Built environment determinants of bicycle volume: A longitudinal analysis
Peng Chen
Harbin Institute of Technology Shenzhen Campus
http://orcid.org/0000-0002-3201-7339
Jiangping Zhou
University of Hong Kong
Feiyang Sun
University of Washington
DOI: https://doi.org/10.5198/jtlu.2017.892
Keywords: bicycle volume, built environment, longitudinal data analysis, generalized linear mixed model
Abstract
This study examines determinants of bicycle volume in the built environment with a five-year bicycle count dataset from Seattle, Washington. A generalized linear mixed model (GLMM) is used to capture the bicycle volume change over time while controlling for temporal autocorrelations. The GLMM assumes that bicycle count follows a Poisson distribution. The model results show that (1) the variables of non-winter seasons, peak hours, and weekends are positively associated with the increase of bicycle counts over time; (2) bicycle counts are fewer in steep areas; (3) bicycle counts are greater in zones with more mixed land use, a higher percentage of water bodies, or a greater percentage of workplaces; (4) the increment of bicycle infrastructure is positively associated with the increase of bicycle volume; and (5) bicycling is more popular in neighborhoods with a greater percentage of whites and younger adults. It concludes that areas with a smaller slope variation, a higher employment density, and a shorter distance to water bodies encourage bicycling. This conclusion suggests that to best boost bicycling, decision-makers should consider building more bicycle facilities in flat areas and integrating the facilities with employment densification and open-space creation and planning.References
Akar, G., & Clifton, K. (2009). Influence of individual perceptions and bicycle infrastructure on decision to bike. Transportation Research Record, 2140, 165–172.
Bachand-Marleau, J., Larsen, J., & El-Geneidy, A. (2011). Much-anticipated marriage of cycling and transit: How will it work? Transportation Research Record, 2247, 109–117.
Bhatia, R., & Wier, M. (2011). “Safety in numbers” re-examined: Can we make valid or practical inferences from available evidence? Accident Analysis & Prevention, 43(1), 235–240.
Bolker, B. M., Brooks, M. E, Clark, C. J, Geange, S. W, Poulsen, J. R., Stevens, M H., & White, J. S. (2009). Generalized linear mixed models: A practical guide for ecology and evolution. Trends in ecology & evolution, 24(3), 127–135.
Brooks, G. P., & Barcikowski, R. S. (1999). The precision efficacy analysis for regression sample size method. Paper presented at the meeting of the American Educational Research Association, Montreal, Quebec, Canada.
Buehler, R. (2012). Determinants of bicycle commuting in the Washington, DC region: The role of bicycle parking, cyclist showers, and free car parking at work. Transportation research part D: Transport and Environment, 17(7), 525–531.
Buehler, R., & Pucher, J. (2012). Cycling to work in 90 large American cities: New evidence on the role of bike paths and lanes. Transportation, 39(2), 409–432.
Buehler, R., Pucher, J., Merom, D., & Bauman, A. (2011). Active travel in Germany and the U.S.: Contributions of daily walking and cycling to physical activity. American Journal of Preventive Medicine, 41(3), 241–250. doi: http://dx.doi.org/10.1016/j.amepre.2011.04.012
Chen, P. (2015). Built environment factors in explaining the automobile-involved bicycle crash frequencies: A spatial statistic approach. Safety Science, 79, 336–343. doi: http://dx.doi.org/10.1016/j.ssci.2015.06.016
Chen, P., & Shen, Q. (2016). Built environment effects on cyclist injury severity in automobile-involved bicycle crashes. Accident Analysis & Prevention, 86, 239–246. doi: http://dx.doi.org/10.1016/j.aap.2015.11.002
dell’Olio, L., Ibeas, A., Bordagaray, M., & Ortúzar, J. de D. (2013). Modeling the effects of pro bicycle infrastructure and policies toward sustainable urban mobility. Journal of Urban Planning and Development, 140(2), 04014001.
Dill, J., & Carr, T. (2003). Bicycle commuting and facilities in major U.S. cities: If you build them, commuters will use them. Transportation Research Record, 1828(-1), 116-123. doi: 10.3141/1828-14
Dill, J., McNeil, N., Broach, J., & Ma, L. (2014). Bicycle boulevards and changes in physical activity and active transportation: Findings from a natural experiment. Preventive medicine, 69, S74–S78.
Dill, J., & Voros, K. (2007). Factors affecting bicycling demand: Initial survey findings from the Portland, Oregon, region. Transportation Research Record, 2031(-1), 9–17. doi: 10.3141/2031-02
El Esawey, M., Lim, C., Sayed, T., & Mosa, A. I. (2013). Development of daily adjustment factors for bicycle traffic. Journal of Transportation Engineering, 139(8), 859–871.
El Esawey, M., Mosa, A. I., & Nasr, K. (2015). Estimation of daily bicycle traffic volumes using sparse data. Computers, Environment and Urban Systems, 54, 195–203.
Ewing, R., & Cervero, R.. (2010). Travel and the built environment: A meta-analysis. Journal of the American Planning Association, 76(3), 265–294.
Faghih-Imani, A., Eluru, N., El-Geneidy, A. M., Rabbat, M., & Haq, U. (2014). How land-use and urban form impact bicycle flows: evidence from the bicycle-sharing system (BIXI) in Montreal. Journal of Transport Geography, 41, 306–314.
Fagnant, D. J., & Kockelman, K. (2016). A direct-demand model for bicycle counts: The impacts of level of service and other factors. Environment and Planning B: Planning and Design, 43(1). 93–107.
Gallop, C., Tse, C,, & Zhao, J. (2012). A seasonal autoregressive model of Vancouver bicycle traffic using weather variables. Paper presented at the Transportation Research Board 91st Annual Meeting. Washington, DC.
Gibbons, R. D., Hedeker, D., & DuToit, S. (2010). Advances in analysis of longitudinal data. Annual Review of Clinical Psychology, 6, 79–107. doi: 10.1146/annurev.clinpsy.032408.153550
Goetzke, F., & Rave, T. (2010). Bicycle use in Germany: Explaining differences between municipalities with social network effects. Urban Studies, 48(2), 427–437.
Goodman, A., Sahlqvist, S., Ogilvie, D., & consortium, iConnect. (2013). Who uses new walking and cycling infrastructure and how? Longitudinal results from the UK iConnect study. Preventive Medicine, 57(5), 518–524.
Gosse, C, & Clarens, A. (2014). Estimating spatially and temporally continuous bicycle volumes by using sparse data. Transportation Research Record, 2443, 115–122.
Griswold, J., Medury, A., & Schneider, R. (2011). Pilot models for estimating bicycle intersection volumes. Transportation Research Record, 2247, 1–7.
Handy, S. L., Xing, Y., & Buehler, T. J. (2010). Factors associated with bicycle ownership and use: A study of six small US cities. Transportation, 37(6), 967–985.
Hankey, S., & Lindsey, G. (2016). Facility-demand models of peak-period pedestrian and bicycle traffic: A comparison of fully-specified and reduced-form models. Paper presented at the Transportation Research Board 95th Annual Meeting, Washington, DC.
Hankey, S., Lindsey, G., & Marshall, J. (2014). Day-of-year scaling factors and design considerations for nonmotorized traffic monitoring programs. Transportation Research Record, 2468, 64–73.
Hankey, S., Lindsey, G., Wang, X., Borah, J., Hoff, K., Utecht, B., & Xu, Z. (2012). Estimating use of non-motorized infrastructure: Models of bicycle and pedestrian traffic in Minneapolis, MN. Landscape and Urban Planning, 107(3), 307–316. doi: http://dx.doi.org/10.1016/j.landurbplan.2012.06.005
Heinen, E., van Wee, B., & Maat, K. (2010). Commuting by bicycle: An overview of the literature. Transport Reviews, 30(1), 59–96.
Krizek, K. J., El-Geneidy, A., & Thompson, K. (2007). A detailed analysis of how an urban trail system affects cyclists’ travel. Transportation, 34(5), 611–624. doi: 10.1007/s11116-007-9130-z
Kuzmyak, J. R., Walters, J., Bradley, M., & Kockelman, K. M. (2014). Estimating bicycling and walking for planning and project development: A guidebook. Washington, DC: Transportation Research Board.
Lindsey, G., Wilson, J., Yang, J. A., & Alexa, C. (2008). Urban greenways, trail characteristics and trail use: implications for design. Journal of Urban Design, 13(1), 53–79.
Lovasi, G. S., Schwartz-Soicher, O., Neckerman, K. M., Konty, K., Kerker, B., Quinn, J., & Rundle, A. (2013). Aesthetic amenities and safety hazards associated with walking and bicycling for transportation in New York City. Annals of Behavioral Medicine, 45(1), 76–85.
Ma, L., & Dill, J. (2015). Associations between the objective and perceived built environment and bicycling for transportation. Journal of Transport & Health, 2(2), 248–255.
Moran, M. R., Plaut, P., & Epel, O. B. (2015). Do children walk where they bike? Exploring built environment correlates of children’s walking and bicycling. Journal of Transport and Land Use, 9(2), 43–65.
Moudon, A. V., Lee, C., Cheadle, A. D., Collier, C. W., Johnson, D., Schmid, T. L., & Weather, R. D. (2005). Cycling and the built environment, a US perspective. Transportation Research Part D: Transport and Environment, 10(3), 245–261.
Muhs, C. D., & Clifton, K. J. (2016). Do characteristics of walkable environments support bicycling? Toward a definition of bicycle-supported development. Journal of Transport and Land Use, 9(2), 147–148.
Niemeier, D. A. (1996). Longitudinal analysis of bicycle count variability: Results and modeling implications. Journal of Transportation Engineering, 122(3), 200–206.
Noland, R. B., Smart, M. J., & Guo, Z. (2016). Bikeshare Trip Generation in New York City. Paper presented at the Transportation Research Board 95th Annual Meeting, Transportation Research Board, Washington, DC.
Pikora, T., Giles-Corti, B., Bull, F. , Jamrozik, K., & Rob, D. (2003). Developing a framework for assessment of the environmental determinants of walking and cycling. Social Science and Medicine, 56(8), 1693–1703.
Pucher, J., Dill, J., & Handy, S. (2010). Infrastructure, programs, and policies to increase bicycling: An international review. Preventive medicine, 50, S106–S125.
Qureshi, I., & Fang, Y. (2010). Socialization in open source software projects: A growth mixture modeling approach. Organizational Research Methods, 4(1), 208–238.
Reynolds, C. C., Harris, M. A., Teschke, K., Cripton, P. A., & Winters, M. (2009). The impact of transportation infrastructure on bicycling injuries and crashes: A review of the literature. Environmental Health, 8(1), 47.
Saelens, B., Sallis, J., & Frank, L. (2003). Environmental correlates of walking and cycling: Findings from the transportation, urban design, and planning literatures. Annals of Behavioral Medicine, 25(2), 80–91. doi: 10.1207/s15324796abm2502_03
Schoner, J. E., & Levinson, D. M. (2014). The missing link: Bicycle infrastructure networks and ridership in 74 US cities. Transportation, 41(6), 1187–1204.
Seattle Department of Transportation (2014). Seattle Master Bicycle Plan, Seattle Department of Transportation, Seattle.
Shaheen, S., Guzman, S., & Zhang, H. (2010). Bikesharing in Europe, the Americas, and Asia: Past, present, and future. Transportation Research Record, 2143, 159–167.
Shoup, D. C. (2005). The high cost of free parking (Vol. 206). Chicago: Planners Press.
Stefansdottir, H. (2014). A theoretical perspective on how bicycle commuters might experience aesthetic features of urban space. Journal of Urban Design, 19(4), 496–510.
Strauss, J., & Miranda-Moreno, L. (2013). Spatial modeling of bicycle activity at signalized intersections. The Journal of Transport and Land Use, 6(2), 47–58.
Stryhn, H., Sanchez, J., Morley, P., Booker, C., & Dohoo, I. R. (2006). Interpretation of variance parameters in multilevel Poisson regression models. Proceedings of the 11th International Symposium on Veterinary Epidemiology and Economics, International Society for Veterinary Epidemiology and Economics, Cairns, Australia.
Su, M., Tan, Y.-Y., Liu, Q.-M., Ren, Y.-J., Kawachi, I., Li, L.-M., & Lv, J. (2014). Association between perceived urban built environment attributes and leisure-time physical activity among adults in Hangzhou, China. Preventive Medicine, 66, 60–64.
Thomas, B., & DeRobertis, M. (2013). The safety of urban cycle tracks: A review of the literature. Accident Analysis & Prevention, 52(0), 219–227. doi: http://dx.doi.org/10.1016/j.aap.2012.12.017
Tin, S., Woodward, A., Robinson, E., & Ameratunga, S. (2012). Temporal, seasonal and weather effects on cycle volume: An ecological study. Environmental Health, 11(1), 12.
Van Acker, V., Derudder, B., & Witlox, F. (2013). Why people use their cars while the built environment imposes cycling. Journal of Transport and Land Use, 6(1), 53–62.
Vanparijs, J., Panis, L. I., Meeusen, R., & de Geus, B. (2015). Exposure measurement in bicycle safety analysis: A review of the literature. Accident Analysis & Prevention, 84, 9–19.
Wang, X., Lindsey, G., Schoner, J. E., & Harrison, A. (2015). Modeling bike share station activity: Effects of nearby businesses and jobs on trips to and from stations. Journal of Urban Planning and Development, 142(1), [04015001]. doi: 10.1061/(ASCE)UP.1943-5444.0000273
Wardman, M., Tight, M., & Page, M. (2007). Factors influencing the propensity to cycle to work. Transportation Research Part A: Policy and Practice, 41(4), 339–350. doi: http://dx.doi.org/10.1016/j.tra.2006.09.011
Winters, M., Davidson, G., Kao, D., & Teschke, K. (2011). Motivators and deterrents of bicycling: Comparing influences on decisions to ride. Transportation, 38(1), 153–168.
Xing, Y., Handy, S. L., & Mokhtarian, P. L. (2010). Factors associated with proportions and miles of bicycling for transportation and recreation in six small US cities. Transportation research part D: Transport and Environment, 15(2), 73–81.
