Autonomous Vehicles, Volume 1

1Anomalous Activity Detection Using Deep Learning Techniques in Autonomous Vehicles

Amit Juyal^1,2, Sachin Sharma¹ and Priya Matta¹*

¹Department of Computer Science and Engineering, Graphic Era (Deemed to be University), Dehradun, Uttarakhand, India

²School of Computing, Graphic Era Hill University, Dehradun, Uttarakhand, India

Abstract

Autonomous driving is self-driving without the intervention of a human driver. A self-driving autonomous vehicle is designed with the help of high-technology sensors that can sense the traffic and traffic signals in the surroundings and move accordingly. It becomes necessary for a self-driving vehicle to take a right decision at the right time in an uncertain traffic environment. Any unusual anomalous activity or unexpected obstacle that could not be detected by an autonomous vehicle can lead to a road accident. For decision making in autonomous vehicles, very precisely designed and optimized programming software are developed and intensively trained to install in vehicle’s computer system. But in spite of these trained software some of the anomalous activity could become a hindrance to detect promptly during self-driving. Therefore, automatic detection and recognition of anomalies in autonomous vehicles is critical to a safe drive. In this chapter we discuss and propos deep learning method for anonymous activity detection of other vehicles that can be danger for safe driving in an autonomous vehicle. The present chapter focuses on various conditions ...