The Application Prospects of Event Data in Traffic Flow Prediction
Conventional methods of predicting traffic flow can often be based on weekdays, certain holidays, road conditions, or signal light circumstances. Nevertheless, because there isn’t always an impact study done for some exceptional occurrences, these forecasting techniques or models might be ineffectiv...
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| Format: | Article |
| Language: | English |
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EDP Sciences
2025-01-01
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| Series: | ITM Web of Conferences |
| Online Access: | https://www.itm-conferences.org/articles/itmconf/pdf/2025/01/itmconf_dai2024_01011.pdf |
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| _version_ | 1825206584741986304 |
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| author | Chen Haochi Guo Zixin Jiang Zicong |
| author_facet | Chen Haochi Guo Zixin Jiang Zicong |
| author_sort | Chen Haochi |
| collection | DOAJ |
| description | Conventional methods of predicting traffic flow can often be based on weekdays, certain holidays, road conditions, or signal light circumstances. Nevertheless, because there isn’t always an impact study done for some exceptional occurrences, these forecasting techniques or models might be ineffective. Recent studies have pointed out that social events such as concerts and large-scale events have a huge impact on Traffic flow. Considering these social events, to more accurately predict Traffic flow, this article refers to previous relevant literature, comprehensively describes the significant improvement of event data in traffic flow prediction (TFP) and how to use it, and generally discusses the relevant models that may apply event data to TFP. In detail, the current research results on STG-NCDE and Bi-LSTM models are presented, and the correlation, advantages, and disadvantages of the two are compared. In addition, the problems and challenges faced by the current application of event data in TFP are innovatively analyzed and discussed. Finally, the further achievements and related technology development trends that may be made in TFP based on this research direction in the prospect, and the article is summarized. |
| format | Article |
| id | doaj-art-aa6c6c7ab136441dbd6de8aad7c7e266 |
| institution | Kabale University |
| issn | 2271-2097 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | ITM Web of Conferences |
| spelling | doaj-art-aa6c6c7ab136441dbd6de8aad7c7e2662025-02-07T08:21:10ZengEDP SciencesITM Web of Conferences2271-20972025-01-01700101110.1051/itmconf/20257001011itmconf_dai2024_01011The Application Prospects of Event Data in Traffic Flow PredictionChen Haochi0Guo Zixin1Jiang Zicong2College of Computer Science and Technology, Civil Aviation University of ChinaSchool of Management, Hefei University of TechnologyShijiazhuang New Century Foreign Language SchoolConventional methods of predicting traffic flow can often be based on weekdays, certain holidays, road conditions, or signal light circumstances. Nevertheless, because there isn’t always an impact study done for some exceptional occurrences, these forecasting techniques or models might be ineffective. Recent studies have pointed out that social events such as concerts and large-scale events have a huge impact on Traffic flow. Considering these social events, to more accurately predict Traffic flow, this article refers to previous relevant literature, comprehensively describes the significant improvement of event data in traffic flow prediction (TFP) and how to use it, and generally discusses the relevant models that may apply event data to TFP. In detail, the current research results on STG-NCDE and Bi-LSTM models are presented, and the correlation, advantages, and disadvantages of the two are compared. In addition, the problems and challenges faced by the current application of event data in TFP are innovatively analyzed and discussed. Finally, the further achievements and related technology development trends that may be made in TFP based on this research direction in the prospect, and the article is summarized.https://www.itm-conferences.org/articles/itmconf/pdf/2025/01/itmconf_dai2024_01011.pdf |
| spellingShingle | Chen Haochi Guo Zixin Jiang Zicong The Application Prospects of Event Data in Traffic Flow Prediction ITM Web of Conferences |
| title | The Application Prospects of Event Data in Traffic Flow Prediction |
| title_full | The Application Prospects of Event Data in Traffic Flow Prediction |
| title_fullStr | The Application Prospects of Event Data in Traffic Flow Prediction |
| title_full_unstemmed | The Application Prospects of Event Data in Traffic Flow Prediction |
| title_short | The Application Prospects of Event Data in Traffic Flow Prediction |
| title_sort | application prospects of event data in traffic flow prediction |
| url | https://www.itm-conferences.org/articles/itmconf/pdf/2025/01/itmconf_dai2024_01011.pdf |
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