Cell Phone Location Data for Travel Behavior Analysis (2018) / Chapter Skim
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Pages 69-77
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From page 69... ...
69 6.1 Roadmap to the Chapter This report has so far discussed raw cell phone data, ways to remove noise from call detail record (CDR) data, and methods for extracting meaningful stay points that reflect locations where individual activities are anchored.
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70 Cell Phone Location Data for Travel Behavior Analysis can reasonable be inferred from observations of cell phone records made over multiple days. For each user, the stay extraction process detailed in Chapter 5 results in a time stamp and duration for each observed visit to a stay location.
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Measuring Individual Activities: Home, Work, "Other" 71 6.2.2.2 Inferring Work Location Inferring a user's work location involves considerably greater uncertainty than inferring his or her home location. Two methods of inferring a user's work location, each of which is based on different assumptions, are discussed below.
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From page 72... ...
72 Cell Phone Location Data for Travel Behavior Analysis 6.2.3 An Individual Example Figure 6-1 shows the results of analysis of 3 days' worth of data by the student who voluntarily donated his self-selected cell phone data, collected over a period of 18 months, to the Massachusetts Institute of Technology HuMNet Lab for research purposes. The spatial distribution of the raw data is shown in Figure 4-11.
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From page 73... ...
Measuring Individual Activities: Home, Work, "Other" 73 The inference of activity types at the extracted stays are also shown: • Home is represented by the yellow-faced circles in Figure 6-1, d–f ; • Work is represented by the blue-faced circles in Figure 6-1, d–f ; and • "Other" is represented by the red-faced circles in Figure 6-1, d–f, and the green-faced circles in Figure 6-1, d and f. The number next to each stay location represents the visitation sequence within each day.
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From page 74... ...
74 Cell Phone Location Data for Travel Behavior Analysis analogy with traditional surveys is the increase in sample size and the focus on geographic and socioeconomic market segments to improve the representativeness of the sample. 6.2.4.3 Analogies with Household Surveys There are some interesting analogies that are worth noting when the cell phone expansion factors are compared with the sampling weights in a traditional household survey.
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Measuring Individual Activities: Home, Work, "Other" 75 to have a lower response rate compared with older, suburban respondents who are more likely to be contacted and to respond to a survey. • However, market penetration is higher and the usage of cell phones more extensive among younger cohorts of the population.
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From page 76... ...
76 Cell Phone Location Data for Travel Behavior Analysis Figure 6-3b also compares work locations aggregated at the town level. As with the raw CDR data on the home end, the distribution of raw workplaces is fairly consistent with the 2006–2010 CTPP.
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From page 77... ...
Measuring Individual Activities: Home, Work, "Other" 77 The CDR data, however, are anonymized and do not include socioeconomic characteristics. The sample expansion used a simpler approach that compares the total population in each Census tract with the number of cell phone users who live each tract.
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