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.
Safely introducing autonomy to trucks requires monitoring their brake systems continuously. Out-of-adjustment push rods and leakages in the air brake system are two major reasons for increased braking distances in trucks, resulting in safety violations. Air leakages can occur due to small cracks or loose/improperly fit couplings, which do not affec
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Dataset
Darbha, S., & Rajagopal, K. (2023). A Diagnostic Machine Learning Model for Air Brake Systems in Commercial Vehicles [supporting dataset] (Report No. 04-100). Safety through Disruption (Safe-D) University Transportation Center (UTC). https://doi.org/10.15787/VTT1/9SWAHY
Darbha, Swaroop and Kumbakonam Rajagopal. A Diagnostic Machine Learning Model for Air Brake Systems in Commercial Vehicles [supporting dataset]. Report no. 04-100. Safety through Disruption (Safe-D) University Transportation Center (UTC), 2023. https://doi.org/10.15787/VTT1/9SWAHY.
Darbha, Swaroop, and Kumbakonam Rajagopal A Diagnostic Machine Learning Model for Air Brake Systems in Commercial Vehicles [supporting dataset]. Safety through Disruption (Safe-D) University Transportation Center (UTC), 2023, Report no. 04-100, ROSA P. https://doi.org/10.15787/VTT1/9SWAHY.
Vehicle manufacturers are introducing increasingly sophisticated vehicle automation systems to improve driving efficiency, comfort, and safety. Despite these improvements, partially and fully automated vehicles introduce new safety risks to the driving environment. Driver inattention can contribute to increased risk, especially when control transfe
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Dataset
Paras, C. R., & Ferris, T. K. (2023). Countermeasures To Detect and Combat Inattention While Driving Partially Automated Systems [supporting dataset] (Report No. 01-002). Safety through Disruption (Safe-D) University Transportation Center (UTC). https://doi.org/10.15787/VTT1/ZXVADS
Paras, Carolina Rodriguez and Thomas K. Ferris. Countermeasures To Detect and Combat Inattention While Driving Partially Automated Systems [supporting dataset]. Report no. 01-002. Safety through Disruption (Safe-D) University Transportation Center (UTC), 2023. https://doi.org/10.15787/VTT1/ZXVADS.
Paras, Carolina Rodriguez, and Thomas K. Ferris Countermeasures To Detect and Combat Inattention While Driving Partially Automated Systems [supporting dataset]. Safety through Disruption (Safe-D) University Transportation Center (UTC), 2023, Report no. 01-002, ROSA P. https://doi.org/10.15787/VTT1/ZXVADS.
The emerging transportation technologies – vehicle connectivity, electrification, and automation – are expected to impact highway expenditures, revenue, and user equity. With regard to the expenditures, the provision of new infrastructure and modification of existing infrastructure will incur significant capital spending. With regard to revenue, th
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Mwamba, I. C., Alabi, B. N., Benny, D., Nafakh, A. J., Labi, S., & Sinha, K. C. (2023). Changes in Highway Expenditures and Revenues in an Era of CAVs – Part A: Road Agencies (Report No. CCAT Report 33A). Center for Connected and Automated Transportation. Purdue University. http://dx.doi.org/10.5703/1288284317702
Mwamba, Isaiah C, Bortiorkor N.T Alabi, Deepak Benny, Abdullah Jalal Nafakh, Samuel Labi, and Kumares C. Sinha. Changes in Highway Expenditures and Revenues in an Era of CAVs – Part A: Road Agencies. Report no. CCAT Report 33A. Center for Connected and Automated Transportation. Purdue University, 2023. http://dx.doi.org/10.5703/1288284317702.
Mwamba, Isaiah C, et al. Changes in Highway Expenditures and Revenues in an Era of CAVs – Part A: Road Agencies. Center for Connected and Automated Transportation. Purdue University, 2023, Report no. CCAT Report 33A, ROSA P. http://dx.doi.org/10.5703/1288284317702.
A sustainable transportation future is one in which people eschew personal car ownership in favor of using automated vehicle (AV) based ridehailing services in a shared mode. However, the traveling public has historically shown a disinclination towards sharing rides and carpooling with strangers. In a future of AV-based ridehailing services, it wil
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Batur, I., Pendyala, R. M., & Magassy, T. B. (2023). A Multidimensional Analysis of Willingness to Share Rides in a Future of Autonomous Vehicles. Center for Teaching Old Models New Tricks (TOMNET). https://rosap.ntl.bts.gov/view/dot/74123
Batur, Irfan, Ram M. Pendyala, and Tassio B Magassy. A Multidimensional Analysis of Willingness to Share Rides in a Future of Autonomous Vehicles. Center for Teaching Old Models New Tricks (TOMNET), 2023. https://rosap.ntl.bts.gov/view/dot/74123.
Batur, Irfan, et al. A Multidimensional Analysis of Willingness to Share Rides in a Future of Autonomous Vehicles. Center for Teaching Old Models New Tricks (TOMNET), 2023, ROSA P. https://rosap.ntl.bts.gov/view/dot/74123.
This research aims to develop data-driven models for suggesting the initiation of an automated car-to-bicycle overtaking process that will be assessed subjectively by human drivers and bicyclists in a driving simulator environment. A naturalistic driving dataset with 102 vehicles involved served as the data source for model development. The models
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Lin, B. T. W., Bao, S., Guo, H., Chen, S. T., Chuang, T. H., & Su, H. J. (2023). A Data-Driven Autonomous Driving System for Overtaking Bicyclists (Report No. UMTRI-2023-21). University of Michigan. Center for Connected and Automated Transportation. https://dx.doi.org/10.7302/22224
Lin, Brian T W, Shan Bao, Huizhong Guo, Szu-Tung Chen, Tzu-Hsuan Chuang, and Hao-Jie Su. A Data-Driven Autonomous Driving System for Overtaking Bicyclists. Report no. UMTRI-2023-21. University of Michigan. Center for Connected and Automated Transportation, 2023. https://dx.doi.org/10.7302/22224.
Lin, Brian T W, et al. A Data-Driven Autonomous Driving System for Overtaking Bicyclists. University of Michigan. Center for Connected and Automated Transportation, 2023, Report no. UMTRI-2023-21, ROSA P. https://dx.doi.org/10.7302/22224.
Partial- and conditional-automated driving systems (ADS) can not only assist drivers with their driving tasks but also significantly reduce the driving-related burden. Yet still, when the AVS is engaged, the human driver still plays a critical role such as monitoring the driving environment and performing certain driving tasks when called upon by t
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Li, Y., Sharma, A., John, A. P., Alabi, B. N., Chen, S., & Labi, S. (2023). Development of Situational Awareness Enhancing System for Manual Takeover of AV (Report No. 53). Center for Connected and Automated Transportation. Purdue University. http://dx.doi.org/10.5703/1288284317730
Li, Yujie, Aishwarya Sharma, Ajuna P John, Bortiorkor N.T Alabi, Sikai Chen, and Samuel Labi. Development of Situational Awareness Enhancing System for Manual Takeover of AV. Report no. 53. Center for Connected and Automated Transportation. Purdue University, 2023. http://dx.doi.org/10.5703/1288284317730.
Li, Yujie, et al. Development of Situational Awareness Enhancing System for Manual Takeover of AV. Center for Connected and Automated Transportation. Purdue University, 2023, Report no. 53, ROSA P. http://dx.doi.org/10.5703/1288284317730.
The application of on-demand ridesharing services can improve the efficiency and usage of a metropolitan transportation system. Implementing air taxis service can reduce the number of required aerial vehicles, mitigate air pollution, increase the revenue of the transportation network companies, and boost local economics. In this report, we propose
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Yang, S., Zhou, J., Sun, D., & Delaurentis, D. (2023). Ride-Sharing With Advanced Air Mobility (Report No. 58). University of Michigan. Center for Connected and Automated Transportation. http://dx.doi.org/10.5703/1288284317662
Yang, Shuting, Jiazhen Zhou, Dengfeng Sun, and Daniel Delaurentis. Ride-Sharing With Advanced Air Mobility. Report no. 58. University of Michigan. Center for Connected and Automated Transportation, 2023. http://dx.doi.org/10.5703/1288284317662.
Yang, Shuting, et al. Ride-Sharing With Advanced Air Mobility. University of Michigan. Center for Connected and Automated Transportation, 2023, Report no. 58, ROSA P. http://dx.doi.org/10.5703/1288284317662.
The transition of the vehicle fleet to incorporate AV will be a long and complex process. AVs will gradually form a larger and larger share of the fleet mix, offering opportunities and challenges for improved efficiency and safety. At any given point during this transition a portion of the AV fleet will be consuming roadway capacity while unoccupie
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Mantri, S., Lownes, N., & Bergman, D. (2023). Prioritizing People - Mixed Equilibrium Assignment for AV Based on Occupancy (Phase II). University of North Carolina at Charlotte. Center for Advanced Multimodal Mobility Solutions and Education. https://rosap.ntl.bts.gov/view/dot/72368
Mantri, Sruthi, Nicholas Lownes, and David Bergman. Prioritizing People - Mixed Equilibrium Assignment for AV Based on Occupancy (Phase II). University of North Carolina at Charlotte. Center for Advanced Multimodal Mobility Solutions and Education, 2023. https://rosap.ntl.bts.gov/view/dot/72368.
Mantri, Sruthi, et al. Prioritizing People - Mixed Equilibrium Assignment for AV Based on Occupancy (Phase II). University of North Carolina at Charlotte. Center for Advanced Multimodal Mobility Solutions and Education, 2023, ROSA P. https://rosap.ntl.bts.gov/view/dot/72368.
In the era of connectivity and automation, the prospective vehicular applications of these technologies go beyond transportation operations and traffic management. Connected and automated vehicles (CAVs) are capable of centralized control, information sharing through connectivity, and integrated surveillance. Also, CAVs are readily amenable to inno
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Pourgholamali, M., Sharma, A., Ye, Z., Arefkhani, H., Dietz, E., & Labi, S. (2023). Exploring the Prospective Role of Connected Vehicles in Monitoring and Response to Pandemics and Disasters (Report No. 54). Center for Connected and Automated Transportation. Purdue University. http://dx.doi.org/10.5703/1288284317736
Pourgholamali, Mohammadhosein, Aishwarya Sharma, Zhongnan Ye, Hessam Arefkhani, Eric Dietz, and Samuel Labi. Exploring the Prospective Role of Connected Vehicles in Monitoring and Response to Pandemics and Disasters. Report no. 54. Center for Connected and Automated Transportation. Purdue University, 2023. http://dx.doi.org/10.5703/1288284317736.
Pourgholamali, Mohammadhosein, et al. Exploring the Prospective Role of Connected Vehicles in Monitoring and Response to Pandemics and Disasters. Center for Connected and Automated Transportation. Purdue University, 2023, Report no. 54, ROSA P. http://dx.doi.org/10.5703/1288284317736.
Vehicle manufacturers are introducing increasingly sophisticated vehicle automation systems to improve driving efficiency, comfort, and safety. Despite these improvements, partially and fully automated vehicles introduce new safety risks to the driving environment. Driver inattention can contribute to increased risk, especially when control transfe
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Paras, C. R., & Ferris, T. K. (2023). Countermeasures To Detect and Combat Inattention While Driving Partially Automated Systems (Report No. 01-002). Safety through Disruption (Safe-D) University Transportation Center (UTC). https://rosap.ntl.bts.gov/view/dot/73308
Paras, Carolina Rodriguez and Thomas K. Ferris. Countermeasures To Detect and Combat Inattention While Driving Partially Automated Systems. Report no. 01-002. Safety through Disruption (Safe-D) University Transportation Center (UTC), 2023. https://rosap.ntl.bts.gov/view/dot/73308.
Paras, Carolina Rodriguez, and Thomas K. Ferris Countermeasures To Detect and Combat Inattention While Driving Partially Automated Systems. Safety through Disruption (Safe-D) University Transportation Center (UTC), 2023, Report no. 01-002, ROSA P. https://rosap.ntl.bts.gov/view/dot/73308.
The global electric vehicle (EV) market is forecasted to grow by 24.3% till 2028 constantly. However, the development in charging infrastructure is still lagging behind that, hindering the EV's widespread application, i.e., 30 million chargers are still needed to support the existing EV demand. Also, based on the survey by Witricity, 86% of EV owne
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Abdulhamed, B., Alavizadeh, H., Ricketts, T., Schneider, B., Attariani, H., Wang, W., & Saville, M. (2023). STAR In-Road Electric Vehicle Charging for Parked Vehicles [Fact Sheet] (Report No. Project 118511). Ohio. Department of Transportation. Office of Statewide Planning and Research. https://rosap.ntl.bts.gov/view/dot/73213
Abdulhamed, Bilal, Hootan Alavizadeh, Tyler Ricketts, Brandon Schneider, Hamed Attariani, Weisong Wang, and Mike Saville. STAR In-Road Electric Vehicle Charging for Parked Vehicles [Fact Sheet]. Report no. Project 118511. Ohio. Department of Transportation. Office of Statewide Planning and Research, 2023. https://rosap.ntl.bts.gov/view/dot/73213.
Abdulhamed, Bilal, et al. STAR In-Road Electric Vehicle Charging for Parked Vehicles [Fact Sheet]. Ohio. Department of Transportation. Office of Statewide Planning and Research, 2023, Report no. Project 118511, ROSA P. https://rosap.ntl.bts.gov/view/dot/73213.
This research aims to develop human data-driven automated lane-change models for freeway weaving sections using computational methods that assist drivers taking an exit ramp or entering a freeway. A naturalistic driving dataset with 108 adult drivers served as the data source to observed drivers’ lane change maneuvers over 53 freeway weaving sectio
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Lin, B. T. W. (2023). Development of Machine-Learning Models for Autonomous Vehicle Decisions on Weaving Sections of Freeway Ramps (Report No. UMTRI-2023-22). University of Michigan. Center for Connected and Automated Transportation. https://dx.doi.org/10.7302/8688
Lin, Brian T W. Development of Machine-Learning Models for Autonomous Vehicle Decisions on Weaving Sections of Freeway Ramps. Report no. UMTRI-2023-22. University of Michigan. Center for Connected and Automated Transportation, 2023. https://dx.doi.org/10.7302/8688.
Lin, Brian T W Development of Machine-Learning Models for Autonomous Vehicle Decisions on Weaving Sections of Freeway Ramps. University of Michigan. Center for Connected and Automated Transportation, 2023, Report no. UMTRI-2023-22, ROSA P. https://dx.doi.org/10.7302/8688.
As of 2021, there were 18,696 small towns in the US with a population of less than 50,000. These communities typically have a low population density, few public transport services, and limited accessibility to daily services. This can pose significant challenges for residents trying to fulfill essential travel needs and access healthcare. Autonomou
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Li, W., Ye, X., Li, X., Dadashova, B., Ory, M. G., Lee, C., Rathinam, S., Usman, M., Chen, A., Bian, J., Li, S., & Du, J. (2023). Autonomous Vehicles for Small Towns: Exploring Perception, Accessibility, and Safety (Report No. 05-109). Safety through Disruption (Safe-D) University Transportation Center (UTC). https://rosap.ntl.bts.gov/view/dot/73305
Li, Wei, Xinyue Ye, Xiao Li, Bahar Dadashova, Marcia G Ory, Chanam Lee, and Sivakumar Rathinam, et al.. Autonomous Vehicles for Small Towns: Exploring Perception, Accessibility, and Safety. Report no. 05-109. Safety through Disruption (Safe-D) University Transportation Center (UTC), 2023. https://rosap.ntl.bts.gov/view/dot/73305.
Li, Wei, et al. Autonomous Vehicles for Small Towns: Exploring Perception, Accessibility, and Safety. Safety through Disruption (Safe-D) University Transportation Center (UTC), 2023, Report no. 05-109, ROSA P. https://rosap.ntl.bts.gov/view/dot/73305.
At the current time, road agencies and city authorities are considering various stimuli (legislations, policies, programs, and infrastructure investment projects) to support or facilitate electric, connected, and/or automation vehicle (ECAV) transportation. A candid and comprehensive assessment of such stimuli is possible only after due considerati
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Labi, R. N., Smith, J., Sabu, J., & Labi, S. (2023). Changes in Highway Expenditures and Revenues in an Era of CAVs, Volume B: Road-User Costs (Report No. CCAT Report No. 33B). Center for Connected and Automated Transportation. Purdue University. http://dx.doi.org/10.5703/1288284317737
Labi, Rachel N, Jalen Smith, Jelin Sabu, and Samuel Labi. Changes in Highway Expenditures and Revenues in an Era of CAVs, Volume B: Road-User Costs. Report no. CCAT Report No. 33B. Center for Connected and Automated Transportation. Purdue University, 2023. http://dx.doi.org/10.5703/1288284317737.
Labi, Rachel N, et al. Changes in Highway Expenditures and Revenues in an Era of CAVs, Volume B: Road-User Costs. Center for Connected and Automated Transportation. Purdue University, 2023, Report no. CCAT Report No. 33B, ROSA P. http://dx.doi.org/10.5703/1288284317737.
Over the past century, landmark advancements in vehicle technology have motivated road agencies to carry out changes in their road infrastructure design and management processes to accommodate these advancements. The advent of Autonomous Vehicles (AVs), however, poses infrastructure challenges that could be more profound compared to those faced in
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Labi, S., Saeed, T., Pourgholamali, M., Saka, Z. A., & Sinha, K. C. (2023). Design and Management of Highway Infrastructure to Accommodate CAVs (Report No. Report No. 29). Center for Connected and Automated Transportation. Purdue University. https://rosap.ntl.bts.gov/view/dot/73995
Labi, Samuel, Tariq Saeed, Mohammadhosein Pourgholamali, Zainab A Saka, and Kumares C. Sinha. Design and Management of Highway Infrastructure to Accommodate CAVs. Report no. Report No. 29. Center for Connected and Automated Transportation. Purdue University, 2023. https://rosap.ntl.bts.gov/view/dot/73995.
Labi, Samuel, et al. Design and Management of Highway Infrastructure to Accommodate CAVs. Center for Connected and Automated Transportation. Purdue University, 2023, Report no. Report No. 29, ROSA P. https://rosap.ntl.bts.gov/view/dot/73995.
This report documents the work conducted as a multi-disciplinary project on the wireless charging of parked Electrical Vehicles (EVs) by Wright State University and supported by the Ohio Department of Transportation (ODOT). This document summarizes our progress on a wide variety of topics, including 1) in-house software to read and label the open-s
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Abdulhamed, B., Alavizadeh, H., Ricketts, T., Schneider, B., Attariani, H., Wang, W., & Saville, M. (2023). STAR In-Road Electric Vehicle Charging for Parked Vehicles (Report No. FHWA/OH-2023-28). Ohio. Department of Transportation. Office of Statewide Planning and Research. https://rosap.ntl.bts.gov/view/dot/73212
Abdulhamed, Bilal, Hootan Alavizadeh, Tyler Ricketts, Brandon Schneider, Hamed Attariani, Weisong Wang, and Mike Saville. STAR In-Road Electric Vehicle Charging for Parked Vehicles. Report no. FHWA/OH-2023-28. Ohio. Department of Transportation. Office of Statewide Planning and Research, 2023. https://rosap.ntl.bts.gov/view/dot/73212.
Abdulhamed, Bilal, et al. STAR In-Road Electric Vehicle Charging for Parked Vehicles. Ohio. Department of Transportation. Office of Statewide Planning and Research, 2023, Report no. FHWA/OH-2023-28, ROSA P. https://rosap.ntl.bts.gov/view/dot/73212.
The connected and automated vehicle (CAV) technologies will bring unprecedented changes in the landscape of transportation systems for areas like operations, management, and infrastructure needs. To assure a safe, reliable, and trustworthy connected and automated transportation system, it is important to have a clear CAV implementation pathway that
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Aziz, H. A., & Islam, A. H. (2023). Connected and Automated Future of Transportation for Kansas [Technical Summary] (Report No. K-TRAN: KSU-21-5). Arkansas. Department of Transportation. https://rosap.ntl.bts.gov/view/dot/70445
Aziz, H.M. Abdul and A.M. Hasibul Islam. Connected and Automated Future of Transportation for Kansas [Technical Summary]. Report no. K-TRAN: KSU-21-5. Arkansas. Department of Transportation, 2023. https://rosap.ntl.bts.gov/view/dot/70445.
Aziz, H.M. Abdul, and A.M. Hasibul Islam Connected and Automated Future of Transportation for Kansas [Technical Summary]. Arkansas. Department of Transportation, 2023, Report no. K-TRAN: KSU-21-5, ROSA P. https://rosap.ntl.bts.gov/view/dot/70445.
Connected Vehicle (CV) communication technology (i.e., Vehicle-to-Everything, V2X) enables vehicles to "talk" to other vehicles on the road (Vehicle-to-Vehicle, V2V), roadside infrastructure (Vehicle-to-Infrastructure, V2I), vulnerable road users (Vehicle-to-Pedestrian, V2P), and the "cloud" (vehicle-to-network, V2N). The V2X connectivity will prov
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The ongoing integration of autonomous vehicles (AVs) into our urban environments represents a fundamental shift in the way cities function and how pedestrians navigate them. Historically, pedestrians have relied on non-verbal cues to interact with human drivers. However, with the rise of AVs, this traditional method of communication is undergoing a
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Lownes, N., Rezwana, S., Shaon, M. R. R., & Jackson, E. (2023). Pedestrian Behavior and Interaction with Autonomous Vehicles (Phase II). University of North Carolina at Charlotte. Center for Advanced Multimodal Mobility Solutions and Education. https://rosap.ntl.bts.gov/view/dot/72371
Lownes, Nicholas, Saki Rezwana, Mohammad Razaur Rahman Shaon, and Eric Jackson. Pedestrian Behavior and Interaction with Autonomous Vehicles (Phase II). University of North Carolina at Charlotte. Center for Advanced Multimodal Mobility Solutions and Education, 2023. https://rosap.ntl.bts.gov/view/dot/72371.
Lownes, Nicholas, et al. Pedestrian Behavior and Interaction with Autonomous Vehicles (Phase II). University of North Carolina at Charlotte. Center for Advanced Multimodal Mobility Solutions and Education, 2023, ROSA P. https://rosap.ntl.bts.gov/view/dot/72371.
The connected and automated vehicle (CAV) technologies will bring unprecedented changes in the landscape of transportation systems for areas like operations, management, and infrastructure needs. To assure a safe, reliable, and trustworthy connected and automated transportation system, it is important to have a clear CAV implementation pathway that
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Aziz, H. A., & Islam, A. H. (2023). Connected and Automated Future of Transportation for Kansas (Report No. K-TRAN: KSU-21-5). Kansas. Department of Transportation. https://rosap.ntl.bts.gov/view/dot/70414
Aziz, H.M. Abdul and A.M. Hasibul Islam. Connected and Automated Future of Transportation for Kansas. Report no. K-TRAN: KSU-21-5. Kansas. Department of Transportation, 2023. https://rosap.ntl.bts.gov/view/dot/70414.
Aziz, H.M. Abdul, and A.M. Hasibul Islam Connected and Automated Future of Transportation for Kansas. Kansas. Department of Transportation, 2023, Report no. K-TRAN: KSU-21-5, ROSA P. https://rosap.ntl.bts.gov/view/dot/70414.
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