"Safety in Numbers" re-examined: can we make valid or practical inferences from available evidence?

"Safety in Numbers"(SIN), a recent concept in transportation research, policy and planning, has emerged as a causal inference from the non-linear statistical association between estimates of the numbers of walkers or bicyclists in an area and the rate or number of traffic collisions experienced by pedestrians or cyclists. Proponents of SIN argue that greater numbers of walkers or cyclists modify the hazardous behaviors of motor vehicle drivers thus creating safer conditions. This paper critically examines the research on the non-linear association as an adequate empirical basis for this causal interpretation. Given the paucity of evidence supporting a specific mechanism for the SIN effect, alternative plausible explanations of the non-linear association behind SIN, and a potential for unintended consequences from its policy application, the authors call for caution in the use of SIN in transportation policy and planning dialogue and decision-making.

[1]  Craig Lyon,et al.  Pedestrian Collision Prediction Models for Urban Intersections , 2002 .

[2]  R Elvik,et al.  Area-wide urban traffic calming schemes: a meta-analysis of safety effects. , 2001, Accident; analysis and prevention.

[3]  A. Constant,et al.  Protecting Vulnerable Road Users from Injury , 2010, PLoS medicine.

[4]  D. Ragland,et al.  The Continuing Debate about Safety in Numbers—Data from Oakland, CA , 2006 .

[5]  B. Clinton,et al.  Executive Order 12898: Federal Actions to Address Environmental Justice in Minority Populations and Low-Income Populations , 1994 .

[6]  R. Norton,et al.  Effect of environmental factors on risk of injury of child pedestrians by motor vehicles: a case-control study , 1995, BMJ.

[7]  Anne T McCartt,et al.  A review of evidence-based traffic engineering measures designed to reduce pedestrian-motor vehicle crashes. , 2003, American journal of public health.

[8]  S. L. Lima,et al.  Randomness, chaos and confusion in the study of antipredator vigilance. , 1998, Trends in ecology & evolution.

[9]  P. A. Bednekoff,et al.  Re–examining safety in numbers: interactions between risk dilution and collective detection depend upon predator targeting behaviour , 1998, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[10]  K Todd,et al.  PEDESTRIAN REGULATIONS IN THE UNITED STATES: A CRITICAL REVIEW , 1992 .

[11]  Paul Wilkinson,et al.  Effect of 20 mph traffic speed zones on road injuries in London, 1986-2006: controlled interrupted time series analysis , 2009, BMJ : British Medical Journal.

[12]  Mohamed Abdel-Aty,et al.  Comprehensive analysis of vehicle-pedestrian crashes at intersections in Florida. , 2005, Accident; analysis and prevention.

[13]  Ezra Hauer,et al.  Traffic conflicts and exposure , 1982 .

[14]  Todd Swanstrom,et al.  Healthy, equitable transportation policy: recommendations and research. , 2009 .

[15]  Lawrence D. Frank,et al.  Understanding the Relationship Between Public Health and the Built Environment: A Report Prepared for the LEED-ND Core Committee , 2006 .

[16]  Bruce W Landis,et al.  Modeling the Roadside Walking Environment: Pedestrian Level of Service , 2001 .

[17]  M. Szklo,et al.  Epidemiology: Beyond the Basics , 1999 .

[18]  Anne E. Magurran,et al.  Minnows and the selfish herd: effects of predation risk on shoaling behaviour are dependent on habitat complexity , 2008, Animal Behaviour.

[19]  Anastasia Loukaitou-Sideris,et al.  Death on the Crosswalk , 2007 .

[20]  U Brüde,et al.  Models for predicting accidents at junctions where pedestrians and cyclists are involved. How well do they fit? , 1993, Accident; analysis and prevention.

[21]  P L Jacobsen,et al.  Who owns the roads? How motorised traffic discourages walking and bicycling , 2009, Injury Prevention.

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

[23]  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.

[24]  P. Jacobsen Safety in numbers: more walkers and bicyclists, safer walking and bicycling , 2003, Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention.

[25]  L. Leden Pedestrian risk decrease with pedestrian flow. A case study based on data from signalized intersections in Hamilton, Ontario. , 2002, Accident; analysis and prevention.

[26]  H-Y Berg,et al.  Reducing crashes and injuries among young drivers: what kind of prevention should we be focusing on? , 2006, Injury Prevention.

[27]  Lars Ekman,et al.  ON THE TREATMENT OF FLOW IN TRAFFIC SAFETY ANALYSIS: A NON-PARAMETRIC APPROACH APPLIED ON VULNERABLE ROAD USERS , 1996 .

[28]  P J Gruenewald,et al.  Demographic and environmental correlates of pedestrian injury collisions: a spatial analysis. , 2000, Accident; analysis and prevention.

[29]  Rajiv Bhatia,et al.  An area-level model of vehicle-pedestrian injury collisions with implications for land use and transportation planning. , 2009, Accident; analysis and prevention.

[30]  N. Haworth,et al.  VISION ZERO: AN ETHICAL APPROACH TO SAFETY AND MOBILITY , 1999 .

[31]  D F Preusser,et al.  LITERATURE REVIEW ON VEHICLE TRAVEL SPEEDS AND PEDESTRIAN INJURIES - FINAL REPORT , 1999 .

[32]  D. Brugge,et al.  Traffic injury data, policy, and public health: Lessons from Boston Chinatown , 2002, Journal of Urban Health.

[33]  D M Zaidel,et al.  A modeling perspective on the culture of driving. , 1992, Accident; analysis and prevention.