Presentations and Training Materials

Information and resources to learn about heavy vehicle event data recorders (HVEDRs), the recovery of the data, and how to interpret the information.

Digital Forensics of Heavy Vehicle Event Data Recorders

This section contains some of the course contents and links for the class taught by Dr. Daily through the University of Tulsa.

Class Presentations from Day 1.pdf

Crash Data Attribution Excel Worksheet.xlsx

Smart Sensor Simulator 2 Overview 2017.pdf

Extracting Event Data from Memory Chips within a Detroit Diesel DDEC V

Jeremy Daily, Andrew Kongs, James Johnson, Jose Corcega

The University of Tulsa


The proper investigation of crashes involving commercial vehicles is critical for fairly assessing liability and damages, if they exist. In addition to traditional physics based approaches, the digital records stored within heavy vehicle electronic control modules (ECMs) are useful in determining the events leading to a crash. Traditional methods of extracting digital data use proprietary diagnostic and maintenance software and require a functioning ECM. However, some crashes induce damage that renders the ECM inoperable, even though it may still contain data. As such, the objective of this research is to examine the digital record in an ECM and understand its meaning. The research was performed on a Detroit Diesel DDEC V engine control module. The data extracted from the flash memory chips include: Last Stop Record, two Hard Brake events, and the Daily Engine Usage Log. The procedure of extracting and reading the memory chips is explained. Details regarding decoding the memory contents to determine meaning are given for the aforementioned datasets. This research revealed higher fidelity data in memory for the Daily Engine Usage Log when compared to the DDEC Reports output. Should an ECM be inoperable, the techniques presented can help investigators extract previously unobtainable information.


SAE Presentation Slides On Chip Level Forensics