Indian Journal of Science and Technology

Abstract

Objectives: Most of the accidents could be avoided or prevented through simple measures like speed limit, precautions for the driver’s safety and discipline among road users. Most of the accidents occur on highways, especially when changing lanes. This paper focuses on reducing such accidents by using Lane Keeping Assist System (LKAS). Methods: This LKAS is based on the concept of neural network model, which has a high complexity and high cost design for functional implementation. Findings: Though this system has more advantages, it cannot be implemented in all range of cars. In order to overcome this, a cost affordable, safety alert system suitable for all range of cars is proposed using low cost and low power consumption open source device, in which vehicles are incorporated with sensors which helps in notifying when the vehicle is overtake and makes it easier for people to control the movements of vehicle. Application/Improvement: It helps to indicate the unconditional changes of vehicle between the lanes and also reduce the accidents. Apart from this, fading and blinking of front head lights automated whenever approaching in opposite direction.
Keywords: Kalman Filtering, Sensor Fusion