A Comparative Study of Event Data Recorder (EDR) Parameter Systems in American and Japanese Passenger Vehicles: Using Actual CDR Data from Toyota (2010 Model) and Jeep (2014 Model) as Examples

Dingwei Chen*
Traffic Management, Guangdong Police College School of Public Security, Guangzhou 510440, China
*Corresponding email: 3416867896@qq.com

With the global proliferation and standardisation of Event Data Recorders (EDRs) in motor vehicles, data fusion across different vehicle brands during accident reconstruction faces technical challenges stemming from incompatible parameter systems. This study examines two representative vehicles – a Toyota (2010 model year, Association for Computing Machinery (ACM) supplied by DENSO) and a Jeep (2014 model, ACM supplied by TRW) as representative subjects. Utilising Bosch Call Detail Record (CDR) tools to extract real collision data, this study systematically compared differences between Japanese and American EDR parameter systems across six dimensions: event recording architecture, collision pulse (ΔV) sampling strategy, pre-collision data acquisition, restraint system trigger logic, data integrity markers, and parameter notation conventions. Findings reveal: Toyota EDR possesses comprehensive multi-event temporal correlation fields yet employs a compliance-oriented minimalist strategy characterised by low sampling frequency and limited parameter types. Jeep EDR demonstrates high sampling precision and rich parameter coverage, enabling detailed recording of driver evasive manoeuvres, but exhibits weaker event management logic through a product competitiveness-driven expansive strategy. Significant discrepancies exist between the two systems in event numbering logic, sampling standards, ΔV symbol definitions, and incomplete event representation methods, directly creating technical barriers to cross-brand accident reconstruction. This study constructs a four-dimensional comparative framework, extracts quantifiable difference metrics, and analyses typical cases to reveal the root causes of these discrepancies. It proposes standardisation recommendations including unified event benchmarks, standardised sampling frequencies and parameter sets, unified coordinate system definitions, and the promotion of common data formats. This provides theoretical foundations and technical support for the integrated application of multi-brand EDR data and the scientific advancement of traffic accident investigation.

References
[1] Gutierrez-Osorio, C., Pedraza, C. (2020) Modern data sources and techniques for analysis and forecast of road accidents: a review. Journal of Traffic and Transportation Engineering (English Edition), 7(4), 432-446.
[2] Rosen, R. E. (2021) Critical dialogue and regulation: learning from engineering mistakes. Transp. LJ, 48, 1.
[3] Ziemiak, M. P. (2019) Event Data Recorder (EDR) systems in the context of claims adjustment in motor insurance. A case of Poland. Prawo Asekuracyjne, 4(101), 33-47.
[4] Merkens, K., Baumann-Pickering, S., Ziegenhorn, M. A., Trickey, J. S., Allen, A. N., Oleson, E. M. (2021) Characterizing the long-term, wide-band and deep-water soundscape off Hawai’i. Frontiers in Marine Science, 8, 752231.
[5] Hamzah, N., Zaman, F. K., Abdullah, S. C., Mazalan, L., Abidin, H. Z., Ahmad, Y. (2023) A review on event data recorder and its implementation in Malaysia: Existing standards and challenges. Journal of the Society of Automotive Engineers Malaysia, 7(3), 183-195.
[6] Kuforiji, J. (2025) Digital Forensics and Incident Response (DFIR) automation: Leveraging AI to accelerate breach investigation, evidence collection, and cyberattack mitigation. Journal of Data Analysis and Critical Management, 1(04), 1-19.
[7] Silva, C., Faria, P., Vale, Z. (2023) Demand response implementation: Overview of Europe and United States status. Energies, 16(10), 4043.
[8] Uribe-Pérez, N., Gonzalez-Garrido, A., Gallarreta, A., Justel, D., González-Pérez, M., González-Ramos, J., Bidaguren, P. (2024) Communications and data science for the success of vehicle-to-grid technologies: current state and future trends. Electronics, 13(10), 1940.
[9] Zhang, S., Shi, J., Huang, Y., Shen, H., He, K., Chen, H. (2024) Investigating the effect of dynamic traffic distribution on network-wide traffic emissions: an empirical study in Ningbo, China. PLoS One, 19(7), e0305481.
[10] Siegel, J. E., Erb, D. C., Sarma, S. E. (2017) A survey of the connected vehicle landscape – architectures, enabling technologies, applications, and development areas. IEEE Transactions on Intelligent Transportation Systems, 19(8), 2391-2406.

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Chen, D. (2025) A Comparative Study of Event Data Recorder (EDR) Parameter Systems in American and Japanese Passenger Vehicles: Using Actual CDR Data from Toyota (2010 Model) and Jeep (2014 Model) as Examples. Scientific Research Bulletin, 2(6), 1-11.

Published

25/02/2026