Abstract: Increasingly, drivers are choosing to buy usage-based automobile insurance (UBI). While researchers have introduced telematics data into automobile insurance pricing, they often neglect the effect of in-vehicle active safety management on crash risk. Manage-how-you-drive (MHYD) insurance, a new type of UBI, incorporates active safety management to monitor driver behavior and manage crash risk. This study examines the key factors underlying large commercial truck crashes based on telematics-related characteristics and in-vehicle monitoring features, and quantifies the effect of these factors on crash risk. A total of 2,185 truck vehicles combined with 105,786 trips and 465,555 in-vehicle monitoring warnings were used in this study. A zero-inflated Poisson (ZIP) regression model was built to assess crash risk and factors affecting it: travel characteristics, driving behavior, and in-vehicle monitoring warning characteristics. A ZIP model without warning variables was considered for comparison, and the standardized regression coefficient method identified the most important variables. The study found that, first, the model considering in-vehicle monitoring warning information is significantly better than the model without warning information. Second, in-vehicle monitoring warning information about yawn and smoke influenced the number of crashes significantly more than did other travel characteristics and driving behavior variables. Finally, freeway mileage, percentage of trips on sunny days, percentage of trips at night, and average speed on freeway also correlated significantly with crash risk. These results can provide a reference for UBI insurance professionals considering active safety management, as well as support freight companies in drafting appropriate working regulations.
Xuxin Zhang, Xuesong Wang*, Yanli Bao, Xiaohui Zhu. Truck safety assessment based on GPS and in-vehicle monitoring data. Transportation Research Board 101st Annual Meeting, Washington D.C., USA, 2022. 1.9-13.