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Lyft is betting the future of the road centers on sharing autonomous vehicles.
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During the process, road center points are also extracted, which introduces a search direction for solving possible blocking problems.
Eye movement behavior was assessed during normal driving using the following performance indicators: number of glances away from road, mean duration away from road, max duration away from road, and percentage road center.
The definition of "percentage road center" was gaze data residing in a circle with 8° radius, centered on the main mode of the gaze data, according to Victor et al. [30].
Equipped with ADAS, drivers allocated more attention to the road center rather than the left and right, crossed intersections in shorter time, engaged in higher speeds, and crossed more often with a critical time-to-collision (TTC) value.
No significant main effect of gender or hearing status arose for the eye movement behavior measures, and no significant interaction effect of condition + hearing status emerged and for percentage road center.
As shown in Fig. 1, the road centreline may be completely defined by assigning the road curvature κ as a function of the road length s, and the position and orientation of the vehicle can be defined using its position s along the route, the distance n from the road center and orientation α relative to the road direction.
In short, the Nordic prediction method first calculates the unattenuated noise level 10 meters from the road center using the number of light and heavy vehicles and the speed limit of each road segment.
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