Vehicle Automation and Car-Following Models for Accident Avoidance

Road accidents contribute to the greatest number of deaths in the world. Deaths and injuries due to road accidents result in financial losses as well as physical and mental suffering. Even though a good driver is attentive enough to take sudden decisions, at some point, there is a requirement for an automatic decision-making ability in the car. Cars that can take prompt actions based on the environment without the driver involved is called a smart car. The car-following models are methods used in smart cars for accident avoidance. This paper presents an in-depth survey of various car following models based on IoT sensors, weather & road conditions, V2V networks, machine learning algorithms. A comparative analysis of multiple research articles with its techniques, merits and research gap is presented. Finally, the inference of the literature survey is provided.