CMT is a trusted, peer-reviewed source of government data.

CMT’s driving analyses have been reviewed and published by the largest government transportation agencies including the National Highway Transportation Safety Administration, the US Department of Transportation, and the Federal Highway Administration.

Our analyses have also been validated by leading safety organizations, academic institutions, and medical associations including the Insurance Institute for Highway Safety (IIHS),  MIT,  National Academy of Science, Stanford University, and the Journal of the American Medical Association (JAMA). 

Learn more about CMT’s validated data studies

IIHS: CMT data provided insights into distracted driving beyond NOPUS’s scope that can be applied on a nationwide scale

“Telematics-derived analysis has been shown to provide a representative sample equal to, and exceeding, the analysis derived from NOPUS observations.” 

–  National Distracted Driving Coalition, in reference to CMT’s 2024 work with IIHS

MIT: CMT trip data, combined with advanced modeling techniques and other sources, can predict high-risk driving with granularity and precision that is representative of road risk – with or without historical crash data

“Besides the improved performance and the useful maps we generated, our evaluations provide insights into how to achieve high performance in the face of accident data sparsity.”

– MIT Study, in reference to creating predictive maps that are representative of real road risk

Stanford: CMT’s data was validated as an accurate representation of the driving population as a whole by comparing it with data from TomTom

“We repeat our analysis on an alternative source of telematics data, from TomTom, and obtain broadly similar results … The estimated coefficients are qualitatively similar to those found with the CMT data—including the heterogeneity across cities.”

– Stanford University Study, in reference to validating CMT’s analytics as a representation of the driving population as a whole

JAMA: CMT driver and passenger identification accuracy is 96.5%

“Smartphone telematics apps hold great promise for measuring and improving driving behavior at scale … Our results confirm that this classification can be done with minimal error using smartphone telematics data.”

– Journal of the American Medical Association, on the reliability of using telematics

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