Image Correlation Based Smart Throttle-Brake Control System for Disability Vehicles

The existing throttle and brake control systems are built as Anti-braking systems with different modes of operation during normal and emergency conditions. Nevertheless, developing an intelligent system in an automated vehicle that supports seamless mobility of the elderly and the physically challenged in dense traffic is an uphill task. Hence, in this paper, a smart vehicle control system with adaptive throttle and brake control is propounded. The self-governing vehicle built using sensors and Raspberry Pi controller uses image processing techniques for taking decisions. The dynamic model controls the throttle valve using servo-motor based Proportional-Derivative (PD) Control. It uses high torque servo motors to pull the brake pedal to the anticipated level using automatic torque control. Correlation based algorithms that integrate brake and speed control are implemented using Firmware. The inherent intelligent functionality in the vehicle based on the sensed traffic offers better accuracy. The steady state error is minimized using Camera. A brake test is performed to examine the performance of the proposed model under loaded conditions of the support vehicle. It is seen that the proposed system outperforms the existing systems in terms of Stopping Time and Braking Torque.