Multi-level Dempster-Shafer Speed Limit Assistant

  • Jérémie Daniel
  • Jean-Philippe Lauffenburger
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 164)


This paper deals with a Speed Limit Assistant (SLA) performing the fusion of a Geographic Information System (GIS) and a vision system. The present strategy is based on multi-level data fusion using Evidence Theory. In a first step, the GIS reliability is estimated through GIS criteria related to the positioning, the localization and the digital map resolution. Contextual criteria also extracted from the GIS define the belief masses of the speed candidates. Afterwards, a multi-criterion fusion is processed to detect potential GIS incoherences (difference between the GIS speed and the road context). The second fusion level (the multi-sensor fusion) then combines the GIS and vision information by considering these sensors as specialized sources. In order to manage the conflict, the Proportional Conflict redistribution Rule 5 (PCR5) has been chosen. The benefits of the proposed solution are shown through real experiments performed with a test vehicle.


Geographical Information System Intelligent Transportation System Evidence Theory Focal Element Geographical Information System Data 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Modélisation Intelligence Processus Systèmes (MIPS) laboratoryMulhouse CedexFrance

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