Safe-D: Safety through Disruption

Critical Areas in Advanced Driver Assistance Systems Safety: Point of Sale and Crash Reporting


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 current crash investigation forms. The current Model Minimum Uniform Crash Criteria includes limited guidance on crash avoidance technologies and most state crash reports do not include ADAS variables. Realizing the full benefit of ADAS relies on salespeople, consumers, and law enforcement understanding their benefits and limitations in improving traffic safety. This project investigated the state of knowledge and current practices on how ADAS technologies are marketed and sold, how ADAS are notated in crash reports, and what existing crash data reveal about ADAS in crash involvement to help illuminate and address gaps in current pre-sale and post-crash ADAS research.

Project Highlights

  • Added to the on-going and growing discussion about widely available and rapidly evolving vehicle safety technologies, particularly by developing a conceptual model of the entire ADAS ecosystem and highlighting research gaps.
  • Demonstrated the need for more research in the pre-purchase phase of ADAS, particularly focused on automaker approaches to marketing, selling, and training regarding ADAS, and the potential need for regulation to standardize practices.
  • Developed recommendations for improvements to a federal crash investigation system and database (NHTSA’s CISS).
  • Developed recommendations for updates to police crash report forms and revealed a need for more research into the best methods for post-crash data collection related to ADAS.

Final Report

06-003 Final Report

EWD & T2 Products

This project created a set of graphical briefs including:

Student Impact Statement(pdf): Five students received funding from and/or worked on this project (Quan Sun; Ph.D., Urban and Regional Science; Landscape Architecture & Urban Planning, Kelly Brasseaux; Master of Urban Planning; Landscape Architecture & Urban Planning; Jaden Banze; Bachelor of Science, Electrical and Computer Engineering; Electrical and Computer Engineering; Divij Batra; Bachelor of Science, Industrial & Systems Engineering; Industrial & Systems Engineering; Ran Wei; Ph.D. Industrial & Systems Engineering; Industrial & Systems Engineering). This file contains a statement by Quan Sun, Kelly Brasseaux and Jaden Branze as to the impact this project had on education and workforce development.


Goddard, T., and Sanders, R.. (2024, February 15). Conceptual Model of the Advanced Driver Assistance Systems (ADAS) Ecosystem:
Gaps in the Literature and Research Needs. Webinar SafeD Virtual Webinar is 
available here. PDF of PowerPoint slides from Webinar available here.

Goddard, T., McDonald, A., Wei, R., & Batra, D. (2022). Advanced Driver Assistance Systems in Top-Selling Vehicles in the United States: Cost, Vehicle Type, and Trim Level Disparities. Findings.

Schoner, J., Sanders, R., & Goddard, T. (2023). Effects of Advanced Driver Assistance Systems on Impact Velocity and Injury Severity: An Exploration of Data from the Crash Investigation Sampling System. Transportation Research Record, 03611981231189740.

Sun, Q., Goddard, T., Sanders, R., Brasseaux, K. (2023). The Role of Police Crash Reporting in Determining the Safety Implications of Vehicle Technologies. Conference paper, Association of Collegiate Schools of Planning Annual Conference, Chicago, IL.

Goddard, T., Sanders, R., Brasseaux, K., & Sun, Qu. (2024). A Conceptual Model of the ADAS Ecosystem: Gaps in the Literature and Research Needs. Poster Session. Transportation Research Board Annual Meeting, Washington, DC.

Lectern session, Transportation Research Board Annual Meeting 3:45-5:30 pm ET, January 9, 2023, “Effects of Advanced Driver Assistance Systems on Impact Velocity and Injury Severity – An Exploration of Data from the Crash Investigation Sampling System”.

Lectern session, Association of Collegiate Schools of Planning, 01:15-2:45 pm CT, October 20, 2023, “The Role of Police Crash Reporting in Determining the Safety Implications of Vehicle Technologies”.

Texas Technology Task Force Meeting, December 7, 2023. Panel title: Needs of a Changing Texas: Preparing the Next Generation Mobility System. TxDOT Stassney.

Final Dataset

The final datasets for this project are located in the Safe-D Collection on the VTTI Dataverse; DOI: 10.15787/VTT1/HEU2CL.

Research Investigators (PI*)

Tara Goddard (TTI/TAMU)*
Rebecca Sanders (Safe Streets)

Project Information

Start Date: 2021-09-01
End Date: 2023-08-31
Status: Complete
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

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