Review of pedestrian trajectory prediction methods
With the breakthrough of deep learning technology and the proposal of large data sets, the accuracy of pedestrian trajectory prediction has become one of the research hotspots in the field of artificial intelligence.The technical classification and research status of pedestrian trajectory prediction...
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| Format: | Article |
| Language: | zho |
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POSTS&TELECOM PRESS Co., LTD
2021-12-01
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| Series: | 智能科学与技术学报 |
| Subjects: | |
| Online Access: | http://www.cjist.com.cn/thesisDetails#10.11959/j.issn.2096-6652.202140 |
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| _version_ | 1850195678737727488 |
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| author | Linhui LI Bin ZHOU Weiwei REN Jing LIAN |
| author_facet | Linhui LI Bin ZHOU Weiwei REN Jing LIAN |
| author_sort | Linhui LI |
| collection | DOAJ |
| description | With the breakthrough of deep learning technology and the proposal of large data sets, the accuracy of pedestrian trajectory prediction has become one of the research hotspots in the field of artificial intelligence.The technical classification and research status of pedestrian trajectory prediction were mainly reviewed.According to the different modeling methods, the existing methods were divided into shallow learning and deep learning based trajectory prediction algorithms, the advantages and disadvantages of representative algorithms in each type of method were analyzed and introduced.Then, the current mainstream public data sets were summarized, and the performance of mainstream trajectory prediction methods based on the data sets was compared.Finally, the challenges faced by the trajectory prediction technology and the development direction of future work were prospected. |
| format | Article |
| id | doaj-art-b0a27e033df1426daaaa7a6c57751834 |
| institution | OA Journals |
| issn | 2096-6652 |
| language | zho |
| publishDate | 2021-12-01 |
| publisher | POSTS&TELECOM PRESS Co., LTD |
| record_format | Article |
| series | 智能科学与技术学报 |
| spelling | doaj-art-b0a27e033df1426daaaa7a6c577518342025-08-20T02:13:41ZzhoPOSTS&TELECOM PRESS Co., LTD智能科学与技术学报2096-66522021-12-01339941159641468Review of pedestrian trajectory prediction methodsLinhui LIBin ZHOUWeiwei RENJing LIANWith the breakthrough of deep learning technology and the proposal of large data sets, the accuracy of pedestrian trajectory prediction has become one of the research hotspots in the field of artificial intelligence.The technical classification and research status of pedestrian trajectory prediction were mainly reviewed.According to the different modeling methods, the existing methods were divided into shallow learning and deep learning based trajectory prediction algorithms, the advantages and disadvantages of representative algorithms in each type of method were analyzed and introduced.Then, the current mainstream public data sets were summarized, and the performance of mainstream trajectory prediction methods based on the data sets was compared.Finally, the challenges faced by the trajectory prediction technology and the development direction of future work were prospected.http://www.cjist.com.cn/thesisDetails#10.11959/j.issn.2096-6652.202140trajectory prediction;deep learning;sequence decision |
| spellingShingle | Linhui LI Bin ZHOU Weiwei REN Jing LIAN Review of pedestrian trajectory prediction methods 智能科学与技术学报 trajectory prediction;deep learning;sequence decision |
| title | Review of pedestrian trajectory prediction methods |
| title_full | Review of pedestrian trajectory prediction methods |
| title_fullStr | Review of pedestrian trajectory prediction methods |
| title_full_unstemmed | Review of pedestrian trajectory prediction methods |
| title_short | Review of pedestrian trajectory prediction methods |
| title_sort | review of pedestrian trajectory prediction methods |
| topic | trajectory prediction;deep learning;sequence decision |
| url | http://www.cjist.com.cn/thesisDetails#10.11959/j.issn.2096-6652.202140 |
| work_keys_str_mv | AT linhuili reviewofpedestriantrajectorypredictionmethods AT binzhou reviewofpedestriantrajectorypredictionmethods AT weiweiren reviewofpedestriantrajectorypredictionmethods AT jinglian reviewofpedestriantrajectorypredictionmethods |