This project seeks to examine whether trafficβ 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. βββββββ
The Safe-D Fall 2018 Workshop was held on September 12, 2018, kicking off the Fall 2018 Call for Proposals.
States are required to have access to annual average daily traffic (AADT) for all public paved roads, including non-Federal aid system (NFAS) roadways. The expectation is to use AADT estimates in data-driven safety analysis. Because collecting data on NFAS roads is financially difficult, agencies are interested in exploring affordable ways to estimate AADT. The goal of this project was to determine the accuracy of AADT estimates developed from alternative data sources and quantify the impact of AADT on safety analysis. The researchers compared 2017 AADT data provided by the Texas Department of Transportation (DOT) and the Virginia DOT against probe-based … Webinar: Use of Disruptive Technologies to Support Safety Analysis and Meet New Federal Requirements
Β Media Contact Eric Holbrook 540-231-9301 eholbrook@vtti.vt.edu News Archive Eileen Herbers named among top transportation students in the country January 9, 2024 (Virginia Tech News) β A fifth-year doctoral student in biomedical engineering and mechanics at Virginia Tech, Eileen Herbers, was named the Student of the Year for the Safe-D: Safety through Disruption University Transportation Center. Herbers was presented with the award for her work on measuring the potential safety impact of automated driving systems at the Council of University Transportation Centers Awards Banquet preceding the Transportation Research Board Annual Meeting on Jan. 6. Virginia Tech Transportation Institute researchers to … Press
(aka Senior Mixer or SMX) Problem Older adult drivers typically experience age-related declines in sensory, cognitive, and psychomotor abilities that might affect their ability to drive safely. Automation is envisioned as a potential remedy to help these individuals continue to maintain their driving safety and mobility. However, the benefits of automated features or advanced driver assistance systems (ADAS) depend on a variety of factors including trust, acceptance, adoption, understanding, as well as usage patterns and the ability to realize the full benefits of such systems. The objective of this study was to investigate whether ADAS can benefit mobility and driving … Examining Senior Driversβ Adaptation to Mixed-Level Automated Vehicles
This project will develop a method to evaluate street noise and documented crash rates on roadways.
Recording Title/Project/Date Speaker Webinar Overview Link (YouTube) Title: Micromobility Regulation Best Practices Review: Scoot Now, Regulate Later Project: Safe-D TTI-05-04 Date: March 26, 2024 Gretchen Stoeltje, J.D., Texas A&M Transportation Institute This webinar will present the scope, methodology and findings of the Safe-D project Micromobility Regulation Best Practices Review (aka Scoot Now, Regulate Later). This project sought to locate data about e-scooter crashes, their actual causes, who or what party was responsible for the cause, and who or what party might be legally liable for the cause based on a combination of statutory and contractual assignment of that liability. The … Webinar Archive
The Transportation Research Board (TRB) 98th Annual Meeting will be held January 13β17, 2019, at the Walter E. Washington Convention Center, in Washington, D.C. The information-packed program is expected to attract more than 13,000 transportation professionals from around the world.Β
The project will evaluate statistical and other related methods that could simplify the analysis of the unique attributes related to safety and transportation-related big data, and present guidelines that can be used by researchers and practitioners for simplifying data analyses.
This project will investigate the influences on motor vehicle and bicyclist operations within a corridor.