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Parallelization and Porting of Multiple ADAS Applications on Embedded Multicore Platforms
Technical Paper
2015-01-0258
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
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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Kareti, V., Ranadive, P., and Vaidya, V., "Parallelization and Porting of Multiple ADAS Applications on Embedded Multicore Platforms," SAE Technical Paper 2015-01-0258, 2015, https://doi.org/10.4271/2015-01-0258.Also In
References
- Yadav Gaurav Kumar , kancharlam Tarun , Nair Smita Real Time Vehicle Detection for Rear and Forward Collision Warning Systems First International Conference, ACC 2011 Kochi, India July 22 24 2011 Proceedings, Part IV
- Dalal Navneet and Triggs Bill Histograms of Oriented Gradients for Human Detection Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference
- Vaidya V.G. , Agrawal P. , Athavale A. , Sane A. , Sudhakar S. , Ranadive P. Increasing Parallelism on multicore processors using Induced parallelism ICSTE 2010 1 V1-5 V1-8
- Jazayeri Amirali , Cai Hongyuan Vehicle Detection and Tracking in Car Video Based on Motion Model IEEE Transactions on International Transportation Systems 12 2 JUNE 2011
- Gao Wenshuo , Zhang Xiaoguang , Yang Lei An Improved Sobel edge detection Computer Science and Information Technology (ICCSIT), 2010 3rd IEEE International Conference July 2011
- Bineeshtr and Simon Philomina Fast Pedestrian Detection using Smart ROI separation and Integral Image based Feature Extraction Bineesh T.R et al. International Journal on Computer Science and Engineering (IJCSE) 4 11 Nov 2012
- Kancharla T. , Karade P. , Gindi S. Edge based segmentation for pedestrian detection using NIR camera Image Information Processing (ICIIP), 2011 International Conference Nov. 2011
- Eranian Stephane What can performance counters do for memory subsystem analysis Proceedings of the 2008 ACM SIGPLAN workshop on Memory systems performance and correctness March 2008
- Vaidya V. , Sah S. , Ranadive P. Optimal Task Scheduler for Multicore Processor ICSTE 2010 1 V1-1 V1-4
- Lai Guan-Joe Tai-Chung A Novel Task Scheduling Algorithm for Distributed Heterogeneous Computing Systems PARA'04 Workshop on State-Of-The-Art in Scientific Computing June 2004
- Jin Shiyuan , Schiavone Guy and Turgut Damla A Performance Study of Multiprocessor Task Scheduling Algorithms The Journal of Super Computing 43 1 Jan 2008 77 97