Object Detection and Prevention Control for Autonomous Vehicles

DOI

10.2991/978-94-6463-754-0_53How to use a DOI?

Keywords

Autonomous Vehicles; Object Detection; Deep Learning; LiDAR

Abstract

Object detection and prevention control are critical components in the design and operation of autonomous cars. These systems enable self-driving vehicles to identify, classify, and respond to objects in their environment, ensuring safe navigation and collision avoidance. This research focuses on integrating advanced object detection algorithms with prevention control mechanisms to enhance the reliability and safety of autonomous vehicles. State-of-the-art techniques such as deep learning-based Convolutional Neural Networks (CNNs) and sensor fusion are employed for object detection. These methods leverage data from LiDAR, radar, and cameras to accurately detect and classify objects, including pedestrians, vehicles, and obstacles, in real-time. The prevention control system integrates with these detection mechanisms to dynamically adjust vehicle speed, apply emergency braking, or reroute the vehicle to avoid potential collisions. The proposed framework emphasizes low-latency processing and high detection accuracy to address challenges such as varying weather conditions, lighting, and complex traffic scenarios. Simulation results and real-world testing demonstrate the system’s effectiveness in improving reaction times and reducing accident risks, highlighting its potential for widespread adoption in autonomous vehicle technologies.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - K. Muthukumar
AU  - C. S. Sathiyaseelan
AU  - J. K. Gokula Kirishnan
AU  - M. Praveen
AU  - K. Venkatesh
PY  - 2025
DA  - 2025/06/30
TI  - Object Detection and Prevention Control for Autonomous Vehicles
BT  - Proceedings of the 2025 International Conference on Advanced Research in Electronics and Communication Systems (ICARECS-2025)
PB  - Atlantis Press
SP  - 607
EP  - 617
SN  - 2589-4943
UR  - https://doi.org/10.2991/978-94-6463-754-0_53
DO  - 10.2991/978-94-6463-754-0_53
ID  - Muthukumar2025
ER  -