Development and Application of Volume Model for Pedestrian Intersections in San Francisco, California
Abstract
The process of modeling pedestrian volume in San Francisco, California, refined the methodology used to develop previous intersection-based models and incorporated variables that were tailored to estimate walking activity in the local urban context. The methodology included two main steps. First, manual and automated pedestrian counts were taken at a sample of 50 study intersections with a variety of characteristics. A series of factor adjustments was applied to produce an estimate of annual pedestrian crossings at each intersection. Second, log-linear regression modeling was used to identify statistically significant relationships between the estimate of annual pedestrian volume and land use, transportation system, local environment, and socioeconomic characteristics near each intersection. Twelve alternative models were considered, and the preferred model had a good overall fit (adjusted R2 = .804). As identified in other communities, pedestrian volumes were positively associated with the number of households and the number of jobs near each intersection. This San Francisco model also found significantly higher pedestrian volumes at intersections (a) in high-activity zones with metered on-street parking, (b) in areas with fewer hills, (c) near university campuses, and (d) under the control of traffic signals. Because the model was based on a relatively small sample of intersections, the number of significant factors was limited to six. Results are being used by public agencies in San Francisco to understand the risks of pedestrian crossings better and to inform citywide pedestrian safety policy and investment.
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References
1. Zegeer C., Nabors D., Gelinne D., Lefler N., and Bushell M. Pedestrian Safety Strategic Plan: Recommendations for Research and Product Development. FHWA-SA-10-035. FHWA, U.S. Department of Transportation, 2010.
2. Schneider R.J., Patten R.S., and Toole J. L. Case Study Analysis of Pedestrian and Bicycle Data Collection in U.S. Communities. In Transportation Research Record: Journal of the Transportation Research Board, No. 1939, Transportation Research Board of the National Academies, Washington, D.C., 2005, pp. 77–90.
3. Wier M., Weintraub J., Humphreys E.H., Seto E., and Bhatia R. An Area-Level Model of Vehicle–Pedestrian Injury Collisions with Implications for Land Use and Transportation Planning. Accident Analysis and Prevention, Vol. 41, No. 1, 2009, pp. 137–145.
4. Purvis C. Incorporating Effects of Smart Growth and TOD in San Francisco Bay Area Travel Demand Models: Current and Future Strategies. 2003. http://www.mtc.ca.gov/maps_and_data/datamart/research/Incorporating_Smart_Growth_MTC_models.pdf.
5. Parsons Brinckerhoff Quade and Douglas, Inc. with Cambridge Systematics, Inc. and Calthorpe Associates. LUTRAQ: Making the Land Use Transportation Air Quality Connection, Volume 4A: The Pedestrian Environment. 1000 Friends of Oregon, 1993. http://ntl.bts.gov/DOCS/tped.html.
6. Clifton K.J., Burnier C.V., Huang S., Kang M.W., and Schneider R. A Meso-Scale Model of Pedestrian Demand. Presented at 4th Joint Meeting of the Association of Collegiate Schools of Planning and the Association of European Schools of Planning, Chicago, Ill., 2008.
7. Raford N., and Ragland D. Space Syntax: Innovative Pedestrian Volume Modeling Tool for Pedestrian Safety. In Transportation Research Record: Journal of the Transportation Research Board, No. 1878, Transportation Research Board of the National Academies, Washington, D.C., 2004, pp. 66–74.
8. Raford N., and Ragland D. Pedestrian Volume Modeling for Traffic Safety and Exposure Analysis. White paper. University of California Traffic Safety Center, Berkeley, 2005. http://repositories.cdlib.org/its/tsc/UCB-TSC-RR-2005-TRB2/.
9. Pushkarev B., and Zupan J. Pedestrian Travel Demand. In Highway Research Record 355, HRB, National Research Council, Washington, D.C., 1971, pp. 37–53.
10. Behnam J., and Patel B. G. A Method for Estimating Pedestrian Volume in a Central Business District. In Transportation Research Record 629, TRB, National Research Council, Washington, D.C., 1977, pp. 22–26.
11. Pulugurtha S.S., and Repaka S. R. Assessment of Models to Measure Pedestrian Activity at Signalized Intersections. In Transportation Research Record: Journal of the Transportation Research Board, No. 2073, Transportation Research Board of the National Academies, Washington, D.C., 2008, pp. 39–48.
12. Schneider R.J., Arnold L.S., and Ragland D. R. Pilot Model for Estimating Pedestrian Intersection Crossing Volumes. In Transportation Research Record: Journal of the Transportation Research Board, No. 2140, Transportation Research Board of the National Academies, Washington, D.C., 2009, pp. 13–26.
13. Liu X., and Griswold J. Pedestrian Volume Modeling: A Case Study of San Francisco. Association of Pacific Coast Geographers Yearbook, Vol. 71, 2009.
14. Jones M.G., Ryan S., Donlan J., Ledbetter L., Arnold L., and Ragland D. Seamless Travel: Measuring Bicycle and Pedestrian Activity in San Diego County and Its Relationship to Land Use, Transportation, Safety, and Facility Type. Alta Planning and Design and Safe Transportation Research and Education Center, University of California, Berkeley, 2010.
15. Haynes M., and Andrzejewski S. GIS Based Bicycle & Pedestrian Demand Forecasting Techniques. Presentation to Travel Model Improvement Program, U.S. Department of Transportation. Fehr & Peers Transportation Consultants, San Francisco, Calif., 2010.
16. Miranda-Moreno L.F., and Fernandes D. Modeling of Pedestrian Activity at Signalized Intersections: Land Use, Urban Form, Weather, and Spatiotemporal Patterns. In Transportation Research Record: Journal of the Transportation Research Board, No. 2264, Transportation Research Board of the National Academies, Washington, D.C., 2011, pp. 74–82.
17. 2010 Demographic Profile Data. U.S. Bureau of the Census. http://factfinder2.census.gov, Accessed July 2011.
18. Geographic Information Systems Data Files. San Francisco Municipal Transportation Agency, Calif., 2011.
19. Schneider R.J., Arnold L.S., and Ragland D. R. Methodology for Counting Pedestrians at Intersections: Use of Automated Counters to Extrapolate Weekly Volumes from Short Manual Counts. In Transportation Research Record: Journal of the Transportation Research Board, No. 2140, Transportation Research Board of the National Academies, Washington, D.C., 2009, pp. 1–12.
20. Schneider R.J., Diogenes M.C., Arnold L.S., Attaset V., Griswold J., and Ragland D. R. Association Between Roadway Intersection Characteristics and Pedestrian Crash Risk in Alameda County, California. In Transportation Research Record: Journal of the Transportation Research Board, No. 2198, Transportation Research Board of the National Academies, Washington, D.C., 2010, pp. 41–51.
21. San Francisco Department of Public Health. Pedestrian Environmental Quality Index. 2011. http://www.sfphes.org/HIA_Tools_PEQI.htm.
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