Aggregating uncertain sensor information for safety related systems

نویسنده

  • R. Savić
چکیده

Safety related systems for automotive applications need reliable information for robust assessment of potentially dangerous driving situations. However, sensor may provide both wrong and uncertain data. This paper proposes a reliable aggregation of sensor data for safety related systems. Herein, the Dempster-Shafer theory is applied to combine multiple unreliable and uncertain knowledge sources. Information about various possibly observed objects are expressed as basic probability assignments and combined by Dempster’s and Yager’s rule of combination. Hence the approach allows the simple fusion of COTS sensor data while preserving uncertainty and conflict between these knowledge sources. To illustrate the approach sensors of a lane change assistance system are briefly discussed, which describes a new generation of advanced driver assistance system for automotive application.

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تاریخ انتشار 2006