An Experimental Bench for Testing a S-CAM Front Car Camera

• Autorzy: Gryś Sławomir

Identyfikatory

DOI

10.24425/ijet.2022.143882

• Języki publikacji: EN

Abstrakty

EN

The paper presents an experimental stand for testing the front car camera S-CAM with embedded image recognition systems. The camera sends CAN messages these are converted to USART messages by microprocessor based system. The messages are interpreted by MATLAB script on the basis of database of traffic signs in accordance with Polish Road Code. The testing stand is mainly aimed for educating students interested in the fields of electronics and technologies related to automotive branch, as well. The second objective is a research on efficiency of traffic sign recognition system being one of functionalities of S-CAM camera. The technical specification of testing stand, its functionality and limitations were also discussed. The bench operation was illustrated with examples of stiff images, animation and real movies.

Słowa kluczowe

EN

automotive technology; driving safety; ADAS; front camera; CAN bus; traffic sign recognition

• Wydawca: Polish Academy of Sciences, Committee of Electronics and Telecommunication
• Czasopismo: International Journal of Electronics and Telecommunications
• Rocznik: 2022
• Tom: Vol. 68. No. 4
• Strony: 755--760
• Opis fizyczny: Bibliogr. 17 poz., fot.

Twórcy

autor

Gryś Sławomir

• Częstochowa University of Technology, Faculty of Electrical Engineering, Poland

Bibliografia

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• [6] Kumar Kukkala, J. Tunnell, et al, “Advanced Driver-Assistance Systems. A path toward autonomous systems,” IEEE Consumer Electronics Magazine, Aug. 2018, https://doi.org/10.1109/MCE.2018.2828440.
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• [8] S. Gryś, “An experimental test bench for the tire pressure monitoring system - discussion of measurement and communication issues,” International Journal of Electronics and Telecommunications, 2019, vol. 65, no. 1, pp. 51-56, https://doi.org/10.24425/123565.
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• [10] White paper “Safety First for Automated Driving,” 10th Sep. 2019, web available.
• [11] A. Arcos-García, J. Álvarez-García, L. Soria-Morillo, “Deep neural network for traffic sign recognition systems: An analysis of spatial transformers and stochastic optimisation methods,” Neural Networks, 99, 2018, pp. 158-165, https://doi.org/10.1016/j.neunet.2018.01.005.
• [12] Shao-Kuo Tai, Ch. Dewi, et al., “Deep Learning for Traffic Sign Recognition Based on Spatial Pyramid Pooling with Scale Analysis,” Applied Science 2020, vol. 10, no. 6997, https://doi.org/10.3390/app10196997.
• [13] Ch. Dewi, Rung-Ching Chen, Shao-Kuo Tai, “Evaluation of Robust Spatial Pyramid Pooling Based on Convolutional Neural Network for Traffic Sign Recognition System.” Electronics, vol. 9, 2020, no. 889, https://doi.org/10.3390/electronics9060889.
• [14] Ch. Dewi, Rung-Ching Chen et al., “Yolo V4 for Advanced Traffic Sign Recognition With Synthetic Training Data Generated by Various GAN,” IEEE Access, vol. 9, 2021, pp. 97228-97242, https://doi.org/10.1109/ACCESS.2021.3094201.
• [15] J. Li and Z. Wang, "Real-time traffic sign recognition based on efficient CNNs in the wild," IEEE Transactions on Intelligent Transportation Systems, vol. 20, no. 3, pp. 975-984, March 2019, https://doi.org/10.1109/TITS.2018.2843815.
• [16] “EyeQ The System-on-Chip for Automotive Applications” https://www.mobileye.com/technology/eyeq-chip/.
• [17] “Rozporządzenie Ministrów Infrastruktury oraz Spraw Wewnętrznych i Administracji z dnia 31 lipca 2002 r. w sprawie znaków i sygnałów drogowych” (En. Regulation of the Ministers of Infrastructure and Interior and Administration (Poland) of July 31, 2002 on road signs and signals.), Dz.U. 2002 nr 170 poz. 1393, https://www.gov.pl/web/infrastruktura/znaki-i-sygnaly-drogowe.

Uwagi

1. Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).

2. The project financed under the program of the Minister of Science and Higher Education under the name ”Regional Initiative of Excellence” in the years 2019 - 2022 project number 020/RID/2018/19, the amount of financing 12 000 000,00 PLN.