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.
In this report, the authors model the system of a platoon mixed with multiple connected human-driven vehicles (HDVs) and a connected and autonomous vehicle (CAV) as a set of differential difference equations (DDEs), by taking into account drivers’ heterogeneous feedback gains and reaction delays as well as the actuator (engine) delay. Then, the aut
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Jiang, Z. P., Ozbay, K., & Cui, L. (2020). Learning To Drive Autonomously. Connected Cities for Smart Mobility toward Accessible and Resilient Transportation Center (C2SMART). https://rosap.ntl.bts.gov/view/dot/59903
Jiang, Zhong-Ping, Kaan Ozbay, and Leilei Cui. Learning To Drive Autonomously. Connected Cities for Smart Mobility toward Accessible and Resilient Transportation Center (C2SMART), 2020. https://rosap.ntl.bts.gov/view/dot/59903.
Jiang, Zhong-Ping, et al. Learning To Drive Autonomously. Connected Cities for Smart Mobility toward Accessible and Resilient Transportation Center (C2SMART), 2020, ROSA P. https://rosap.ntl.bts.gov/view/dot/59903.
Individuals with autism represent a sizeable share of the U.S. population (almost 2%), and nearly half of those with autism have average to high levels of intelligence. However, available research shows that adults with autism have a much more difficult time becoming employed and living independently compared to both typically developing adults and
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Rodier, C. (2020). The Potential for Autonomous Vehicle Technologies To Address Barriers to Driving for Individuals With Autism (Report No. 20-01). Mineta Transportation Institute. https://rosap.ntl.bts.gov/view/dot/62045
Rodier, Caroline. The Potential for Autonomous Vehicle Technologies To Address Barriers to Driving for Individuals With Autism. Report no. 20-01. Mineta Transportation Institute, 2020. https://rosap.ntl.bts.gov/view/dot/62045.
Rodier, Caroline The Potential for Autonomous Vehicle Technologies To Address Barriers to Driving for Individuals With Autism. Mineta Transportation Institute, 2020, Report no. 20-01, ROSA P. https://rosap.ntl.bts.gov/view/dot/62045.
Emerging transportation technologies including electric and autonomous vehicles and emerging mobility services such as ride-hailing and vehicle sharing are bringing about transformative changes in the transportation landscape. With the emergence of new transportation technologies and services, it is critical that transportation forecasting models b
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Khoeini, S., Pendyala, R. M., da Silva, D. C., Batur, I., Magassy, T. B., & Sharda, S. (2020). Attitudes Towards Emerging Mobility Options and Technologies – Phase 3: Survey Data Compilation, and Analysis. Center for Teaching Old Models New Tricks (TOMNET). https://rosap.ntl.bts.gov/view/dot/65848
Khoeini, Sara, Ram M. Pendyala, Denise Capasso da Silva, Irfan Batur, Tassio B Magassy, and Shivam Sharda. Attitudes Towards Emerging Mobility Options and Technologies – Phase 3: Survey Data Compilation, and Analysis. Center for Teaching Old Models New Tricks (TOMNET), 2020. https://rosap.ntl.bts.gov/view/dot/65848.
Khoeini, Sara, et al. Attitudes Towards Emerging Mobility Options and Technologies – Phase 3: Survey Data Compilation, and Analysis. Center for Teaching Old Models New Tricks (TOMNET), 2020, ROSA P. https://rosap.ntl.bts.gov/view/dot/65848.
The objective of this research was to provide the Tennessee Department of Transportation (TDOT) an evaluation on the performance of an autonomous truck mounted attenuator (ATMA) system(s), based on previous relevant research projects and on actual testing of the equipment during a demonstration pilot. A set of testing scenarios were developed in cl
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Kohls, A. G. (2020). Autonomous Truck Mounted Attenuator (ATMA) Pilot (Report No. RES 2019-15). Tennessee. Department of Transportation. https://rosap.ntl.bts.gov/view/dot/56277
Kohls, Airton G. Autonomous Truck Mounted Attenuator (ATMA) Pilot. Report no. RES 2019-15. Tennessee. Department of Transportation, 2020. https://rosap.ntl.bts.gov/view/dot/56277.
Kohls, Airton G Autonomous Truck Mounted Attenuator (ATMA) Pilot. Tennessee. Department of Transportation, 2020, Report no. RES 2019-15, ROSA P. https://rosap.ntl.bts.gov/view/dot/56277.
Over the next several decades, highly automated driving systems (HADS) will become increasingly common on our roads, greatly reducing traffic accidents and road congestion. However, for the foreseeable future, the human driver will be required to take control when automation fails. Therefore, it is critical to understand how take-overs from HADS af
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Miles, J., & Strybel, T. (2020). Evaluation of Autonomous Vehicles and Smart Technologies for Their Impact on Traffic Safety and Traffic Congestion (Report No. PSR-17-11). California. Dept. of Transportation. Division of Research and Innovation. https://rosap.ntl.bts.gov/view/dot/54429
Miles, James and Thomas Strybel. Evaluation of Autonomous Vehicles and Smart Technologies for Their Impact on Traffic Safety and Traffic Congestion. Report no. PSR-17-11. California. Dept. of Transportation. Division of Research and Innovation, 2020. https://rosap.ntl.bts.gov/view/dot/54429.
Miles, James, and Thomas Strybel Evaluation of Autonomous Vehicles and Smart Technologies for Their Impact on Traffic Safety and Traffic Congestion. California. Dept. of Transportation. Division of Research and Innovation, 2020, Report no. PSR-17-11, ROSA P. https://rosap.ntl.bts.gov/view/dot/54429.
Our research generated demographic, survey, and behavior data related to driver performance on a simulated highway environment. Data was collected from 36 individuals, that were predominantly undergraduate and graduate students at California State University Long Beach. All identifying information has been removed from the data. Specifically, data
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DatasetSupporting Files
Miles, J., & Strybel, T. (2020). Replication Data for: Evaluation of Autonomous Vehicles and Smart Technologies for Their Impact on Traffic Safety and Traffic Congestion [supporting datasets] (Report No. PSR-17-11). California. Dept. of Transportation. Division of Research and Innovation. https://doi.org/10.7910/DVN/BWCCET
Miles, James and Thomas Strybel. Replication Data for: Evaluation of Autonomous Vehicles and Smart Technologies for Their Impact on Traffic Safety and Traffic Congestion [supporting datasets]. Report no. PSR-17-11. California. Dept. of Transportation. Division of Research and Innovation, 2020. https://doi.org/10.7910/DVN/BWCCET.
Miles, James, and Thomas Strybel Replication Data for: Evaluation of Autonomous Vehicles and Smart Technologies for Their Impact on Traffic Safety and Traffic Congestion [supporting datasets]. California. Dept. of Transportation. Division of Research and Innovation, 2020, Report no. PSR-17-11, ROSA P. https://doi.org/10.7910/DVN/BWCCET.
This report recaps Our New Mobility Future, a thought leadership speaker series held from May to September 2019 at the U.S. DOT Volpe Center in Kendall Square, Cambridge, MA. The series convened distinguished experts in transportation entrepreneurialism, design, policy, anddata science who are transforming novel transportation modes to explore the
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McGovern, S., & Bell, E. (2020). Our New Mobility Future: A U.S. DOT Volpe Center Thought Leadership Series (Report No. DOT-VNTSC-20-01). John A. Volpe National Transportation Systems Center (U.S.). https://rosap.ntl.bts.gov/view/dot/43616
McGovern, Seamus and Ellen Bell. Our New Mobility Future: A U.S. DOT Volpe Center Thought Leadership Series. Report no. DOT-VNTSC-20-01. John A. Volpe National Transportation Systems Center (U.S.), 2020. https://rosap.ntl.bts.gov/view/dot/43616.
McGovern, Seamus, and Ellen Bell Our New Mobility Future: A U.S. DOT Volpe Center Thought Leadership Series. John A. Volpe National Transportation Systems Center (U.S.), 2020, Report no. DOT-VNTSC-20-01, ROSA P. https://rosap.ntl.bts.gov/view/dot/43616.
The objective of the Work Zone Data Exchange (WZDx) Specification is to enable infrastructure owners and operators (IOOs) to make harmonized work zone data available for third party use. The project aims to get data on work zones into vehicles to help automated driving systems (ADS) and human drivers navigate more safely. The main objectives of the
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Rebello, K., Acosta, D., Gold, A., Ricciardi, E., & Spurlock, A. (2020). Work Zone Data Exchange Workshop – Summary Report (Report No. FHWA-JPO-20-782). United States. Department of Transportation. Intelligent Transportation Systems Joint Program Office. https://rosap.ntl.bts.gov/view/dot/49616
Rebello, Katarina, Dani Acosta, Ariel Gold, Eric Ricciardi, and Ashley Spurlock. Work Zone Data Exchange Workshop – Summary Report. Report no. FHWA-JPO-20-782. United States. Department of Transportation. Intelligent Transportation Systems Joint Program Office, 2020. https://rosap.ntl.bts.gov/view/dot/49616.
Rebello, Katarina, et al. Work Zone Data Exchange Workshop – Summary Report. United States. Department of Transportation. Intelligent Transportation Systems Joint Program Office, 2020, Report no. FHWA-JPO-20-782, ROSA P. https://rosap.ntl.bts.gov/view/dot/49616.
This report discusses the foundation of innovative decentralized mobility services for individuals with physical or cognitive disabilities using disability-friendly autonomous electric mobility on-demand (AEMoD) services. By leveraging both the Internet-of-things (IoT) and its associated fog control capabilities, this framework will enable real-tim
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Belakaria, S., Ammous, M., Sorour, S., & Abdel-Rahim, A. (2020). Decentralized Autonomous Electric Mobility-on-Demand Services for Individuals With Physical and Cognitive Disabilities (Report No. 2017-S-UI-3). Pacific Northwest Transportation Consortium (PacTrans) (UTC). https://rosap.ntl.bts.gov/view/dot/54016
Belakaria, Syrine, Mustafa Ammous, Sameh Sorour, and Ahmed Abdel-Rahim. Decentralized Autonomous Electric Mobility-on-Demand Services for Individuals With Physical and Cognitive Disabilities. Report no. 2017-S-UI-3. Pacific Northwest Transportation Consortium (PacTrans) (UTC), 2020. https://rosap.ntl.bts.gov/view/dot/54016.
Belakaria, Syrine, et al. Decentralized Autonomous Electric Mobility-on-Demand Services for Individuals With Physical and Cognitive Disabilities. Pacific Northwest Transportation Consortium (PacTrans) (UTC), 2020, Report no. 2017-S-UI-3, ROSA P. https://rosap.ntl.bts.gov/view/dot/54016.
Autonomous vehicles (AVs) are a near future reality and the implications of AVs on city development and urban form, while potentially widespread and dramatic, are not well understood. In addition, there are other fundamentally disruptive technological forces undergoing simultaneous rapid development and deployment, including the introduction of new
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Howell, A., Tan, H., Brown, A., Schlossberg, M., Karlin-Resnick, J., Lewis, R., Anderson, M., Larco, N., Tierney, G., Carlton, I., Kim, J., & Steckler, B. (2020). Multilevel Impacts of Emerging Technologies on City Form and Development. University of Oregon, Urbanism Next Center. https://rosap.ntl.bts.gov/view/dot/60638
Howell, Amanda, Huijun Tan, Anne Brown, Marc Schlossberg, Josh Karlin-Resnick, Rebecca Lewis, and Marco Anderson, et al.. Multilevel Impacts of Emerging Technologies on City Form and Development. University of Oregon, Urbanism Next Center, 2020. https://rosap.ntl.bts.gov/view/dot/60638.
Howell, Amanda, et al. Multilevel Impacts of Emerging Technologies on City Form and Development. University of Oregon, Urbanism Next Center, 2020, ROSA P. https://rosap.ntl.bts.gov/view/dot/60638.
The Eco-Approach and Departure (EAD) application has been proved to be environmentally efficient for a Connected and Automated Vehicles (CAVs) system. In the real-world traffic, traffic conditions and signal timings are usually dynamic and uncertain due to mixed vehicle types, various driving behaviors and limited sensing range, which is challengin
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Hao, P., Wei, Z., Bai, Z., & Barth, M. J. (2020). Developing an Adaptive Strategy for Connected Eco-Driving Under Uncertain Traffic and Signal Conditions (Report No. NCST-UCR-RR-20-03). National Center for Sustainable Transportation (NCST) (UTC). https://doi.org/10.7922/G2F18WZ1
Hao, Peng, Zhensong Wei, Zhengwei Bai, and Matthew J. Barth. Developing an Adaptive Strategy for Connected Eco-Driving Under Uncertain Traffic and Signal Conditions. Report no. NCST-UCR-RR-20-03. National Center for Sustainable Transportation (NCST) (UTC), 2020. https://doi.org/10.7922/G2F18WZ1.
Hao, Peng, et al. Developing an Adaptive Strategy for Connected Eco-Driving Under Uncertain Traffic and Signal Conditions. National Center for Sustainable Transportation (NCST) (UTC), 2020, Report no. NCST-UCR-RR-20-03, ROSA P. https://doi.org/10.7922/G2F18WZ1.
It is predicted that half of the vehicles sold and 40% of vehicle travels could be autonomous in the 2040s (Litman 2017). However, how the presence of connected and autonomous vehicles (CAV) impacts highway capacity and network system performance remains unclear. Without this knowledge, it is hard to understand and quantify the implication of the d
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Soleimaniamiri, S., Shi, X., Li, X. (., & Hu, Y. (2020). Incorporating Mixed Automated Vehicle Traffic in Capacity Analysis and System Planning Decisions. Center for Transportation, Equity, Decisions and Dollars (CTEDD) (UTC). https://rosap.ntl.bts.gov/view/dot/54431
Soleimaniamiri, Saeid, Xiaowei Shi, Xiaopeng (Shaw) Li, and Yujie Hu. Incorporating Mixed Automated Vehicle Traffic in Capacity Analysis and System Planning Decisions. Center for Transportation, Equity, Decisions and Dollars (CTEDD) (UTC), 2020. https://rosap.ntl.bts.gov/view/dot/54431.
Soleimaniamiri, Saeid, et al. Incorporating Mixed Automated Vehicle Traffic in Capacity Analysis and System Planning Decisions. Center for Transportation, Equity, Decisions and Dollars (CTEDD) (UTC), 2020, ROSA P. https://rosap.ntl.bts.gov/view/dot/54431.
Winter maintenance of major transportation corridors in northern states presents a persistent challenge, necessitating substantial investment by Departments of Transportation (DOTs). Inefficient snow removal operations contribute to safety hazards, reduced road capacity, and economic losses, particularly for freight transportation. This study devel
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Zhang, Y., Khani, A., & Hourdos, J. (2020). Optimization of Winter Maintenance Stations for Safe and Efficient Freight Transportation (Report No. FMRI-Y2R5- 18). Freight Mobility Research Institute. Florida Atlantic University. https://rosap.ntl.bts.gov/view/dot/79809
Zhang, Yufeng, Alireza Khani, and John Hourdos. Optimization of Winter Maintenance Stations for Safe and Efficient Freight Transportation. Report no. FMRI-Y2R5- 18. Freight Mobility Research Institute. Florida Atlantic University, 2020. https://rosap.ntl.bts.gov/view/dot/79809.
Zhang, Yufeng, et al. Optimization of Winter Maintenance Stations for Safe and Efficient Freight Transportation. Freight Mobility Research Institute. Florida Atlantic University, 2020, Report no. FMRI-Y2R5- 18, ROSA P. https://rosap.ntl.bts.gov/view/dot/79809.
Considering the rapid boom in information technology and people’s increasing dependence on mobile data, automotive manufacturers have started equipping vehicles with wireless communication capabilities, manufacturing what are commonly known as connected vehicles, and autonomous systems to assist drivers with certain driving tasks. These technologic
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Jeihani, M., Banerjee, S., Kabir, M. M., & Khadem, N. (2020). Driver's Interactions with Advanced Vehicles in Various Traffic Mixes and Flows (Connected and Autonomous Vehicles (CAVs), Electric Vehicles (EVs), V2X, Trucks, Bicycles and Pedestrians) - Phase I: Driver Behavior Study and Parameters Estimation. Urban Mobility & Equity Center. https://rosap.ntl.bts.gov/view/dot/54708
Jeihani, Mansoureh, Snehanshu Banerjee, Md Muhib Kabir, and Nashid Khadem. Driver's Interactions with Advanced Vehicles in Various Traffic Mixes and Flows (Connected and Autonomous Vehicles (CAVs), Electric Vehicles (EVs), V2X, Trucks, Bicycles and Pedestrians) - Phase I: Driver Behavior Study and Parameters Estimation. Urban Mobility & Equity Center, 2020. https://rosap.ntl.bts.gov/view/dot/54708.
Jeihani, Mansoureh, et al. Driver's Interactions with Advanced Vehicles in Various Traffic Mixes and Flows (Connected and Autonomous Vehicles (CAVs), Electric Vehicles (EVs), V2X, Trucks, Bicycles and Pedestrians) - Phase I: Driver Behavior Study and Parameters Estimation. Urban Mobility & Equity Center, 2020, ROSA P. https://rosap.ntl.bts.gov/view/dot/54708.
Research Motivation and Objectives: • The emergence of shared autonomous vehicles (SAVs) is expected to alter transportation costs and patterns, thus affecting accessibility and mobility • Assess the socio-economic implications related to SAVs, such as access to opportunities and flexible and affordable mobility.
Losada-Rojas, L. L., Gkartzonikas, C., & Gkritza, K. �. (2020). Market Acceptance of Autonomous Vehicles in Transportation Disadvantaged Areas: Implications for Policy and Planning. Purdue University. https://rosap.ntl.bts.gov/view/dot/66751
Losada-Rojas, Lisa Lorena, Christos Gkartzonikas, and Konstantina “Nadia” Gkritza. Market Acceptance of Autonomous Vehicles in Transportation Disadvantaged Areas: Implications for Policy and Planning. Purdue University, 2020. https://rosap.ntl.bts.gov/view/dot/66751.
Losada-Rojas, Lisa Lorena, et al. Market Acceptance of Autonomous Vehicles in Transportation Disadvantaged Areas: Implications for Policy and Planning. Purdue University, 2020, ROSA P. https://rosap.ntl.bts.gov/view/dot/66751.
Advances in emerging technologies – such as autonomous vehicles (AVs), e-commerce, and the sharing economy – are having profound effects not only on how we live, move, and spend our time in cities, but also on urban form and development itself. These new technologies are changing how people and goods move around a city and are beginning to have sub
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Lewis, R., & Steckler, R. (2020). Emerging Technologies and Cities: Assessing the Impacts of New Mobility on Cities (Report No. NITC-RR-1249). National Institute for Transportation and Communities (NITC). https://rosap.ntl.bts.gov/view/dot/60643
Lewis, Rebecca and Rebecca Steckler. Emerging Technologies and Cities: Assessing the Impacts of New Mobility on Cities. Report no. NITC-RR-1249. National Institute for Transportation and Communities (NITC), 2020. https://rosap.ntl.bts.gov/view/dot/60643.
Lewis, Rebecca, and Rebecca Steckler Emerging Technologies and Cities: Assessing the Impacts of New Mobility on Cities. National Institute for Transportation and Communities (NITC), 2020, Report no. NITC-RR-1249, ROSA P. https://rosap.ntl.bts.gov/view/dot/60643.
Distracted driving related to cell phone usage ranks among the top three causes of fatal crashes on the road. Although forty-eight of 50 U.S. states allow the use of personal devices if operated hands-free and secured in the vehicle, scientific studies have yet to quantify the safety improvement presumed to be introduced by voice-to-text interactio
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Favaro, F. M. (2020). Impact of Smart Phones’ Interaction Modality on Driving Performance for Conventional and Autonomous Vehicles (Report No. 20-04). Mineta Transportation Institute. https://doi.org/10.31979/mti.2020.1813
Favaro, Francesca M. Impact of Smart Phones’ Interaction Modality on Driving Performance for Conventional and Autonomous Vehicles. Report no. 20-04. Mineta Transportation Institute, 2020. https://doi.org/10.31979/mti.2020.1813.
Favaro, Francesca M Impact of Smart Phones’ Interaction Modality on Driving Performance for Conventional and Autonomous Vehicles. Mineta Transportation Institute, 2020, Report no. 20-04, ROSA P. https://doi.org/10.31979/mti.2020.1813.
Stringless paving is the process of constructing a pavement using non-contact, electronic guidance systems to control the paver elevation and steering without the aid of string lines. Contractors across the United States are switching their primary method of paving from string line to stringless control. The differences between the two processes sh
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United States. Federal Highway Administration (2020). Stringless Paving Construction (Report No. FHWA-HIF-20-086). United States. Federal Highway Administration. https://rosap.ntl.bts.gov/view/dot/54125
United States. Federal Highway Administration. Stringless Paving Construction. Report no. FHWA-HIF-20-086. United States. Federal Highway Administration, 2020. https://rosap.ntl.bts.gov/view/dot/54125.
United States. Federal Highway Administration Stringless Paving Construction. United States. Federal Highway Administration, 2020, Report no. FHWA-HIF-20-086, ROSA P. https://rosap.ntl.bts.gov/view/dot/54125.
Autonomous vehicles represent an evolution in transportation technology and the system of transportation itself. The vehicles will change how current transportation infrastructure is utilized, along with how people use transportation, and the environmental impacts of the transportation system. App based autonomous taxis are considered, using a stat
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Hicks, A., Ahn, S., & Kontar, W. (2019). Autonomous Vehicle Adoption: Assessing Operational and Environmental Impacts. Center for Transportation, Equity, Decisions and Dollars (CTEDD) (UTC). https://rosap.ntl.bts.gov/view/dot/53553
Hicks, Andrea, Soyoung Ahn, and Wissam Kontar. Autonomous Vehicle Adoption: Assessing Operational and Environmental Impacts. Center for Transportation, Equity, Decisions and Dollars (CTEDD) (UTC), 2019. https://rosap.ntl.bts.gov/view/dot/53553.
Hicks, Andrea, et al. Autonomous Vehicle Adoption: Assessing Operational and Environmental Impacts. Center for Transportation, Equity, Decisions and Dollars (CTEDD) (UTC), 2019, ROSA P. https://rosap.ntl.bts.gov/view/dot/53553.
Self-driving vehicles, as a revolution in mobility, are emerging and developing rapidly. However, public attitudes toward this new unproven technology are still uncertain. Given the significant influence of attitude toward a new technology on the intention to use it, the question arises as to why some people are in favor of this technology whereas
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DatasetSupporting Files
Xing, Y., Handy, S. L., Circella, G., Wang, Y., & Alemi, F. (2019). Exploring the Role of Attitude in the Acceptance of Self-Driving Shuttles Dataset. University of California, Berkeley. Institute of Transportation Studies. https://doi.org/10.25338/B8532T
Xing, Yan, Susan L Handy, Giovanni Circella, Yunshi Wang, and Farzad Alemi. Exploring the Role of Attitude in the Acceptance of Self-Driving Shuttles Dataset. University of California, Berkeley. Institute of Transportation Studies, 2019. https://doi.org/10.25338/B8532T.
Xing, Yan, et al. Exploring the Role of Attitude in the Acceptance of Self-Driving Shuttles Dataset. University of California, Berkeley. Institute of Transportation Studies, 2019, ROSA P. https://doi.org/10.25338/B8532T.
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