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 across the passenger vehicle fleet, nor is there standardization in how their uses and limitations are marketed to potential buyers or demonstrated at point of sale, including by increasingly popular online “dealerships” like Vroom and Carvana. The proliferation of ADAS has also outpaced crash scene data collection methods and updates to current crash investigation forms. ADAS variables are not currently included in the Model Minimum Uniform Crash Criteria (MMUCC) guidelines and thus unlikely to exist on crash reports for most states. Realizing the full benefit of Advanced Driver Assistance Systems (ADAS) relies on salespeople, consumers, and law enforcement understanding their benefits and limitations in improving traffic safety. Through three interrelated studies, this project will investigate the state of knowledge and current practices on how ADAS technologies are marketed, sold, and demonstrated at point-of-sale, how information on ADAS is collected in crash reports, and what existing crash data reveal about the state of knowledge on ADAS in crash involvement. This project addresses gaps that create a substantial safety risk where salespeople, drivers, and law enforcement may not understand the correct use and limitations of ADAS.
Project Highlights
Coming Soon!
Final Report
Coming Soon!
EWD & T2 Products
Coming Soon!
Presentations/Publications
Coming Soon!
Research Investigators (PI*)
Tara Goddard (TTI/TAMU)*
Rebecca Sanders (Safe Streets)
Project Information
Start Date: 2021-09-01
End Date: 2023-08-31
Status: Active
Grant Number: 69A3551747115
Total Funding: Finalizing
Source Organization: Safe-D National UTC
Project Number: 06-003
Safe-D Theme Areas
Automated Vehicles
Big Data Analytics
Safe-D Application Areas
Driver Factors and Interfaces
Performance Measures
Vehicle Technology
Risk Assessment
More Information
RiP URL
UTC Project Information Form
Sponsor Organization
Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC 20590 United States
Performing Organization
Texas A&M University
Texas A&M Transportation Institute
3135 TAMU
College Station, Texas 77843-3135
USA