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http://dx.doi.org/10.5302/J.ICROS.2015.14.9007

Multiple Vehicle Recognition based on Radar and Vision Sensor Fusion for Lane Change Assistance  

Kim, Heong-Tae (Department of mechanical engineering, Ajou University)
Song, Bongsob (Department of mechanical engineering, Ajou University)
Lee, Hoon (ADAS recognition development team, Hyundai motor company)
Jang, Hyungsun (ADAS recognition development team, Hyundai motor company)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.21, no.2, 2015 , pp. 121-129 More about this Journal
Abstract
This paper presents a multiple vehicle recognition algorithm based on radar and vision sensor fusion for lane change assistance. To determine whether the lane change is possible, it is necessary to recognize not only a primary vehicle which is located in-lane, but also other adjacent vehicles in the left and/or right lanes. With the given sensor configuration, two challenging problems are considered. One is that the guardrail detected by the front radar might be recognized as a left or right vehicle due to its genetic characteristics. This problem can be solved by a guardrail recognition algorithm based on motion and shape attributes. The other problem is that the recognition of rear vehicles in the left or right lanes might be wrong, especially on curved roads due to the low accuracy of the lateral position measured by rear radars, as well as due to a lack of knowledge of road curvature in the backward direction. In order to solve this problem, it is proposed that the road curvature measured by the front vision sensor is used to derive the road curvature toward the rear direction. Finally, the proposed algorithm for multiple vehicle recognition is validated via field test data on real roads.
Keywords
vehicle recognition; guardrail recognition; road curvature;
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Times Cited By KSCI : 3  (Citation Analysis)
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