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A platform for research: civil engineering, architecture and urbanism
Estimating Sectional Volume of Travelers Based on Mobile Phone Data
The sectional volume of travelers refers to the number of travelers crossing a section boundary (e.g., river, mountain, railway line, etc.) within a certain time period. Mobile phone data provides continuous and large-scale mobility pattern information without compromising the comprehensiveness of travel modes. We propose a three-stage framework to estimate the sectional volume of travelers using the base station trajectory from massive mobile phone data. In the first two stages, the spatial and temporal uncertainties of trajectories are explicitly addressed by a hybrid filtering algorithm and a cell-to-cell trajectory inference algorithm, respectively. In the third stage, the sectional volume of travelers is estimated using aggregated trajectories. The proposed framework is validated using a sampled dataset with annotated ground truth and a city-scale dataset. The results show that the proposed framework is effective in dealing with spatial and temporal uncertainties of trajectories. The sectional volume estimation method performs stably with a low average error rate and is applicable to section boundaries of different scales.
Estimating Sectional Volume of Travelers Based on Mobile Phone Data
The sectional volume of travelers refers to the number of travelers crossing a section boundary (e.g., river, mountain, railway line, etc.) within a certain time period. Mobile phone data provides continuous and large-scale mobility pattern information without compromising the comprehensiveness of travel modes. We propose a three-stage framework to estimate the sectional volume of travelers using the base station trajectory from massive mobile phone data. In the first two stages, the spatial and temporal uncertainties of trajectories are explicitly addressed by a hybrid filtering algorithm and a cell-to-cell trajectory inference algorithm, respectively. In the third stage, the sectional volume of travelers is estimated using aggregated trajectories. The proposed framework is validated using a sampled dataset with annotated ground truth and a city-scale dataset. The results show that the proposed framework is effective in dealing with spatial and temporal uncertainties of trajectories. The sectional volume estimation method performs stably with a low average error rate and is applicable to section boundaries of different scales.
Estimating Sectional Volume of Travelers Based on Mobile Phone Data
Liu, Zhichen (author) / Fu, Xiao (author) / Liu, Yang (author) / Tong, Weiping (author) / Liu, Zhiyuan (author)
2020-07-20
Article (Journal)
Electronic Resource
Unknown
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