Collaborative processing and data optimization of environmental perception technologies for autonomous vehicles
ISSN: 0144-5154
Article publication date: 5 May 2021
Issue publication date: 22 July 2021
Abstract
Purpose
Autonomous driving depends on the collection, processing and analysis of environmental information and vehicle information. Environmental perception and processing are important prerequisite for the safety of self-driving of vehicles; it involves road boundary detection, vehicle detection, pedestrian detection using sensors such as laser rangefinder, video camera, vehicle borne radar, etc.
Design/methodology/approach
Subjected to various environmental factors, the data clock information is often out of sync because of different data acquisition frequency, which leads to the difficulty in data fusion. In this study, according to practical requirements, a multi-sensor environmental perception collaborative method was first proposed; then, based on the principle of target priority, large-scale priority, moving target priority and difference priority, a multi-sensor data fusion optimization algorithm based on convolutional neural network was proposed.
Findings
The average unload scheduling delay of the algorithm for test data before and after optimization under different network transmission rates. It can be seen that with the improvement of network transmission rate and processing capacity, the unload scheduling delay decreased after optimization and the performance of the test results is the closest to the optimal solution indicating the excellent performance of the optimization algorithm and its adaptivity to different environments.
Originality/value
In this paper, the results showed that the proposed method significantly improved the redundancy and fault tolerance of the system thus ensuring fast and correct decision-making during driving.
Keywords
Acknowledgements
This research was funded by 2018 Industrial Internet innovation and development project – Basic Standards and experimental verification of industrial internet edge computing, the National Key Research and Development Program (No. 2018YFB2003500, 2018YFB1700200), Foshan entrepreneurship and innovation team project (2017IT100032). The authors would like to thank several anonymous reviewers and readers in China and abroad who gave valuable comments and suggestions.
Citation
Song, H., Zhou, S., Chang, Z., Su, Y., Liu, X. and Yang, J. (2021), "Collaborative processing and data optimization of environmental perception technologies for autonomous vehicles", Assembly Automation, Vol. 41 No. 3, pp. 283-291. https://doi.org/10.1108/AA-01-2021-0007
Publisher
:Emerald Publishing Limited
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