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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.

Concepts of forensic soundness as they are currently understood in the field of digital forensics are related to the digital data on heavy vehicle electronic control modules (ECMs). An assessment for forensic soundness addresses: 1) the integrity of the data, 2) the meaning of the data, 3) the processes for detecting or predicting errors, 4) transparency of the operation, and 5) the expertise of the practitioners. The integrity of the data can be verified using cryptographic hash functions. Interpreting and understanding the meaning of the data is based on standards or manufacturer software. Comparison of interpreted ECM data to external reference measurements is reviewed from the current literature. Meaning is also extracted from interpreting hexadecimal data based on the J1939 and J1587 standards. Error detection and mitigation strategies are discussed in the form of sensor simulators to eliminate artificial fault codes.