Cited By
View all- Abid MLorig FHolmgren JPetersson J(2024)Ambulance Travel Time Estimation using Spatiotemporal DataProcedia Computer Science10.1016/j.procs.2024.06.024238(265-272)Online publication date: 2024
Bus Travel Time Prediction Based on Multi-Source Data Fusion
Authors: 
Lijun Zhu, Weibo Wei, Yang Xia, Liping FuAuthors Info & Claims
Lijun Zhu, Weibo Wei, Yang Xia, Liping FuAuthors Info & ClaimsPages 97 - 102
Abstract
Advocating public transport travel can reduce carbon emissions and pollutant emissions, alleviating the problem of global warming. Accurate bus travel time prediction can improve the level of public transportation services and contribute to the improvement of intelligent transportation systems. Unfortunately, there are many complex factors that affect the accuracy of bus travel time prediction, which greatly affects the accuracy of the prediction. In addition, weather and travel dates have a greater impact on road congestion. Therefore, this paper proposes a bus travel time prediction method based on multi-source data fusion and captures external influencing factors such as weather and travel date. Learning spatial-temporal features between trajectory data using CNN and LSTM. The experimental results show that the model based on multi-source data fusion proposed in this paper can provide higher prediction accuracy compared with the model based on single-source data.
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Published In
September 2022
454 pages
ISBN:9781450396875
DOI:10.1145/3565291
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Association for Computing Machinery
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Publication History
Published: 16 December 2022
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- Research-article
- Research
- Refereed limited
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- Science and Technology Support Plan for Youth Innovation of College and Universities of Shandong Province of China
Conference
ICBDT 2022
ICBDT 2022: 2022 5th International Conference on Big Data Technologies
September 23 - 25, 2022
Qingdao, China
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View all- Abid MLorig FHolmgren JPetersson J(2024)Ambulance Travel Time Estimation using Spatiotemporal DataProcedia Computer Science10.1016/j.procs.2024.06.024238(265-272)Online publication date: 2024
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