Office of Operations
21st Century Operations Using 21st Century Technologies

Parking Cruising Analysis Methodology: Final Project Report

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United States Department of Transportation logo.

U.S. Department of Transportation
Federal Highway Administration
Office of Operations
1200 New Jersey Avenue, SE
Washington, DC 20590
ops.fhwa.dot.gov

March 2023

FHWA-HOP-23-004

Table of Contents

[ Foreword ] [ Notices and Quality Assurance Statement ] [ Technical Report Documentation Page ] [ SI Conversion Factors ] [ Abbreviations and Acronyms ]

Executive Summary
Chapter 1. Introduction
Purpose and Scope
Chapter 2. Project Description
Methodology and Approach
Cruise Detector
Determine Streams of Global Positioning System Location Pings That Represent Travel
Match the Global Positioning System Data Streams to a Street Network
Build a Potential Parking Search Radius around the Final Location
Determine a Shortest Path from the Search Radius Boundary to the Final Location
Compare the Path Taken with the Shortest Path
Analyze the Processed Data to Gain Insight into Cruising Conditions
Code Development
Global Positioning System-Independent Cruising Estimates Model
Chapter 3. Specific City Findings
Washington, DC: Cross-Sectional Analysis Focus on Metrorail Stations
Where Cruising Occurs
When Cruising Occurs
Summary
Atlanta, Georgia: Longitudinal Analysis and Mixed-Use Focus
Where Cruising Occurs
When Cruising Occurs
Comparison Case: April 1–September 30, 2020
Summary
Chicago, Illinois: Year Over Year and Time of Day
Where Cruising Occurs
When Cruising Occurs
Do Cruising Patterns Change throughout the Day?
Metered Streets
Summary
Seattle, Washington: Two Meter Policies
Where Cruising Occurs
When Cruising Occurs
Comparison: Before versus after Business-as-Usual Meter Price Change
Cruising Pattern Changes in Response to Meter Decommissioning
Summary
Chapter 4. Lessons Learned
Use Case Summary
Considerations
Third-Party Processing or Raw Location Data
Computing Resources
Data Quality Concerns
Applications
Conclusions
Appendix A. Data Comparability
Comparison of Data Sources
Appendix B. Cruise Detector User Guide
Introduction
Software Requirements
Installation
Data Requirements and Format
Street Network
Census Boundaries
Global Positioning System Data
Config File Changes
Load the Data
Import Street Network
Import Census Boundaries
Import Global Positioning System Data
Map-Matching from User-Generated Traces
Results and Interpretation
Glossary for the Cruise Detector User Guide
Appendix C. Global Positioning System-Independent Cruise Estimator Model Estimation
Overview
Empirical Models
Results
Conclusion

List of Figures

Figure 1. Illustration. Scarce parking can reduce vehicle miles traveled
Figure 2. Illustration. Locations overlaid on a hypothetical street grid.
Figure 3. Illustration. Locations linked chronologically.
Figure 4. Illustration. Probable trips.
Figure 5. Illustration. Cruising: identified when paths traveled exceed shortest paths.
Figure 6. Map. Example showing Chicago cruising hotspots disaggregate data.
Figure 7. Map. Example showing Atlanta cruising hot spots aggregate data.
Figure 8. Graph. Example showing diurnal distribution of trips and cruising trips Washington, DC.
Figure 9. Map. Washington, DC, study area.
Figure 10. Map. Washington, DC, cruising frequency.
Figure 11. Map. Washington, DC, cruising impact.
Figure 12. Graph. Diurnal distribution of all trips and cruising trips.
Figure 13. Graph. Cruising frequency and overall trip making.
Figure 14. Graph. Cruising frequency and total trips, Metrorail catchment area.
Figure 15. Graph. Cruising frequency and total trips, outside Metrorail catchment.
Figure 16. Graph. Diurnal distribution of cruising and cruising as percent of all trips.
Figure 17. Map. Atlanta study area.
Figure 18. Map. Baseline cruising Atlanta.
Figure 19. Map. Cruising impact.
Figure 20. Graph. Diurnal distribution of all trips and cruising trips.
Figure 21. Graph. Cruising frequency and overall trip making.
Figure 22. Map. Atlanta area of detail trip ends.
Figure 23. Map. Atlanta area of detail cruising trip ends.
Figure 24. Graph. Diurnal distribution of trips.
Figure 25. Graph. Proportion of trips cruising.
Figure 26. Map. Cruising trip ends, April–September, 2020.
Figure 27. Map. Cruising impact, April–September, 2020.
Figure 28. Graph. Diurnal distribution of trips and cruising trips, April–September, 2020.
Figure 29. Graph. Diurnal distribution of trips and rate of cruising, April–September, 2020.
Figure 30. Map. Trip ends area of detail, April–September, 2020.
Figure 31. Map. Cruising area of detail.
Figure 32. Graph. Diurnal distribution of trips and cruising trips, April–September, 2020.
Figure 33. Graph. Diurnal distribution of trips with cruise rate superimposed, April–September, 2020.
Figure 34. Map. Cruising 2019.
Figure 35. Map. Cruising 2020.
Figure 36. Map. Comparison of trip ends 2019 and 2020.
Figure 37. Map. Change in cruising frequency.
Figure 38. Graph. Diurnal distribution of trips and cruising trips.
Figure 39. Graph. Diurnal distribution of trips and cruising trips ending on metered streets.
Figure 40. Graph. Diurnal distribution of trips and cruising trips ending on unmetered streets.
Figure 41. Graph. Diurnal distribution of weekday trips.
Figure 42. Graph. Cruising frequency by time of day 2019 and 2020.
Figure 43. Graph. Mean cruising time 2019 and 2020.
Figure 44. Map. Peak and midday comparison of cruising.
Figure 45. Map. West Loop cruising peak and midday.
Figure 46. Map. River North cruising peak and midday.
Figure 47. Map. Hyde Park cruising peak and midday.
Figure 48. Map. Lakeview cruising peak and midday.
Figure 49. Loop cruising meters on and meters off.
Figure 50. Map. Seattle study area.
Figure 51. Map. Cruising frequency.
Figure 52. Map. Cruising impact area.
Figure 53. Map. Cruising for parking boundary effects.
Figure 54. Graph. Diurnal distribution of trips and cruising trips.
Figure 55. Graph. Diurnal distribution of trips and cruising as percent of trips.
Figure 56. Graph. Diurnal trips and cruising on metered and near-metered streets.
Figure 57. Graph. Diurnal distribution of trips and cruising frequency on metered and near metered streets.
Figure 58. Graph. Diurnal distribution of trips and cruising frequency in non-metered areas.
Figure 59. Graph. Change in cruising by meter price change and area type.
Figure 60. Graph. Time spent cruising by meter price change.
Figure 61. Graph. Diurnal distribution of baseline trips and early lockdown trips.
Figure 62. Graph. Cruising frequency in early 2020 and in early spring 2020.
Figure 63. Comparison of cruising hot spots.
Figure 64. Graph. Cruising rates before and after meter suspension.
Figure 65. Graph. Average time spent cruising before and after meter suspension.
Figure 66. Cruising across geographies.
Figure 67. Chart. Volume comparison.
Figure 68. Chart. Cruising frequency by policy time period.
Figure 69. Graph. Time-of-day trip distribution Seattle data sources.
Figure 70. Chart. Spatial distribution of trips Seattle data comparison.

List of Tables

Table 1. Seattle mean cruising time by street type and time of day, in seconds.
Table 2. Trip intensity by area type.
Table 3. Mean cruising time by time of day, in seconds.
Table 4. Summary of data and cruising characteristics.