Recent Advancement in Autonomous Vehicle and Driver Assistance Systems

In past two decades, the popularity and use of autonomous vehicles and driver assistance systems has accelerated due to the advancement in artificial intelligence techniques, big data analysis, machine learning, computer vision, smart sensors and Internet of Things (IoT). Autonomous vehicles (AVs) are gaining popularity because it reduces traffic congestion along with increase in safety and fuel efficiency. The present paper focuses on the functionality of the driver-less car and Advanced Driver & Driving Assistance Systems (ADDAS). Driver assistance systems help drivers to driving safely by avoiding and minimising distractions by observing their actions. Artificial Intelligence can be incorporated when AVs drive alongside human-driven vehicles (HVs), also known as the era of Mixed Autonomy. The Markov decision process (MDP) can be used to represent the communication between the driver-less vehicles and the surroundings, where, MDP is a discrete-time imaginary command process. MDP is utilized in various fields like automation, economics, manufacturing, and automatic control. This paper provides a detailed review on recent research and developments on autonomous vehicles and ADDAS. Some onfield examples of ADDAS are Automatic Parking, Automatic Braking System (ABS), Blind Spot Monitors, Adaptive Cruise Control (ACC), etc.