Safe-D: Safety through Disruption

Research

Safe-D Project featured in USDOT RD&T UTC Video Forum on Artificial Intelligence in Transportation

Traffic Monitoring: Virginia Beach, VA

USDOT’s University Transportation Centers (UTC) program as part of the Office of Research, Development and Technology, in collaboration with the Intelligent Transportation Systems Joint Program Office (ITS/JPO), presented a series of video forums focused on emerging technologies and research in transportation.

CIITR’s Jason Wu Applies LiDAR Sensors to Safety, Traffic Monitoring

TTI researchers collect data for LiDAR research on The Texas A&M University System’s RELLIS Campus.

Texas A&M Transportation Institute (TTI) researchers in the Center for International Intelligent Transportation Research (CIITR) are currently implementing a pilot roadside LiDAR-based traffic monitoring system at international ports of entry (POEs).

Driving Risk Evaluation Web Application

Feng Guo

Detecting crashes and near-crashes in real-time can greatly benefit traffic safety management, development of safety countermeasures, and naturalistic driving data analysis.

Public Information Officers’ Quick Reference: Social Media Guidelines for Discussing Automated Vehicles

As part of a research project (Data Mining Twitter to Improve Automated Vehicle Safety), Safe-D researchers have created guidelines for automated vehicle crash responses to help public information officers structure their communications about crashes.

Increasing safety for electric cars and pedestrians

Michael Roan works in the Acoustics, Signal Processing, and Immersive Reality Lab. Photo provided by Michael Roan.

An interdisciplinary research group at Virginia Tech is using an award of $550,000 to create a virtual environment to test safety measures for the interaction between electric vehicles (EVs) and pedestrians. The award is an 18-month project funded by the Safety through Disruption (Safe-D) University Transportation Center.