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 […]
Abstract With the integration of SAE Level 4 or Highly Automated Vehicle’s (Level 4 Vehicle) into our environment, the development of external communication systems is underway by numerous stakeholders across the globe. Mixed fleets, comprised of both human drivers and automated vehicles, must be able to effectively communicate with each other. Most research on level […]
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, […]
Abstract This project aims to develop a general evaluation protocol for transit readiness in the area for Automated shuttle implementation. Using the data gathered from the EasyMile shuttle implemented in Fairfax County, Virginia, the research team will perform risk assessments and safety analysis for the automated shuttle to understand the risks associated with the interactions […]
Abstract In fall 2020, a novel autonomous-vehicle (AV) service named ENDEAVRide will start pilot testing in Nolanville, a typical rural town in central Texas. The AV will serve as a taxicab and a mobile telemedicine portal. This project marks the first attempt to conduct a real-world assessment of AV’s potential safety impacts as a disruptive […]
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 […]
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 […]
Abstract The National Highway Traffic Safety Administration (NHTSA) recently granted permission to deploy low-speed autonomous delivery vehicles (ADVs). Unlike conventional low-speed vehicles, these ADVs are designed to have no human occupants and they operate exclusively using an automated driving system. However, extensive safety-related issues of these vehicles have not been examined. With the enormous […]
Abstract This project will propose testing and evaluation criteria to investigate crash compatibility between autonomous and human-driven vehicles, with consideration of different potential crash scenarios. Finite element computer models will then be utilized to conduct predictive simulations investigating potential cases of impacts between human-driven and autonomous vehicles. Current regulations defining IIHS testing criteria will be […]
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 […]
Theme Areas: Transportation as a Service
This project will result in an updated scooter design that will induce safer riding behavior. A study conducted by the Austin Public Health Department (APH) and the CDC found that only one of 190 injured e-scooter users wore helmets while operating the scooter.
This project proposes a sensor fusion approach to augment radar data in a scaled environment that uses an off-the-shelf LiDAR as a high spatial resolution sensor.
This research project will investigate road user interactions with e-scooters.
This case-study project will provide an in-depth examination of e-scooter safety considerations through a data-driven approach using Austin as the proposed study site.
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.
This project will use a combination of Radars and FIR cameras in addition to a LIDAR based system to map the environment and localize the vehicle with respect to the lanes on the road.
This project will develop a diagnostic system for estimating the leakage and stroke of the pushrod and corroborating the efficacy of the developed system on an experimental air brake system setup.
This project will the data ownership and privacy implications of big data collection and processing.
This project will identify how the BVI community perceives the safety of TNCs relative to other travel modes, and how the BVI community utilizes TNCs for safe mobility.
This project will examine disruptive technologies that could address critical transportation safety challenges in future years.
This project will assess the potential of TNCs to enhance safety by decreasing the number of older drivers on the roadways while increasing their mobility options.
This project will conduct an analysis of the current state of child passengers and child safety seat use in ride-sourced vehicles along with other more traditional sources of transit such as taxicabs.
Theme Areas: Transportation as a Service
The project will allow analysis of data during several distinct phases of smartphone app use.
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