Cell Phone Location Data for Travel Behavior Analysis (2018)

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2018 N A T I O N A L C O O P E R A T I V E H I G H W A Y R E S E A R C H P R O G R A M NCHRP RESEARCH REPORT 868 Cell Phone Location Data for Travel Behavior Analysis Cambridge Systematics, Inc. Chicago, IL w i t h Massachusetts Institute of Technology Cambridge, MA Subscriber Categories Data and Information Technology • Highways • Planning and Forecasting Research sponsored by the American Association of State Highway and Transportation Officials in cooperation with the Federal Highway Administration

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C O O P E R A T I V E R E S E A R C H P R O G R A M S AUTHOR ACKNOWLEDGMENTS In NCHRP Project 08-95, the research team evaluated the use of cell phone location data for travel behavior analysis and developed guidelines for practitioners. The team, led by Cambridge Systematics, Inc. staff Kimon Proussaloglou, Daniel Beagan, and Anurag Komanduri, analyzed travel data derived from call detail records (CDRs) and contrasted them with estimates derived from survey data and models to provide practical guidance on the value and uses of CDR data. We want to acknowledge the key research contributions of our colleagues at the Massachusetts Institute of Technology (MIT). The case study analysis and results presented in Chapters 4 through 8 and parts of Chapter 2 were contributed by Professor Marta González and Dr. Shan Jiang and based on their original research and data analysis. The case study also reflects work undertaken in prior studies by Professor González and her research group at MIT. Cambridge Systematics developed the background approach and set the stage for the analysis and the guidelines by adopting a practitioner’s perspective in the summary and Chapters 1 through 3. We contrib- uted to the literature review and added our insights to the case study discussed in Chapters 4 through 8 through the lens of a practitioner’s perspective focusing on the inference of stay activity locations and the practical comparisons presented. Finally, we developed Chapter 9 to distill the findings and develop practical guidance for transportation practitioners. This concluding chapter discusses administrative, data-related, and modeling considerations for using cell phone data and presents recent research aimed at improving the industry’s best practices. CRP STAFF FOR NCHRP RESEARCH REPORT 868 Christopher J. Hedges, Director, Cooperative Research Programs Lori L. Sundstrom, Deputy Director, Cooperative Research Programs Lawrence D. Goldstein, Senior Program Officer Anthony P. Avery, Senior Program Assistant Eileen P. Delaney, Director of Publications Natalie Barnes, Associate Director of Publications Janet M. McNaughton, Senior Editor NCHRP PROJECT 08-95 PANEL Field of Transportation Planning—Area of Forecasting Kermit W. Wies, Northwestern University Transportation Center, Evanston, IL (Chair) Rebekah S. Anderson, Ohio DOT, Columbus Tae-Gyu Kim, North Carolina DOT, Raleigh Guy Rousseau, Atlanta Regional Commission, GA Erik E. Sabina, Colorado DOT, Denver Reginald R. Souleyrette, University of Kentucky, Lexington Fang Yuan, Delaware Valley Regional Planning Commission, Philadelphia, PA Sarah Sun, FHWA Liaison Michael L. Cohen, NAS Committee on National Statistics (CNSTAT) Liaison Jennifer L. Weeks, TRB Liaison

NCHRP Research Report 868: Cell Phone Location Data for Travel Behavior Analysis presents guidelines for transportation planners and travel modelers on how to (1) evaluate the extent to which cell phone location data and associated products accurately depict travel; (2) identify whether and how these extensive data resources can be used to improve understanding of travel characteristics and the ability to model travel patterns and behavior more effectively; and (3) support practitioners’ evaluation of the strengths and weaknesses of anonymized call detail record locations from cell phone data. The report includes guidelines for transportation practitioners and agency staff with a vested interest in developing and applying new methods of capturing travel data from cell phones to enhance travel models. This is an emerging field of interest subject to complexi- ties linked to acquiring data and applying these data while maintaining privacy in a complex legal and practical framework. The emergence of these data constitutes a significant oppor- tunity for change in the travel modeling community, with access to detail and volume not previously available. A better understanding of the strengths and weaknesses of these data is an important step in this direction. Information on billions of locations is generated every day from mobile devices. Over the past decade, cell phone location data have become commercially available for trans- portation planning purposes. Mobile signaling can provide a detailed picture showing how people move throughout the day. Cell phone location data used and analyzed in this study correspond to “call detail records,” which include location information every time a call is made or answered, a text message is sent or received, or the Internet is accessed. Call detail records from cell phone location data offer the potential to provide informa- tion about activity location, frequency of repeated travel, travel outside of a study area, and origin–destination data for travel to special events. This information can be used to model, evaluate, and analyze the flow patterns of both residents and visitors in a given study area. With the emergence of large amounts of data, research is needed to explore and evaluate methods used for processing cell phone location data to generate travel behavior infor- mation and provide guidelines for the use of the information by transportation planning practitioners. In tackling this problem, the research team led by Cambridge Systematics, Inc., with support from the Massachusetts Institute of Technology, had to address a broad range of significant questions to evaluate and test opportunities for use of cell phone data. The study approach used travel in the Boston, Massachusetts, region as a case study to compare and contrast traditional travel survey data and regional models with Census data and with F O R E W O R D By Lawrence D. Goldstein Staff Officer Transportation Research Board

cell phone-derived data describing regional travel characteristics. The questions that were addressed included the following: • What are the best options for using cell phone data for travel estimates in support of modeling techniques? • What are the strengths and weaknesses of cell phone data that can support travel behavior analysis and policy decision making? • How can cell phone data be used to enhance access to information on travel behavior characteristics necessary for effective model applications? • What tools and techniques are available for collecting and analyzing cell phone data? • How can travel modelers overcome practical and legal problems associated with data acquisition, and how can this acquisition process respond to privacy requirements? These questions represent only a portion of the detailed considerations required to evaluate the potential application of cell phone data in improving travel behavior modeling as input to overall transportation planning efforts. The first three chapters of NCHRP Research Report 868 set the stage for the analysis and guidelines for practitioners by adopting a practitioner’s perspective and discussing how the strengths and weaknesses of cell phone data are likely to influence planning for transpor- tation projects. Chapters 4 through 6 provide an in-depth discussion of the types of data available and procedures that can be used to apply these data to primary issues affecting travel modeling. The report describes data available; how call detail record data are analyzed to extract daily trajectories; steps involved in identifying activity types encompassing home, work, and “other”; how to derive trip purpose by time of day; and, finally, methods used to develop trip tables using cell phone data. Chapters 7 and 8 present a case study approach to compare the inferred trip tables extracted from the cell detail record data with trip tables from Boston, household travel surveys, and the Boston regional travel demand model. In Chapter 9, the report concludes with guidelines for practitioners, summarizing key admin- istrative, data-related, and modeling considerations about the potential uses of cell phone data and applications by planning and modeling practitioners.

1 Summary 5 Chapter 1 Roadmap to the Report 8 Chapter 2 Travel Behavior from Cell Phone Data 8 2.1 Research Objectives 9 2.2 Current Practice: Data 9 2.3 Survey Data: Strengths and Weaknesses 10 2.4 Current Practice: Models 11 2.5 Cell Phones: Sensors for Data Collection 12 2.6 Cell Data: Strengths and Weaknesses 13 2.7 Inferring Trip Ends and Activities 13 2.8 Inferring Travel Flows 15 Chapter 3 A Planner’s View of Cell Phone Data 15 3.1 Cell Phone Data in Transportation Planning 19 3.2 Transportation Planner Needs 24 3.3 Utility of Cell Phone Data 30 3.4 Research Framework 32 3.5 Summary 33 Chapter 4 Description of Raw Data 33 4.1 Roadmap to the Chapter 33 4.2 Context: Rapid Urbanization 34 4.3 General Description of Data 37 4.4 A Closer Look at Cell Phone Data 42 4.5 Evaluation of CDR Data for This Research 55 4.6 Summary 56 Chapter 5 Extraction of Daily Trajectories 56 5.1 Roadmap to the Chapter 56 5.2 Motivation and Purpose 58 5.3 Stay Extraction Algorithms 60 5.4 Stay Extraction Results 67 5.5 Mapping Stay Locations to Zones 68 5.6 Summary 69 Chapter 6 Measuring Individual Activities: Home, Work, “Other” 69 6.1 Roadmap to the Chapter 69 6.2 Activity Inference 75 6.3 Validation 76 6.4 Summary C O N T E N T S

78 Chapter 7 Trips by Purpose and Time of Day 78 7.1 Roadmap to the Chapter 78 7.2 Concept of Ground Truth 80 7.3 Modeling Departure Time 81 7.4 Modeling Person-Trips 83 7.5 Time-of-Day Patterns 84 7.6 Activity Duration Patterns 85 7.7 Daily Trip-Making Patterns 87 7.8 Commuter Flows 89 7.9 Summary 90 Chapter 8 Model Comparison: Origin–Destination Trips 90 8.1 Roadmap to the Chapter 90 8.2 Data Sources and Model Definition 94 8.3 Comparisons at the Regional Level 105 8.4 Summary 110 Chapter 9 Guidelines for Practitioners 110 9.1 Roadmap to the Chapter 111 9.2 Administrative Considerations 113 9.3 Data Considerations 122 9.4 Modeling Considerations 128 9.5 Future Research Directions 132 9.6 Epilogue 133 Glossary 136 References 142 Additional Resources