Examining the Cycle: How Perceived and Actual Bicycling Risk Influence Cycling Frequency, Roadway Design Preferences, and Support for Cycling Among Bay Area Residents

This dissertation investigates the connection between perceived and actual bicycling risk, andhow they both affect and are affected by one’s attitudes, knowledge, behavior, and experiences. Understanding bicycling risk has gained importance as efforts by the U.S. Department of Transportation, the Environmental Protection Agency, the Centers for Disease Control & Prevention, and others have urged communities to increase cycling for its health, environmental, and social equity benefits. Research has identified numerous barriers to increased bicycling in the U.S., including topography, weather, and trip distance, but the barrier that appears most consistently between studies is the perceived hazard associated with cycling near motorists. Yet, little research has fully explored the concept of risk to understand its component parts, including how 1) various driver actions affect perceived and actual cycling risk, 2) reported crash statistics reflect perceived and actual risk, 3) roadway design preferences are affected by perceived risk, and 4) attitudes toward cycling and cycling risk—especially among drivers—influence support for bicycling in one’s community. A deeper understanding of perceived and actual risk is critical for knowing how to address it, and, ultimately, to encourage more people to bicycle. To begin to answer these questions and demystify bicycling risk, this dissertation employs three main methods: focus groups, an online survey (n=463), and an analysis of reported crash data from the San Francisco Bay Area, one of the regions at the forefront of cycling efforts in the U.S. My findings confirm that perceived and actual cycling risk influence the decision to bicycle, but indicate that the causal pathways are more nuanced than previously understood. First, my data suggest that cyclists experience two types of roadway risk: pervasive risk in the form of near misses that occur frequently, and acute risk that occurs when a cyclist is struck—a less frequent, but more injurious incident. Both types—but particularly near misses— significantly affect perceived risk for cyclists and their family and friends, yet we lack systematic data on near misses and are therefore almost completely ignorant about the extent and effect of their occurrence. Routinely-collected reported crash data provide only limited insight into the type and extent of risk cyclists experience. Second, roadway design preferences are significantly related to perceived risk, and particularly important for attracting new cyclists. Surprisingly, drivers and cyclists both prefer roadway designs with separated space for bicyclists, particularly if barrier-separated, regardless of cycling frequency. Shared space designs are less popular among drivers and much less popular among cyclists, particularly for people who might consider cycling but do not currently do so: only a tiny fraction of potential cyclists feel comfortable sharing space with drivers on commercial streets. Third, perceived cycling risk extends beyond fear of danger for oneself, and is significantly related to support for cycling in one’s community. Structural equation models of perceived cycling risk, attitudes, and behavior revealed that respondents are affected by their perceived risk as cyclists, but also as drivers sharing the roadway with cyclists they view as “scofflaws”, and the risks they project onto other cyclists—particularly those cycling with children. This multi-pronged belief in cycling risk significantly negatively affects bicycling support, including support for new bicycle facilities and public funding to encourage cycling. Based on these findings, I propose a revised theoretical framework for conceptualizing cycling risk and its influences. I conclude the dissertation with policy recommendations for addressing perceived risk.

[1]  K. Teschke,et al.  Motivators and deterrents of bicycling: comparing influences on decisions to ride , 2011 .

[2]  Nathan McNeil,et al.  FOUR TYPES OF CYCLISTS? Testing a Typology to Better Understand Bicycling Behavior and Potential , 2012 .

[3]  T. W. van der Schaaf,et al.  Near Miss Reporting as a Safety Tool , 1991 .

[4]  William W. Hunter,et al.  Police Reporting of Pedestrians and Bicyclists Treated in Hospital Emergency Rooms , 1998 .

[5]  M. Zanna,et al.  Attitudinal qualities relating to the strength of the attitude-behavior relationship☆ , 1978 .

[6]  Jennifer Dill,et al.  Factors Affecting Bicycling Demand , 2007 .

[7]  Susan L Handy,et al.  Explaining Gender Difference in Bicycling Behavior , 2009 .

[8]  R. Fazio How do attitudes guide behavior , 1986 .

[9]  Simon Washington,et al.  On the relationships between self-reported bicycling injuries and perceived risk among cyclists in Queensland, Australia , 2012 .

[10]  Chandra R. Bhat,et al.  Who are Bicyclists? Why and how much are they Bicycling? , 2009 .

[11]  Michael Grant,et al.  How Far Out of the Way Will We Travel? , 2010 .

[12]  K. Teschke,et al.  Route Preferences among Adults in the near Market for Bicycling: Findings of the Cycling in Cities Study , 2010, American journal of health promotion : AJHP.

[13]  John G. Stehlin Regulating Inclusion: Spatial Form, Social Process, and the Normalization of Cycling Practice in the USA , 2014 .

[14]  R. Schneider Theory of routine mode choice decisions: An operational framework to increase sustainable transportation , 2013 .

[15]  J Forester THE BICYCLE TRANSPORTATION CONTROVERSY , 2001 .

[16]  Bradley Flamm,et al.  Environmental Knowledge, Environmental Attitudes, and Vehicle Ownership and Use , 2006 .

[17]  Rune Elvik,et al.  The non-linearity of risk and the promotion of environmentally sustainable transport. , 2009, Accident; analysis and prevention.

[18]  Jill F. Cooper,et al.  The Effects of Transportation Corridor Features on Driver and Pedestrian Behavior and on Community Vitality , 2012 .

[19]  Russell H. Fazio,et al.  On the consistency between attitudes and behavior: Look to the method of attitude formation , 1977 .

[20]  Mary Sissons Joshi,et al.  A diary study of the risk perceptions of road users , 2001 .

[21]  Paul Slovic,et al.  The affect heuristic , 2007, Eur. J. Oper. Res..

[22]  Stephen M. Johnson,et al.  The affect heuristic in judgments of risks and benefits , 2000 .

[23]  I. Ajzen Nature and operation of attitudes. , 2001, Annual review of psychology.

[24]  Jack T Dennerlein,et al.  Risk of injury for bicycling on cycle tracks versus in the street , 2011, Injury Prevention.

[25]  Maria Johansson,et al.  The effects of attitudes and personality traits on mode choice , 2006 .

[26]  Ann M Dellinger,et al.  Motor vehicle crash injury rates by mode of travel, United States: using exposure-based methods to quantify differences. , 2007, American journal of epidemiology.

[27]  Alan Wachtel,et al.  Risk Factors for Bicycle-Motor Vehicle Collisions at Intersections * , 1994 .

[28]  Peter A Cripton,et al.  Route infrastructure and the risk of injuries to bicyclists: a case-crossover study. , 2012, American journal of public health.

[29]  J. Pucher,et al.  Bicycling renaissance in North America? An update and re-appraisal of cycling trends and policies , 2011 .

[30]  Mark Wardman,et al.  Models of perceived cycling risk and route acceptability. , 2007, Accident; analysis and prevention.

[31]  J. Sivacek,et al.  Vested interest as a moderator of attitude–behavior consistency. , 1982 .

[32]  S. Ilgin Guler,et al.  Using Time-Based Metrics to Compare Crash Risk Across Modes and Locations , 2013 .

[33]  Jennifer Dill,et al.  Bicycle Commuting and Facilities in Major U.S. Cities: If You Build Them, Commuters Will Use Them , 2003 .

[34]  Peter G. Furth,et al.  Low-Stress Bicycling and Network Connectivity , 2012 .

[35]  Susan L Handy,et al.  Factors associated with proportions and miles of bicycling for transportation and recreation in six small US cities , 2009 .

[36]  Jill F. Cooper,et al.  Do All Roadway Users Want the Same Things? , 2013 .

[37]  Jana Lynott,et al.  How the Travel Patterns of Older Adults Are Changing: Highlights from the 2009 National Household Travel Survey , 2011 .

[38]  Narelle L. Haworth,et al.  How Do Level of Experience, Purpose for Riding, and Preference for Facilities Affect Location of Riding? , 2011 .

[39]  David R. Ragland,et al.  Pedestrian and Bicycle Safety Evaluation for the City of Emeryville at Four Intersections , 2005 .

[40]  Lindsay S. Arnold,et al.  Association between Roadway Intersection Characteristics and Pedestrian Crash Risk in Alameda County, California , 2010 .

[41]  D. Levinson,et al.  TRAILS, LANES, OR TRAFFIC: VALUING BICYCLE FACILITIES WITH AN ADAPTIVE STATED PREFERENCE SURVEY , 2007 .

[42]  Venkat R. Vattikuti,et al.  Real-Time Human Perceptions: Toward a Bicycle Level of Service , 1997 .

[43]  Maarten A. Hajer,et al.  Discourse Coalitions and the Institutionalization of Practice: The Case of Acid Rain in Great Britain , 2002, The Argumentative Turn in Policy Analysis and Planning.

[44]  F. Fischer Reframing Public Policy: Discursive Politics and Deliberative Practices , 2003 .

[45]  M. Edberg Essentials Of Health Behavior: Social And Behavioral Theory In Public Health , 2007 .

[46]  Meghan Winters,et al.  Safe Cycling: How Do Risk Perceptions Compare With Observed Risk? , 2012, Canadian Journal of Public Health.

[47]  Jennifer Dill,et al.  Where do cyclists ride? A route choice model developed with revealed preference GPS data , 2012 .

[48]  E. McAuley,et al.  Promoting physical activity among older adults: from ecology to the individual. , 2003, American journal of preventive medicine.

[49]  Eric Dumbaugh,et al.  Safe Streets, Livable Streets , 2005 .

[50]  W. Marshall,et al.  Research Article: Evidence on Why Bike-Friendly Cities Are Safer for All Road Users , 2011 .

[51]  Dawn Royal,et al.  National Survey of Bicyclist and Pedestrian Attitudes and Behavior. Volume II: Findings Report , 2008 .

[52]  N. Fairclough Discourse and social change , 1992 .

[53]  E. Singer,et al.  The effects of response rate changes on the index of consumer sentiment. , 2000, Public opinion quarterly.

[54]  S. Granville,et al.  SHARING ROAD SPACE: DRIVERS AND CYCLISTS AS EQUAL ROAD USERS , 2001 .