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Multiple-Sensor-Collision avoidance system for automotive applications using an IMM approach for obstacle tracking
| Content Provider | Semantic Scholar |
|---|---|
| Author | Amditis, Angelos Polychronopoulos, Aris Karaseitanidis, Ioannis |
| Copyright Year | 2002 |
| Abstract | In this paper a multi-sensor collision avoidance system is presented for automotive applications. For obstacle detection and tracking, Millimeter Wave (MMW) Radar and a Far Infrared (FIR) Camera are chosen in order to provide object lists to the sensors trackers respectively. The algorithm of the track management, data association, filtering and prediction for both sensors is also presented, focusing on the Kalman filtering. Thus, an Interacting Multiple Model (IMM) filter is designed for coping with all possible modes in which a car may be. Finally, distributed fusion architecture, using a central track file for the objects tracks, is adopted and described analytically. The results of the work presented will be used, among others, for the purposes of European co-funded project EUCLIDE. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://fusion.isif.org/proceedings/fusion02CD/pdffiles/papers/T1D01.pdf |
| Alternate Webpage(s) | http://isif.org/fusion/proceedings/fusion02CD/pdffiles/papers/T1D01.pdf |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | Automotive Occupations Centralized computing Chimeric antigen receptor Coping Behavior Correspondence problem Entity Name Part Qualifier - adopted Extraction Finite impulse response Kalman filter Network congestion Numerous Probabilistic analysis of algorithms Radar tracker Rendering (computer graphics) Signal processing Spectroscopy, Near-Infrared Track (course) algorithm collision sensor (device) |
| Content Type | Text |
| Resource Type | Article |
