Cell Phone Location Data for Travel Behavior Analysis (2018) / Chapter Skim
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56 5.1 Roadmap to the Chapter This technical chapter discusses how the noisy and massive cell phone call detail record (CDR) data were analyzed to extract daily trajectories.
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Extraction of Daily Trajectories 57 Passively collected cell phone data provide an unparalleled scale of observation. New methods of estimating travel demand need to balance trade-offs between small, but complete, data for a short period as compared with large, but incomplete, data over a longer period (Toole et al.
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58 Cell Phone Location Data for Travel Behavior Analysis are designed to filter the cell phone data to infer human activities and travel in space and time. Parsing passive cell phone data to extract "stay locations" identifies activity anchor points in an individual's daily travels.
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Extraction of Daily Trajectories 59 As shown by Zheng et al.
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60 Cell Phone Location Data for Travel Behavior Analysis required to be no more than a certain threshold. Again, the observation is moved to the location of the new medoid of the clusters, as shown in Figure 5-2.
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Extraction of Daily Trajectories 61 Figure 5-3. Pattern of stay durations: (top)
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62 Cell Phone Location Data for Travel Behavior Analysis Figure 5-5. Stay locations extracted by using grid-based algorithm (blue points = user's raw cell phone data; red bulbs = stays extracted by using grid algorithm and anonymous user data.
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Extraction of Daily Trajectories 63 Figure 5-6. Effect of grid- and point-based algorithms on stay locations (blue points = raw phone records; circles = filtered locations)
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64 Cell Phone Location Data for Travel Behavior Analysis point-based algorithm presented in Section 5.3.2 and compares the results with those derived using the grid-based algorithm. In both cases, the noise in the raw cell phone data was removed and locations were reduced to a few anchor points where the individual was estimated to have conducted activities.
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Extraction of Daily Trajectories 65 Figure 5-9, which was presented in an earlier published study of the authors' research group (Widhalm et al.
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66 Cell Phone Location Data for Travel Behavior Analysis Legend Source: Jiang et al.
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Extraction of Daily Trajectories 67 correspond to work activities. There is also a concentration of 10- to 16-hour stays starting between 4 p.m.
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68 Cell Phone Location Data for Travel Behavior Analysis of calls between 10 meters and 100 meters. By using this method, the stay points were easily converted into zones such as Census tracts.
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