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.
The first part of this study addresses the use of fog-cloud architecture for a deep reinforcement learning-based control framework and presents a case study involving urban traffic dynamic rerouting. Past work has shown that dynamic rerouting can mitigate traffic congestion and can be facilitated using emerging technologies such as Deep Reinforceme
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Du, R., Ha, P. (. J., Dong, J., Chen, S., & Labi, S. (2022). Large Network Multi-Level Control for CAV and Smart Infrastructure: AI-Based Fog-Cloud Collaboration (Report No. 55). University of Michigan. Center for Connected and Automated Transportation. http://dx.doi.org/10.5703/1288284317465
Du, Runjia, Paul (Young Joun) Ha, Jiqian Dong, Sikai Chen, and Samuel Labi. Large Network Multi-Level Control for CAV and Smart Infrastructure: AI-Based Fog-Cloud Collaboration. Report no. 55. University of Michigan. Center for Connected and Automated Transportation, 2022. http://dx.doi.org/10.5703/1288284317465.
Du, Runjia, et al. Large Network Multi-Level Control for CAV and Smart Infrastructure: AI-Based Fog-Cloud Collaboration. University of Michigan. Center for Connected and Automated Transportation, 2022, Report no. 55, ROSA P. http://dx.doi.org/10.5703/1288284317465.
The rapid rise of on-demand transportation and e-commerce goods deliveries, as well as increased cycling rates and transit use, are increasing demand for curb space. This demand has resulted in competition among modes, failed goods deliveries, roadway and curbside congestion, and illegal parking. This research increases our understanding of existin
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Dataset
Chang, K., Goodchild, A., Ranjbari, A., & McCormack, E. (2022). Managing Increasing Demand for Curb Space in the City of the Future [Supporting Dataset] (Report No. 2019-M-UI-1). Pacific Northwest Transportation Consortium (PacTrans) (UTC). https://doi.org/10.7910/DVN/J9LGQ1
Chang, Kevin, Anne Goodchild, Andisheh Ranjbari, and Edward McCormack. Managing Increasing Demand for Curb Space in the City of the Future [Supporting Dataset]. Report no. 2019-M-UI-1. Pacific Northwest Transportation Consortium (PacTrans) (UTC), 2022. https://doi.org/10.7910/DVN/J9LGQ1.
Chang, Kevin, et al. Managing Increasing Demand for Curb Space in the City of the Future [Supporting Dataset]. Pacific Northwest Transportation Consortium (PacTrans) (UTC), 2022, Report no. 2019-M-UI-1, ROSA P. https://doi.org/10.7910/DVN/J9LGQ1.
Asset managers continue to prepare physical infrastructure investments needed to accommodate the emerging technologies, namely vehicle connectivity, electrification, and automation. The provision of new infrastructure and modification of existing infrastructure is expected to incur a significant amount of capital investment. Secondly, with increasi
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Mwamba, I. C. (2022). Vehicle Autonomy, Connectivity and Electric Propulsion: Consequences on Highway Expenditures, Revenues and Equity. Purdue University. https://rosap.ntl.bts.gov/view/dot/73495
Mwamba, Isaiah C. Vehicle Autonomy, Connectivity and Electric Propulsion: Consequences on Highway Expenditures, Revenues and Equity. Purdue University, 2022. https://rosap.ntl.bts.gov/view/dot/73495.
Mwamba, Isaiah C Vehicle Autonomy, Connectivity and Electric Propulsion: Consequences on Highway Expenditures, Revenues and Equity. Purdue University, 2022, ROSA P. https://rosap.ntl.bts.gov/view/dot/73495.
The primary objective of the second phase of this project is to develop and deploy a significantly enhanced version of the original toolbox, NJDOT ATSPM 2.0, along with a pilot study on the integration of adaptive signal controllers with CAV technologies. NJDOT arterial management operators can then use the ATSPM platform to generate key performanc
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Jin, P. J., Brennan, T. M. J., & Jalayer, M. (2022). Real-Time Signal Performance Measurement Phase Ⅱ: Data and Functionality Enhancement, Large Scale Deployment, Connected and Autonomous Vehicles Integration [Technical Brief] (Report No. FHWA-NJ-2022-002 May 2022). New Jersey. Department of Transportation. Bureau of Research. https://rosap.ntl.bts.gov/view/dot/63559
Jin, Peter J., Thomas M. Jr. Brennan, and Mohammad Jalayer. Real-Time Signal Performance Measurement Phase Ⅱ: Data and Functionality Enhancement, Large Scale Deployment, Connected and Autonomous Vehicles Integration [Technical Brief]. Report no. FHWA-NJ-2022-002 May 2022. New Jersey. Department of Transportation. Bureau of Research, 2022. https://rosap.ntl.bts.gov/view/dot/63559.
Jin, Peter J., et al. Real-Time Signal Performance Measurement Phase Ⅱ: Data and Functionality Enhancement, Large Scale Deployment, Connected and Autonomous Vehicles Integration [Technical Brief]. New Jersey. Department of Transportation. Bureau of Research, 2022, Report no. FHWA-NJ-2022-002 May 2022, ROSA P. https://rosap.ntl.bts.gov/view/dot/63559.
University of Florida researchers tested the automated truck-mounted attenuator (ATMA) in controlled, off-road settings and on active roadways in simulated work zones.
Agarwal, N. (2022). Florida ATMA Pilot Demonstration and Evaluation [Summary]. Florida. Department of Transportation. Research Center. https://rosap.ntl.bts.gov/view/dot/61960
Agarwal, Nithin. Florida ATMA Pilot Demonstration and Evaluation [Summary]. Florida. Department of Transportation. Research Center, 2022. https://rosap.ntl.bts.gov/view/dot/61960.
Agarwal, Nithin Florida ATMA Pilot Demonstration and Evaluation [Summary]. Florida. Department of Transportation. Research Center, 2022, ROSA P. https://rosap.ntl.bts.gov/view/dot/61960.
Volume II provides supplementary material for Volume I. The content includes: the operational manual for ATSPM (Automated Traffic Signal Performance Measures) metadata processing and archiving program, training modules and field test data for CV (Connected Vehicle) OBU (On-Board Unit) and RSU (Roadside Unit), and details of the meeting discussion a
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Jin, P. J., Zhang, T., Brennan, T. M., & Jalayer, M. (2022). Real-Time Traffic Signal System Performance Measurement Phase II: Data and Functionality Enhancement, Large Scale Deployment, Connected and Autonomous Vehicles Integration Final Report Volume II (Report No. FHWA-NJ-2022-002). New Jersey. Department of Transportation. Bureau of Research. https://rosap.ntl.bts.gov/view/dot/63560
Jin, Peter J., Tianya Zhang, Thomas M. Brennan, and Mohammad Jalayer. Real-Time Traffic Signal System Performance Measurement Phase II: Data and Functionality Enhancement, Large Scale Deployment, Connected and Autonomous Vehicles Integration Final Report Volume II. Report no. FHWA-NJ-2022-002. New Jersey. Department of Transportation. Bureau of Research, 2022. https://rosap.ntl.bts.gov/view/dot/63560.
Jin, Peter J., et al. Real-Time Traffic Signal System Performance Measurement Phase II: Data and Functionality Enhancement, Large Scale Deployment, Connected and Autonomous Vehicles Integration Final Report Volume II. New Jersey. Department of Transportation. Bureau of Research, 2022, Report no. FHWA-NJ-2022-002, ROSA P. https://rosap.ntl.bts.gov/view/dot/63560.
Connected vehicle technologies have a promising role in advancing vehicle safety, but just how much of an impact can connected vehicles have on driver safety? This study uses crash and near-crash events from the Second Strategic Highway Research Program Naturalistic Driving Study (SHRP2 NDS) to reconstruct crash events so that the benefit of line-o
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Herbers, E., & Stowe, L. (2022). Impacts of Connected Vehicle Technology on Automated Vehicle Safety (Report No. 04-120). Safety through Disruption (Safe-D) University Transportation Center (UTC). https://rosap.ntl.bts.gov/view/dot/62818
Herbers, Eileen and Loren Stowe. Impacts of Connected Vehicle Technology on Automated Vehicle Safety. Report no. 04-120. Safety through Disruption (Safe-D) University Transportation Center (UTC), 2022. https://rosap.ntl.bts.gov/view/dot/62818.
Herbers, Eileen, and Loren Stowe Impacts of Connected Vehicle Technology on Automated Vehicle Safety. Safety through Disruption (Safe-D) University Transportation Center (UTC), 2022, Report no. 04-120, ROSA P. https://rosap.ntl.bts.gov/view/dot/62818.
The primary objective of the second phase of this project is to develop and deploy a significantly enhanced version of the original toolbox, NJDOT ATSPM 2.0, along with a pilot study on the integration of adaptive signal controllers with CAV technologies. NJDOT arterial management operators can then use the ATSPM platform to generate key performanc
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Jin, P. J., Brennan Jr., T. M., & Jalayer, M. (2022). Real-Time Signal Performance Measurement Phase Ⅱ: Data and Functionality Enhancement, Large Scale Deployment, Connected and Autonomous Vehicles Integration [Technical Brief] (Report No. FHWA-NJ-2022-002). New Jersey. Department of Transportation. Bureau of Research. https://rosap.ntl.bts.gov/view/dot/67013
Jin, Peter J., Thomas M. Brennan Jr., and Mohammad Jalayer. Real-Time Signal Performance Measurement Phase Ⅱ: Data and Functionality Enhancement, Large Scale Deployment, Connected and Autonomous Vehicles Integration [Technical Brief]. Report no. FHWA-NJ-2022-002. New Jersey. Department of Transportation. Bureau of Research, 2022. https://rosap.ntl.bts.gov/view/dot/67013.
Jin, Peter J., et al. Real-Time Signal Performance Measurement Phase Ⅱ: Data and Functionality Enhancement, Large Scale Deployment, Connected and Autonomous Vehicles Integration [Technical Brief]. New Jersey. Department of Transportation. Bureau of Research, 2022, Report no. FHWA-NJ-2022-002, ROSA P. https://rosap.ntl.bts.gov/view/dot/67013.
Rapid growth in information and communication technologies has spawned a number of major innovations in transportation area, including automation and connectivity. At the same time, the advancement in battery technology has accelerated the electrification of transportation vehicle propulsion. This paper, focusing on highway-oriented surface transpo
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Labi, S., & Sinha, K. C. (2022). Emerging Transportation Innovations: Promises and Pitfalls (Report No. 69A3551747105). World Scientific Publishing Co. https://doi.org/10.1142/S2737599422400011
Labi, Samuel and Kumares C. Sinha. Emerging Transportation Innovations: Promises and Pitfalls. Report no. 69A3551747105. World Scientific Publishing Co, 2022. https://doi.org/10.1142/S2737599422400011.
Labi, Samuel, and Kumares C. Sinha Emerging Transportation Innovations: Promises and Pitfalls. World Scientific Publishing Co, 2022, Report no. 69A3551747105, ROSA P. https://doi.org/10.1142/S2737599422400011.
Autonomous vehicles (AVs) have generated great excitement for the future of transportation. The promise of self-driving vehicles offers a valuable transportation option to those who do not drive, own a car, or are exploring how to get around their community without driving. For older adults, AVs might provide a vital link to shopping, entertainment
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Classen, S. (2022). Develop, Refine, and Validate a Survey to Assess Adult’s Perspectives of Autonomous Ride-Sharing Services [Summary]. Florida. Department of Transportation. Research Center. https://rosap.ntl.bts.gov/view/dot/61850
Classen, Sherrilene. Develop, Refine, and Validate a Survey to Assess Adult’s Perspectives of Autonomous Ride-Sharing Services [Summary]. Florida. Department of Transportation. Research Center, 2022. https://rosap.ntl.bts.gov/view/dot/61850.
Classen, Sherrilene Develop, Refine, and Validate a Survey to Assess Adult’s Perspectives of Autonomous Ride-Sharing Services [Summary]. Florida. Department of Transportation. Research Center, 2022, ROSA P. https://rosap.ntl.bts.gov/view/dot/61850.
The research objective was to develop and demonstrate tools that can serve as the foundation of coordinated ACES activities in Florida. The researchers also conducted outreach events with stakeholders to introduce and encourage use of the tools.
Lin, P. S. (2022). Toward a Florida Automated, Connected, Electric and Shared (ACES) Transportation System Roadmap: Phase I [Summary]. Florida. Department of Transportation. Research Center. https://rosap.ntl.bts.gov/view/dot/61932
Lin, Pei-Sung. Toward a Florida Automated, Connected, Electric and Shared (ACES) Transportation System Roadmap: Phase I [Summary]. Florida. Department of Transportation. Research Center, 2022. https://rosap.ntl.bts.gov/view/dot/61932.
Lin, Pei-Sung Toward a Florida Automated, Connected, Electric and Shared (ACES) Transportation System Roadmap: Phase I [Summary]. Florida. Department of Transportation. Research Center, 2022, ROSA P. https://rosap.ntl.bts.gov/view/dot/61932.
Sponsored by the Tennessee Department of Transportation, this project aims to assist the State of Tennessee prepare for future intelligent mobility strategies that encompass connected and automated vehicles, electric vehicles, multimodal personal and freight movements, all done in a safe, secure, and equitable way. The project has developed a serie
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Khattak, A., Mahdinia, I., & Sartipi, M. (2022). Connected and Automated Vehicles Investment and Smart Infrastructure in Tennessee (Report No. RES2019-07). Tennessee. Department of Transportation. https://rosap.ntl.bts.gov/view/dot/62693
Khattak, Asad, Iman Mahdinia, and Mina Sartipi. Connected and Automated Vehicles Investment and Smart Infrastructure in Tennessee. Report no. RES2019-07. Tennessee. Department of Transportation, 2022. https://rosap.ntl.bts.gov/view/dot/62693.
Khattak, Asad, et al. Connected and Automated Vehicles Investment and Smart Infrastructure in Tennessee. Tennessee. Department of Transportation, 2022, Report no. RES2019-07, ROSA P. https://rosap.ntl.bts.gov/view/dot/62693.
Transportation innovations captured through intelligent mobility strategies are critical to achieving economic development, safety, mobility, energy, environmental, and equity goals. Intelligent mobility is broadly defined to encompass connected and automated vehicles, electric vehicles, and multi-modal personal and freight movements, all done safe
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Khattak, A., Mahdinia, I., Taherkhani, M. S., & Lee, S. (2022). Connected and Automated Vehicles Investment and Smart Infrastructure in Tennessee - Part 5: A Comprehensive View of Intelligent Mobility in Tennessee (Report No. RES2019-07). Tennessee. Department of Transportation. https://rosap.ntl.bts.gov/view/dot/73417
Khattak, Asad, Iman Mahdinia, Mohammad Safari Taherkhani, and Steve Lee. Connected and Automated Vehicles Investment and Smart Infrastructure in Tennessee - Part 5: A Comprehensive View of Intelligent Mobility in Tennessee. Report no. RES2019-07. Tennessee. Department of Transportation, 2022. https://rosap.ntl.bts.gov/view/dot/73417.
Khattak, Asad, et al. Connected and Automated Vehicles Investment and Smart Infrastructure in Tennessee - Part 5: A Comprehensive View of Intelligent Mobility in Tennessee. Tennessee. Department of Transportation, 2022, Report no. RES2019-07, ROSA P. https://rosap.ntl.bts.gov/view/dot/73417.
Traffic signal performance measurement and visualization provide insights as operational tools to help traffic management centers (TMC) get more paybacks from infrastructure investment. However, evaluating and monitoring signal performance is challenging in real-time, which requires immediate data collection and analysis capability. As part of the
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Jin, P. J., Zhang, T., Brennan, T. M., Jalayer, M., Wang, Y., Ge, Y., Chen, A., & Patel, D. (2022). Real-Time Traffic Signal System Performance Measurement Phase II: Data and Functionality Enhancement, Large Scale Deployment, Connected and Autonomous Vehicles Integration (Report No. FHWA-NJ-2022-002). New Jersey. Department of Transportation. Bureau of Research. https://rosap.ntl.bts.gov/view/dot/63555
Jin, Peter J., Tianya Zhang, Thomas M. Brennan, Mohammad Jalayer, Yizhou Wang, Yi Ge, Anjiang Chen, and Deep Patel. Real-Time Traffic Signal System Performance Measurement Phase II: Data and Functionality Enhancement, Large Scale Deployment, Connected and Autonomous Vehicles Integration. Report no. FHWA-NJ-2022-002. New Jersey. Department of Transportation. Bureau of Research, 2022. https://rosap.ntl.bts.gov/view/dot/63555.
Jin, Peter J., et al. Real-Time Traffic Signal System Performance Measurement Phase II: Data and Functionality Enhancement, Large Scale Deployment, Connected and Autonomous Vehicles Integration. New Jersey. Department of Transportation. Bureau of Research, 2022, Report no. FHWA-NJ-2022-002, ROSA P. https://rosap.ntl.bts.gov/view/dot/63555.
The recent progress in autonomous vehicle research and development has led to increasingly widespread testing of fully autonomous vehicles on public roads, where complex traffic scenarios arise. Along with these vehicles, partially autonomous vehicles, manually-driven vehicles, pedestrians, cyclists, and some animals can be present on the road, to
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Ghorai, P., Eskandarian, A., Kim, Y. K., & Meh, G. (2022). State Estimation and Motion Prediction of Vehicles and Vulnerable Road Users for Cooperative Autonomous Driving: A Survey. United States. Department of Transportation. National Transportation Library [distributor]. https://rosap.ntl.bts.gov/view/dot/62533
Ghorai, Prasenjit, Azim Eskandarian, Young-Keun Kim, and Goodarz Meh. State Estimation and Motion Prediction of Vehicles and Vulnerable Road Users for Cooperative Autonomous Driving: A Survey. United States. Department of Transportation. National Transportation Library [distributor], 2022. https://rosap.ntl.bts.gov/view/dot/62533.
Ghorai, Prasenjit, et al. State Estimation and Motion Prediction of Vehicles and Vulnerable Road Users for Cooperative Autonomous Driving: A Survey. United States. Department of Transportation. National Transportation Library [distributor], 2022, ROSA P. https://rosap.ntl.bts.gov/view/dot/62533.
The rapid rise of on-demand transportation and e-commerce goods deliveries, as well as increased cycling rates and transit use, are increasing demand for curb space. This demand has resulted in competition among modes, failed goods deliveries, roadway and curbside congestion, and illegal parking. This research increases our understanding of existin
...
Chang, K., Goodchild, A., Ranjbari, A., & McCormack, E. (2022). Managing Increasing Demand for Curb Space in the City of the Future (Report No. 2019-M-UI-1). Pacific Northwest Transportation Consortium (PacTrans) (UTC). https://rosap.ntl.bts.gov/view/dot/62950
Chang, Kevin, Anne Goodchild, Andisheh Ranjbari, and Edward McCormack. Managing Increasing Demand for Curb Space in the City of the Future. Report no. 2019-M-UI-1. Pacific Northwest Transportation Consortium (PacTrans) (UTC), 2022. https://rosap.ntl.bts.gov/view/dot/62950.
Chang, Kevin, et al. Managing Increasing Demand for Curb Space in the City of the Future. Pacific Northwest Transportation Consortium (PacTrans) (UTC), 2022, Report no. 2019-M-UI-1, ROSA P. https://rosap.ntl.bts.gov/view/dot/62950.
Researchers at the University of California, Davis investigated the range of potential impacts that rapid adoption of CAVs in California might have on vehicle miles traveled and emissions. The researchers estimated the vehicle miles traveled and emissions of each scenario using a statewide travel demand model, emissions factors from California agen
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Circella, G., Jaller, M., Sun, R., Qian, X., & Alemi, F. (2022). Future Connected and Automated Vehicle Adoption Will Likely Increase Car Dependence and Reduce Transit Use without Policy Intervention [Policy Brief]. National Center for Sustainable Transportation (NCST) (UTC). https://doi.org/10.7922/G2BZ64CX
Circella, Giovanni, Miguel Jaller, Ran Sun, Xiaodong Qian, and Farzad Alemi. Future Connected and Automated Vehicle Adoption Will Likely Increase Car Dependence and Reduce Transit Use without Policy Intervention [Policy Brief]. National Center for Sustainable Transportation (NCST) (UTC), 2022. https://doi.org/10.7922/G2BZ64CX.
Circella, Giovanni, et al. Future Connected and Automated Vehicle Adoption Will Likely Increase Car Dependence and Reduce Transit Use without Policy Intervention [Policy Brief]. National Center for Sustainable Transportation (NCST) (UTC), 2022, ROSA P. https://doi.org/10.7922/G2BZ64CX.
Poster from 2022 Global Symposium on Connected and Automated Vehicles and Infrastructure, April 14, 2022, Ann Arbor, Michigan.
Zhang, Y., & Fricker, J. D. (2022). Making Crosswalks Smarter: Using Sensors and Learning Algorithms to Safeguard Heterogenous Road Users. Center for Connected and Automated Transportation. Purdue University. https://rosap.ntl.bts.gov/view/dot/72954
Zhang, Yunchang and Jon D. Fricker. Making Crosswalks Smarter: Using Sensors and Learning Algorithms to Safeguard Heterogenous Road Users. Center for Connected and Automated Transportation. Purdue University, 2022. https://rosap.ntl.bts.gov/view/dot/72954.
Zhang, Yunchang, and Jon D. Fricker Making Crosswalks Smarter: Using Sensors and Learning Algorithms to Safeguard Heterogenous Road Users. Center for Connected and Automated Transportation. Purdue University, 2022, ROSA P. https://rosap.ntl.bts.gov/view/dot/72954.
The Little Roady Autonomous Vehicle (AV) shuttle pilot was coordinated by the Rhode Island Department of Transportation and consisted of a free daily shuttle service operated from May 2019 through June 2020 along a twelve-stop, 5.3-mile loop along the Woonasquatucket Corridor in Rhode Island. Key goals of the Little Roady project were to safely int
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Marini, M., Simpson, T., Jain, P., Larrick, S., Liao, L., Townsend, A., De La Cruz, M., Armstrong, B., Fisher, K., & Xenophontos, C. (2022). A Rhode Trip: Lessons for the Future of Mobility From the Little Roady Autonomous Microtransit Pilot (Report No. RIDOT-RTD-SPR-235-2279). Rhode Island. Department of Transportation. https://rosap.ntl.bts.gov/view/dot/64116
Marini, Megan, Troy Simpson, Priyanka Jain, Stephen Larrick, Lorraine Liao, Anthony Townsend, Melissa De La Cruz, Ben Armstrong, Kate Fisher, and Christos Xenophontos. A Rhode Trip: Lessons for the Future of Mobility From the Little Roady Autonomous Microtransit Pilot. Report no. RIDOT-RTD-SPR-235-2279. Rhode Island. Department of Transportation, 2022. https://rosap.ntl.bts.gov/view/dot/64116.
Marini, Megan, et al. A Rhode Trip: Lessons for the Future of Mobility From the Little Roady Autonomous Microtransit Pilot. Rhode Island. Department of Transportation, 2022, Report no. RIDOT-RTD-SPR-235-2279, ROSA P. https://rosap.ntl.bts.gov/view/dot/64116.
Passenger and heavy-duty vehicles make up 36% of California’s greenhouse gas (GHG) emissions. Reducing emissions from vehicular travel is therefore paramount for any path towards carbon neutrality. Efforts to reduce GHGs by encouraging mode shift or increasing vehicle efficiency are, and will continue to be, a critical part of decarbonizing the tra
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Almatrudi, S., Parvate, K., Rothchild, D., & Vijay, U. (2022). Using Automated Vehicle (AV) Technology to Smooth Traffic Flow and Reduce Greenhouse Gas Emissions (Report No. UC-ITS-2021-26). University of California, Berkeley. Institute of Transportation Studies. http://doi.org/10.7922/G2JS9NRB
Almatrudi, Sulaiman, Kanaad Parvate, Daniel Rothchild, and Upadhi Vijay. Using Automated Vehicle (AV) Technology to Smooth Traffic Flow and Reduce Greenhouse Gas Emissions. Report no. UC-ITS-2021-26. University of California, Berkeley. Institute of Transportation Studies, 2022. http://doi.org/10.7922/G2JS9NRB.
Almatrudi, Sulaiman, et al. Using Automated Vehicle (AV) Technology to Smooth Traffic Flow and Reduce Greenhouse Gas Emissions. University of California, Berkeley. Institute of Transportation Studies, 2022, Report no. UC-ITS-2021-26, ROSA P. http://doi.org/10.7922/G2JS9NRB.
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