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A Multi-target Tracking Algorithm for Application to Adaptive Cruise Control  

Moon Il-ki (Department of Automotive Engineering, Hanyang University)
Yi Kyongsu (School of Mechanical Engineering, Hanyang University)
Cavency Derek (Department of Mechanical Engineering, University of California)
Hedrick J. Karl (Department of Mechanical Engineering, University of California)
Publication Information
Journal of Mechanical Science and Technology / v.19, no.9, 2005 , pp. 1742-1752 More about this Journal
Abstract
This paper presents a Multiple Target Tracking (MTT) Adaptive Cruise Control (ACC) system which consists of three parts; a multi-model-based multi-target state estimator, a primary vehicular target determination algorithm, and a single-target adaptive cruise control algorithm. Three motion models, which are validated using simulated and experimental data, are adopted to distinguish large lateral motions from longitudinally excited motions. The improvement in the state estimation performance when using three models is verified in target tracking simulations. However, the performance and safety benefits of a multi-model-based MTT-ACC system is investigated via simulations using real driving radar sensor data. The MTT-ACC system is tested under lane changing situations to examine how much the system performance is improved when multiple models are incorporated. Simulation results show system response that is more realistic and reflective of actual human driving behavior.
Keywords
Interacting Multiple Model; Probabilistic Data Association; Adaptive Cruise Control; Stop and Go Cruise Control; Advanced Safety Vehicle; Milli-meter Wave Radar;
Citations & Related Records

Times Cited By Web Of Science : 1  (Related Records In Web of Science)
Times Cited By SCOPUS : 7
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