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.
Autonomous vehicle (AV) and connected vehicle (CV) technologies are rapidly maturing and the timeline for their wider deployment is currently uncertain. These technologies are expected to have a number of significant societal benefits: traffic safety, improved mobility, improved road efficiency, reduced cost of congestion, reduced energy use, and r
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Ukkusuri, S. V., Sagir, F., Mahajan, N., Bowman, B., & Sharma, S. (2019). Strategic and Tactical Guidance for the Connected and Autonomous Vehicle Future (Report No. FHWA/IN/JTRP-2019/02). Purdue University. Joint Transportation Research Program. https://rosap.ntl.bts.gov/view/dot/43894
Ukkusuri, Satish V., Fasil Sagir, Nishtha Mahajan, Benjamin Bowman, and Salil Sharma. Strategic and Tactical Guidance for the Connected and Autonomous Vehicle Future. Report no. FHWA/IN/JTRP-2019/02. Purdue University. Joint Transportation Research Program, 2019. https://rosap.ntl.bts.gov/view/dot/43894.
Ukkusuri, Satish V., et al. Strategic and Tactical Guidance for the Connected and Autonomous Vehicle Future. Purdue University. Joint Transportation Research Program, 2019, Report no. FHWA/IN/JTRP-2019/02, ROSA P. https://rosap.ntl.bts.gov/view/dot/43894.
Research Objectives: • Assess the socio-economic implications related to SAVs • Identify market segments with different characteristics and different levels of adoption • Identify transportation disadvantaged areas • Provide best strategies and suggestions to these areas to ensure smooth transition.
Gkartzonikas, C., Losada-Rojas, L., & Gkritza, K. �. (2019). Assessing the Socio-Economic Implications Related to the Emergence of Shared Autonomous Vehicles: The Tale of Two Midwestern Cities. Purdue University. https://rosap.ntl.bts.gov/view/dot/66756
Gkartzonikas, Christos, Lisa Losada-Rojas, and Konstantina “Nadia” Gkritza. Assessing the Socio-Economic Implications Related to the Emergence of Shared Autonomous Vehicles: The Tale of Two Midwestern Cities. Purdue University, 2019. https://rosap.ntl.bts.gov/view/dot/66756.
Gkartzonikas, Christos, et al. Assessing the Socio-Economic Implications Related to the Emergence of Shared Autonomous Vehicles: The Tale of Two Midwestern Cities. Purdue University, 2019, ROSA P. https://rosap.ntl.bts.gov/view/dot/66756.
The authors present an autonomous driving research vehicle with minimal appearance modifications that is capable of a wide range of autonomous and intelligent behaviors, including smooth and comfortable trajectory generation and following; lane keeping and lane changing; intersection handling with or without vehicle-to-infrastructure (V2I) and vehi
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Wei, J., Snider, J. M., Kim, J., Dolan, J. M., Rajkumar, R., & Litkouhi, B. (2019). Towards a Viable Autonomous Driving Research Platform. Technologies for Safe and Efficient Transportation. University Transportation Center. https://rosap.ntl.bts.gov/view/dot/62056
Wei, Junqing, Jarrod M Snider, Junsung Kim, John M Dolan, Raj Rajkumar, and Bakhtiar Litkouhi. Towards a Viable Autonomous Driving Research Platform. Technologies for Safe and Efficient Transportation. University Transportation Center, 2019. https://rosap.ntl.bts.gov/view/dot/62056.
Wei, Junqing, et al. Towards a Viable Autonomous Driving Research Platform. Technologies for Safe and Efficient Transportation. University Transportation Center, 2019, ROSA P. https://rosap.ntl.bts.gov/view/dot/62056.
This study proposes a novel CACC strategy, CACC-OIFT, to explicitly factor IFT dynamics and to leverage it to enhance the platoon performance in an unreliable V2V communication context for a pure CAV platoon.
Wang, C., Gong, S., Zhou, A., Li, T., & Peeta, S. (2019). Cooperative Adaptive Cruise Control for Connected Autonomous Vehicles by Factoring Communication-Related Constraints (Report No. 19-00155). Georgia Institute of Technology. https://rosap.ntl.bts.gov/view/dot/66678
Wang, Chaojie, Siyuan Gong, Anye Zhou, Tao Li, and Srinivas Peeta. Cooperative Adaptive Cruise Control for Connected Autonomous Vehicles by Factoring Communication-Related Constraints. Report no. 19-00155. Georgia Institute of Technology, 2019. https://rosap.ntl.bts.gov/view/dot/66678.
Wang, Chaojie, et al. Cooperative Adaptive Cruise Control for Connected Autonomous Vehicles by Factoring Communication-Related Constraints. Georgia Institute of Technology, 2019, Report no. 19-00155, ROSA P. https://rosap.ntl.bts.gov/view/dot/66678.
This study develops a technology roadmap of the development of driverless vehicles, exploring the likely impacts for the transportation systems of the state of Georgia and the operations of the Georgia Department of Transportation (GDOT). The roadmap consists of two elements. First, a range of contingencies shaping the development pathways for auto
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Hunter, M., Kingsley, G., Guin, A., Horadam, N., Hanus, A., Bleckley, C., & Siangjaeo, S. (2018). GDOT Roadmap for Driverless Vehicles (Report No. FHWA-GA-18-1723). Georgia. Department of Transportation. Office of Performance-Based Management & Research. https://rosap.ntl.bts.gov/view/dot/40157
Hunter, Michael, Gordon Kingsley, Angshuman Guin, Nathaniel Horadam, Andrew Hanus, Claire Bleckley, and Sorawit Siangjaeo. GDOT Roadmap for Driverless Vehicles. Report no. FHWA-GA-18-1723. Georgia. Department of Transportation. Office of Performance-Based Management & Research, 2018. https://rosap.ntl.bts.gov/view/dot/40157.
Hunter, Michael, et al. GDOT Roadmap for Driverless Vehicles. Georgia. Department of Transportation. Office of Performance-Based Management & Research, 2018, Report no. FHWA-GA-18-1723, ROSA P. https://rosap.ntl.bts.gov/view/dot/40157.
Connected and automated vehicle (CAV) technologies can dramatically improve safety by reducing human errors, which contribute substantially (an estimated 94 percent) to roadway crashes. CAVs can eventually operate effectively on roadways without experiencing decreased performance due to distraction or fatigue. However, technological advances will n
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Supporting Files
McDonald, N. C., Khattak, A. J., Combs, T. S., & Shay, E. (2018). Connected and Automated Vehicles and Safety of Vulnerable Road Users: A Systems Approach (Report No. CSCRS-R6). Collaborative Sciences Center for Road Safety. https://rosap.ntl.bts.gov/view/dot/62321
McDonald, Noreen C, Asad J. Khattak, Tabitha S Combs, and Elizabeth Shay. Connected and Automated Vehicles and Safety of Vulnerable Road Users: A Systems Approach. Report no. CSCRS-R6. Collaborative Sciences Center for Road Safety, 2018. https://rosap.ntl.bts.gov/view/dot/62321.
McDonald, Noreen C, et al. Connected and Automated Vehicles and Safety of Vulnerable Road Users: A Systems Approach. Collaborative Sciences Center for Road Safety, 2018, Report no. CSCRS-R6, ROSA P. https://rosap.ntl.bts.gov/view/dot/62321.
Technological advances of connected and automated vehicles (CAVs) will not uniformly decrease crash risks as some environments, crash types, and user groups will continue to experience elevated risks, particularly vulnerable road users such as pedestrians. This project addresses these critical safety issues by: 1) assessing the current and future l
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McDonald, N. C. (2018). Connected and Automated Vehicles and Safety of Vulnerable Road Users: A Systems Approach [Research Brief] (Report No. CSCRS-R6). Collaborative Sciences Center for Road Safety. https://rosap.ntl.bts.gov/view/dot/78255
McDonald, Noreen C. Connected and Automated Vehicles and Safety of Vulnerable Road Users: A Systems Approach [Research Brief]. Report no. CSCRS-R6. Collaborative Sciences Center for Road Safety, 2018. https://rosap.ntl.bts.gov/view/dot/78255.
McDonald, Noreen C Connected and Automated Vehicles and Safety of Vulnerable Road Users: A Systems Approach [Research Brief]. Collaborative Sciences Center for Road Safety, 2018, Report no. CSCRS-R6, ROSA P. https://rosap.ntl.bts.gov/view/dot/78255.
Motivated by autonomous and connected vehicle technology, truck platooning has significant economic benefits on the freight transportation industry. Lower average fuel consumption can be achieved due to the reduced air-drag force experienced by the platoon during operation. This report presents the procedure and results of computational fluid dynam
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She, R., Ouyang, Y., & Al-Qadi, I. L. (2018). CDF Analysis and Prediction Model for Air Resistance on Platooned Freight Trucks (Report No. ICT-20-011). University of Michigan. Center for Connected and Automated Transportation. https://doi.org/10.36501/0197-9191/20-011
She, Ruifeng, Yanfeng Ouyang, and Imad L Al-Qadi. CDF Analysis and Prediction Model for Air Resistance on Platooned Freight Trucks. Report no. ICT-20-011. University of Michigan. Center for Connected and Automated Transportation, 2018. https://doi.org/10.36501/0197-9191/20-011.
She, Ruifeng, et al. CDF Analysis and Prediction Model for Air Resistance on Platooned Freight Trucks. University of Michigan. Center for Connected and Automated Transportation, 2018, Report no. ICT-20-011, ROSA P. https://doi.org/10.36501/0197-9191/20-011.
The introduction of autonomous and connected trucks (ACTs) is expected to result in drastic changes in operational characteristics of freight shipments, which may in turn have significant impacts on efficiency, safety, energy consumption, and infrastructure durability. One such change is the formation of truck platoons. Truck platoons will become m
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Gungor, O. E., She, R., Al-Qadi, I. L., & Ouyang, Y. (2018). Optimization of Lateral Position of Autonomous Trucks (Report No. ICT-20-009). University of Michigan. Center for Connected and Automated Transportation. https://doi.org/10.36501/0197-9191/20-009
Gungor, Osman Erman, Ruifeng She, Imad L Al-Qadi, and Yanfeng Ouyang. Optimization of Lateral Position of Autonomous Trucks. Report no. ICT-20-009. University of Michigan. Center for Connected and Automated Transportation, 2018. https://doi.org/10.36501/0197-9191/20-009.
Gungor, Osman Erman, et al. Optimization of Lateral Position of Autonomous Trucks. University of Michigan. Center for Connected and Automated Transportation, 2018, Report no. ICT-20-009, ROSA P. https://doi.org/10.36501/0197-9191/20-009.
Lateral position of loading, which is an important input to pavement design and analysis, is a random phenomenon for human-driven trucks because they do not follow a straight path as they travel. Therefore, in the pavement-design community, this variable has been called “wheel wander” and conventionally considered in an implicit way. However, with
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Gungor, O. E., & Al-Qadi, I. L. (2018). Development of a Flexible Pavement Design Framework for Autonomous and Connected Trucks (Report No. ICT-20-010). University of Michigan. Center for Connected and Automated Transportation. https://doi.org/10.36501/0197-9191/20-010
Gungor, Osman Erman and Imad L Al-Qadi. Development of a Flexible Pavement Design Framework for Autonomous and Connected Trucks. Report no. ICT-20-010. University of Michigan. Center for Connected and Automated Transportation, 2018. https://doi.org/10.36501/0197-9191/20-010.
Gungor, Osman Erman, and Imad L Al-Qadi Development of a Flexible Pavement Design Framework for Autonomous and Connected Trucks. University of Michigan. Center for Connected and Automated Transportation, 2018, Report no. ICT-20-010, ROSA P. https://doi.org/10.36501/0197-9191/20-010.
United States. Federal Highway Administration. Office of Operations Research, Development, and Technology
2018-11-01
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Traffic congestion is typically caused by oversaturation, poor weather, vehicle crashes, work zones, poor signal timing, and special events. Over saturation occurs when more vehicles use a road than the road is designed to accommodate. The resulting congestion leads to unstable traffic flow, which instigates breakdowns and bottlenecks.The Federal H
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United States. Federal Highway Administration. Office of Operations Research, Development, and Technology (2018). Mitigating Oversaturation With Cooperative Automated Driving Systems : Applying Bundled Speed Harmonization, Cooperative Adaptive Cruise Control, and Cooperative Merging Applications to Managed Lane Facilities : [fact sheet] (Report No. FHWA-HRT-19-006;HRDO-10/11-18(200)E). United States. Federal Highway Administration. Office of Operations Research and Development. https://rosap.ntl.bts.gov/view/dot/38026
United States. Federal Highway Administration. Office of Operations Research, Development, and Technology. Mitigating Oversaturation With Cooperative Automated Driving Systems : Applying Bundled Speed Harmonization, Cooperative Adaptive Cruise Control, and Cooperative Merging Applications to Managed Lane Facilities : [fact sheet]. Report no. FHWA-HRT-19-006;HRDO-10/11-18(200)E. United States. Federal Highway Administration. Office of Operations Research and Development, 2018. https://rosap.ntl.bts.gov/view/dot/38026.
United States. Federal Highway Administration. Office of Operations Research, Development, and Technology Mitigating Oversaturation With Cooperative Automated Driving Systems : Applying Bundled Speed Harmonization, Cooperative Adaptive Cruise Control, and Cooperative Merging Applications to Managed Lane Facilities : [fact sheet]. United States. Federal Highway Administration. Office of Operations Research and Development, 2018, Report no. FHWA-HRT-19-006;HRDO-10/11-18(200)E, ROSA P. https://rosap.ntl.bts.gov/view/dot/38026.
The potential of dynamic ridesharing as a Mobility-as-a-Service centerpiece in cities that are not dense enough for viable and effective public transit systems is being extensively studied by transportation supply researchers. With the era of autonomous vehicles quickly approaching, dynamic ridesharing services could have an important role in incre
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Lavieri, P. S., & Bhat, C. R. (2018). Modeling Individuals’ Willingness to Share Trips With Strangers in an Autonomous Vehicle Future (Report No. D-STOP/2018/141). University of Texas at Austin. Data-Supported Transportation Operations & Planning Center (D-STOP). https://rosap.ntl.bts.gov/view/dot/66264
Lavieri, Patricia S. and Chandra R. Bhat. Modeling Individuals’ Willingness to Share Trips With Strangers in an Autonomous Vehicle Future. Report no. D-STOP/2018/141. University of Texas at Austin. Data-Supported Transportation Operations & Planning Center (D-STOP), 2018. https://rosap.ntl.bts.gov/view/dot/66264.
Lavieri, Patricia S., and Chandra R. Bhat Modeling Individuals’ Willingness to Share Trips With Strangers in an Autonomous Vehicle Future. University of Texas at Austin. Data-Supported Transportation Operations & Planning Center (D-STOP), 2018, Report no. D-STOP/2018/141, ROSA P. https://rosap.ntl.bts.gov/view/dot/66264.
This report presents a review of the main sensors used in connected and autonomous vehicles (CAVs). Radar, ultrasonic sensors, a global positioning system, radio-frequency identification, lidar, cameras, inertial measurement units, and capacitive–proximity sensors were detailed, listing their working principles, advantages, and disadvantages. Based
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Dahal, S., Hernandez, J., & Roesler, J. (2018). Infrastructure Enhancements for CAV Navigation (Report No. ICT-20-008, UILU-ENG-2020-2008). University of Michigan. Center for Connected and Automated Transportation. https://doi.org/10.36501/0197-9191/20-008
Dahal, Sachindra, Jaime Hernandez, and Jeffery Roesler. Infrastructure Enhancements for CAV Navigation. Report no. ICT-20-008, UILU-ENG-2020-2008. University of Michigan. Center for Connected and Automated Transportation, 2018. https://doi.org/10.36501/0197-9191/20-008.
Dahal, Sachindra, et al. Infrastructure Enhancements for CAV Navigation. University of Michigan. Center for Connected and Automated Transportation, 2018, Report no. ICT-20-008, UILU-ENG-2020-2008, ROSA P. https://doi.org/10.36501/0197-9191/20-008.
This project developed a conceptual framework for an analysis, modeling, and simulation system for evaluating the impacts of connected and automated vehicle (CAV) technologies on transportation facilities at the strategic and operational levels, providing the basis for future development of CAV-enabled evaluation tools. The objective of this projec
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Mahmassani, H. S., Elfar, A., Shladover, S. E., & Huang, Z. (2018). Development of an Analysis/Modeling/Simulation (AMS) Framework for V2I and Connected/Automated Vehicle Environment (Report No. FHWA-JPO-18-725). United States. Department of Transportation. Intelligent Transportation Systems Joint Program Office. https://rosap.ntl.bts.gov/view/dot/39965
Mahmassani, Hani S., Amr Elfar, Steven E. Shladover, and Zhitong Huang. Development of an Analysis/Modeling/Simulation (AMS) Framework for V2I and Connected/Automated Vehicle Environment. Report no. FHWA-JPO-18-725. United States. Department of Transportation. Intelligent Transportation Systems Joint Program Office, 2018. https://rosap.ntl.bts.gov/view/dot/39965.
Mahmassani, Hani S., et al. Development of an Analysis/Modeling/Simulation (AMS) Framework for V2I and Connected/Automated Vehicle Environment. United States. Department of Transportation. Intelligent Transportation Systems Joint Program Office, 2018, Report no. FHWA-JPO-18-725, ROSA P. https://rosap.ntl.bts.gov/view/dot/39965.
Regional coordination in anticipation of the widespread use of connected vehicles/autonomous vehicles (CVs/AVs) will better educate New England’s population, influence policy, reduce costs, and provide safer and more efficient roadways for the traveling public. This document provides considerations for identified cross-border issues and a roadmap f
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Chaffee, C., & Murtha, S. (2018). Quick Response: New England Connected and Autonomous Vehicles (Report No. NETC QR17-1, NETCR108). New England Transportation Consortium. https://rosap.ntl.bts.gov/view/dot/64449
Chaffee, Chris and Suzanne Murtha. Quick Response: New England Connected and Autonomous Vehicles. Report no. NETC QR17-1, NETCR108. New England Transportation Consortium, 2018. https://rosap.ntl.bts.gov/view/dot/64449.
Chaffee, Chris, and Suzanne Murtha Quick Response: New England Connected and Autonomous Vehicles. New England Transportation Consortium, 2018, Report no. NETC QR17-1, NETCR108, ROSA P. https://rosap.ntl.bts.gov/view/dot/64449.
Preparing for the Future of Transportation: Automated Vehicles 3.0 (AV 3.0) advances U.S. DOT’s commitment to supporting the safe, reliable, efficient, and cost-effective integration of automation into the broader multimodal surface transportation system. AV 3.0 builds upon—but does not replace—voluntary guidance provided in Automated Driving Syste
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United States. Department of Transportation (2018). Preparing for the Future of Transportation: Automated Vehicles 3.0. United States. Department of Transportation. https://doi.org/10.21949/xqx2-hg02
United States. Department of Transportation. Preparing for the Future of Transportation: Automated Vehicles 3.0. United States. Department of Transportation, 2018. https://doi.org/10.21949/xqx2-hg02.
United States. Department of Transportation Preparing for the Future of Transportation: Automated Vehicles 3.0. United States. Department of Transportation, 2018, ROSA P. https://doi.org/10.21949/xqx2-hg02.
The Northeast Autonomous and Connected Vehicle Summit was hosted by the Connecticut Department of Transportation and the Federal Highway Administration on June 12-13, 2018, at the Windsor Hartford Marriott. The event provided an open forum for stakeholders in the Northeast to network, share and discuss a wide range of topics related to the future o
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Jackson, E., Simler, T., Calcaterra, P., & Runowicz, E. (2018). Northeast Autonomous and Connected Vehicle Summit Report (Report No. CT-2311-F-18-6). Connecticut. Department of Transportation. https://rosap.ntl.bts.gov/view/dot/63549
Jackson, Eric, Tara Simler, Peter Calcaterra, and Eric Runowicz. Northeast Autonomous and Connected Vehicle Summit Report. Report no. CT-2311-F-18-6. Connecticut. Department of Transportation, 2018. https://rosap.ntl.bts.gov/view/dot/63549.
Jackson, Eric, et al. Northeast Autonomous and Connected Vehicle Summit Report. Connecticut. Department of Transportation, 2018, Report no. CT-2311-F-18-6, ROSA P. https://rosap.ntl.bts.gov/view/dot/63549.
Regional coordination in anticipation of the widespread use of connected vehicles/autonomous vehicles (CVs/AVs) will better educate New England’s population, influence policy, reduce costs, and provide safer and more efficient roadways for the traveling public. This document provides considerations for identified cross-border issues and a roadmap f
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Chaffee, C., & Murtha, S. (2018). Quick Response: New England Connected and Autonomous Vehicles (Report No. NETC QR17-1, NETCR108). New England Transportation Consortium. https://rosap.ntl.bts.gov/view/dot/67666
Chaffee, Chris and Suzanne Murtha. Quick Response: New England Connected and Autonomous Vehicles. Report no. NETC QR17-1, NETCR108. New England Transportation Consortium, 2018. https://rosap.ntl.bts.gov/view/dot/67666.
Chaffee, Chris, and Suzanne Murtha Quick Response: New England Connected and Autonomous Vehicles. New England Transportation Consortium, 2018, Report no. NETC QR17-1, NETCR108, ROSA P. https://rosap.ntl.bts.gov/view/dot/67666.
In this paper we identified the most important bicyclist crash scenarios for crash imminent braking systems. Our tested scenario involved a crash geometry that is responsible for approximately a quarter of cyclist social cost and a third of cyclist fatalities in single light vehicle crashes. Its primary contribution is that it is based on actual te
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Chen, Y. (2018). Pre-Crash Interactions between Pedestrians and Cyclists and Intelligent Vehicles. Ohio State University. Crash Imminent Safety (CrIS) University Transportation Center. https://rosap.ntl.bts.gov/view/dot/38734
Chen, Yaobin. Pre-Crash Interactions between Pedestrians and Cyclists and Intelligent Vehicles. Ohio State University. Crash Imminent Safety (CrIS) University Transportation Center, 2018. https://rosap.ntl.bts.gov/view/dot/38734.
Chen, Yaobin Pre-Crash Interactions between Pedestrians and Cyclists and Intelligent Vehicles. Ohio State University. Crash Imminent Safety (CrIS) University Transportation Center, 2018, ROSA P. https://rosap.ntl.bts.gov/view/dot/38734.
The goal of this project was to understand how multi-agent models of the driver and vehicle can inform design principles for optimized autonomous vehicle systems. In this project, a computational model for human behavior in pre-crash scenarios was developed and investigated. A multi-agent model with both human drivers and autonomous and semi-autono
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Kurt, A., Ozguner, U., Liu, P., Ramyar, S., Amsalu, S. B., Wang, Z., Majd, K., & Homaifar, A. (2018). Driver Models for Both Human and Autonomous Vehicles. Ohio State University. https://rosap.ntl.bts.gov/view/dot/37070
Kurt, Arda, Umit Ozguner, Peng Liu, Saina Ramyar, Seifemichael B. Amsalu, Zihao Wang, Keyvan Majd, and Abdollah Homaifar. Driver Models for Both Human and Autonomous Vehicles. Ohio State University, 2018. https://rosap.ntl.bts.gov/view/dot/37070.
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