Browsing Safety through Disruption (SAFE-D) University Transportation Center (UTC) by Issue Date
Now showing items 1-20 of 63
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Exploring the Science of Retroreflectivity: Curriculum for Grades 4 through 6
(SAFE-D: Safety Through Disruption National University Transportation Center, 2018-10)According to the United States Department of Commerce, careers in science, technology, engineering, and mathematics (STEM) are growing faster than occupations in other areas. However, in-class academic concepts can seem ... -
Safety Perceptions of Transportation Network Companies (TNCs) by the Blind and Visually Impaired
(SAFE-D: Safety Through Disruption National University Transportation Center, 2018-10)For individuals that are visually impaired, access to safe and reliable transportation can be a significant challenge. The limited menu of mobility options can culminate in a reduced quality of life and more difficulty ... -
Sources and Mitigation of Bias in Big Data for Transportation Safety
(SAFE-D: Safety Through Disruption National University Transportation Center, 2018-11)Emerging big data resources and practices provide opportunities to improve transportation safety planning and outcomes. However, researchers and practitioners recognize that big data includes biases in who the data represents ... -
Street Noise Relationship to Bicycling Road User Safety
(SAFE-D: Safety Through Disruption National University Transportation Center, 2018-12)Vulnerable road users, such as bicyclists, experience road noise directly. This study explored the relationship between bicycle crash risk and street-level road noise as measured in Austin, Texas and the Washington, D.C. ... -
Vehicle Operating Speed on Urban Arterial Roadways
(SAFE-D: Safety Through Disruption National University Transportation Center, 2019-01)This research explored (1) the relationship between suburban vehicle operating speed and roadway characteristics,especially the presence of bicyclists and (2) whether crowdsourced speed data could be used to estimate ... -
Behavior-based Predictive Safety Analytics – Pilot Study
(SAFE-D: Safety Through Disruption National University Transportation Center, 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 ... -
Older Drivers and Transportation Network Companies: Investigating Opportunities for Increased Safety and Improved Mobility
(SAFE-D: Safety Through Disruption National University Transportation Center, 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
(SAFE-D: Safety Through Disruption National University Transportation Center, 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 ... -
Motorcycle Crash Data Analysis to Support Development of a Retrofit Concrete Barrier System for Freeway Ramps
(SAFE-D: Safety Through Disruption National University Transportation Center, 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 ... -
Analyzing Highway Safety Datasets: Simplifying Statistical Analyses from Sparse to Big Data
(SAFE-D: Safety Through Disruption National University Transportation Center, 2019-07)Data used for safety analyses have characteristics that are not found in other disciplines. In this research, we examine three characteristics that can negatively influence the outcome of these safety analyses: (1) crash ... -
Design and Evaluation of a Connected Work Zone Hazard Detection and Communication System for Connected and Automated Vehicles (CAVs)
(SAFE-D: Safety Through Disruption National University Transportation Center, 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 ... -
Emerging Legal Issues for Transportation Researchers Using Passively Collected Data Sets
(SAFE-D: Safety Through Disruption National University Transportation Center, 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
(SAFE-D: Safety Through Disruption National University Transportation Center, 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 ... -
Factors Surrounding Child Seat Usage in Rideshare Services
(SAFE-D: Safety Through Disruption National University Transportation Center, 2019-09)This project represents a collaborative, multimodal effort to understand the current state of child passenger safety with respect to rideshare vehicles, with the aim of using this information to develop an effective set ... -
Implications of Truck Platoons for Roadside Hardware and Vehicle Safety
(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
(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, ... -
Vehicle Occupants and Driver Behavior: A Novel Data Approach to Assessing Speeding
(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 ... -
Standardized Performance Evaluation of Vehicles with Automated Capabilities
(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
(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 ... -
Exploring Crowdsourced Monitoring Data for Safety
(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 ...
