Cell Phone Location Data for Travel Behavior Analysis (2018) / Chapter Skim
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Pages 15-32
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15 Transportation agencies across the country have either purchased or are evaluating the purchase of anonymized and aggregate cell phone data to supplement, enhance, or even replace traditional data sources in support of planning and modeling projects. Agency staff and practitioners need to be clear about the terminology used to describe cell phone data derived from call detail records (CDRs)
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16 Cell Phone Location Data for Travel Behavior Analysis this description. Data streams that are termed "big data" meet one or more of the following "V" criteria:1 • Volume, the size of the amount of data.
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A Planner's View of Cell Phone Data 17 • The frequency and amount of CDR data generation depend on user usage patterns. Frequent users, through repeated use of their devices, provide a lot of information about their daily travel as compared with occasional or infrequent users.
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18 Cell Phone Location Data for Travel Behavior Analysis • Cell phone traces obtained through CDR or GPS data are synthesized through sophisticated algorithms to provide estimates of locations, activities, and travel patterns. To do this, the analyst needs to address the following issues: – Qualifying criteria are needed to determine which devices have sufficient trace information to support further algorithmic investigation.
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A Planner's View of Cell Phone Data 19 – Activity stops at which the activity duration is shorter than the threshold used in the algorithm, and – Activity purposes for locations other than home and work. • Cell phone carrier restrictions aimed at preserving intellectual property and user privacy do not allow the end user to know how exactly the data are collected.
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20 Cell Phone Location Data for Travel Behavior Analysis planning staff, academics, and modeling practitioners -- understand the data needed for traditional transportation models and the more extensive data requirements for detailed activity-based models. Most of the participants have conducted or used traditional household, onboard, and intercept surveys and have considered using nontraditional sources of data to develop, augment, or validate regional and corridor-level models.
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A Planner's View of Cell Phone Data 21 3.2.1.1 Agency Needs That Can Be Addressed by Cell Phone Data Agency staff recognized the need for increasingly complex travel demand models to address today's more nuanced and policy-sensitive questions. Issues included congestion by time of day, the mix of passenger and freight flows, introduction of technology and new modes, optimization of existing facilities, and experimentation with new tools (e.g., congestion pricing and technology)
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22 Cell Phone Location Data for Travel Behavior Analysis activity-based models. The behavioral paradigm may evolve again in response to emerging policy and analysis needs and may benefit from current ongoing research on locational data in transportation and related fields.
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A Planner's View of Cell Phone Data 23 3.2.2.1 Data Collection Program First and foremost, planners should position cell phone data requests within the bigger picture of the agency's data collection program that responds to the different analysis requests and modeling requirements. In particular, questions that agency staff and practitioners need to ask themselves and discuss in detail with data vendors include the following: • Where do cell phone data fit within the bigger picture of the agency's overall planning functions?
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24 Cell Phone Location Data for Travel Behavior Analysis 3.2.2.3 Questions to Ask CDR Data Vendors As a third and final step, agency staff evaluating cell phone data should ask vendors a range of specific questions and hold discussions with their colleagues to help determine the value of cell phone data packages. • What is the technology supported in the data product (e.g., 4G versus 3G)
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A Planner's View of Cell Phone Data 25 3.3.1 CDR Data Utility as a Source of Travel Data Because of the large sample size of cell phone data matrices and their lower unit costs as compared with traditional household travel surveys, there are often discussions about replacing household travel surveys with cell phone data. Table 3-2 contributes to this discussion by showing the strengths and weaknesses of cell phone data as compared with survey data: • The lower unit cost and lower total cost of cell phone data allow the collection of a much larger data set that often spans multiple days.
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26 Cell Phone Location Data for Travel Behavior Analysis that use a smaller sample focus mostly on travel during a single day, and are administered every 10 years or so. • The units of the analysis are different.
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A Planner's View of Cell Phone Data 27 or university activities. However, cell phone–derived data do not provide detail for activities other than home and work.
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28 Cell Phone Location Data for Travel Behavior Analysis • Travel modes. Mode choice can be imputed in cell phone data tables by using a combination of travel speeds and perhaps some transit routing information.
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A Planner's View of Cell Phone Data 29 and display significant peaking. A better understanding of these events can benefit from offmodel components that can be readily updated by using periodic surveys or snapshots that use CDR data.
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30 Cell Phone Location Data for Travel Behavior Analysis area boundaries. Traditional license plate number recording and follow-up survey methods are labor intensive and can be supplemented or replaced by CDR data to provide snapshots of total external–internal or through travel.
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A Planner's View of Cell Phone Data 31 for a range of purposes, from estimating travel demand models or model components to providing selected model outputs for estimation or validation to serving as interim data sets between consecutive travel behavior survey efforts. 3.4.1 Research Method The overarching goal of this research is to present a method that extracts activity locations (stay points)
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32 Cell Phone Location Data for Travel Behavior Analysis • Census Transportation Planning Products. These data were used to obtain journey-to-work travel flows for 2010 (Federal Highway Administration 2013)
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