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International Journal of Intelligent Transportation Systems Research

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04-10-2024

An Adaptive Sequencing Approach for Object Detection in Autonomous Vehicles

Authors: Christopher Wolfe, Khatereh Mohammadi, Hasan Ferdowsi

Published in: International Journal of Intelligent Transportation Systems Research | Issue 3/2024

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Abstract

The article introduces an adaptive sequencing approach for object detection in autonomous vehicles, addressing the challenge of optimizing computational resources to enhance reaction times. It discusses the importance of autonomous driving systems in mitigating traffic congestion and road accidents. The method proposed integrates feedback from the vehicle's motion planner to prioritize object detection sequences, thereby improving the vehicle's ability to react to potential hazards. The article also provides a comprehensive simulation model in MATLAB and Simulink, demonstrating the effectiveness of the proposed approach through various experiments. The results show that the adaptive method significantly reduces reaction times and enhances the safety of autonomous vehicles.

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Title: An Adaptive Sequencing Approach for Object Detection in Autonomous Vehicles
Authors: Christopher Wolfe
Khatereh Mohammadi
Hasan Ferdowsi
Publication date: 04-10-2024
Publisher: Springer US
Published in: International Journal of Intelligent Transportation Systems Research / Issue 3/2024
Print ISSN: 1348-8503
Electronic ISSN: 1868-8659
DOI: https://doi.org/10.1007/s13177-024-00401-8

Multi-Model Traffic Forecasting in Smart Cities using Graph Neural Networks and Transformer-based Multi-Source Visual Fusion for Intelligent Transportation Management

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An Adaptive Sequencing Approach for Object Detection in Autonomous Vehicles

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