DocumentCode
3082696
Title
PerSEE: A central sensors fusion electronic control unit for the development of perception-based ADAS
Author
Gruyer, Dominique ; Belaroussi, Rachid ; Xuanpeng Li ; Lusetti, Benoit ; Revilloud, Marc ; Glaser, Sebastien
Author_Institution
Dev. & Network Component & Syst. Dept., French Inst. of Sci. & Technol. for Transp., Versailles, France
fYear
2015
fDate
18-22 May 2015
Firstpage
250
Lastpage
254
Abstract
Automated vehicles and Advanced Driver Assistance Systems (ADAS) face a variety of complex situations that are dealt with numerous sensors for the perception of the local driving area. Going forward, we see an increasing use of multiple, different sensors inputs with radar, camera and inertial measurement the most common sensor types. Each system has its own purpose and either displays information or performs an activity without consideration for any other ADAS systems, which does not make the best use of the systems. This paper presents an embedded real-time system to combine the attributes of obstacles, roadway and ego-vehicle features in order to build a collaborative local map. This embedded architecture is called PerSEE: a library of vision-based state-of-the-art algorithms was implemented and distributed in processors of a main fusion electronic board and on smart-cameras board. The embedded hardware architecture of the full PerSEE platform is detailed, with block diagrams to illustrate the partition of the algorithm on the different processors and electronic boards. The communications interfaces as well as the development environment are described.
Keywords
automotive electronics; cameras; embedded systems; intelligent transportation systems; road vehicle radar; sensor fusion; traffic engineering computing; PerSEE platform; advanced driver assistance systems; automated vehicles; central sensor fusion electronic control unit; collaborative local map; communications interfaces; egovehicle features; embedded hardware architecture; embedded real-time system; fusion electronic board; inertial measurement; perception-based ADAS; roadway; sensor types; smart-cameras board; vision-based state-of-the-art algorithms; Cameras; Radar tracking; Roads; Sensor fusion; Vehicles;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Vision Applications (MVA), 2015 14th IAPR International Conference on
Conference_Location
Tokyo
Type
conf
DOI
10.1109/MVA.2015.7153178
Filename
7153178
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