Parallelization and Porting of Multiple ADAS Applications on Embedded Multicore Platforms

Venkatesh Kareti; Priti Ranadive; Vinay Vaidya

doi:10.4271/2015-01-0258

Various Advanced Driver Assists Systems (ADAS) are being used today to increase safety of drivers. These systems viz. Forward Collision Warning (FCW), Lane Departure Warning (LDW), Pedestrian Detection (PD), are all based on inputs captured using a front mounted camera. It would be useful to combine all these applications together and process the same input for different application purpose.

Additionally, multicore processors are now easily available and can be used for integrating multiple ADAS applications. This would lead to reduced cost and maintenance of ADAS systems with the same performance benefits. Since current ADAS applications are sequential and/or use single core processors there is a need to parallelize these applications so that multiple cores can be utilized optimally.

In this paper, we discuss our experiments and results while attempting to integrate two such ADAS applications on a multicore embedded platform. We discuss what changes we made to the PD and FCW algorithm to improve performance by 66% and 53% respectively. We also discuss our experiments to integrate the two applications that led to performance degradation and the possible reasons for the performance degradation.

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Parallelization and Porting of Multiple ADAS Applications on Embedded Multicore Platforms 2015-01-0258

SAE MOBILUS