References

Abduljabbar, Rusul, Hussein Dia, Sohani Liyanage, and Saeed Asadi Bagloee. 2019. “Applications of Artificial Intelligence in Transport: An Overview.” Sustainability 11 (1): 189.

AECOM. 2021a. “TxDOT Statewide TSMO: Cooperative Automated Transportation Integration.” Version 3.0. Texas Department of Transportation. https://ftp.txdot.gov/pub/txdot-info/trf/tsmo/connected-autonomous-vehicles.pdf.

AECOM. 2021b. “TxDOT Statewide TSMO Strategic Plan Update.” Version 4.0. Texas Department of Transportation. https://ftp.txdot.gov/pub/txdot-info/trf/tsmo/statewide-strategic-plan.pdf.

Ahmed, Mohamed, Anik Das, Md Nasim Khan, Britton E. Hammit, and Elhashemi Ali. 2021. “Driver Performance and Behavior in Adverse Weather Conditions: Microsimulation and Variable Speed Limit Implementation of the SHRP2 Naturalistic Driving Study Results - Phase 3.” WY-2105F. Wyoming Department of Transportation. https://rosap.ntl.bts.gov/view/dot/60907.

Allmeroth, Becky, and Ploisongsaeng Intaratip. 2022. “Predictive Analytics for Traffic Management on I-270 in St. Louis.” Missouri Department of Transportation. 2022. https://www.modot.org/predictive-analytics-traffic-management-i-270-st-louis.

Alsrehin, N. O., A. F. Klaib, and A. Magableh. 2019. “Intelligent Transportation and Control Systems Using Data Mining and Machine Learning Techniques: A Comprehensive Study.” IEEE Access 7: 49830–57. https://doi.org/10.1109/ACCESS.2019.2909114.

Ang, Kenneth Li-Minn, Jasmine Kah Phooi Seng, Ericmoore Ngharamike, and Gerald K. Ijemaru. 2022. “Emerging Technologies for Smart Cities’ Transportation: Geo-Information, Data Analytics and Machine Learning Approaches.” ISPRS International Journal of Geo-Information 11 (2): 85.

Angarita-Zapata, J. S., A. D. Masegosa, and I. Triguero. 2019. “A Taxonomy of Traffic Forecasting Regression Problems From a Supervised Learning Perspective.” IEEE Access 7: 68185–205. https://doi.org/10.1109/ACCESS.2019.2917228.

Arasteh, Megan. n.d. “Pinellas County Smart Community 2020 ATCMTD.” FDOT. Accessed September 22, 2022. https://www.fdot.gov/traffic/teo-divisions.shtm/cav-ml-stamp/cv/maplocations/pinellas-county-smart-community-project.

Azin, Bahar, and Xianfeng Terry Yang. 2021. “I-80 Hybrid Regulatory Speed Limit Signing Design and VSL System Evaluation.” UT-21.07. Utah Department of Transportation. https://rosap.ntl.bts.gov/view/dot/56456.

Balali, Vahid, Arash Jahangiri, and Sahar Ghanipoor Machiani. 2017. “Multi-Class US Traffic Signs 3D Recognition and Localization via Image-Based Point Cloud Model Using Color Candidate Extraction and Texture-Based Recognition.” Advanced Engineering Informatics 32 (April): 263–74. https://doi.org/10.1016/j.aei.2017.03.006.

Baroud, Hiba, Abhishek Dubey, and Sayyed Mohsen Vazirizade. 2021. “Collaborative Research Project to Coordinate the Data from the CRASH Predictive Analytics Program Between TDOT and TDOSHS.” RES2019-02. Tennessee Department of Transportation. https://rosap.ntl.bts.gov/view/dot/61069.

Bashar, Mohammad Z., and Cristina Torres-Machi. 2021. Performance of Machine Learning Algorithms in Predicting the Pavement International Roughness Index. Transportation Research Record: Journal of the Transportation Research Board, No. 2675(5), pp. 226–237. https://doi.org/10.1177/0361198120986171.

Bešinović, N., L. De Donato, F. Flammini, R. M. P. Goverde, Z. Lin, R. Liu, S. Marrone, R. Nardone, T. Tang, and V. Vittorini. 2022. “Artificial Intelligence in Railway Transport: Taxonomy, Regulations, and Applications.” IEEE Transactions on Intelligent Transportation Systems 23 (9): 14011–24. https://doi.org/10.1109/TITS.2021.3131637.

Bianchi, Eric, and Matthew Hebdon. 2021. “Forecasting Infrastructure Deterioration with Inverse GANs.” In Applications of Machine Learning 2021, 11843:1184304. SPIE. https://doi.org/10.1117/12.2595111.

Boukerche, Azzedine, Yanjie Tao, and Peng Sun. 2020. “Artificial Intelligence-Based Vehicular Traffic Flow Prediction Methods for Supporting Intelligent Transportation Systems.” Computer Networks 182 (December): 107484. https://doi.org/10.1016/j.comnet.2020.107484.

Boulder AI. 2020. “Boulder-Based Visual Intelligence Company Lands Contract with City of Denver, Colorado to Improve Pedestrian Safety.” June 16, 2020. https://boulderai.com/boulder-based-visual-intelligence-company-lands-contract-with-city-of-denver-colorado-to-improve-pedestrian-safety/.

Boyer, Ryan C., William T. Scherer, and Michael C. Smith. 2017. Trends Over Two Decades of Transportation Research: A Machine Learning Approach. Transportation Research Record: Journal of the Transportation Research Board, No. 2614, pp. 1–9. https://doi.org/10.3141/2614-01.

California DMV. n.d. “Autonomous Vehicles Program.” California DMV. Accessed September 26, 2022. https://www.dmv.ca.gov/portal/vehicle-industry-services/autonomous-vehicles/.

Cano-Ortiz, Saúl, Pablo Pascual-Muñoz, and Daniel Castro-Fresno. 2022. “Machine Learning Algorithms for Monitoring Pavement Performance.” Automation in Construction 139 (July): 104309. https://doi.org/10.1016/j.autcon.2022.104309.

Chen, Changlu, Yanbin Liu, Ling Chen, and Chengqi Zhang. 2022. “Bidirectional Spatial-Temporal Adaptive Transformer for Urban Traffic Flow Forecasting,” IEEE Transactions on Neural Networks and Learning Systems, 1–13. https://doi.org/10.1109/TNNLS.2022.3183903.

Chen, Yihan, Xingyu Gu, Zhen Liu, and Jia Liang. 2022. “A Fast Inference Vision Transformer for Automatic Pavement Image Classification and Its Visual Interpretation Method.” Remote Sensing 14 (8). https://doi.org/10.3390/rs14081877.

Chung, Sai-Ho. 2021. “Applications of Smart Technologies in Logistics and Transport: A Review.” Transportation Research Part E: Logistics and Transportation Review 153 (September): 102455. https://doi.org/10.1016/j.tre.2021.102455.

City of Bellevue, WA. 2021. “Accelerating Vision Zero with Advanced Video Analytics: Video-Based Network-Wide Conflict and Speed Analysis.” National Operations Center of Excellence Case Study. February 12, 2021. https://transportationops.org/case-studies/accelerating-vision-zero-advanced-video-analytics-video-based-network-wide-conflict-and.

Codjoe, Julius, Raju Thapa, and Afia Serwaa Yeboah. 2020. “Exploring Non-Traditional Methods of Obtaining Vehicle Volumes.” FHWA/LA.20/635. Louisiana Department of Transportation and Development. https://rosap.ntl.bts.gov/view/dot/58337.

Corns, Steven M., Suzanna K. Long, Hari Gude, Jacob Hale, and Bhanu Kanwar. 2020. “Predictive Deep Learning for Flood Evacuation Planning and Routing.” cmr 20-002. Missouri Department of Transportation (SPR-B). https://spexternal.modot.mo.gov/sites/cm/CORDT/cmr20-002.pdf.

Damaj, Issam, Salwa K. Al Khatib, Tarek Naous, Wafic Lawand, Zainab Z. Abdelrazzak, and Hussein T. Mouftah. 2022. “Intelligent Transportation Systems: A Survey on Modern Hardware Devices for the Era of Machine Learning.” Journal of King Saud University - Computer and Information Sciences 34 (8, Part B): 5921–42. https://doi.org/10.1016/j.jksuci.2021.07.020.

Das, Subasish, Karen Dixon, Xiaoduan Sun, Anandi Dutta, and Michelle Zupancich. 2017. Trends in Transportation Research: Exploring Content Analysis in Topics. Transportation Research Record: Journal of the Transportation Research Board, No. 2614, pp. 27–38. https://doi.org/10.3141/2614-04.

Delaware DOT. n.d. “Innovative Transportation Management Projects.” Integrated Transportation Management Program. Accessed September 22, 2022. https://deldot.gov/Programs/itms/index.shtml?dc=projects.

Demiroluk, Sami, and Kaan Ozbay. 2014. Adaptive Learning in Bayesian Networks for Incident Duration Prediction. Transportation Research Record: Journal of the Transportation Research Board, No. 2460, pp. 77–85. https://doi.org/10.3141/2460-09.

Donaldson, Gene, Caroline Trueman, and George Zhao. 2022. “Artificial Intelligence Enhanced Integrated Transportation Management System (AI-ITMS): DelDOT’s ATCMTD Project Update.” Virtual, January 26.

Dong, J., S. Chen, S. Zong, T. Chen, and S. Labi. 2021. “Image Transformer for Explainable Autonomous Driving System.” In, 2732–37. https://doi.org/10.1109/ITSC48978.2021.9565103.

Drake, Bob. 2018. “35 State DOTs Are Deploying Drones.” Civil + Structural Engineer Magazine (blog). March 28, 2018. https://csengineermag.com/35-state-dots-deploying-drones/.

DriveOhio. 2020. “I-70 Truck Automation Corridor | DriveOhio.” 2020. https://drive.ohio.gov/programs/av-cv/70-truck-automated-corridor.

Fang, Yuchen, Fang Zhao, Yanjun Qin, Haiyong Luo, and Chenxing Wang. 2022. “Learning All Dynamics: Traffic Forecasting via Locality-Aware Spatio-Temporal Joint Transformer,” IEEE Transactions on Intelligent Transportation Systems, pp. 1–14. https://doi.org/10.1109/TITS.2022.3197640.

FHWA. 2019. “Press Release: U.S. Department of Transportation Awards Nearly $5 Million Grant to Delaware’s Artificial Intelligence Transportation Management System, 4/01/2019 | Federal Highway Administration.” 2019. https://www.fhwa.dot.gov/pressroom/fhwa1906_delaware.cfm.

FHWA. 2020a. “VIRGINIA: AI Meets ICM: Realizing the Next Generation of Regional Mobility.” https://ops.fhwa.dot.gov/fastact/atcmtd/2019/awards/factsheet/pdf/virginia.pdf.

FHWA. 2020b. “WASHINGTON: Deployment of the Washington State Virtual Coordination Center for Multimodal Integrated Corridor Management.” https://ops.fhwa.dot.gov/fastact/atcmtd/2019/awards/factsheet/pdf/washington.pdf.

FHWA. 2020c. “U.S. Department of Transportation Awards $1 Million to Missouri’s I-270 Predictive Layered Operations Initiative | FHWA.” 2020. https://highways.dot.gov/newsroom/us-department-transportation-awards-1-million-missouris-i-270-predictive-layered.

FHWA. 2022a. “The Role of Artificial Intelligence and Machine Learning in Federally Supported Surface Transportation 2022 Updates.” FHWA-HRT-22-026. Washington, DC: FHWA Exploratory Advanced Research Program. https://doi.org/10.21949/1521711.

FHWA. 2022b. “What Is Transportation Systems Management and Operations (TSMO)? | Transportation Systems Management and Operations (TSMO) Plans | Organizing and Planning for Operations - FHWA Office of Operations.” April 8, 2022. https://ops.fhwa.dot.gov/tsmo/.

FHWA. 2022c. “CARMA Program Overview.” April 27, 2022. https://highways.dot.gov/research/operations/CARMA.

Fowler, Summer. 2021. “Artificial Intelligence in Autonomous Vehicle.” Presented at the Carnegie Mellon University “Managing AI in Transportation” course, May 7.

Garrett, J. Kyle, Hani S. Mahmassani, Deepak Gopalakrishna, Bryan C. Krueger, Jiaqi Ma, Fang Zhou, Zihan Hong, Marija Ostojic, and Nayel Urena Serulle. 2017. “Integrated Modeling for Road Condition Prediction [Final Report].” FHWA-JPO-18-631. ITS Joint Program Office. https://rosap.ntl.bts.gov/view/dot/35421.

Gartner. 2021. “Gartner Says Cloud Will Be the Centerpiece of New Digital Experiences.” Gartner. 2021. https://www.gartner.com/en/newsroom/press-releases/2021-11-10-gartner-says-cloud-will-be-the-centerpiece-of-new-digital-experiences.

Gettman, Douglas. 2019. “Raising Awareness of Artificial Intelligence for Transportation Systems Management and Operations.” FHWA-HOP-19-052. Federal Highway Administration, Office of Operations. https://rosap.ntl.bts.gov/view/dot/44201.

Goodfellow, Ian J., Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. 2014. “Generative Adversarial Networks.” arXiv. https://doi.org/10.48550/arXiv.1406.2661.

Guin, Angshuman, Michael Hunter, Han Gyol Kim, and Nishu Choudhary. 2020. “Detection Technology Testbed on I 475: Technology Feasibility Study.” FHWA-GA-21-1720. Georgia Department of Transportation. https://rosap.ntl.bts.gov/view/dot/56905.

Hadi, Mohammed, Yan Xiao, Md Shahadat Iqbal, Tao Wang, Rajib Saha, and Mosammat Tahnin Tariq. 2019. “Data and Modeling Support of Off-Line and Real-Time Decisions Associated with Integrated Corridor Management.” Florida Department of Transportation. https://rosap.ntl.bts.gov/view/dot/49875.

Haghighat, Arya Ketabchi, Varsha Ravichandra-Mouli, Pranamesh Chakraborty, Yasaman Esfandiari, Saeed Arabi, and Anuj Sharma. 2020. “Applications of Deep Learning in Intelligent Transportation Systems.” Journal of Big Data Analytics in Transportation 2 (2): 115–45. https://doi.org/10.1007/s42421-020-00020-1.

Hallak, Adel El. 2022. “One Click to the Cloud: NVIDIA, Google Cloud Help Enterprises Build AI Faster.” NVIDIA Blog. 2022. https://blogs.nvidia.com/blog/ngc-google-cloud-jupyter-notebooks/.

Han, Chengjia, Tao Ma, Ju Huyan, Zheng Tong, Handuo Yang, and Yaowen Yang. 2024. “Multi-Stage Generative Adversarial Networks for Generating Pavement Crack Images.” Engineering Applications of Artificial Intelligence 131 (May): 107767. https://doi.org/10.1016/j.engappai.2023.107767.

Hoeft, Brian C. 2019. “Advanced Transportation and Congestion Management Technologies Deployment Initiative (ATCMTD) - Southern Nevada Smart Transportation Project.” Federal Highway Administration Office of Operations. April 26, 2019. https://ops.fhwa.dot.gov/fastact/atcmtd/2017/applications/southernnevada/project.htm.

Hong Vin, Koay, Chuah Joon Huang, and Chow Chee-Onn. 2021a. “Convolutional Neural Network or Vision Transformer? Benchmarking Various Machine Learning Models for Distracted Driver Detection.” In, 417–22. TENCON 2021 - 2021 IEEE Region 10 Conference (TENCON). Piscataway, NJ, USA: IEEE. https://doi.org/10.1109/TENCON54134.2021.9707341.

Hong Vin, Koay, Chuah Joon Huang, and Chow Chee-Onn. 2021b. “Shifted-Window Hierarchical Vision Transformer for Distracted Driver Detection.” In, 7 pp. 2021 IEEE Region 10 Symposium (TENSYMP). Piscataway, NJ, USA: IEEE. https://doi.org/10.1109/TENSYMP52854.2021.9550995.

Hu, Krystal, and Krystal Hu. 2023. “ChatGPT Sets Record for Fastest-Growing User Base - Analyst Note.” Reuters, February 2, 2023, sec. Technology. https://www.reuters.com/technology/chatgpt-sets-record-fastest-growing-user-base-analyst-note-2023-02-01/.

Huiqin, Chen, Liu Hao, Feng Xiexing, and Chen Hailong. 2021. “Distracted Driving Recognition Using Vision Transformer for Human-Machine Co-Driving.” In, 7 pp. 2021 5th CAA International Conference on Vehicular Control and Intelligence (CVCI). Piscataway, NJ, USA: IEEE. https://doi.org/10.1109/CVCI54083.2021.9661254.

Iowa Department of Transportation. 2021. “Iowa’s Comprehensive Work Zone Program.” National Operations Center of Excellence Case Study. January 27, 2021. https://transportationops.org/case-studies/iowa%E2%80%99s-comprehensive-work-zone-program.

ITS Deployment Evaluation. 2021. “Artificial Intelligence and Machine Learning for Transportation.” U.S. DOT ITS Joint Program Office. https://www.itskrs.its.dot.gov/briefings.

ITS Deployment Evaluation. 2022. “Leveraging Existing Infrastructure and Computer Vision for Pedestrian Detection.” U.S. DOT ITS Joint Program Office. https://www.itskrs.its.dot.gov/decision-support/case-study/leveraging-existing-infrastructure-and-computer-vision-pedestrian.

ITS Joint Program Office, U.S. DOT. n.d. “Integration of Pikalert(R) into the Wyoming CV Pilot Will Save Lives and Reduce Delay.” Connected Vehicle Pilot Deployment Program. Accessed September 22, 2022. https://www.its.dot.gov/pilots/wydot_pikalert.htm.

Jiang, Weiwei. 2022. “Cellular Traffic Prediction with Machine Learning: A Survey.” Expert Systems with Applications 201 (September): 117163. https://doi.org/10.1016/j.eswa.2022.117163.

Jiang, Weiwei, and Jiayun Luo. 2022. “Graph Neural Network for Traffic Forecasting: A Survey.” Expert Systems with Applications, 117921.

Jun, Gao, Yi Jiangang, and Y. L. Murphey. 2021. “A Lane-Changing Detection Model Using Span-Based Transformer.” In , 2733–38. 2021 33rd Chinese Control and Decision Conference (CCDC). Piscataway, NJ, USA: IEEE. https://doi.org/10.1109/CCDC52312.2021.9601457.

Kim, Kyounggon, Jun Seok Kim, Seonghoon Jeong, Jo-Hee Park, and Huy Kang Kim. 2021. “Cybersecurity for Autonomous Vehicles: Review of Attacks and Defense.” Computers and Security 103. https://doi.org/10.1016/j.cose.2020.102150.

Kocamaz, Mehmet Kemal, Jian Gong, and Bernardo R. Pires. 2016. “Vision-Based Counting of Pedestrians and Cyclists.” In 2016 IEEE Winter Conference on Applications of Computer Vision (WACV), 1–8. https://doi.org/10.1109/WACV.2016.7477685.

Kolar, Maria. 2021. “North Carolina Department of Transportation (NCDOT) to Pilot Waycare to Support Traffic Management Operations, Reduce Crashes and Congestion.” Press Release. PRWeb. May 27, 2021. https://www.prweb.com/releases/north_carolina_department_of_transportation_ncdot_to_pilot_waycare_to_support_traffic_management_operations_reduce_crashes_and_congestion/prweb17963612.htm.

Korbmacher, Raphael, and Antoine Tordeux. 2021. “Review of Pedestrian Trajectory Prediction Methods: Comparing Deep Learning and Knowledge-Based Approaches,” arXiv, .

Lamczyk, Stephen, Kwame Ampofo, Behrouz Salashour, Mecit Cetin, and Khan M. Iftekharuddin. 2022. “SURFGenerator: Generative Adversarial Network Modeling for Synthetic Flooding Video Generation.” In 2022 International Joint Conference on Neural Networks (IJCNN), 1–8. https://doi.org/10.1109/IJCNN55064.2022.9891969.

Lee, Bobby. 2022a. “Clearing a Pathway in Rancho Cordova.” LYT (blog). July 26, 2022. https://lyt.ai/customer-success-stories/clearing-a-pathway-in-rancho-cordova/.

Lee, Bobby. 2022b. “LYT Expands Its Transit Signal Prioritization Technology From 20 Intersections to 142 Throughout San Jose.” Press Release. LYT (blog). August 11, 2022. https://lyt.ai/press-release/lyt-expands-its-transit-signal-prioritization-technology-from-20-intersections-to-142-throughout-san-jose/.

Lee, Bobby. 2022c. “Speeding Up Transit in East Palo Alto.” LYT (blog). August 23, 2022. https://lyt.ai/customer-success-stories/speeding-up-transit-in-east-palo-alto/.

Li, D., and J. Lasenby. 2022. “A Revised Video Vision Transformer for Traffic Estimation With Fleet Trajectories.” IEEE Sensors Journal 22 (17): 17103–12. https://doi.org/10.1109/JSEN.2022.3193663.

Li, Ruimin, Francisco C. Pereira, and Moshe E. Ben-Akiva. 2018. “Overview of Traffic Incident Duration Analysis and Prediction.” European Transport Research Review 10 (2): 22. https://doi.org/10.1186/s12544-018-0300-1.

Liang, J., H. Zhu, E. Zhang, and J. Zhang. 2022. “Stargazer: A Transformer-Based Driver Action Detection System for Intelligent Transportation.” In, 3159–66. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). Piscataway, NJ, USA: IEEE. https://doi.org/10.1109/CVPRW56347.2022.00356.

Liang, Wencan, Haibin Li, Yaqian Li, Junjie Hou, Wengming Zhang, and Cunjun Xiao. 2022. “Traffic Sign Detection Algorithm Based on Reduced-Channel-Mixing Mlp and Convolution Transformer,” SSRN.

Lin, Hongyi, Yang Liu, Shen Li, and Xiaobo Qu. 2023. “How Generative Adversarial Networks Promote the Development of Intelligent Transportation Systems: A Survey.” IEEE/CAA Journal of Automatica Sinica 10 (9): 1781–96. https://doi.org/10.1109/JAS.2023.123744.

Liu, H., X. Xiong, Y. Jiang, Z. Guan, and L. Liu. 2021. “Research on Traffic Accident Fatality Prediction Based on BP Neural Network.” In, 194–98. 2021 IEEE 20th International Conference on Cognitive Informatics Cognitive Computing (ICCI*CC). Piscataway, NJ, USA: IEEE. https://doi.org/10.1109/ICCICC53683.2021.9811306.

Liu, W., X. Liu, H. Feng, Y. Wang, L. Guan, W. Xu, G. Shen, Z. Liu, and X. Kong. 2021. “ST-TAP: A Traffic Accident Prediction Framework Based on Spatio-Temporal Transformer.” In, 360–65. https://doi.org/10.1109/DASC-PICom-CBDCom-CyberSciTech52372.2021.00068.

Maloch, Mike. 2021. “ATCMTD - Smart Spines.” Pittsburgh Department of Mobility and Infrastructure. https://apps.pittsburghpa.gov/redtail/images/12941_ATCMTD_Smart_Spines_Fact_Sheet.pdf.

Manibardo, Eric L, Ibai Laña, and Javier Del Ser. 2021. “Deep Learning for Road Traffic Forecasting: Does It Make a Difference?” IEEE Transactions on Intelligent Transportation Systems.

Manzari, Omid Nejati, Amin Boudesh, and Shahriar B. Shokouhi. 2022. “Pyramid Transformer for Traffic Sign Detection,” arXiv, . https://doi.org/10.48550/arXiv.2207.06067.

MassDOT. n.d. “Self-Driving Systems in Massachusetts | Mass.Gov.” Accessed September 26, 2022. https://www.mass.gov/self-driving-systems-in-massachusetts.

McKinsey. 2023. “Economic Potential of Generative AI | McKinsey.” 2023. https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier#introduction.

Mishra, Santosh, and Brooke Ramsey. 2022. “Phase 1 Enabling Technology Readiness Assessment — Heart of Iowa Regional Transit Agency ITS4US Deployment Project.” FHWA-JPO-21-887. ITS Joint Program Office. https://rosap.ntl.bts.gov/view/dot/62477.

MnDOT. 2022. “CAV Challenge - Connected and Automated Vehicles - MnDOT.” 2022. http://www.dot.state.mn.us/automated/cavchallenge.html.

MoDOT. 2022. “Predictive Analytics for Traffic Management on I-270 in St. Louis | Missouri Department of Transportation.” 2022. https://www.modot.org/predictive-analytics-traffic-management-i-270-st-louis.

Mohammadian, Abolfazl, Homa Taghipour, and Amir Bahador Parsa. 2020. “Dynamic Travel Time Estimation for Northeast Illinois Expressways.” FHWA-ICT-20-007. Illinois Department of Transportation (SPR). https://doi.org/10.36501/0197-9191/20-012.

Nama, Mahima, Ankita Nath, Nancy Bechra, Jitendra Bhatia, Sudeep Tanwar, Manish Chaturvedi, and Balqies Sadoun. 2021. “Machine Learning-Based Traffic Scheduling Techniques for Intelligent Transportation System: Opportunities and Challenges.” International Journal of Communication Systems 34 (9): e4814. https://doi.org/10.1002/dac.4814.

National Academy of Sciences. 2022. “The Era of Smart Infrastructure Demands Strong Data, Technology Management | National Academies.” September 2022. https://www.nationalacademies.org/trb/blog/the-era-of-smart-infrastructure-demands-strong-data-and-technology-management.

National Center for Atmospheric Research. n.d. “Pikalert®.” NCAR Research Applications Laboratory. Accessed September 22, 2022. https://ral.ucar.edu/solutions/products/pikalert.

National Highway Traffic Safety Administration. 2020. “AV TEST Initiative | Automated Vehicle Tracking Tool.” June 2020. https://www.nhtsa.gov/automated-vehicle-test-tracking-tool.

“OSADP/Pikalert-Vehicle-Data-Translator-.” 2020. JavaScript. OSADP. https://github.com/OSADP/Pikalert-Vehicle-Data-Translator-.

Ozbay, Kaan, and Nebahat Noyan. 2006. “Estimation of Incident Clearance Times Using Bayesian Networks Approach.” Accident Analysis & Prevention 38 (3): 542–55. https://doi.org/10.1016/j.aap.2005.11.012.

Pinellas Suncoast Transit Authority (PSTA). 2020. “PSTA Launches First of Its Kind AV Pilot in Tampa Bay Region | Mass Transit.” Mass Transit. November 24, 2020. https://www.masstransitmag.com/alt-mobility/autonomous-vehicles/press-release/21164072/pinellas-suncoast-transit-authority-psta-psta-launches-first-of-its-kind-av-pilot-in-tampa-bay-region.

Pisano, Paul. 2018. “Integrated Modeling for Road Condition Prediction (IMRCP).” FHWA-JPO-17-601. USDOT Road Weather Management. https://rosap.ntl.bts.gov/view/dot/34715.

Pourhomayoun, Mohammad. 2020. “Automatic Traffic Monitoring and Management for Pedestrian and Cyclist Safety Using Deep Learning and Artificial Intelligence.” 20–29. California Department of Transportation. https://rosap.ntl.bts.gov/view/dot/51786.

Pugliese, Raffaele, Stefano Regondi, and Riccardo Marini. 2021. “Machine Learning-Based Approach: Global Trends, Research Directions, and Regulatory Standpoints.” Data Science and Management 4 (December): 19–29. https://doi.org/10.1016/j.dsm.2021.12.002.

Rekor Systems. 2021a. “Rekor Systems Announces Selection of Waycare Technologies by Louisiana Department of Transportation and Development for Pilot Program to Reduce State Traffic Congestion and Crashes.” Press Release. September 9, 2021. https://www.rekor.ai/post/rekor-systems-announces-selection-of-waycare-technologies-by-louisiana-department-of-transportation-and-development.

Rekor Systems. 2021b. “Rekor Subsidiary Waycare Launches Road Safety Pilot with the Utah Department of Transportation (UDOT) and Utah Department of Public Safety (DPS).” Press Release. September 21, 2021. https://www.rekor.ai/post/rekor-subsidiary-waycare-launches-road-safety-pilot-with-the-utah-department-of-transportation-udot-and-utah-department-of-public-safety-dps.

Rekor Systems. 2022. “Missouri DOT Selects Rekor Systems’ Advanced AI-Driven Solutions to Improve Highway Congestion and Reduce Traffic Fatalities.” Press Release. June 9, 2022. https://www.rekor.ai/post/missouri-dot-selects-rekor-systems-advanced-ai-driven-solutions-to-improve-highway-congestion-and-reduce-traffic-fatalities.

Rittmuller, Robert J. 2022. “SHRP2 NDS Video Analytics (SNVA) v0.2.2.” Python. Volpe National Transportation Systems Center. https://github.com/VolpeUSDOT/SNVA.

Roadbotics. 2022. “Dublin, Ohio Case Study.” Roadbotics.Com (blog). March 10, 2022. https://www.roadbotics.com/dublin-ohio-case-study/.

Roberts, Jack. 2021. “Virginia Port to Evaluate Autonomous Trucks.” February 1, 2021. https://www.truckinginfo.com/10135804/virginia-port-authority-receives-federal-grant-to-evaluate-autonomous-truck-capa.

Russell, Sheldon M., Myra Blanco, Jon Atwood, W. Andy Schaudt, Vikki L. Fitchett, and Scott Tidwell. 2018. “Naturalistic Study of Level 2 Driving Automation Functions.” DOT HS 812 642. National Highway Traffic Safety Administration.

SAE ORAD Committee, and ISO TC204/WG14. 2021. “J3016_202104: Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor Vehicles - SAE International.” Society of Automative Engineers International. https://www.sae.org/standards/content/j3016_202104/.

Sanchez, Robert, Michelle Neuner, and Tracy B. Gonzalez. 2020. “Integrated Modeling for Road Condition Prediction – Phase 3 Evaluation Report.” FHWA-HOP-20-062. Federal Highway Administration. https://rosap.ntl.bts.gov/view/dot/55716.

Santana, Eder, and George Hotz. 2016. “Learning a Driving Simulator.” arXiv. https://doi.org/10.48550/arXiv.1608.01230.

Santos, Kenny, Joao P. Dias, and Conceicao Amado. 2022. “A Literature Review of Machine Learning Algorithms for Crash Injury Severity Prediction.” Journal of Safety Research 80: 254–69. https://doi.org/10.1016/j.jsr.2021.12.007.

Sheehan, Dan. 2021. “ATCMTD Project Update: Recent Accomplishments and Upcoming Activities.” Metropolitan Washington Council of Governments presented at the Commuter Connections, Washington, DC, November 16. https://www.mwcog.org/file.aspx?&A=6u8qlO2E5UwHHc5g3wyKrRyblySEQwQ1r9neVUtPgb8%3D.

Sighencea, Bogdan Ilie, Rare Ion Stanciu, and Ctlin Daniel Cleanu. 2021. “A Review of Deep Learning-Based Methods for Pedestrian Trajectory Prediction.” Sensors 21 (22). https://doi.org/10.3390/s21227543.

Silva, Philippe Barbosa, Michelle Andrade, and Sara Ferreira. 2020. “Machine Learning Applied to Road Safety Modeling: A Systematic Literature Review.” Journal of Traffic and Transportation Engineering (English Edition) 7 (6): 775–90. https://doi.org/10.1016/j.jtte.2020.07.004.

Singer, Nancy. 2017. “Press Release: FHWA 17G-17 - FHWA Awards $4 Million Grant to South Carolina’s Greenville County for Automated Taxi Shuttles, 10/4/2017 | Federal Highway Administration.” October 4, 2017. https://www.fhwa.dot.gov/pressroom/fhwa1717g.cfm.

Singer, Nancy. 2020a. “U.S. Department of Transportation Awards $2.6 Million for Tennessee’s Artificial Intelligence Tools for Integrated Corridors.” FHWA Newsroom. June 16, 2020. https://highways.dot.gov/newsroom/us-department-transportation-awards-26-million-tennessees-artificial-intelligence-tools.

Singer, Nancy. 2020b. “U.S. Department of Transportation Awards Nearly $3 Million to the Metro Washington Council of Governments’ Dynamic Travel Demand Management Project.” FHWA Newsroom. June 16, 2020. https://highways.dot.gov/newsroom/us-department-transportation-awards-nearly-3-million-metro-washington-council-governments.

Singer, Nancy. 2020c. “U.S. Department of Transportation Awards $4.6 Million to Pinellas County for Pinellas Connected Community.” FHWA Newsroom. December 31, 2020. https://highways.dot.gov/newsroom/us-department-transportation-awards-46-million-pinellas-county-pinellas-connected.

Singh, Amita, Magnus Wiktorsson, and Jannicke Baalsrud Hauge. 2021. “Trends In Machine Learning To Solve Problems In Logistics.” Procedia CIRP 103 (January): 67–72. https://doi.org/10.1016/j.procir.2021.10.010.

Singh, S. 2015. “Critical Reasons for Crashes Investigated in the National Motor Vehicle Crash Causation Survey.” DOT HS 812 115. Washington, DC: National Highway Traffic Safety Administration. https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/812115.

Southern Nevada TMC. 2019. “Waycare Platform Deployment in Southern Nevada Traffic Management Center.” National Operations Center of Excellence Case Study. May 23, 2019. https://transportationops.org/case-studies/waycare-platform-deployment-southern-nevada-traffic-management-center.

Stone, Tom. 2021. “Utah DOT Launches AI Asset Management Pilot with Blyncsy.” Traffic Technology Today (blog). May 27, 2021. https://www.traffictechnologytoday.com/news/asset-management/utah-dot-launches-ai-asset-management-pilot-with-blyncsy.html.

Svitak, Tyler, dir. 2022. AvCo Video_2022 Update. https://www.avco.city/.

Tang, Ruifan, Lorenzo De Donato, Nikola Besinovi, Francesco Flammini, Rob M. P. Goverde, Zhiyuan Lin, Ronghui Liu, Tianli Tang, Valeria Vittorini, and Ziyulong Wang. 2022. “A Literature Review of Artificial Intelligence Applications in Railway Systems.” Transportation Research Part C: Emerging Technologies 140. https://doi.org/10.1016/j.trc.2022.103679.

Townsend, Haley, Matthew Samach, Kelly Bare, Mecit Cetin, Sherif Ishak, and Kaan Ozbay. 2024. NCHRP Research Report 1122: Implementing Machine Learning at State Departments of Transportation: A Guide. Transportation Research Board, Washington, DC.

Tran, Tram, Callum Parker, and Martin Tomitsch. 2021. “A Review of Virtual Reality Studies on Autonomous Vehicle-Pedestrian Interaction.” IEEE Transactions on Human-Machine Systems 51 (6): 641–52. https://doi.org/10.1109/THMS.2021.3107517.

Tsai, Meng-Ju, Zhiyong Cui, Hao Yang, and Yinhai Wang. 2022. “Traffic-Twitter Transformer: A Nature Language Processing-Joined Framework for Network-Wide Traffic Forecasting,” https://doi.org/10.48550/arXiv.2206.11078.arXiv.

Vasudevan, Meenakshy, Haley Townsend, Thao Nhi Dang, Amy O’Hara, Carolina Burnier, and Kaan Ozbay. 2020. “Identifying Real-World Transportation Applications Using Artificial Intelligence (AI): Summary of Potential Application of AI in Transportation.” FHWA-JPO-20-787. Intelligent Transportation Systems Joint Program Office. https://rosap.ntl.bts.gov/view/dot/50651.

Vasudevan, Meenakshy, Haley Townsend, Matt Samach, Atizaz Ali, Patrick Walsh, Peiwei Wang, Anand Seshadri, and Ian McManus. 2022. “(Draft Report) Artificial Intelligence (AI) for Intelligent Transportation Systems (ITS): Challenges and Potential Solutions, Insights, and Lessons Learned.” FHWA-JPO-XX-XXX. U.S. DOT Intelligent Transportation Systems Joint Program Office.

Vasudevan, Meenakshy, Haley Townsend, Edward Schweikert, Karl Wunderlich, Carolina Burnier, Britton Hammit, Douglas Gettman, and Kaan Ozbay. 2020. “Identifying Real-World Transportation Applications Using Artificial Intelligence (AI)- Real-World AI Scenarios in Transportation for Possible Deployment.” FHWA-JPO-20-810. https://rosap.ntl.bts.gov/view/dot/50752.

Vaswani, Ashish, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017. “Attention Is All You Need.” Advances in Neural Information Processing Systems 30.

Vermont Agency of Transportation. 2020. “Vermont Automated Vehicle Testing Permit.” Vermont Agency of Transportation Policy, Planning, and Intermodal Development https://vtrans.vermont.gov/sites/aot/files/planning/documents/planning/VT%20AV%20Testing%20Guidance%20andDivision.%20Application101520.pdf.

Virginia DOT. 2022. “RFP AI-Based Decision Support System.” eVA. March 14, 2022. https://mvendor.cgieva.com/Vendor/public/ADVSODetails.jsp?PageTitle=SO%20Details&DOC_CD=RFP&Details_Page=ADVSODetails.jsp&DEPT_CD=A501&BID_INTRNL_NO=1884&BID_NO=1884&BID_VERS_NO=3.

Wakhisi, Kofi, Maria Roell, Polly Okunieff, Natalie Smusz-Mengelkoch, J.D. Schneeberger, Atlanta Regional Commission, and Go Systems and Solutions. 2022. “Phase 1 Systems Engineering Management Plan (SEMP) — ARC ITS4US Deployment Project.” FHWA-JPO-21-915. ITS Joint Program Office. https://rosap.ntl.bts.gov/view/dot/62483.

Wang, Ning, Kunpeng Zhang, Liang Zheng, Jaeyoung Lee, and Shukai Li. 2023. “Network-Wide Traffic State Reconstruction: An Integrated Generative Adversarial Network Framework with Structural Deep Network Embedding.” Chaos, Solitons & Fractals 174 (September): 113830. https://doi.org/10.1016/j.chaos.2023.113830.

Wang, Yuan, Dongxiang Zhang, Ying Liu, Bo Dai, and Loo Hay Lee. 2019. “Enhancing Transportation Systems via Deep Learning: A Survey.” Transportation Research Part C: Emerging Technologies 99 (February): 144–63. https://doi.org/10.1016/j.trc.2018.12.004.

Work, Dan. 2022. “Improving ICM through AI.” Presented at the ASCE International Conference on Transportation & Development, Seattle, WA, June 2.

Xiang, X., Z. Wang, and Y. Qiao. 2022. “An Improved YOLOv5 Crack Detection Method Combined With Transformer.” IEEE Sensors Journal, IEEE Sens. J. (USA), 22 (14): 14328–35. https://doi.org/10.1109/JSEN.2022.3181003.

Xu, Yufei, Yu Wang, and Srinivas Peeta. 2022. Leveraging Transformer Model to Predict Vehicle Trajectories in Congested Urban Traffic. Transportation Research Record: Journal of the Transportation Research Board, No. 2677(2), pp. 898–909. https://doi.org/10.1177/03611981221109594.

Yan, H., X. Ma, and Z. Pu. 2021. “Learning Dynamic and Hierarchical Traffic Spatiotemporal Features With Transformer.” IEEE Transactions on Intelligent Transportation Systems, 1–14. https://doi.org/10.1109/TITS.2021.3102983.

Yan, Ran, Shuaian Wang, and Harilaos N. Psaraftis. 2021. “Data Analytics for Fuel Consumption Management in Maritime Transportation: Status and Perspectives.” Transportation Research Part E: Logistics and Transportation Review 155 (November): 102489. https://doi.org/10.1016/j.tre.2021.102489.

Yifan, Sui, Zhou Shaodong, Ju Zhiyang, and Zhang Hui. 2022. “A Vision-Based System Design and Implementation for Accident Detection and Analysis via Traffic Surveillance Video.” IEEE Canadian Journal of Electrical and Computer Engineering, IEEE Can. J. Electr. Comput. Eng. (USA), 45 (2): 171–81. https://doi.org/10.1109/ICJECE.2022.3154294.

Yin, Xueyan, Genze Wu, Jinze Wei, Yanming Shen, Heng Qi, and Baocai Yin. 2021. “Deep Learning on Traffic Prediction: Methods, Analysis and Future Directions.” IEEE Transactions on Intelligent Transportation Systems.

Young, Rhonda, Brittany Welch, and Amanda Siems-Anderson. 2019. “Generating Weather Alerts Including High Wind Blowover Hazards Using Pikalert(R) for the Wyoming Connected Vehicle Pilot Project.” https://sicop.transportation.org/wp-content/uploads/sites/36/2019/06/TRB_2019_RYoung.pdf.

Yu, Zhuoping, Xiaozhou Ren, Yuyao Huang, Wei Tian, and Junqiao Zhao. 2020. Detecting Lane and Road Markings at A Distance with Perspective Transformer Layers.

Zantalis, Fotios, Grigorios Koulouras, Sotiris Karabetsos, and Dionisis Kandris. 2019. “A Review of Machine Learning and IoT in Smart Transportation.” Future Internet 11 (4): 94.

Zhang, Jiaming, Kailun Yang, Angela Constantinescu, Kunyu Peng, Karin Muller, and Rainer Stiefelhagen. 2022. “Trans4Trans: Efficient Transformer for Transparent Object and Semantic Scene Segmentation in Real-World Navigation Assistance,” IEEE Transactions on Intelligent Transportation Systems, https://doi.org/10.1109/TITS.2022.3161141.

Zhang, Jiawei, Maosi Geng, Jiangsa Gu, and Xiqun Chen. 2021. “Short-Term Speed Forecasting of Large-Scale Urban Road Network Based on Transformer.” In CICTP 2021, 609–18. https://doi.org/10.1061/9780784483565.059.

Zhang, Yunfeng, Ross Cutts, and Jianshu Xu. 2021. “Implementing Machine Learning With Highway Datasets.” MD-21SHA/UM/5-23. Maryland Department of Transportation (SPR). https://rosap.ntl.bts.gov/view/dot/56625.

Zhou, Hao, Jorge Laval, Anye Zhou, Yu Wang, Wenchao Wu, Zhu Qing, and Srinivas Peeta. 2022. Review of Learning-Based Longitudinal Motion Planning for Autonomous Vehicles: Research Gaps Between Self-Driving and Traffic Congestion. Transportation Research Record: Journal of the Transportation Research Board, No. 2676(1), pp. 324–341. https://doi.org/10.1177/03611981211035764.

Zhu, L., F. R. Yu, Y. Wang, B. Ning, and T. Tang. 2019. “Big Data Analytics in Intelligent Transportation Systems: A Survey.” IEEE Transactions on Intelligent Transportation Systems 20 (1): 383–98. https://doi.org/10.1109/TITS.2018.2815678.

Zhu, Meixin, Simon S. Du, Xuesong Wang, Hao Frank Yang, Ziyuan Pu, and Yinhai Wang. 2022. “TransFollower: Long-Sequence Car-Following Trajectory Prediction through Transformer,” arXiv.

Zhu, Z., and H. Zhao. 2022. “A Survey of Deep RL and IL for Autonomous Driving Policy Learning.” IEEE Transactions on Intelligent Transportation Systems 23 (9): 14043–65. https://doi.org/10.1109/TITS.2021.3134702.