Inference of large truck driver's intent to change lanes to pass a lead vehicle via analyses of driver's eye glance behavior in the real world

Abstract
Inference of driver's intent is a vital issue for developing intelligent driving support systems. In this study, we analyzed two professional truck drivers' eye glance behavior when they changed lanes in the real world and developed a method to detect the driver's intent to change lanes. The method was effective detecting the drivers' intent just before they initiated a lane change maneuver. This method is essentially the same as the method proposed in Zhou et al. (2006). We conclude that Zhou, et al. (2006)'s detection algorithm would be useful for professional drivers in the real world.

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