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This paper presents the confidence assessment algorithm of lane mark detected by a vision sensor for lane change decision and its application to lane-level localization. The lane mark information is critical to determine whether driving maneuver is either lane following or lane change. Furthermore, it should be considered that the detected lane mark could be wrong due to its worn-out or soil/snow/obstacles...
This paper presents a lane-level localization algorithm based on situational awareness fusing radar, vision, GPS, and digital map on highway. Under the assumption that the maximum number of lanes is known by both GPS and digital map, the position of a vehicle is determined in a term of lane-level position via situational awareness on highway. The situational awareness aims at recognizing maneuver...
In this paper, a vehicle recognition algorithm based on radar and vision sensors is proposed with the application to automatic emergency braking. While the commercial radar detects both vehicles and road infrastructure including guardrail and tunnel, in general it does not distinguish between a vehicle and a non-vehicle object. Furthermore, it is well known that while it provides relatively coarse...
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