Abstract
This work aims to evaluate the real-time processing system in the context of an autonomous vehicle with limited hardware and software capabilities. We elaborate algorithm implemented in 1/10 scale electric car using a line scan camera, speed sensors, and embedded electronic control system. The vehicle navigates in an arbitrary one-lane circuit using an edge detection algorithm. The challenge was to make a complete one loop of the arbitrary circuit in the shortest time with various lighting conditions. The experiments show that several issues were revealed in each step of data sensors processing and need a robust algorithm to handle exceptions caused by multiple disturbances. Furthermore, we paid particular attention to time constraints in embedded processor calculation and actuators response time to achieve reliable critical software control algorithms.
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References
Katare, D., El-Sharkawy, M.: Embedded system enabled vehicle collision detection: an ANN classifier. In: 2019 IEEE 9th Annual Computing and Communication Workshop and Conference (CCWC), pp. 0284–0289. IEEE (2019)
Gao, T., Lai, Z., Mei, Z., Wu, Q.: Hybrid SVM-CNN classification technique for moving targets in automotive FMCW radar system. In: 2019 11th International Conference on Wireless Communications and Signal Processing (WCSP), pp. 1–6. IEEE (2019)
Ren, J., Ren, R., Green, M., Huang, X.: A deep learning method for fault detection of autonomous vehicles. In: 2019 14th International Conference on Computer Science & Education (ICCSE), pp. 749–754. IEEE (2019)
Essaid, M., Idoumghar, L., Lepagnot, J., Brévilliers, M.: GPU parallelization strategies for metaheuristics: a survey. Int. J. Parall. Emerg. Distrib. Syst. 34(5), 497–522 (2019)
Hamm, M., Huhn, W.: Glare investigations and safety research on digital light technologies. In: SAE Technical Paper (2019)
Verma, M., Collette, C.: Active vibration isolation system for drone cameras. In: Proceedings of International Conference on Vibration Problems: ICOVP (2019)
Alejandre, I., Artés, M.: Method for the evaluation of optical encoders performance under vibration. Precis. Eng. 31(2), 114–121 (2007)
Shariff, H.M., Rahiman, M.H.F., Adnan, R., Marzaki, M.H., Tajjudin, M., Jalil, M.H.A.: The PID integrated anti-windup scheme by Ziegler-Nichols tuning for small-scale steam distillation process. In: 2019 IEEE 9th International Conference on System Engineering and Technology (ICSET), pp. 391–395 (2019)
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El Hafid, Y., El Rharras, A., Chehri, A., Saadane, R., Wahbi, M. (2020). Real-Time Data Processing in Autonomous Vehicles Based on Distributed Architecture: A Case Study. In: Qu, X., Zhen, L., Howlett, R.J., Jain, L.C. (eds) Smart Transportation Systems 2020. Smart Innovation, Systems and Technologies, vol 185. Springer, Singapore. https://doi.org/10.1007/978-981-15-5270-0_13
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DOI: https://doi.org/10.1007/978-981-15-5270-0_13
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