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Data Fusion-Based Obstacle Detection for Rail Transit Scenarios Shanghai Fuxin Intelligent Traffic Control Company, LTD

SAE Technical Papers (1906-current) Available online

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Format:
Book
Conference/Event
Author/Creator:
Feng, Junyi, author.
Contributor:
Liang, Xiao
Wu, Yingying
Conference Name:
2022 World General Artificial Intelligence Congress (2022-03-30 : Shanghai, China)
Language:
English
Physical Description:
1 online resource cm
Place of Publication:
Warrendale, PA SAE International 2022
Summary:
In order to solve the problem of obstacle detection for rail transit scenarios, a recognition method of obstacle based on data fusion is proposed. First, the image data, which is obtained through a telephoto camera and a wide-angle camera, is synchronized. Then, the artificial intelligence model for objects detection is applied to image data processing, where the distance measuring module is added to transform the recognition results into three-dimensional output with object distance. Finally, the output of the model is processed by data fusion and visualized. Taking tram as experimental background, the experimental results show that the method in this paper can effectively recognize objects in the front of tram, and can be used as a part of the rail transit automatic sensing system to ensure the safety of driving
Notes:
Vendor supplied data
Publisher Number:
2022-01-7027
Access Restriction:
Restricted for use by site license

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