Autonomous Emergency Braking and Pre-Crash System

Abstract

Autonomous driving is a major application in the field of Artificial Intelligence (AI). Autonomous Vehicles (AV) are installed
with cameras, ultrasonic sensors, etc., for helping the drivers to understand the surroundings better. The sensors generate a huge
amount of data. The objective of this paper is to Integrate AEB (Autonomous Emergency Braking) with the Pre-crash system to avoid
collisions in autonomous (self-driving) vehicles. The crash type considered is head-on collisions. IoT is implemented for remote
monitoring and analysis. AEB systems are used to avoid the impact on the car by warning the driver that some action is required. It
produces a collision avoidance maneuver, if feasible, or, otherwise, an emergency braking will be applied to reduce the impact. The image
processing technique is implemented to avoid collisions through continuous monitoring of the dynamics of the vehicle. The actions of the
driver are monitored to observe the panic scenario. The obstacles in front of the car are determined by the ultrasonic sensors. The
output is to alert the driver about the imminent collision by applying the emergency brake that immediately removes the slack from seat
belts; adjusts the seating positions to optimize for airbag performance and shuts the windows to prevent ejection. The simulation results
show that the proposed control strategy has performed better than the conventional one.
Index Terms—AEB, Pre-crash system, Image processing, Ultrasonic sensor.