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Assessing street attractiveness for bicycle route choice : an agent-based approach to investigate travellers' preferences.

Rel. Cristina Pronello, Valentina Rappazzo, José Veiga Simão. Politecnico di Torino, Corso di laurea magistrale in Pianificazione territoriale, urbanistica e paesaggistico-ambientale, 2016



Cycling mobility is a sustainable mode of transport that nowadays governments are trying to promote in order to increase the use of non-motorized vehicles and reduce traffic- related air pollution in urban areas. Bicycling policies try to encourage more people to cycle mainly providing new bicycle paths, but what do inhabitants really need to consider bicycles a good alternative to cars? Which are the best routes for cycling and do bicyclists' preferences change for different users? An in-depth study on travel behavior and route choice represents an essential starting point to understand travelers’ attitudes to cycle. This research aims at assessing the street attractiveness for bicycle route choice, by investigating factors that mostly influence cyclists' preferences when choosing the route. The assessment of these attributes represents a first step for the development of a route choice model that simulates the transport demand.

This research starts during an internship at the Institute of Transport Research of DLR, German Aerospace Center (Deutsches Zentrum fur Luft- und Raumfahrt), in Berlin.

The first chapter of the study presents a literature review on the most relevant attributes influencing bicycle route choice and reports previous studies on route choice models.

The second chapter presents the research objectives and the methodology used to evaluate how much relevant are factors influencing bicycle route choice in Torino and how preferences of different groups of users change depending on the characteristics of the route. For this purpose a survey has been carried out through a questionnaire designed with the group of transport research of Politecnico of Torino, coordinated by Prof. Cristina Pronello, whose results represent the base for the travel demand modelling. Chapter 2 also reports a methodology tested in an urban area in Berlin to visualize the effects of factors on the street network using ArcGIS, defining an approach suitable to work with both linear and zonal data, in order to identify the most attractive streets for cycling.

Chapter 3 reports the results of this study including both the outcomes of the geoanalysis of factors influencing bicycle route choice and the statistical analyses carried out using the data from the survey conducted in Torino.

Finally, the discussion compares the results with the relevant literature and the conclusions summarize the main results of the research.

Relatori: Cristina Pronello, Valentina Rappazzo, José Veiga Simão
Soggetti: U Urbanistica > UK Pianificazione urbana
Corso di laurea: Corso di laurea magistrale in Pianificazione territoriale, urbanistica e paesaggistico-ambientale
URI: http://webthesis.biblio.polito.it/id/eprint/4614



1. Literature review

1.1. Factors influencing bicycle route choice

1.1.1. Stimulating and hindering factors 1.1.2. Relevance of macro-factors on bicycle route choice

1.1.3. Preferences related to groups of users 1.2. Bicycle route choice models

2. Objectives and methodology

2.1. Geoanalysis of factors influencing bicycle route choice by ArcGIS

2.2. The questionnaire design

2.2.1. Travel habits and use of bicycle

2.2.2. Revealed preferences and stated preferences

2.2.3. Preferences related to the most habitual bicycle trips

2.2.4. Assessment of the relevance of factors influencing route choice

2.3. Target population, sample selection and administration of the questionnaire

2.4. Data analysis design

3. Results

3.1. Geoanalysis of factors by ArcGIS

3.1.1. Results of the land use entropy index 3.1.2. Visualization of influences of factors on the street network

3.1.3. Hierarchy of links for bicycle route choice

3.2. Factors and macro-factors influencing the route choice

3.2.1. Description of the sample

3.2.2. Travel habits of users

3.2.3. Comparison between revealed and stated preferences

3.2.4. Perception of macro-factors related to users' routes

3.2.5. Evaluation of factors' effect on bicycle route choice

3.2.6. Definition of latent factors through Factor Analysis

4. Discussion




Appendix I - Geocomputation of a land use entropy index by ArcGIS

Appendix II - Transfer of punctual, linear and zonal data to the graph

Appendix III - Assignment of impedances to the factors based on their relevance



Appleyard, B. (2014), New methods to measure the built environment for sustainable and active travel research and practice: human-scale individual access corridor analytics (IAC) to better understand human-scale behaviors, San Diego State University.

Broach, J., Dill, J., Gliebe, J. (2012), Where do cyclists ride? A route choice model developed with revealed preference GPS data, Transportation Research, part A, 46: 1730- 1740.

Cervero, R., Duncan, M. (2006), Which reduces vehicle travel more: jobs-housing balance or retail-housing mixing?, Journal of the American Planning Association, 72(4): 475-490.

Cervero, R., Kockelman, K. (1997), Travel demand and the 3Ds: density, diversity, and design, Transportation Research, part D, 2(3): 199-219.

Comrey, A. L., Lee, H. B. (1995), Introduzione all'analisi fattoriale, Casa Editrice Ambrosiana, Milano.

Davies, D. G., Halliday, M. E., Mayes, Pocock, R. L. (1997), Attitude to cycling: a qualitative study and conceptual framework, Report RR14, Transport Research Laboratory, Crowthorne.

Dill, J. (2009), Bicycling for transportation and health: the role of infrastructure, J Public Health Pol, 30: 95-110.

Evans-Cowley, J. S., Akar, G. (2013), Streetseen: factors influencing the desirability of a street for bicycling, Annual Meeting of the Transportation Research Board.

Fabrigar, L. R., MacCallum, R. C., Wegener, D. T., Strahan, E. J. (1999), Evaluating the use of Exploratory Factor Analysis in psychological Research, Psychological Methods, 4(3): 272-299.

Field, A. (2009), Discovering statistics using SPSS, Sage, London.

Groves, R., Fowler, F., Couper, M., Lepkowski, J., Singer, E., Tourangeau, R. (2004), Survey methodology, Hoboken, New Jersey, Wiley and Sons.

Habib, K. N., Mann, J., Mahmoud, M., Weiss, A. (2014j, Synopsis of Bicycle Demand in the City of Toronto: Investigating the Effects of Perception, Consciousness and Comfortability on the Purpose of Biking and Bike Ownership, Transportation Research Part A, 70: 67-80.

Heesch, K., Sahlqvist, S., Garrard, J. (2012), Gender differences in recreational and transport cycling: a cross-sectional mixed-methods comparison of cycling patterns, motivators, and constraints, International Journal of Behavioral Nutrition and Physical Activity, 9:106.

Kang, L., Fricker, J.D. (2013), Bicyclist commuters' choice of on-street versus off-street route segments, Transportation, 40: 887-902.

Krenn, P. J., Oja, P., Titze, S. (2014), Route choice of transport bicyclists: a comparison of actually used and shortest routes, International Journal of behavioral nutrition and physical activity, 11 (31).

Li, X. (2006), A spatial entropy-based decision tree for classification of geographical information, Transactions in GIS, 10(3): 451-467.

Maslow, A. H. (1954), Motivation and personality, Harper & Row.

Ortùzar, J., Willumsen, L. G. (2004), Pianificazione dei sistemi di trasporto, Hoepli.

Ortùzar, J., Willumsen, L. G. (2011), Modelling transport, John Wiley & Sons.

Patil, V. H., Singh, S. N., Mishra, S., Donavan, D. T. (2008), Efficient theory development and factor retention criteria: abandon the 'eigenvalue greater than one' criterion, Journal of Business Research, 61: 162-170.

Pereira Segadilha, A. B., da Penha Sanches, S. (2014), Identification of factors that

influence cyclists' route choice, Procedia Social and behavioral sciences, 160: 372-380.

Pronello, C., Camusso, C. (2011), Travellers' profiles definition using statistical multivariate analysis of attitudinal variable, Journal of Transport Geography, 19:1294-1308.

Pucher, J., Buehler, R. (2012), City cycling, MIT Press, London.

Richardson, A. J., Ampt, E. S., Meyburg, A. H. (1995), Survey Methods for Transport Planning, Eucalyptus Press.

Sener, I. N., Eluru, N., Bhat., C. R. (2009), An analysis of bicycle route choice preferences in Texas, U.S., Transportation, 36 (5): 511-539.

Snizek, B., Sick Nielsen, T.A., Skov-Petersen, H. (2013), Mapping bicyclists' experiences in Copenhagen, Journal of Transport Geography, 30: 227-233.

Song, Y., Rodriguez, D. (2005), The measurement of the level of mixed land uses: a synthetic approach, Carolina Transportation Program White Paper Series, Chapel Hill, NC.

Srinivasan, S. (2002), Quantifying Spatial Characteristics of Cities, Urban Studies, 39 (11): 2005-2028.

Stefánsdottir, H. (2014), Urban routes and commuting bicyclists' aesthetic experiences, FORMakademisk, 7(2, 4): 1-21.

Vaughn, S. T. (2011), Women's Safety and Security Issues with Bicycling and Walking: Examination of Potential Planning, Design, and Technology Solutions, Transportation Research Board Conference on Women's Issues in Transportation, 2009 Chicago Illinois, United States: 95-104.

Wahlgren, L., Schantz, P. (2012), Exploring bikeability in a metropolitan setting: stimulating and hindering factors in commuting route environments, BMC Public Health, 12 (168).

Wholey, J., Hartry, H., Newcomer, K. (2004), Handbook of practical program evaluation, San Francisco, CA, Wiley and Sons.

Winters, M., et al. (2010), How far out of the way will we travel? Built environment influences on route selection for bicycle and car travel, Annual Meeting of the Transportation Research Board.




Computation of the entropy index


Cluster analysis


Environmental Atlas Berlin


Factor analysis







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