Identification of Individual Mobility Anchor Places and Patterns Based on Mobile Phone GPS Data
Abstract
1. Introduction
2. Previous Work
3. Data and Methods
3.1. Data Preparation
3.1.1. Overview
3.1.2. Data Filtering
3.2. Primary and Secondary Activity Inferences
3.2.1. Trip and Activity Attributes
3.2.2. Identification of the Primary and Secondary Places
3.2.3. Comparison with the 2018 Household Travel Survey
3.3. Three-Stage Clustering Process
3.3.1. Stage 1: Activity Types
3.3.2. Stage 2: Day Types
3.3.3. Stage 3: Individual Mobility Patterns and Groups
4. Applied Analysis of Daily Mobility Patterns
4.1. Importance of Weekdays and Weekends
4.2. Modal Shares
4.3. Mobility Variability
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Paper | Activity Inference | Activity Pattern Detection | ||||
---|---|---|---|---|---|---|
Rule-Based | Learning-Based | Hybrid | Activity (Trip) Level | Day Level | Individual Level | |
[11] | x | x | ||||
[13] | x | x | ||||
[14] | x | x | x | |||
[15] | x | x | ||||
[16] | x | |||||
[17] | x | x | x | |||
[18] | x | x | x | |||
[19] | x | x | x | x | ||
[20] | x | x | x |
Feb. | May | Oct. | Nov. | EGT-2018 (Age of 15–60) | |
---|---|---|---|---|---|
Ave. daily number of trips | 3.6 | 3.0 | 3.6 | 3.1 | 4.2 |
Ave. daily travel distance (km) | 25.1 | 18.7 | 26.3 | 22.0 | 24.8 |
Ave. daily travel time (min) | 118 | 89 | 155 | 126 | 111 |
Feb. | May | Oct. | Nov. | EGT-2018 (Age of 15–60) | |
---|---|---|---|---|---|
Daily number of activities (>15 min, unique places) | 2.8 | 2.4 | 2.7 | 2.4 | 2.7 |
Daily outdoor activity duration (min) | 403 | 321 | 371 | 336 | 420 |
Activity distance from home (km) | 8.8 | 7.6 | 9.0 | 8.4 | 8.9 |
Type (%) | Activity Duration (h) | Activity Distance (km) | Activity Frequency (Days) | Inference |
---|---|---|---|---|
AT1 (35.0) | 1.1 | 5.0 | 3.5 | Low duration, short distance, and low frequency activity (e.g., shopping) |
AT2 (6.7) | 1.7 | 29.1 | 3.5 | Low duration, far away, and low frequency activity (e.g., leisure) |
AT3 (8.9) | 1.8 | 4.0 | 18.7 | Low duration, short distance, and medium frequency activity (e.g., sports) |
AT4 (6.7) | 8.3 | 9.7 | 6.1 | Medium duration, medium distance, and low frequency activity (e.g., part-time jobs) |
ATP (28.1) | 14.3 | 0.1 | 42.8 | High duration, nearby home, and high frequency activity (e.g., home staying) |
ATS (14.5) | 6.6 | 9.6 | 25.5 | Medium for all (e.g., work or study) |
Type | DTD | DNT | AT1 | AT2 | AT3 | AT4 | ATS | Inference |
---|---|---|---|---|---|---|---|---|
DMP1 (22.9%) | 9.5 | 1.8 | 0.9 | 0.1 | 0.0 | 0.0 | 0.0 | Short daily travel distance + AT1 |
DMP2 (8.9%) | 12.0 | 2.9 | 0.7 | 0.0 | 1.2 | 0.0 | 0.0 | AT3 |
DMP3 (23.3%) | 19.2 | 2.6 | 0.5 | 0.0 | 0.0 | 0.0 | 1.0 | Commuting day |
DMP4 (15.1%) | 21.4 | 2.8 | 0.6 | 0.1 | 0.1 | 1.0 | 0.1 | AT4 |
DMP5 (6.6%) | 21.9 | 3.9 | 0.6 | 0.0 | 1.1 | 0.0 | 1.0 | Commuting day + AT3 |
DMP6 (10.8%) | 24.4 | 5.1 | 3.0 | 0.1 | 0.2 | 0.1 | 0.3 | Medium daily travel distance + AT1 |
DMP7 (8.3%) | 62.9 | 3.9 | 0.6 | 1.6 | 0.1 | 0.1 | 0.3 | AT2 |
DMPP (4.1%) | 6.4 | 2.0 | 0.4 | 0.0 | 0.1 | 0.0 | 0.1 | Home day |
SED | Feb. | May | Oct. | Nov. |
---|---|---|---|---|
Feb. | - | 42.5 | 43.1 | 53.5 |
May | 42.5 | - | 48.1 | 47.7 |
Oct. | 43.1 | 48.1 | - | 31.9 |
Nov. | 53.5 | 47.7 | 31.9 | - |
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Hao, X.; Yin, B.; Liu, L. Identification of Individual Mobility Anchor Places and Patterns Based on Mobile Phone GPS Data. Future Transp. 2024, 4, 1318-1333. https://doi.org/10.3390/futuretransp4040063
Hao X, Yin B, Liu L. Identification of Individual Mobility Anchor Places and Patterns Based on Mobile Phone GPS Data. Future Transportation. 2024; 4(4):1318-1333. https://doi.org/10.3390/futuretransp4040063
Chicago/Turabian StyleHao, Xuguang, Biao Yin, and Liu Liu. 2024. "Identification of Individual Mobility Anchor Places and Patterns Based on Mobile Phone GPS Data" Future Transportation 4, no. 4: 1318-1333. https://doi.org/10.3390/futuretransp4040063
APA StyleHao, X., Yin, B., & Liu, L. (2024). Identification of Individual Mobility Anchor Places and Patterns Based on Mobile Phone GPS Data. Future Transportation, 4(4), 1318-1333. https://doi.org/10.3390/futuretransp4040063