Abstract Automated driving systems (ADS) are being developed faster than any point in history. There is a need to have an independent system to measure the safety of ADS across technologies and corporations. There are a variety of efforts around the world trying to estimate the impact of these systems on safety both prior to … Measuring the Safety of ADS: How safe is safe enough?
Abstract Intersection related traffic crash and fatalities are one of the major concerns for road safety. In this project we aim to understand the major cause of conflicts at an intersection by studying the intricate interplay between all the roadway agents. We propose to use the current traffic camera systems to automatically process traffic video … Real Time Risk Prediction at Signalized Intersection Using Graph Neural Network
Abstract Frequent vehicle collisions involving pedestrians or bicyclists indicate that there are opportunities to improve safe walking or biking. Concerns for child safety are among the strongest impediments to children walking or biking to school, but for some, walking or bicycling to school is a necessity due to financial or other circumstances. In fact, walking … Evaluating the Safe Routes to School (SR2S) transportation program in socially vulnerable communities in San Diego County, California
Abstract During the last decade, non-motorized modes of transportation, including cycling and walking, have been spreading as they are considered economical, eco-friendly, and energy-efficient. With the expansion of active transportation, statistics show a significant increase in the number of fatalities. Between 2010 and 2019, there was a 36 percent increase in bicycle deaths in the … Developing a framework for prioritizing bicycle safety improvement projects using crowdsourced and image-based data
Abstract Improving safety during interactions between human drivers and automated vehicles requires an environment where autonomous vehicle software can interact with realistic human driving behavior. Generating this behavior has been challenging due to a lack of driver models that accurately reflect both vehicle kinematics and driver cognition. In this project, we propose to develop an … Enhancing automated vehicle safety through testing with realistic driver models
Abstract A significant majority of the state of the art autonomous sensing and navigation technologies rely on good lane markings or detailed 3D maps of the environment and are more suited for urban communities. On the other hand, a large number of rural roads in the U.S. do not have lane markings and have irregular … Technology to Ensure Equitable Access to Automated Vehicles for Rural Areas
Abstract Automated vehicle technologies vary from simple alerts to partially automated driving tasks that are increasingly available in today’s vehicles. Advanced driver assistance systems (ADAS) seek to alert a driver to critical events (e.g., forward collision warning) or even intervene (e.g., emergency braking, lane-keeping steering) to prevent crashes. These technologies, however, are not available equally … Critical Areas in Advanced Driver Assistance Systems Safety: Point of Sale and Crash Reporting
Abstract Traffic crashes are a leading cause of death in the United States. The conventional safety evaluation methods incorporate safety modeling to determine the risk scoring of the roadways and provide these risk maps in non-reproducible format. For roadway users, these risk maps are not usable in their daily roadway trips. On the other hand, … Developing AI-driven Safe Navigation Tool
Abstract Roadway safety improvement in low-income and ethnically diverse communities in the United States has long been a major concern. This research is defined to addresses this issue by developing a data-driven approach and computational tools to quantify the equity issues in roadway safety. Particularly, we explore two important research questions: (1) What is the … Building Equitable Safe Streets for All: Data-Driven Approach and Computational Tools
Abstract Humans operating motor vehicles are often required to engage in decision-making while under substantial cognitive loads imposed by the driving environment itself. Experiencing elevated emotions can influence driver decision-making in a way that increases the risk to the safety of the driver and system performance. Emotion regulation techniques (ERTs) can be used to improve … Evaluating Emotion Regulation Techniques for Supporting Driving Safety and Performance
Abstract Safety issues that stem from commercial truck parking shortages are a national concern. National hours-of-service (HOS) regulations limit drivers’ time on the road, in an attempt to increase safety by limiting fatigue; thereby, creating a need for drivers to locate safe, secure, and legal parking wherever they are when or before they hit … Connected Vehicle Information for Improving Safety Related to Unknown or Inadequate Truck Parking
Abstract Advanced driver assistance systems (ADAS) have significantly improved safety on today’s roadways but their impact may be limited by driver errors. Understanding and identifying these driver errors will require the integration of multi-domain datasets through predictive modeling and data integration approaches. The goals of this project are to identify relevant datasets for ADAS … Identifying Deviations from Normal Driving Behavior
Abstract This project is inspired by major gaps identified in the literature pertaining to the work zone safety monitoring systems that leverage advanced technologies for tracking workers, identifying hazardous situations, and alerting individuals in danger. The existing systems have two key shortcomings. First, they either target safety hazards external to the work zone (e.g., only … A Holistic Work Zone Safety Alert System through Automated Video and Smartphone Sensor Data Analysis
Abstract Distracted drivers are involved in approximately 4 million vehicle accidents each year in the U.S. (Dingus et al. 2016). These crashes result in many lives lost and billions of dollars in damages. This widespread issue has resulted in the adoption of regulations in the European Union that will require all new vehicles produced by mid-2022 to be equipped with driver monitoring … Improving Methods to Measure Attentiveness through Driver Monitoring
Abstract COVID-19 has led to a reduction in vehicle miles traveled by motorized vehicles. Anecdotal evidence suggests that there may a shift to non-motorized modes. Getting more of the Virginia Tech community (including student, faculty, and staff) to walk, use the bus, carpool or ride bicycles for alternative transportation to decrease dependency on vehicle use … Using Health Behavior Theory and Relative Risk Information to Increase and Inform Use of Alternative Transportation
Abstract The increased popularity of rideshare scooters was recently observed due to their availability, accessibility, and low cost. Benefits to their use include reduced traffic congestion and more environmentally friendly alternative to motor vehicles. However, there are some concerns regarding the safety of riders and the impacts these vehicles have on those who share roads … Simulation-based approach to investigate the electric scooter rider protection during traffic accidents. A step forward for safer e-scooters and for standardized national safety policies
Abstract Driver impairment, due to drowsiness or fatigue, has a significant impact on the safety of all road users. Assessing an impairment such as driver drowsiness, through the use of vehicle-based technology, continues to be an area of interest. Both the initial detection, as well as continued monitoring, of driver drowsiness have been the emphasis … Behavioral Indicators of Drowsy Driving: Active Search Mirror Checks
Abstract The goal of the proposed project is to systematically extract traffic safety information from multiple complex sources of flood monitoring such as remote sensing technologies, flow gages, and weather stations, which can support informed planning for transportation safety against flooding in future smart cities. Flooding poses a significant hazard to the moving vehicles … Evaluation of transportation safety against flooding in disadvantaged communities
Alternative Title Assessment of Work Zone Pre-Crash Scenarios Using Crowdsourced Data Abstract Pavements play a vital role in the transportation infrastructure in the United States. Damage to public road transportation infrastructure causes roadways to fail to perform as intended and increases crash risks. Road damage must be detected quickly and accurately in order to maintain … Detecting Pavement Distresses Using Crowdsourced Dashcam Camera Images
Abstract As rented and shared micromobility options, e-scooters are new and potentially transformative app-based modes that promise to alleviate first mile/last mile mobility issues, congestion, and more. Yet their safe deployment has not yet been systematically understood or standardized by users, cities, or operators. As of December 2019, 1,500 people had been injured and … Micromobility Safety Regulation: Municipal Best Practices Review
Abstract This project supports a student in support of the National Cooperative Highway Research Program (NCHRP) Project 07-23 Access Management in the Vicinity of Interchanges and was led by Karen Dixon (TTI/TAMU)* and Maryam Shirinzadeh Dastgiri (TAMU). This project used a large volume of operational field data, micro-simulation data, and crash data to identify … Development of Analytic Method to Determine Weaving Patterns for Safety Analysis near Freeway Interchanges with Access Management Treatments (TTI/TAMU)
This study will leverage data collected from 50 participants who drove personally owned vehicles equipped with ADSs for 12 months. The work is expected to contribute to a greater understanding of the prevalence and safety consequences of ADS use on public roadways, as well as drivers’ perception of the early production ADS.
This project will deploy a fleet of e-scooters on the Virginia Tech campus through an exclusive, controlled research program which will collect data to assess safety impact, what behaviors are exhibited that may be beneficial or problematic, and ways in which kinematic and/or other data may be used to predict risky behavior and develop subsequent countermeasures.
Abstract This project encompasses four different activities to explore safety applications of emerging crowd-sourced data and datasets available from commercial aggregators. The first activity examines systems used to monitor and count pedestrian activity. Developing crash rates for these vulnerable users depends on knowing the volume of activity. Data from metropolitan planning organizations as well … Exploring Crowdsourced Monitoring Data for Safety
This project seeks to examine whether traffic volume estimates developed from disruptive technologies such as cell phones, GPS/Bluetooth devices, and alternative data sources (e.g., demographic, socioeconomic, land use data) can be used confidently and accurately to support data-driven safety analysis (i.e., network screening) to meet the 2016 Highway Safety Improvement Program (HSIP) Final Rule requirements.
This project will develop a framework which will bring together traditional and emerging data sources, and will be developed in such a way that it can be up- or down-scaled based on the available data sources of a study area. The exposure estimation output will then be used for crash assessment tailored to the needs of the study area.