How Far Out of the Way Will We Travel?: Built Environment Influences on Route Selection for Bicycle and Car Travel
Abstract
Current travel demand models are calibrated for motorized transportation and do not perform as well for nonmotorized modes. Little evidence exists on how much, and for what reasons, the routes people travel deviate from the shortest-path or least-cost routes generated by transportation models. This paper investigates differences in total distance, road type used, and built environment features for shortest-path routes versus actual routes for utilitarian bicycle trips (n = 50) and car trips (n = 67) in Metro Vancouver, Canada. Bike trips were, on average, 360 m longer than the shortest possible route; car trips were 540 m longer. Regardless of mode, people do not detour far off the shortest route: detour ratios (actual distance/shortest distance) were similar, with three-fourths of trips within 10% of the shortest distance and at least 90% within 25%. Differences in the built environment measures en route suggest why bike commuters chose to detour: the actual routes had significantly more bicycle facilities (traffic-calming features, bike stencils, and signage) than did the shortest-path routes. Compared with shortest-path routes, cyclists spent significantly less of their travel distance along arterial roads and significantly more along local roads, off-street paths, and routes with bike facilities. As expected, car trips were more likely to be along highways and less likely to be along local roads than predicted by the shortest route. The results illustrate factors that might be included in travel models to more accurately model nonmotorized transportation and provide guidance for how dense bike facilities need to be when infrastructure to support cycling is designed.
Get full access to this article
View all access and purchase options for this article.
References
1. Meyer M., and Miller E. Urban Transportation Planning: A Decision-Oriented Approach, 2nd ed. McGraw-Hill, New York, 2001.
2. Prochaska J. O., Redding C. A., and Evers K. E. The Transtheoretical Model and Stages of Change. In Health Behavior and Health Education: Theory, Research, and Practice (Glanz K., Rimer B. K., and Lewis F. M., eds.), Jossey-Bass, San Francisco, Calif., 2002, pp. 99–120.
3. Prochaska J. O., Velicer W. F., Rossi J. S., Goldstein M. G., Marcus B. H., Rakowski W., Fiore C., Harlow L. L., Redding C. A., Rosenbloom D.et al. Stages of Change and Decisional Balance for 12 Problem Behaviors. Health Psychology, Vol. 13, Issue 1, 1994, pp. 39–46.
4. Statistics Canada. Employed Labour Force 15 Years and over Having a Usual Place of Work in Occupied Private Dwellings by Commuting Distance, 2006 Counts. http://www12.statcan.ca/english/census06/data/highlights/POW/Table605.cfm?Lang=E&T=605&GH=8&GF=0&G5=0&SC=1&RPP=100&SR=1&SO=0&O=D&D1=1. Accessed March 2, 2009.
5. Statistics Canada. Employed Labour Force by Mode of Transportation, Both Sexes, 2006 Counts. http://www12.statcan.ca/english/census06/data/highlights/POW/Table603.cfm?Lang=E&T=603&GH=2&GF=933&SC=1&SO=0&O=A. Accessed March 2, 2009.
6. Winters M., and Teschke K. Route Preferences Among Adults in the Near Market for Cycling: Findings of the Cycling in Cities Study. American Journal of Health Promotion, in press.
7. GIS Innovations. http://www.gis-innovations.bc.ca/atlas_overview.htm. Accessed May 1, 2008.
8. Brownson R. C., Hoehner C. M., Day K., Forsyth A., and Sallis J. F. Measuring the Built Environment for Physical Activity: State of the Science. American Journal of Preventive Medicine, Vol. 36, Issue 4, Supplement 1, 2009, pp. S99–S123.
9. Statistics Canada. Complete Cumulative Profile, Including Income and Earnings, and Shelter Costs, Canada, Provinces, Territories, Census Divisions, Census Subdivisions, and Dissemination Areas: Census of Canada, 2006 Data. http://data.library.ubc.ca/java/jsp/database/production/detail.jsp?id=1057.
10. Su J. G., Brauer M., and Buzzelli M. Estimating Urban Morphometry at the Neighborhood Scale for Improvement in Modeling Long-Term Average Air Pollution Concentrations. Atmospheric Environment, Vol. 42, Issue 24, 2008, pp. 7884–7893.
11. Henderson S. B., Beckerman B., Jerrett M., and Brauer M. Application of Land Use Regression to Estimate Long-Term Concentrations of Traffic-Related Nitrogen Oxides and Fine Particulate Matter. Environmental Science and Technology, Vol. 41, Issue 7, 2007, pp. 2422–2428.
12. Forsyth A., ed. Environment and Physical Activity: GIS Protocols. Version 4.1. University of Minnesota, Minneapolis, and Cornell University, Ithaca, N.Y., 2007.
13. BC Assessment. http://www.bcassessment.bc.ca/products/index.asp. Accessed January 2006.
14. Saelens B. E., Sallis J. F., and Frank L. D. Environmental Correlates of Walking and Cycling: Findings from the Transportation, Urban Design and Planning Literatures. Annals of Behavioral Medicine, Vol. 25, Issue 2, 2003, pp. 80–91.
15. Hess P. M., Moudon A. V., and Logsdon M. G. Measuring Land Use Patterns for Transportation Research. In Transportation Research Record: Journal of the Transportation Research Board, No. 1780, TRB, National Research Council, Washington, D.C., 2001, pp. 17–24.
16. Song Y., and Rodríguez D. A. The Measurement of the Level of Mixed Land Uses: A Synthetic Approach. White Paper series. Carolina Transportation Program, Chapel Hill, N.C., 2005.
17. Hyodo T., Suzuki N., and Takahashi K. Modeling of Bicycle Route and Destination Choice Behavior for Bicycle Road Network Plan. In Transportation Research Record: Journal of the Transportation Research Board, No. 1705, TRB, National Research Council, Washington, D.C., 2000, pp. 70–76.
18. Aultman-Hall L., Hall F. L., and Baetz B. B. Analysis of Bicycle Commuter Routes Using Geographic Information Systems: Implications for Bicycle Planning. In Transportation Research Record 1578, TRB, National Research Council, Washington, D.C., 1997, pp. 102–110.
19. Howard C., and Burns E. K. Cycling to Work in Phoenix: Route Choice, Travel Behavior, and Commuter Characteristics. In Transportation Research Record: Journal of the Transportation Research Board, No. 1773, TRB, National Research Council, Washington, D.C., 2001, pp. 39–46.
20. Krizek K., El-Geneidy A., and Thompson K. A Detailed Analysis of How an Urban Trail System Affects Cyclists' Travel. Transportation, Vol. 34, Issue 5, 2007, pp. 611–624.
21. Dill J. Bicycling for Transportation and Health: The Role of Infrastructure. Journal of Public Health Policy, Vol. 30, Supplement 1, 2009, pp. S95–S110.
22. Hunt J. D., and Abraham J. E. Influences on Bicycle Use. Transportation, Vol. 34, Issue 4, 2007, pp. 453–470.
23. Winters M.et al. Motivators and Deterrents of Bicycling: Comparing Influences on Decisions to Ride. Transportation, www.springerlink.com/content/ex63304355024117
24. Stinson M. A., and Bhat C. R. Commuter Bicyclist Route Choice: Analysis Using a Stated Preference Survey. In Transportation Research Record: Journal of the Transportation Research Board, No. 1828, Transportation Research Board of the National Academies, Washington, D.C., 2003, pp. 107–115.
25. Tilahun N. Y., Levinson D. M., and Krizek K. J. Trails, Lanes, or Traffic: Valuing Bicycle Facilities with an Adaptive Stated Preference Survey. Transportation Research Part A: Policy and Practice, Vol. 41, Issue 4, 2007, pp. 287–301.
26. Forester J. The Bicycle Transportation Controversy. Transportation Quarterly, Vol. 55, Issue 2, 2001, pp. 7–17.
27. Pucher J., and Buehler R. Making Cycling Irresistible: Lessons from the Netherlands, Denmark, and Germany. Transport Reviews, Vol. 28, Issue 4, 2008, pp. 495–528.
28. Winters M., and Cooper A. What Makes a Neighbourhood Bikeable: Reporting on the Results of Focus Group Sessions. Translink and University of British Columbia, Vancouver, British Columbia, Canada, 2008.
29. Krizek K. J. Operationalizing Neighborhood Accessibility for Land Use—Travel Behavior Research and Regional Modeling. Journal of Planning Education and Research, Vol. 22, 2003, pp. 270–287.
30. McGinn A. P., Evenson K. R., Herring A. H., and Huston S. L. The Relationship Between Leisure, Walking, and Transportation Activity with the Natural Environment. Health and Place, Vol. 13, Issue 3, 2007, pp. 588–602.
31. Troped P. J., Saunders R. P., Pate R. R., Reininger B., Ureda J. R., and Thompson S. J. Associations Between Self-Reported and Objective Physical Environmental Factors and Use of a Community Rail-Trail. Preventive Medicine, Vol. 32, Issue 2, 2001, pp. 191–200.
32. Moudon A. V., Lee C., Cheadle A. D., Collier C. W., Johnson D., Schmid T. L., and Weather R. D. Cycling and the Built Environment, a US Perspective. Transportation Research Part D, Vol. 10, 2005, pp. 245–261.
33. Cervero R., and Duncan M. Walking, Bicycling, and Urban Landscapes: Evidence from the San Francisco Bay Area. American Journal of Public Health, Vol. 93, Issue 9, pp. 1478–1483.
Cite article
Cite article
Cite article
OR
Download to reference manager
If you have citation software installed, you can download article citation data to the citation manager of your choice
Information, rights and permissions
Information
Published In
Article first published online: January 1, 2010
Issue published: January 2010
Authors
Metrics and citations
Metrics
Journals metrics
This article was published in Transportation Research Record: Journal of the Transportation Research Board.
VIEW ALL JOURNAL METRICSArticle usage*
Total views and downloads: 725
*Article usage tracking started in December 2016
Altmetric
See the impact this article is making through the number of times it’s been read, and the Altmetric Score.
Learn more about the Altmetric Scores
Articles citing this one
Receive email alerts when this article is cited
Web of Science: 0
Crossref: 89
- Road infrastructures, spatial surroundings, and the demand and route c...
- A systematic scoping review of methods for estimating link-level bicyc...
- Introducing a Framework for Cycling Investment Prioritization
- Perceptions, People, and Places: Influences on Cycling for Latino Immi...
- Another Form of Neighborhood Effect Bias:The Neighborhood Effect Polar...
- Disclosing the Impact of Micro-level Environmental Characteristics on ...
- Maximizing modal shift in bicycle network design
- Measuring urban vibrancy of neighborhood performance using social medi...
- Built environment bikeability as a predictor of cycling frequency: Les...
- Pedaling through a virtually redesigned city: Evaluation of traffic pl...
- Understanding preferences for bicycling and bicycle infrastructure
- Evaluating the TOPODATA digital elevation model as a source of informa...
- Dimensioning of Cycle Lanes Based on the Assessment of Comfort for Cyc...
- Have Paved Trails and Protected Bike Lanes Led to More Bicycling in At...
- Understanding bikeability: a methodology to assess urban networks
- Exploring Users’ perceptions of factors influencing cycling route choi...
- Cycling in Tibet: An analysis of tourists’ spatiotemporal behavior and...
- Türkiye'de Uzun Bisiklet Parkurlarının Bisiklet Kullanımına Etkisinin ...
- Network level design for cycling
- Investigating the Determinants of Dockless Bikeshare and Bus Integrati...
- An E-Scooter Route Assignment Framework to Improve User Safety, Comfor...
- Assessing cyclists’ routing preferences by analyzing extensive user se...
- More than Bike Lanes—A Multifactorial Index of Urban Bikeability
- Assessing filtered permeability around the globe: The unknown beloved ...
- “Going through a little bit of growing pains”: A qualitative study of ...
- Are young users willing to shift from carsharing to scooter–sharing?
- E-scooters and sustainability: Investigating the relationship between ...
- Conceptualizing cycling experience in urban design research: a systema...
- Route choice of bike share users: Leveraging GPS data to derive choice...
- The path and time efficiency of residents' trips of different purposes...
- Bicycle network performance: Assessing the directness of bicycle facil...
- Road environments and bicyclist route choice: The cases of Davis and S...
- Electric vehicle charging station locations: Elastic demand, station c...
- Networks of need: a geospatial analysis of secondary cities
- The built environment and active transportation safety in children and...
- You say one route, we observe four: Using naturalistic observation to ...
- Evidence of Green Areas, Cycle Infrastructure and Attractive Destinati...
- Objective vs. subjective measures of street environments in pedestrian...
- Impact of household proximity to the cycling network on bicycle riders...
- Bike network design problem with a path-size logit-based equilibrium c...
- Does One Bicycle Facility Type Fit All? Evaluating the Stated Usage of...
- Low-stress bicycling connectivity: Assessment of the network build-out...
- Built environment determinants of pedestrians’ and bicyclists’ route c...
- Winter Sabotage: The Three-Way Interactive Effect of Gender, Age, and ...
- Correcting Bias in Crowdsourced Data to Map Bicycle Ridership of All B...
- Data-driven methods for dockless bike infrastructure planning
- Network design, built and natural environments, and bicycle commuting:...
- Shortest path distance vs. least directional change: Empirical testing...
- Why do bicyclists take detours? A multilevel regression model using sm...
- Associations of built environments with spatiotemporal patterns of pub...
- Modeling Bikeability of Urban Systems
- Perceived Safety and Separated Bike Lanes in the Midwest: Results from...
- The Keys to Connectivity: The District of Columbia’s Innovative Approa...
- Modal shift potential of improvements in cycle access to exurban train...
- An adaption of the level of traffic stress based on evidence from the ...
- Examining the role of trip destination and neighborhood attributes in ...
- Differences in physical environmental characteristics between adolesce...
- Exploring adoption determinants of tax-subsidized company-leasing bicy...
- Cycling injury risk in London: A case-control study exploring the impa...
- Built environment and public bike usage for metro access: A comparison...
- How do cyclists make their way? - A GPS-based revealed preference stud...
- Understanding bike share cyclist route choice using GPS data: Comparin...
- Assessing area-wide bikeability: A grey analytic network process
- Analysing cyclist behaviour at cycling facility discontinuities using...
- GIS-based episode reconstruction toolkit (GERT): A transferable, modul...
- A GPS data-based analysis of built environment influences on bicyclist...
- Revealed Preference Methods for Studying Bicycle Route Choice—A System...
- Monitoring city wide patterns of cycling safety
- Bicycle equity in Brazil: Access to safe cycling routes across neighbo...
- Evaluating bicycle–vehicle conflicts and delays on urban streets with ...
- Public bike system pricing and usage in Taipei
- Helmet Use Among Personal Bicycle Riders and Bike Share Users in Vanco...
- Bicyclists’ preferences for route characteristics and crowding in Cope...
- Examining Associations of Environmental Characteristics with Recreatio...
- We can all get along: The alignment of driver and bicyclist roadway de...
- Short-term planning and policy interventions to promote cycling in urb...
- Urban transport justice
- Embodied bicycle commuters in a car world
- Mapping ridership using crowdsourced cycling data
- Bikeway Networks: A Review of Effects on Cycling
- Are GIS-modelled routes a useful proxy for the actual routes followed ...
- Where does bicycling for health happen? Analysing volunteered geograph...
- Optimization Framework for Bicycle Network Design
- Influence of bridge facility attributes on bicycle travel behavior
- Mapping Bikeability: A Spatial Tool to Support Sustainable Travel
- Perception of safety of cyclists in Dublin City
- Where do cyclists ride? A route choice model developed with revealed p...
- Exploring bikeability in a metropolitan setting: stimulating and hinde...
- Built Environment Influences on Healthy Transportation Choices: Bicycl...
Figures and tables
Figures & Media
Tables
View Options
Get access
Access options
If you have access to journal content via a personal subscription, university, library, employer or society, select from the options below:
loading institutional access options
Alternatively, view purchase options below:
Purchase 24 hour online access to view and download content.
Access journal content via a DeepDyve subscription or find out more about this option.
