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Prediction of Cancellation Probability of Online Car-Hailing Orders Based on Multi-source Heterogeneous Data Fusion

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Abstract

In recent years, the demand for urban travel is increasing and the travel modes are diverse. Online car Hailing has become an important way to meet the travel needs of residents. The online car-hailing platform receives tens of thousands of travel requests every day. However, a large portion of the thousands of orders are unfinished, that is, canceled by passengers. This not only reduces the income of drivers but also affects the order dispatching efficiency of the online car-hailing platform. To predict the cancellation probability of online car-hailing orders(OCP), the relationship between multi-source heterogeneous data and OCP is first introduced, in which the presence of idle taxis is the main factor for passengers to cancel their orders during the waiting period. Secondly, a deep learning model based on the Seq2Seq structure is designed to predict OCP in real-time. The model consists of an attribute fusion module, encoder layer, and decoder layer. Finally, a full experiment is carried out using the Didi Chengdu online car-hailing order data set to verify the effectiveness of the algorithm.

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Acknowledgement

This research was supported in part by National Key Research and Development Plan Key Special Projects under Grant No. 2018YFB2100303, Shandong Province colleges and universities youth innovation technology plan innovation team project under Grant No. 2020KJN011, Shandong Provincial Natural Science Foundation under Grant No. ZR2020MF060, Program for Innovative Postdoctoral Talents in Shandong Province under Grant No. 40618030001, National Natural Science Foundation of China under Grant No. 61802216, and Postdoctoral Science Foundation of China under Grant No. 2018M642613.

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Authors and Affiliations

  1. College of Computer Science and Technology, Qingdao University, Qingdao, 266071, China

    Haokai Sun, Zhiqiang Lv & Jianbo Li

  2. Institute of Ubiquitous Networks and Urban Computing, Qingdao University, Qingdao, 266701, China

    Zhiqiang Lv, Zhihao Xu, Zhaoyu Sheng & Zhaobin Ma

Authors
  1. Haokai Sun

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  2. Zhiqiang Lv

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  3. Jianbo Li

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  4. Zhihao Xu

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  5. Zhaoyu Sheng

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  6. Zhaobin Ma

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Corresponding author

Correspondence toJianbo Li.

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Editors and Affiliations

  1. Dalian University of Technology, Dalian, China

    Lei Wang

  2. Ben-Gurion University of the Negev, Beer-Sheva, Israel

    Michael Segal

  3. Chang Gung University, Taiwan, China

    Jenhui Chen

  4. Tianjin University, Tianjin, China

    Tie Qiu

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Sun, H., Lv, Z., Li, J., Xu, Z., Sheng, Z., Ma, Z. (2022). Prediction of Cancellation Probability of Online Car-Hailing Orders Based on Multi-source Heterogeneous Data Fusion. In: Wang, L., Segal, M., Chen, J., Qiu, T. (eds) Wireless Algorithms, Systems, and Applications. WASA 2022. Lecture Notes in Computer Science, vol 13472. Springer, Cham. https://doi.org/10.1007/978-3-031-19214-2_14

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