Influence of Location Frequency on Travel Mode Extraction Using Cellular Phone Data

WANG Yanchen; YANG Fei; LI Rongling; ZHOU Tao

doi:10.3969/j.issn.0258-2724.20220136

Volume 59 Issue 5

Oct. 2024

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Journal of Southwest Jiaotong University > 2024 > 59(5): 1158-1166.

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WANG Yanchen, YANG Fei, LI Rongling, ZHOU Tao. Influence of Location Frequency on Travel Mode Extraction Using Cellular Phone Data[J]. Journal of Southwest Jiaotong University, 2024, 59(5): 1158-1166. doi: 10.3969/j.issn.0258-2724.20220136

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Influence of Location Frequency on Travel Mode Extraction Using Cellular Phone Data

doi: 10.3969/j.issn.0258-2724.20220136

1.
School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 611756, China
2.
China Mobile Group Sichuan Co., Ltd., Chengdu 610084，Chengdu
3.
Chongqing Transportation Planning and Research Institute, Chongqing 401132, China

Received Date: 23 Feb 2022
Rev Recd Date: 05 Jun 2022

Available Online: 20 Jul 2024

Publish Date: 14 Oct 2022

Abstract

Abstract

As a key factor affecting location quality of cellular phone data, location frequency has an important influence on the extraction accuracy of travel mode. In order to quantify the change rule between the location frequency and accuracy of travel mode extraction, a travel mode extraction model based on random forest is proposed. Second, with the help of communication operators, through a field data collection, individual cellular phone data and corresponding real travel information were simultaneously acquired. The dataset is used to verify the travel mode extraction model. Finally, a series of cellular phone datasets with different location frequencies are built through data sampling. With this series of datasets, the extraction accuracy of traffic modes under different location frequencies is evaluated. The evaluation results show that the overall extraction accuracy for walking, non-motorized vehicles, cars, and buses is 79.2%, and the sensitivity of each travel mode to location frequency is different. The sensitivity of non-motorized vehicles and buses is higher, and the sensitivity of walking and cars is relatively low. As the location frequency is decreased from 48 seconds per data to 241 seconds per data, the overall accuracy of non-motorize vehicles and buses is decreased by 19.2% and 21.5%, respectively, while that of walking and car is decreased by 12.8% and 11.5%, respectively. Owning to the requirements of extraction accuracy and computing efficiency, 60 seconds per data is recommended as the optimal threshold for user screening and data sampling.
- intelligent traffic,
- travel mode,
- cellular phone data,
- location frequency,
- random forest

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References(16)

References

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