Meta-analysis of the relevance of the physical urban environment for bicycling Kerstin Robertson, VTI, Sebastian Bamberg, University of Bielefeld, John Parkin, London South Bank University, Aslak Fyhri, TØI
Background Kommun Ökad cykeltrafik Ökad gångtrafik Basår Målår Stockholm Cyklandet ska öka under alla 2006 tider på året Göteborg Öka andelen från 8 9 % till Andelen fotresor ska öka 2005 2010 12 % Malmö Öka med 10 procentenheter 10 år Linköping Öka andelen från 30 till 40 % 2008 2028 Örebro Öka andelen till 33 % 2020 Jönköping Öka antalet med 20 % i 2005 centrala Jönköping Umeå Att resor med cykel och till fots tillsammans ska bli de mest använda färdsättet (vardagar) för boende inom tätorten Att andelen resor som görs med kollektivtrafik, cykel eller 2012 till fots utgör tillsammans minst 55 % av alla resor för boende inom tätorten :// minst 65 % av alla resor för boende inom tätorten 2020 Lund Cykeltrafiken per invånare Gångtrafiken per 2004 2013 ska öka med 5 % invånare ska öka Cykeltrafiken per invånare ska öka med 10 % 2004 2030 Gävle Andelen resor <4 km som sker med cykel ska öka (från 23 till 40 % respektive 60 %) Öka antal cykelresor* Antal besökare av centrum och Stortorget ska öka Karlstad Kristianstad Öka andelen med 25 % 2006 2008 2015/2025 Source: Niska, A. et al. (2010) Methodsfor estimating pedestrian and cycle traffic., VTI Report 686.
Bicycle share of trips in Sweden (NTS)
Objective Improved knowledge about the relevance of different environmental (physical) factors for bicycling in urban areas
Systematic review Meta-analysis Qualities Comprehensive / All relevant literature Perspicuous and reproducible Minimizes subjectivity Steps Localizes Evaluates Synthesizes www.ski-epic.com/amsterdam_bicycles/
Theoretical basis Environment Perceived Objective Preferences, attitudes Travel behaviour Living conditions Perceived Objective From Handy (2005)
Environment (objective and perceived) Functional dimensions of the environment land use patterns, the transportation system, safety Aesthetic dimension of the environemnt design. natural landscape (trees, foliage, and greenery) Human use Preferences, intentions Travel behaviour Living conditions Perceived Objective
Examples of operationalization's used in the literature for measuring land use patterns (Handy, 2005) Objective land use characteristics Population density Employment density Retail density Land use mix Land use diversity Land use balance Rating of land use, density, and urban form Indicator of mixed-use or not Indicator high density or not Amount of single-family housing within 300 feet Ratio of single-family housing to multifamily housing within 300 feet
Examples of operationalization's used in the literature for measuring transportation system characteristics (Handy, 2005) Objective transportation system characteristics Percent of network that is a grid Street density Average block area Median walk distance and median walk speed Indicator for presence of sidewalks Indicator for presence of bike paths Percent of streets with sidewalks Average sidewalk width Pedestrian-/Bicycle-friendly design
Literature search Search terms (addressing title, abstract and keywords) cycling and mode choic*, modal choic*, transport*, active transport*, travel*, journey*, commut*, transport demand, cyclist*, bicycl*, biking, bike, bikes, bikeway*, cycle, lane*, path*, route*, track*, trail*, facilit*, "mobility management", commut*, "bike and ride", "land use", "social cohesion", "social capital", resident*, dwelling, housing, planning, design, behavio*r*, demand, town*, urban, traffic, plan*, population, densit*, employment, unemployment, retail, residential, street, character Databases Cambridge Scientific Abstracts (CSA) EBSCO Scopus Web of Science about 3000 hits (gross)
Sourcing of data 1st review Relevance (based on title and summary) 300 2nd review Data availability 100 3rd review Data extraction 23 www.ski-epic.com/amsterdam_bicycles/
Studies used for data extraction/country (% bicycling, share of trips) (0.4 %)* (2 %) (1.2 %)* (26 %) *Cycling to work
Types of studies 8 15
Meta-analysis Dependent variable Frequency or percentage of active commuting or bicycling to school or to work General measure of bicycling frequency Cycling share of journeys Independent variables (aggregated) Distance Land use (including for example accessibility and density), Transport system (including characteristics of both bicycle and other infrastructure, and traffic), Transport safety Neighbourhood characteristics (for example aesthetic qualities)
Significance of variables 5% level of significance Distance Transport system Transport safety Neighbourhood characteristics 8% level of significance Land use
Examples of relevant factors Land use Residential density / Population density Accessibility to retail, service, recreation, workplaces Land use mix Transport system Bicycle facilities / Bike lanes / Walkability Street connectivity Intersections / street mile Road density Crossings Amount and speed of traffic No of stops/km / Hindrances www.ski-epic.com/amsterdam_bicycles/
Examples of relevant factors Transport safety Traffic safety Safety from crime Safe neighborhood Traffic control Safety from theft Neighborhood characteristics Urban / Suburban Neighborhood aesthetics Attractiveness Parkland area / Green space Hilliness Neighborhood walkability
Thank you for your attention! kerstin.robertson@vti.se www.vti.se/cycling