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Artificial Intelligence Deployment Center of Excellence (AI COE)

rosaP Repository & Open Science Access Portal

The AI COE Collection is a central resource for transportation stakeholders that may aid in deployment of safe and responsible AI in surface transportation. The collection will feature current and emerging resources, innovations, and technologies. For more information on the AI COE, go to https://highways.dot.gov/ai-coe.

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Showing 601 - 613 of 613 results
  • Lifecycle Assessment Using Snowplow Trucks Automatic Vehicle Location Data
    Lifecycle Assessment Using Snowplow Trucks' Automatic Vehicle Location Data
    Liu, Xiaoyue Cathy ;
    Yi, Zhiyan
    2021-03-21 | PDF
    Snowplow trucks serve a crucial role in winter maintenance activities by removing, loading and disposing snow. An effective performance monitoring and analysis process can assist transportation agencies in effectively managing the snowplow trucks and maintaining normal functioning of roadways. Previous literature suggests that most snowplow truck p ...
  • Big Transportation Data Analytics
    Big Transportation Data Analytics
    Liu, Xiaoyue Cathy ;
    Yi, Zhiyan
    2021-03-01 | PDF
    Traffic volume data is crucial in many applications, including transportation operation analysis, congestion management, accident prevention, etc. Yet an extensive capture of accurate volume information on a large-scale network can be difficult and costly. This research focuses on hourly traffic volume prediction in a statewide network using spatia ...
  • Utilizing Machine Learning To CrossCheck Traffic Data and Understand Urban Mobility
    Utilizing Machine Learning To Cross-Check Traffic Data and Understand Urban Mobility
    Zhang, Zhao ;
    Yang, Xianfeng (Terry)
    2021-03-01 | PDF
    At UDOT, PeMS stores point data collected by roadside radar sensors, loop detectors, and micro-loops, while ClearGuide contains statewide probe data. PeMS data can greatly support mobility pattern studies but are only available at detector locations. In contrast, ClearGuide can provide statewide traffic speed information based on probe vehicle data ...
  • Vehicle-Traffic Control with Limited-Capacity Connected/Automated Vehicles [supporting datasets]
    Ban, Xuegang (Jeff) ;
    Guo, Qiangqiang
    2021-02-09 | PDF
    This project studies methods to control both vehicle and traffic under limited penetration of low-level connected and autonomous vehicles (LCAVs). The investigation includes three major parts: (1) the Eco-Driving algorithm for a single CAV with low-level automation; (2) the vehicle in the loop (VIL) simulation platform; and (3) the integrated vehic ...
    Dataset
  • Data Mining Twitter To Improve Automated Vehicle Safety
    Data Mining Twitter To Improve Automated Vehicle Safety
    McDonald, Tony ;
    Huang, Bert
    2021-02-01 | PDF
    Automated vehicle (AV) technologies may significantly improve driving safety, but only if they are widely adopted and used appropriately. Adoption and appropriate use are influenced by user expectations, which are increasingly being driven by social media. In the context of AVs, prior studies have observed that major news events such as crashes and ...
  • A Personalized Trip Planner for Vulnerable Road Users
    A Personalized Trip Planner for Vulnerable Road Users
    Park, Hyoshin ;
    Owens, Justin M
    2021-02-01 | PDF
    This research presents an adaptive and personalized routing model that enables individuals with disabilities to save their route preferences to a mobility assistant platform. The proactive approach based on anticipated user need accommodates vulnerable road users' personalized optimum dynamic routing rather than a reactive approach passively awaiti ...
  • Rotorcraft Landing Sites An AIBased Identification System
    Rotorcraft Landing Sites - An AI-Based Identification System
    Rasool, Ghulam ;
    Bouaynaya, Nidhal
    2021-02-01 | PDF
    Location data about U.S. heliports is often inaccurate or nonexistent in the FAA's databases, which leaves pilots and air ambulance operators with erroneous information about where to find safe landing zones. In the 2018 FAA Reauthorization Act, Congress required the FAA to collect better information from the helicopter industry under part 157, whi ...
  • Intelligent Camera Aided Railway Emergency System iCARES
    Intelligent Camera Aided Railway Emergency System (i-CARES)
    Qian, Yu ;
    Wang, Yi
    2021-02-01 | PDF
    The highway-railroad grade crossings are a hot spot in terms of vehicle-train collisions. The unexpected crossing blockage not only brings traffic congestion but also raises serious safety concerns for commuters. Previous researchers have already investigated the accident loss and frequency of the accidents around the crossing areas. However, there ...
  • Development of CostEffective Sensing Systems and Analytics CeSSA To Monitor Roadway Conditions and Mobility Safety
    Development of Cost-Effective Sensing Systems and Analytics (CeSSA) To Monitor Roadway Conditions and Mobility Safety
    Ho, Chun-Hsing ;
    Zhang, Dada
    2021-01-01 | PDF
    The project presents a pavement sensing system along with a list of promising computing models that can be used to predict pavement conditions using a vehicle-based sensing technology. The project started with data acquisition obtained from the previous field data collection followed by a series of data computing using machine learning methods to d ...
  • Development of CostEffective Sensing Systems and Analytics CeSSA to Monitor Roadway Conditions and Mobility Safety Research Brief
    Development of Cost-Effective Sensing Systems and Analytics (CeSSA) to Monitor Roadway Conditions and Mobility Safety [Research Brief]
    Ho, Chun-Hsing
    ORCID ICON IMG
    2021-01-01 | PDF
    The objectives of the project are to (1) determine promising computing models for prediction of pavement distresses (2) evaluate the promising/optimum placements/locations of sensor loggers within a vehicle, and (3) provide an affordable method that will benefit state, city, county governments, as well as local communities who have an immediate nee ...
  • Predictive Deep Learning for Flash Flood Management Phase II
    Predictive Deep Learning for Flash Flood Management Phase II
    Corns, Steven M ;
    Long, Suzanna K
    2021-01-01 | PDF
    This research was completed in tandem as a project funded through MoDOT and the Mid-America Transportation Center. It used deep learning methods, along with weather information from NOAA/National Weather Service and geospatial data from the USGS National Map and other public geospatial data sources, to develop forecasting tools capable of assessing ...
  • Predictive Deep Learning for Flash Flood Management
    Predictive Deep Learning for Flash Flood Management
    Corns, Steven M ;
    Long, Suzanna K
    2021-01-01 | PDF
    This research was completed in tandem as a project funded through MoDOT and the Mid-America Transportation Center. It used deep learning methods, along with weather information from NOAA/National Weather Service and geospatial data from the USGS National Map and other public geospatial data sources, to develop forecasting tools capable of assessing ...
  • ITS Deployment Evaluation Executive Briefing Artificial Intelligence and Machine Learning for Transportation
    ITS Deployment Evaluation Executive Briefing: Artificial Intelligence and Machine Learning for Transportation
    United States. Department of Transportation. Intelligent Transportation Systems Joint Program Office
    2021-01-01 | PDF
    Artificial Intelligence (AI) is revolutionizing every walk of life, allowing machines to learn from experience, adapt, and perform tasks that have historically required human cognition. Factors that have led to increased attention to AI in the last decade include increased computing power, mass data collection and storage, and innovations in AI alg ...
601 - 613 / 613
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