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http://dx.doi.org/10.5302/J.ICROS.2013.13.1874

Neighboring Vehicle Maneuver Detection using IMM Algorithm for ADAS  

Jung, Sun-Hwi (Department of Automotive Engineering, Kookmin University)
Lee, Woon-Sung (Department of Automotive Engineering, Kookmin University)
Kang, Yeonsik (Department of Automotive Engineering, Kookmin University)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.19, no.8, 2013 , pp. 718-724 More about this Journal
Abstract
In today's automotive industry, there exist several systems that help drivers reduce the possibility of accidents, such as the ADAS (Advanced Driver Assistance System). The ADAS helps drivers make correct and quick decisions during dangerous situations. This study analyzed the performance of the IMM (Interacting Multiple Model) method based on multiple Kalman filters using the data acquired from a driving simulator. An IMM algorithm is developed to identify the current discrete state of neighboring vehicles using the sensor data and the vehicle dynamics. In particular, the driving modes of the neighboring vehicles are classified by the cruising and maneuvering modes, and the transition between the states is modeled using a Markovian switching coefficient. The performance of the IMM algorithm is analyzed through realistic simulations where a target vehicle executes sudden lane change or acceleration maneuver.
Keywords
active safety system; ADAS (Advanced Driver Assistance System); vehicle tracking;
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Times Cited By KSCI : 1  (Citation Analysis)
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