Theoretical and Natural Science
- The Open Access Proceedings Series for Conferences
Theoretical and Natural Science
Vol. 28, 26 December 2023
Open
Access | Article
Using sensor fusion technology to realize pedestrian recognition and hazard assessment
* Author to whom correspondence should be addressed.
Abstract
The prevailing technology for pedestrian recognition in unmanned driving, predominantly reliant on LiDAR, confronts the dual challenges of elevated expenses and limited anti-interference capabilities. To surmount these obstacles, this paper introduces an inventive fusion methodology that harmonizes inputs from visual cameras, 4D millimeter wave radar, and thermal imaging sensors. The advantages and promising development prospects of 4D millimeter wave radar over laser radar are comprehensively elucidated. By leveraging advanced signal processing algorithms, a robust mathematical model is formulated, facilitating the synthesis of information from a multitude of distinctive feature parameters. In tandem, an assessment of the hazard index is executed using the analytic hierarchy process, enriching vehicular safety and driving efficiency. This innovative approach strives to foster the progression of autonomous vehicle technology and expedite its commercial assimilation into the burgeoning autonomous driving market. By harnessing the synergistic capabilities of multiple sensor modalities, the proposed fusion technique not only addresses the existing limitations but also charts a transformative course towards a safer and more efficient autonomous driving landscape. Through the amalgamation of these cutting-edge technologies, this research aspires to carve a path for the accelerated evolution and widespread deployment of autonomous vehicles.
Keywords
autonomous driving, pedestrian recognition, multi-sensor, 4D millimeter wave radar
References
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Data Availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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- Volume Title
- Proceedings of the 2023 International Conference on Mathematical Physics and Computational Simulation
- ISBN (Print)
- 978-1-83558-261-9
- ISBN (Online)
- 978-1-83558-262-6
- Published Date
- 26 December 2023
- Series
- Theoretical and Natural Science
- ISSN (Print)
- 2753-8818
- ISSN (Online)
- 2753-8826
- DOI
- 10.54254/2753-8818/28/20230463
- Copyright
- 26 December 2023
- Open Access
- This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited