In this paper, a real-time perception system for autonomous car is presented. It is based on a highly parallel architecture using state of the art Field Programmable Gate Array (FPGA) to perform both low and intermediary levels image processing tasks at video frame rate (i.e. 30 frames / s). The hardware algorithm consists to perform noise removal and edge detection, followed by Hough transform task to extract the segments corresponding the lanes boundaries. The rich hardware resources which are available in nowadays FPGAs (e.g. large built-in distributed RAM memories, DSP blocks, and reconfigurable PLLs) yielded for a compact and low power consumption real-time vision system. Series of tests on different roads within Abu Dhabi city were successfully conducted for different scenarios such as continues lines, discontinues lines and slightly curved lines for which the car speed reached up to 122 km/h.
An embedded vision system for autonomous vehicles
ODS 2020: Industrial Optical Devices and Systems ; 2020 ; Online Only,California,United States
Proc. SPIE ; 11500
2020-08-20
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
An embedded vision system for autonomous vehicles
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