A Hybrid Deep Learning Based Autonomous Vehicle Navigation and Obstacles Avoidance
| Autor: | Habiba A. Ibrahim, Zahra Fathy Ibrahim, Ahmad Taher Azar, Hossam Hassan Ammar |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
0209 industrial biotechnology
Automatic control Computer science business.industry Deep learning Control (management) Particle swarm optimization Control engineering 02 engineering and technology Convolutional neural network 020901 industrial engineering & automation 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing State (computer science) Artificial intelligence business |
| Zdroj: | Advances in Intelligent Systems and Computing ISBN: 9783030442880 AICV |
| Popis: | Technological revolution has reached all life activities starting from day planning reaching communication, entertainment, industry, and transportation. Each of previously mentioned categories get improved in a way making human life easier and safer. In the use of automatic control, several researches focused on automating vehicles’ systems to make driving easier and safer. The availability of autonomous vehicles will avoid accidents caused by taking a late decision or lack of driving experience in such situation. Approaching autonomous driving, an autonomous vehicle must be able to respond to the state of objects in the surrounding, be it stationary or in motion. This paper outlines the techniques which enable the car to become conscious of its immediate environment while it moves independently and to decide its next course of action to avoid obstacles. It investigates two approaches which are Neuro-Fuzzy System tuned by Particle Swarm Optimization (PSO) and Convolutional Neural Network (CNN) tuned by Adaptive Moment estimation (Adam). Such control can allow cars on roads to operate smoothly and, according to trained data, take quick accurate decisions. Results showed high performance of deep learning algorithms specially CNN with Adam; however, it needs more computational time than Neuro-Fuzzy system tuned with PSO. |
| Databáze: | OpenAIRE |
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