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 or biking to school is more than twice as common among students from low-income households than students from higher income households. Creating safe routes is one key mechanism to achieve social equity goals by providing safe opportunities to walk and bike regardless of a community’s … Evaluating the Safe Routes to School (SR2S) transportation program in socially vulnerable communities in San Diego County, California
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 4 vehicle external communication has been conducted using simulator or virtual reality platforms to assess driver/road user knowledge, opinions, and attitudes via survey metrics evaluating a single level 4 vehicle. However, it is vital to understand how the external communication is perceived in real world … Allusion 2: External Communication for SAE L4 Vehicles
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, popular navigation applications such as Google Maps and Apple Maps provide distance-based or travel time-based alternative routes with no real-time risk scoring. There is a need for a real-time navigation system that can provide data-driven decision on the safest path or route. Obtaining data from … Developing AI-driven Safe Navigation Tool
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 between the automated shuttle and other road users, roadway infrastructure, and traffic conditions. Protocols for future deployment planning and evaluation of pilot programs will be developed by the research team based on the data analysis results. The project is related to transportation safety as it … Evaluation Tools for Automated Shuttle Transit Readiness of the Area
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 technology to offer older adults a pathway to continued independent mobility in underserved communities. Collaborating with industry partners, we will explore how older adults (60+) can more safely transit and get access to health care with a “2-in-1” (taxi + telemedicine) service delivered via autonomous … Exploring the Safety Impacts of the Older Population’s Access to Automated Vehicles and Telemedicine: A Real-World Experiment in Small and Rural Communities (ENDEAVRide)
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 and traffic around the VT campus and increase overall safety is a goal of the VT Alternative Transportation Department. With COVID-19 impacting carpools and the bus system due to limited capacity and possible fear of public transportation, and fear of injury related to alternative transportation … 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 and sidewalks with them (e.g. 2.4 to 18 times more people per trip are injured on e-scooter sharing than on bicycle sharing). While non-collision-induced falls seem to be the main cause of scooter injuries (~60-80%), the collisions with vehicles and pedestrians represent the causes of … 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 The National Highway Traffic Safety Administration (NHTSA) recently granted permission to deploy low-speed autonomous delivery vehicles (ADVs) on roadways. Although the mobility of ADVs is limited to low-speed roads and these vehicles are occupant-less, frequent stops and mobility among residential neighborhoods cause safety-related concerns. There is a need for a comprehensive safety impact analysis of ADVs. This study examined the safety implications and safety impacts of ADVs by using novel approaches. The objective of this study is to understand the safety-related issues associated with ADVs. Due to the limitation of acquiring large-scale vehicle movement data from ADV operators, … Autonomous Delivery Vehicle as a Disruptive Technology: How to Shape the Future with a Focus on Safety?
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 investigated to determine how the newly proposed testing conditions might need to be modified to address the worst-case testing scenario, such as maximizing the potential for occupant compartment deformation and intrusion during the crash event. Testing evaluation criteria might also have to be modified to … Crashworthiness Compatibility Investigation of Autonomous Vehicles with Current Passenger Vehicles
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 8 killed in e-scooter crashes. These devices are not yet regulated by a federal agency like the National Highway Transportation Safety Administration (NHTSA) or the Consumer Product Safety Commission (CPSC), and their use is not uniformly regulated at the municipal level. Some jurisdictions are imposing … Micromobility Safety Regulation: Municipal Best Practices Review
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 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.
The project will allow analysis of data during several distinct phases of smartphone app use.