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Sensors 2016, 16(10), 1668; doi:10.3390/s16101668

Effective World Modeling: Multisensor Data Fusion Methodology for Automated Driving

1
Integrated Vehicle Safety department, Netherlands Organization for Applied Scientific Research TNO, Helmond 5700 AT, The Netherlands
2
Department of Mechanical Engineering, Eindhoven University of Technology, Eindhoven 5600 MB, The Netherlands
*
Author to whom correspondence should be addressed.
Academic Editors: Xue-Bo Jin, Feng-Bao Yang, Shuli Sun and Hong Wei
Received: 22 July 2016 / Revised: 2 September 2016 / Accepted: 26 September 2016 / Published: 11 October 2016
(This article belongs to the Special Issue Advances in Multi-Sensor Information Fusion: Theory and Applications)
View Full-Text   |   Download PDF [1648 KB, uploaded 11 October 2016]   |  

Abstract

The number of perception sensors on automated vehicles increases due to the increasing number of advanced driver assistance system functions and their increasing complexity. Furthermore, fail-safe systems require redundancy, thereby increasing the number of sensors even further. A one-size-fits-all multisensor data fusion architecture is not realistic due to the enormous diversity in vehicles, sensors and applications. As an alternative, this work presents a methodology that can be used to effectively come up with an implementation to build a consistent model of a vehicle’s surroundings. The methodology is accompanied by a software architecture. This combination minimizes the effort required to update the multisensor data fusion system whenever sensors or applications are added or replaced. A series of real-world experiments involving different sensors and algorithms demonstrates the methodology and the software architecture. View Full-Text
Keywords: multisensor; data fusion; world modeling; automated driving multisensor; data fusion; world modeling; automated driving
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MDPI and ACS Style

Elfring, J.; Appeldoorn, R.; van den Dries, S.; Kwakkernaat, M. Effective World Modeling: Multisensor Data Fusion Methodology for Automated Driving. Sensors 2016, 16, 1668.

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