactive Crash Estimation on Roadways with Conventional and Autonomous Vehicle Scenarios. Purdue University. Joint Transportation Research Program, 2023, Report no. FHWA/IN/JTRP-2023/02, ROSA P. https://doi.org/10.5703/1288284317587.
The development of Autonomous vehicles (AVs) has brought many opportunities but implementing AV-based public transportation services has numerous unforeseen issues. One primary research gap is that existing studies on AV transit systems consist of predictions and speculation without actual cases and data support. Another issue is that a measurement
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Peng, Z. R., Liu, Y., & Lu, K. (2023). Examining Data Needs and Implementation Process of AV-Based Microtransit Service: A Case Study in Lake Nona. Florida Department of Transportation. https://rosap.ntl.bts.gov/view/dot/74775
Peng, Zhong-Ren, Yanghe Liu, and Kaifa Lu. Examining Data Needs and Implementation Process of AV-Based Microtransit Service: A Case Study in Lake Nona. Florida Department of Transportation, 2023. https://rosap.ntl.bts.gov/view/dot/74775.
Peng, Zhong-Ren, et al. Examining Data Needs and Implementation Process of AV-Based Microtransit Service: A Case Study in Lake Nona. Florida Department of Transportation, 2023, ROSA P. https://rosap.ntl.bts.gov/view/dot/74775.
Traffic simulation is an important tool that can assist researchers, analysts, and policymakers in testing vehicle/traffic control algorithms, gaining insights into micro/macro traffic dynamics, and designing traffic management strategies. However, different implementations require different simulation scales, and no multiscale simulation platform
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Ban, J., Angah, O., Zhang, Y., & Guo, Q. (2022). A Multiscale Simulation Platform for Connected and Automated Transportation Systems. Connected Cities for Smart Mobility toward Accessible and Resilient Transportation Center (C2SMART). https://rosap.ntl.bts.gov/view/dot/67308
Ban, Jeff, Ohay Angah, Yiran Zhang, and Qiangqiang Guo. A Multiscale Simulation Platform for Connected and Automated Transportation Systems. Connected Cities for Smart Mobility toward Accessible and Resilient Transportation Center (C2SMART), 2022. https://rosap.ntl.bts.gov/view/dot/67308.
Ban, Jeff, et al. A Multiscale Simulation Platform for Connected and Automated Transportation Systems. Connected Cities for Smart Mobility toward Accessible and Resilient Transportation Center (C2SMART), 2022, ROSA P. https://rosap.ntl.bts.gov/view/dot/67308.
Shared-use mobility services such as ride sourcing, bike sharing, and carsharing have been introduced in a few rural communities and a fair number of small-urban communities. Input about the interest and potential willingness to use these services, and adoption of various emerging vehicle technologies, could help improve understanding and planning
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Godavarthy, R., & Hough, J. (2022). Interest of Shared Mobility and Emerging Vehicle Technologies in Rural America (Report No. SURTCOM 22-15). Upper Great Plains Transportation Institute. https://rosap.ntl.bts.gov/view/dot/65991
Godavarthy, Ranjit and Jill Hough. Interest of Shared Mobility and Emerging Vehicle Technologies in Rural America. Report no. SURTCOM 22-15. Upper Great Plains Transportation Institute, 2022. https://rosap.ntl.bts.gov/view/dot/65991.
Godavarthy, Ranjit, and Jill Hough Interest of Shared Mobility and Emerging Vehicle Technologies in Rural America. Upper Great Plains Transportation Institute, 2022, Report no. SURTCOM 22-15, ROSA P. https://rosap.ntl.bts.gov/view/dot/65991.
An EasyMile EZ10 low speed autonomous vehicle (LSAV) was deployed on a route between the Virginia Tech Transportation Institute campus and a nearby bus transit stop to study prospective user attitudes and acceptance regarding trust in technology, system safety, and personal security. The LSAV operated on this route within normal travel lanes and in
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Grove, K., Alden, A., & Druta, C. (2022). Automated Last Mile Connectivity for Vulnerable Road Users – Real-world Low Speed Autonomous Vehicle Deployment (Report No. CATM-2022-R8-VTTI). North Carolina A&T Sate University. Transportation Institute. Center For Advanced Transportation Mobility. https://rosap.ntl.bts.gov/view/dot/66410
Grove, Kevin, Andy Alden, and Cristian Druta. Automated Last Mile Connectivity for Vulnerable Road Users – Real-world Low Speed Autonomous Vehicle Deployment. Report no. CATM-2022-R8-VTTI. North Carolina A&T Sate University. Transportation Institute. Center For Advanced Transportation Mobility, 2022. https://rosap.ntl.bts.gov/view/dot/66410.
Grove, Kevin, et al. Automated Last Mile Connectivity for Vulnerable Road Users – Real-world Low Speed Autonomous Vehicle Deployment. North Carolina A&T Sate University. Transportation Institute. Center For Advanced Transportation Mobility, 2022, Report no. CATM-2022-R8-VTTI, ROSA P. https://rosap.ntl.bts.gov/view/dot/66410.
Autonomous vehicles have a huge potential to improve transportation systems by increasing roadway capacity, safety, accessibility and reducing pollution, congestion. This emerging technology promises safer, efficient roadways and can help reduce pollution. For the various levels of autonomy to be deployed into the real world safely and efficiently,
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Anne, V. S. R., Tenenboim, E., & Peeta, S. (2022). Using Driving Simulator Environment to Determine Interactions Between User Behavior and Infrastructure Design Under Autonomous Vehicles (Report No. CCAT Report #39). University of Michigan. Center for Connected and Automated Transportation. http://dx.doi.org/10.5703/1288284317647
Anne, Viswa Sri Rupa, Einat Tenenboim, and Srinivas Peeta. Using Driving Simulator Environment to Determine Interactions Between User Behavior and Infrastructure Design Under Autonomous Vehicles. Report no. CCAT Report #39. University of Michigan. Center for Connected and Automated Transportation, 2022. http://dx.doi.org/10.5703/1288284317647.
Anne, Viswa Sri Rupa, et al. Using Driving Simulator Environment to Determine Interactions Between User Behavior and Infrastructure Design Under Autonomous Vehicles. University of Michigan. Center for Connected and Automated Transportation, 2022, Report no. CCAT Report #39, ROSA P. http://dx.doi.org/10.5703/1288284317647.
Intersections in the urban network are potential sources of traffic flow inefficiency. Existing intersection control mostly adopts the “cross” flow pattern model, while the use of the roundabout circular flow pattern is rather sparse. Connected and autonomous vehicle (CAV) technologies can enable roundabouts to better compete with traditional inter
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Wang, C., Tenenboim, E., & Peeta, S. (2022). Adapting Land Use and Infrastructure for Automated Driving (Report No. 69A3551747105). University of Michigan. Center for Connected and Automated Transportation. http://dx.doi.org/10.5703/1288284317645
Wang, Chaojie, Einat Tenenboim, and Srinivas Peeta. Adapting Land Use and Infrastructure for Automated Driving. Report no. 69A3551747105. University of Michigan. Center for Connected and Automated Transportation, 2022. http://dx.doi.org/10.5703/1288284317645.
Wang, Chaojie, et al. Adapting Land Use and Infrastructure for Automated Driving. University of Michigan. Center for Connected and Automated Transportation, 2022, Report no. 69A3551747105, ROSA P. http://dx.doi.org/10.5703/1288284317645.
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