After that, Folium is used to depict the geographical location. Geoip2 (a python library) retrieves the longitude and latitude from the equipped system’s IP address to report the live geographical position to the authorities. Nvidia CNN architecture has been followed, containing nine layers including five convolution layers and three dense layers to develop the steering angle predictive model. A buck converter regulates a 5V 3A power supply to the raspberry pi to be working. The 3-cell 12V LiPo battery handles the power supply to the raspberry pi and L298 motor driver. Based upon this direction, L298 decides either forward or left or right or backwards movement. Then the steering angle value is passed to the raspberry pi that directs the L298 motor driver which direction the wheel should follow. The image is fed to the pre-trained deep learning model that predicts the steering angle regarding that situation. The raspberry pi sends the camera image and waits for the steering angle value. The equipped camera module captures the road image and transfers it to the computer via socket server programming. This study proposes Delicar, a self-driving product delivery vehicle that can drive the vehicle on the road and report the current geographical location to the authority in real-time through a map. Additional staff are also required to follow the delivery vehicle while it transports documents or records to another destination. The rapid expansion of a country’s economy is highly dependent on timely product distribution, which is hampered by terrible traffic congestion.
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