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Motion Prediction for Autonomous Vehicles Using Deep Learning Techniques

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Akash Adhikari; Pankaj Raj Dawadi
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Abstract:

Autonomous vehicles require motion prediction of nearby traffic agents to guarantee secure navigation. By anticipating the movements of surrounding objects such as other ...Show More

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Abstract:

Autonomous vehicles require motion prediction of nearby traffic agents to guarantee secure navigation. By anticipating the movements of surrounding objects such as other vehicles, pedestrians, and bicycles, the autonomous vehicle can make informed decisions to prevent collisions, adjust speed and direction, and operate effectively in changing conditions. Motion prediction is an essential aspect of autonomous vehicle systems, contributing to increased safety, dependability, and efficiency. This work generates an effective mechanism to predict the movement direction of nearby traffic entities around our ego vehicle (the vehicle that we originally reference) using deep learning techniques and the inclusion of a LIDAR-based dataset.
Published in: 2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT)
Date of Conference: 06-08 July 2023
Date Added to IEEE Xplore: 23 November 2023
ISBN Information:

ISSN Information:

DOI: 10.1109/ICCCNT56998.2023.10306682
Conference Location: Delhi, India
References is not available for this document.
Contents

I. Introduction

Computer systems can easily solve mathematical functions and equations that humans find difficult. However, there are some problems that we as humans can solve "intuitively" but the same problem is incredibly challenging for computers to solve. One such task is the problem of motion prediction of nearby objects that are moving constantly. Predicting the behaviour of traffic agents around autonomous vehicles is an unsolved problem that needs to be tackled to attain full self-driving autonomy. Since the very beginning, the self-driving vehicle industry has been working on creating or utilizing many sensors in the form of RADAR (Radio Detection And Ranging), LIDAR (Light Detection and Ranging), Cameras, etc [10]. The motive of these sensors is to ensure the safety of the vehicle during the driving process at a particular point in time by locating the nearby traffic agents. Addressing the physical state of the traffic agents at a given point in time is crucial to have a safe and pleasurable ride. The prediction problem involves knowing the future state of the traffic agents that are interacting with the autonomous vehicle. This predictive modelling problem is primarily detected by the sensor installed on the vehicle which is then subjected to various predictive modelling techniques.

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