A Novel Design of Autonomous Cars using IoT and Visual Features

Autonomous car is a ground vehicle that is capable of driving without user interference. Traffic congestion and number of collisions are major issues in road traffic control due to rapid increase day-by-day. Autonomous cars provide a solution to this problem in an efficient and economical way. The proposed system utilizes mathematical models like neural networks and image processing techniques to sense the environment. This is implemented as three major components: curved road detection (steering), road sign and signal detection and obstacle detection (collision avoidance). Back Propagation is used for steering control with detection of curved roads; Haar features are used for road signal, sign detection and a distance sensor for collision avoidance. Data collected from the sensors is sent to a server for processing. Based on the result, a command is sent to the car. A GPS module attached to the car identifies the location of the car and with the help of a 3rd party location service, route to destination is identified and directions are sent to the car. Wireless networks are used to transmit data between sensors and the server. Python scripts are used to control and integrate all the units together. The designed system can attain high accuracy with real - time constraints.