The near-future deployment of high-level automation vehicles (AVs) can render promising opportunities to solve ongoing\nhindrances in modern safety-related research. Monitoring fatigued drivers on any road section is one of these challenges. Vehicle\ntrajectory big data, monitored through AVs, include key information with which to monitor fatigued drivers on roads. To mine\nthis upcoming opportunity, a new data-driven approach which allows the direct monitoring of fatigued drivers on road segments\nis proposed here for the first time. A feasible study was conducted using big vehicle trajectory data and real-life traffic accident\ndata. The results showed that fatigued drivers on a target road section can be successfully surveyed using the driving durations\nfrom departure locations to the target road section. It was found that, with a statistical correlation of 0.90, an index for fatigued\ndrivers has strong explanatory power about the traffic accident rate. This finding indicates that the proposed method will be a\npromisingmeans by which tomonitor fatigued drivers at road locations in the upcoming era of autonomous vehicles. In addition,\nthe method is immediately practicable if vehicle trajectory data are available.
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