Recent Submissions

  • Real-World Use of Automated Driving Systems and their Safety Consequences: A Naturalistic Driving Data Analysis 

    Kim, Hyungil; Song, Miao; Doerzaph, Zachary R. (SAFE-D: Safety Through Disruption National University Transportation Center, 2020-11)
    Automated driving systems (ADS) have the potential to fundamentally change transportation, and a growing number of these systems have entered the market and are currently in use on public roadways. However, drivers may not ...
  • Response of Autonomous Vehicles to Emergency Response Vehicles (RAVEV) 

    Nayak, Abhishek; Rathinam, Sivakumar; Gopalswamy, Swaminathan (SAFE-D: Safety Through Disruption National UTC, 2020-06)
    The objective of this project was to explore how an autonomous vehicle identifies and safely responds to emergency vehicles using visual and other onboard sensors. Emergency vehicles can include police, fire, hospital and ...
  • Big Data Visualization and Spatiotemporal Modeling of Risky Driving 

    Jahangiri, Arash; Marks, Charles; Machiani, Sahar Ghanipoor; Nara, Atsushi; Hasani, Mahdie; Cordova, Eduardo; Tsou, Ming-Hsiang; Starner, Joshua (SAFE-D: Safety Through Disruption National UTC, 2020-07)
    Statistical evidence shows the role of risky driving as a contributing factor in roadway collisions, highlighting the importance of identifying such driving behavior. With the advent of new technologies, vehicle kinematic ...
  • Assessing Alternate Approaches for Conveying Automated Vehicle ‘Intentions’ 

    Basantis, Alexis; Miller, Marty; Doerzaph, Zachary; Neurauter, Luke (SAFE-D: Safety Through Disruption National UTC, 2020-05)
    One of the biggest highly automated vehicle (HAV) market barriers may be a lack of user trust in the automated driving system itself. Research has shown that this lack of faith in the system primarily stems from a lack of ...
  • Development of Analytic Method to Determine Weaving Patterns for Safety Analysis near Freeway Interchanges with Access Management Treatments 

    Dastgiri, Maryam Shirinzadeh; Dixon, Karen K. (SAFE-D: Safety Through Disruption National UTC, 2020-07)
    Urban arterials near freeway interchanges are vital elements of urban road infrastructures. They connect freeway network with high mobility and low access to urban network with lower mobility and higher access. This study ...
  • Identification of Railroad Requirements for the Future Automated and Connected Vehicle (AV/CV) Environment 

    Morgan, Curtis A.; Warner, Jeffery E.; Lee, Dahye; Florence, David (SAFE-D: Safety Through Disruption National University Transportation Center, 2020-06)
    The Federal Rail Administration (FRA) Highway-Rail Grade Crossing Inventory database from 2019 states that there are approximately 127,000 public, at-grade highway-rail grade crossings in the U.S. Despite this large number ...
  • Exploring Crowdsourced Monitoring Data for Safety 

    Turner, Shawn; Martin, Michael; Griffin, Greg P.; Le, Minh; Das, Subasish; Wang, Ruihong; Dadashova, Bahar; Li, Xiao (SAFE-D: Safety Through Disruption National University Transportation Center, 2020-03)
    This project included four distinct but related exploratory studies of data sources that could improve roadway safety analysis. The first effort evaluated passively gathered crowdsourced bicyclist activity data from ...
  • Formalizing Human Machine Communication in the Context of Autonomous Vehicles 

    Gopalswamy, Swaminathan; Saripalli, Srikanth; Shell, Dylan; Hickman, Jeff; Hsu, Ya-Chuan (SAFE-D: Safety Through Disruption National University Transportation Center, 2020-05)
    There are many situations where tacit communication between drivers and pedestrians governs and enhances safety. The goal of this study was to formalize this communication and apply it to the driving strategy of an autonomous ...
  • Standardized Performance Evaluation of Vehicles with Automated Capabilities 

    Basantis, Alexis; Harwood, Leslie; Doerzaph, Zachary; Neurauter, Luke (SAFE-D: Safety Through Disruption National University Transportation Center, 2019-12)
    Advanced driver-assistance systems (ADAS) are becoming widely available in the new vehicle landscape, increasing of both vehicle occupants’ and other road users’ safety. In some vehicles, longitudinal and lateral positioning ...
  • Optimizing the Lateral Wandering of Automated Vehicles to Improve Roadway Safety and Pavement Life 

    Zhou, Fujie; Hu, Sheng; Xue, Wenjing; Flintsch, Gerardo W. (SAFE-D: Safety Through Disruption National University Transportation Center, 2019-12)
    Because most automated vehicles (AVs) are programmed to follow a set path and maintain a lateral position in thecenter of the lane, over time significant pavement rutting will occur. This study directly measured AV ...
  • Vehicle Occupants and Driver Behavior: A Novel Data Approach to Assessing Speeding 

    Martin, Michael W.; Green, Lisa L.; Shipp, Eva; Chigoy, Byron; Mars, Rahul (SAFE-D: Safety Through Disruption National University Transportation Center, 2019-11)
    The question of whether driver behavior, and speeding in particular, differs based on passenger(s) presence requires the use of large amounts of data, some of which may be difficult to accurately obtain. Traditional methods ...
  • Implications of Truck Platoons for Roadside Hardware and Vehicle Safety 

    Dobrovolny, Chiara S.; Untaroiu, Costin; Sharma, Roshan; Jin, Hanxiang; Meng, Yunzhu (SAFE-D: Safety Through Disruption National University Transportation Center, 2019-10)
    Platooning is an extension of cooperative adaptive cruise control and forward collision avoidance technology, which provides automated lateral and longitudinal vehicle control to maintain short following distances and tight ...
  • Data Mining to Improve Planning for Pedestrian and Bicyclist Safety 

    Jahangiri, Arash; Hasani, Mahdie; Sener, Ipek N.; Munira, Sirajum; Owens, Justin; Appleyard, Bruce; Ryan, Sherry; Turner, Shawn M.; Machiani, Sahar Ghanipoor (SAFE-D: Safety Through Disruption National University Transportation Center, 2019-11)
    Between 2009 and 2016, the number of pedestrian and bicyclist fatalities saw a marked trend upward. Taken together, the overall percentage of pedestrian and bicycle crashes now accounts for 18% of total roadway fatalities, ...
  • Motorcycle Crash Data Analysis to Support Development of a Retrofit Concrete Barrier System for Freeway Ramps 

    Wilson, Jonathan; Sulaica, Heather; Dobrovolny, Chiara Silvestri; Perez, Marcie (Safe-D: Safety Through Disruption, 2019-07)
    This project was intended to review the most relevant national and international studies, as well as protocols and standards that were developed to support motorcycle safety on roadways. In addition, crash data analysis ...
  • Design and Evaluation of a Connected Work Zone Hazard Detection and Communication System for Connected and Automated Vehicles (CAVs) 

    Mollenhauer, Michael A.; White, Elizabeth; Roofigari-Esfahan, Nazila (Safe-D: Safety Through Disruption, 2019-08)
    Roadside work zones (WZs) present imminent safety hazards for roadway workers as well as passing motorists. In 2016, 764 fatalities occurred in WZs in the United States due to motor vehicle traffic crashes, which are the ...
  • Older Drivers and Transportation Network Companies: Investigating Opportunities for Increased Safety and Improved Mobility 

    Tooley, Melissa; Zmud, Johanna; Ettelman, Benjamin; Moran, Maarit; Higgins, Laura; Shortz, Ashley; Wheeler, Eric (Safe-D: Safety Through Disruption, 2019-06)
    Transportation network companies (TNCs) such as Uber and Lyft offer an increasingly popular alternative to driving a personal vehicle. This project investigated the potential of TNCs to increase the safety and enhance the ...
  • Driver Training Research and Guidelines for Automated Vehicle Technology 

    Manser, Michael P.; Noble, Alexandria M.; Machiani, Sahar Ghanipoor; Shortz, Ashley; Klauer, Sheila G.; Higgins, Laura; Ahmadi, Alidad (Safe-D: Safety Through Disruption, 2019-07)
    The advent of advanced driver-assistance systems presents the opportunity to significantly improve transportation safety. Complex sensor-based systems within vehicles can take responsibility for tasks typically performed ...
  • Emerging Legal Issues for Transportation Researchers Using Passively Collected Data Sets 

    Stoeltje, Gretchen; Moran, Maarit; Zmud, Johanna; Ramsey, Nijm; Stibbe, Jayson (Safe-D: Safety Through Disruption, 2019-08)
    With the advent of new technologies to gather and process data, large data sets are being collected that are of interest to transportation researchers. However, legal and ethical questions around data ownership and protection ...
  • Examining Senior Drivers Adaptation to Mixed Level Automated Vehicles: A Naturalistic Study 

    Liang, Dan; Antin, Jonathan F.; Lau, Nathan Ka Ching; Stulce, Kelly E.; Baker, Stephanie Ann; Wotring, Brian (Safe-D: Safety Through Disruption, 2019-08)
    Advances in the development of advanced vehicle technologies (AVTs), such as blind spot alerts, lane keep assist,lane alert, and adaptive cruise control, can benefit senior drivers by reducing exposure to hazards andcompensating ...
  • Behavior-based Predictive Safety Analytics – Pilot Study 

    Engström, Johan; Miller, Andrew; Huang, Wenyan; Soccolich, Susan; Machiani, Sahar Ghanipoor; Jahangiri, Arash; Dreger, Felix; de Winter, Joost (Safe-D: Safety Through Disruption, 2019-04)
    This report gives an overview of the main findings from the Behavior-based Predictive Safety Analytics – Pilot Study project. The main objective of the project was to investigate the possibilities of developing statistical ...

View more