Research Project

Defective truck equipment is a significant cause of many truck accidents and incidents. Planned or unannounced inspections are critical for ensuring truck safety while greatly hindering fleet operational efficiency and mobility.  Conducting safety inspection programs with a minimum impact on the mobility of commercial vehicle fleets, therefore, becomes a practical challenge for maintaining fleet safety and efficiency.

This research examines commercial vehicle fleets’ safety-efficiency tradeoffs by analyzing historical inspection records of multiple commercial motor carriers. Two algorithms, including K-means clustering and Latent Dirichlet Allocation, collectively analyzed different temporal-spatial failure modes among vehicles and carriers. The identified component failure modes could prioritize inspection and maintenance plans for inspectors, drivers and fleet managers, which help avoid repetitive out-of-service violations and improve fleet operational strategies with less mobility reduction. 

In the United States, vehicles such as trucks are federally mandated to undergo safety and maintenance inspections. The truck inspection rate is affected by multiple factors. This research explored the impacts of the vehicle make, vehicle driving area, vehicle age, and vehicle mileage on the overall inspection rate and vehicle component level inspection rate of heavy trucks and trailers, and designed graphical user interfaces for human-machine interaction to help truck fleet managers and truck drivers make better decisions through data analysis results in the dashboard.