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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 521 - 540 of 613 results
  • Use of Machine Learning to Predict LongTerm Skid Resistant of Concrete Pavement
    Use of Machine Learning to Predict Long-Term Skid Resistant of Concrete Pavement
    Rajabipour, Farshad ;
    Yoon, Jinyoung
    2021-11-30 | PDF
    An adequate level of skid resistance over the service life of concrete pavements is crucial for the safety of drivers, especially in wet weather. It has been known that frictional properties of concrete pavements are influenced by concrete mixture proportions, type/properties of aggregates, surface texturing, and degree of surface polishing. Severa ...
  • Cooperative Perception of Roadside Unit and Onboard Equipment with Edge Artificial Intelligence for Driving Assistance [supporting datasets]
    Wang, Yinhai ;
    Sun, Wei
    2021-11-29 | PDF
    Recently, 2D detection in images has made significant progress owing to the emergence of a convolutional neural network (CNN), which can extract high-level features from the images. However, detecting objects in 3D instead of 2D space is an essential topic when building perception systems for autonomous driving. An autonomous vehicle (AV) needs to ...
    Dataset Supporting Files
  • AERMOD RLINE and RLINEXT Case Study Analyses in Atlanta Georgia
    AERMOD, RLINE, and RLINEXT Case Study Analyses in Atlanta, Georgia
    Guensler, Randall ;
    Lu, Hongyu
    2021-11-05 | PDF
    This research assessed the impact of USEPA's AERMOD dispersion model (version of 19191) source types on predicted pollutant concentrations via a case study for the I-75/I-575 Northwest Corridor (NWC) in Atlanta, GA. Using MOVES-Matrix for MOVES 2014b, carbon monoxide (CO) emissions rates for every hour of a one-year study period were generated usin ...
  • Accelerating Rural Road Safety Using Artificial Intelligence to Unlock Predictive Insights from Videolog Data
    Accelerating Rural Road Safety Using Artificial Intelligence to Unlock Predictive Insights from Videolog Data
    Yi, Hong ;
    Bizon, Chris
    2021-11-01 | PDF
    Roadway safety, especially in rural areas, is one of the most critical components in transportation planning. In collaboration with North Carolina Department of Transportation (NCDOT), UNC Highway Safety Research Center (HSRC), and DOT Volpe National Transportation Systems Center, UNC Renaissance Computing Institute (RENCI) developed a roadside fea ...
  • Improved Disaster Management Through Automated Damage Assessment Using Unmanned Aerial Vehicles UAVs
    Improved Disaster Management Through Automated Damage Assessment Using Unmanned Aerial Vehicles (UAVs)
    Haddad, Rami J ;
    Gonzalez Bocanegra, Maria
    2021-11-01 | PDF
    Natural disasters cause devastating effects on transportation networks by causing significant damage and obstruction on frequently traveled roads. This report describes the design and implementation of an automated Unmanned Aerial Vehicle (UAV) based damage management using convolutional neural networks (CNNs). This system utilizes image processing ...
  • Estimating Switching Times of Actuated Coordinated Traffic Signals A Deep Learning Approach
    Estimating Switching Times of Actuated Coordinated Traffic Signals: A Deep Learning Approach
    Eteifa, Seifeldeen ;
    Rakha, Hesham A.
    2021-11-01 | PDF
    Acceleration and deceleration maneuvers at signalized intersections are a major hindrance to fuel-efficient vehicle operations. Green Light Optimal Speed Advisory (GLOSA) allows for the control of vehicles in a fuel-efficient manner but requires reliable estimates of signal switching times. This study attempts to utilize data from actuated coordina ...
  • Analytical Models for Traffic Congestion and Accident Analysis
    Analytical Models for Traffic Congestion and Accident Analysis
    Liu, Hongrui ;
    Shetty, Rahul Ramachandra
    2021-11-01 | PDF
    In the US, over 38,000 people die in road crashes each year, and 2.35 million are injured or disabled, according to the statistics report from the Association for Safe International Road Travel (ASIRT) in 2020. In addition, traffic congestion keeping Americans stuck on the road wastes millions of hours and billions of dollars each year. Using stati ...
  • The Transportation Future Trends Transportation and Travel
    The Transportation Future: Trends, Transportation, and Travel
    United States. Federal Highway Administration
    2021-11-01 | PDF
    Transportation is undergoing a period of significant change in the United States, evident by changes in transportation demand. Many factors influence transportation demand and in different ways. Some trends increase demand; some decrease demand; and others shift demand across modes, time of day, and geographies. Technological advances, coupled with ...
  • Combining Crowdsourcing and Machine Learning to Collect Sidewalk Accessibility Data at Scale [supporting datasets]
    Froehlich, Jon E
    ORCID ICON IMG
    2021-10-27 | PDF
    The authors are developing new data collection approaches that use a combination of remote crowdsourcing, machine learning, and online map imagery. Their newest effort, called Project Sidewalk, enables online crowdworkers to remotely label pedestrian-related accessibility problems by virtually walking through city streets in Google Street View. In ...
    Dataset Supporting Files
  • Truck Parking Pattern Aggregation and Availability Prediction by Deep Learning
    Truck Parking Pattern Aggregation and Availability Prediction by Deep Learning
    Yang, Hao ;
    Liu, Chenxi
    2021-10-20 | PDF
    With the significant increase of e-commerce, freight transportation demand has surged significantly over the past decade. Most of the demand has been served by trucks in the United States. One major problem commonly identified across the country is the worsening truck parking availability because the increase of truck parking facilities has lagged ...
  • Artificial Intelligence AI for Intelligent Transportation Systems ITS Program Emerging and Enabling Technologies Research
    Artificial Intelligence (AI) for Intelligent Transportation Systems (ITS) Program Emerging and Enabling Technologies Research
    United States. Department of Transportation. Intelligent Transportation Systems Joint Program Office
    2021-10-05 | PDF
    The ITS Joint Program Office (JPO) established the AI for ITS Program recognizing the promise AI offers for achieving significant benefits in safety, mobility, efficiency, equity, accessibility, productivity, resilience, and reductions to individual and societal costs, emissions, and other negative environmental impacts. AI refers to processes that ...
  • Driver Performance and Behavior in Adverse Weather Conditions Microsimulation and Variable Speed Limit Implementation of the SHRP2 Naturalistic Driving Study Results Phase 3
    Driver Performance and Behavior in Adverse Weather Conditions: Microsimulation and Variable Speed Limit Implementation of the SHRP2 Naturalistic Driving Study Results - Phase 3
    Ahmed, Mohamed ;
    Das, Anik
    2021-10-01 | PDF
    The negative impact of adverse weather conditions on traffic safety and operation is the primary focus of many studies. However, in-depth investigations of driver behavior and performance during adverse weather at a trajectory level using naturalistic driving data are limited. Over the years, researchers have utilized aggregate traffic and weather ...
  • Application of Machine Learning Techniques to Pavement Performance Modeling
    Application of Machine Learning Techniques to Pavement Performance Modeling
    Ashtiani, Ali Z
    2021-10-01 | PDF
    The Federal Aviation Administration (FAA) has initiated research to develop models of long-term airport pavement performance that can be incorporated into a methodology for extended-life pavement design. This report includes a review of machine learning (ML) techniques for prediction of long-term pavement performance. The study examined applicabili ...
  • Exploring the Relationship Between Mandatory Helmet Use Regulations and Adult Cyclists Behavior in California Using Hybrid Machine Learning Models
    Exploring the Relationship Between Mandatory Helmet Use Regulations and Adult Cyclists' Behavior in California Using Hybrid Machine Learning Models
    Kakhki, Fatemeh Davoudi ;
    Chierichetti, Maria
    2021-10-01 | PDF
    In 2019, the National Transportation Safety Board recommended the introduction of all-ages helmet law, to reduce fatalities involving cyclists. Even though the benefits of wearing helmets in protecting cyclists against trauma in cycling crashes has been documented, the use of helmets is still limited, and there is opposition against mandatory helme ...
  • Comparing Combining Existing Emerging Data Collection Modeling Strategies in Support of Signal Control Optimization Management
    Comparing & Combining Existing & Emerging Data Collection & Modeling Strategies in Support of Signal Control Optimization & Management
    Hadi, Mohammed ;
    Sisiopiku, Virginia
    2021-09-14 | PDF
    For decades, traffic signal management agencies have used signal timing optimization tools combined with fine-tuning of signal timing based on field observations in their updates of time-of-day signal timing plans. These traditional signal optimization methods and tools use very limited amount of data and depend on default values in the signal timi ...
  • Deep Learning Architectures for SkateboarderPedestrian Surrogate Safety Measures
    Deep Learning Architectures for Skateboarder-Pedestrian Surrogate Safety Measures
    Shourov, Chowdhury Erfan ;
    Sarkar, Mahasweta
    2021-09-12 | PDF
    Skateboarding as a method of transportation has become prevalent, which has increased the occurrence and likelihood of pedestrian-skateboarder collisions and near-collision scenarios in shared-use roadway areas. Collisions between pedestrians and skateboarders can result in significant injury. New approaches are needed to evaluate shared-use areas ...
  • Developing a DataDriven Safety Assessment Framework for RITI Communities in Washington State 2021
    Developing a Data-Driven Safety Assessment Framework for RITI Communities in Washington State [2021]
    Wang, Yinhai ;
    Sun, Wei
    2021-09-10 | PDF
    The roadway safety of the Rural, Isolated, Tribal, or Indigenous (RITI) communities has become an important social issue in the United States. Official data from the Federal Highway Administration (FHWA) shows that, in 2012, 54 percent of all fatalities occurred on rural roads while only 19 percent of the US population lived in rural communities. U ...
  • Impact of Connected and Autonomous Vehicles on Nontraditional Intersection Design Superstreets
    Impact of Connected and Autonomous Vehicles on Nontraditional Intersection Design: Superstreets
    Fan, Wei (David) ;
    Liu, Shaojie
    2021-09-01 | PDF
    Congestion has been becoming a critical issue for transportation professionals as it increases travel time, energy use and pollutant emissions. Thanks to recent technology development of wireless communication and artificial intelligence, connected and autonomous vehicles (CAVs) become a promising and practical approach to increasing road capacity. ...
  • Best Practice Operation of Reversible Express Lanes for the Kennedy Expressway
    Best Practice Operation of Reversible Express Lanes for the Kennedy Expressway
    Mohammadian, Abolfazl ;
    Parsa, Amir Bahador
    2021-09-01 | PDF
    Reversible lanes in Chicago's Kennedy Expressway are an available infrastructure that can significantly improve traffic performance; however, a special focus on congestion management is required to improve their operation. This research project aims to evaluate and improve the operation of reversible lanes in the Kennedy Expressway. The Kennedy Exp ...
  • Deep Reinforcement Learningbased Project Prioritization for Rapid PostDisaster Recovery of Transportation Infrastructure Systems
    Deep Reinforcement Learning-based Project Prioritization for Rapid Post-Disaster Recovery of Transportation Infrastructure Systems
    Lee, Yong-Cheol ;
    Choi, Kunhee
    2021-09-01 | PDF
    Among various natural hazards that threaten transportation infrastructure, flooding represents a major hazard in Region 6's states to roadways as it challenges their design, operation, efficiency, and safety. The catastrophic flooding disaster event generally leads to massive obstruction of traffic, direct damage to highway/bridge structures/paveme ...
521 - 540 / 613
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