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Safety in numbers

Introduction

There are many myths about cycling and in particular about the safety of cycling. Cycle helmet promotion builds strongly on the fear that cycling is unsafe, but there is clear evidence that people who cycle regularly live longer than those who do not cycle, with less ill health (BHRF, 1185). How can an activity that enhances health and longevity more than any other be unsafe?

Moreover, there is good evidence that the most important factor in enhancing safety for an individual when cycling in traffic is the number of other people who cycle. When cycle use doubles, the risk of a motorist hitting a cyclist goes down by about a third. This is the most likely explanation why it is in countries with large cycling populations, such as the Netherlands and Denmark, that risk is lowest.

The benefits of 'Safety in numbers' have now been shown to be valid within and across countries and continents. They are also consistent across time. The studies below are some of the evidence. They demonstrate not only that risk when cycling decreases the more people who cycle, but also the converse, that anything which leads to fewer people cycling increases risk for those who continue. This could be one reason why cycle helmet promotion and laws have not led to a detectable decrease in risk, for the most significant outcome has been to discourage cycling.

Road safety professionals concerned about reducing the likelihood of crashes between motorists and cyclists should consider measures that increase cycling.

Comparison of European and US cycling and walking casualty data

Jacobsen, 2003

In this study, Jacobsen examined population level data from 68 cities in California USA, 47 towns in Denmark and 14 European countries, to compare the amount of cycling and walking and the injuries occuring in collisions with motor vehicles. Additionally, time series data was considered for the United Kingdom and the Netherlands. The amount of cycling and walking varied from 6% of all trips in the USA to 46% in the Netherlands.

It was found across all the data sets that motorists are less likely to hit bicyclists and pedestrians when there are more people bicycling or walking. Modeling this relationship as a power curve yielded the result that at the population level, the number of motorists hitting bicyclists and walkers will increase at roughly 0.4 power of the number of people bicycling or walking. For example, a community doubling its cycle use can expect a 32% increase in injuries (20.4 = 1.32). Taking into account the amount of bicycling, the probability that a motorist will strike an individual person bicycling declines with the roughly -0.6 power of the number of persons cycling. An individual’s risk while cycling in a community with twice as much cycling will reduce to 66% (20.4/2 = 2-0.6 = 0.66).

The author considers that the primary mechanism at work in reducing risk when more people cycle is behaviour adaptation by motorists. Therefore, not only are policies that increase the numbers of people walking and cycling a good way to improve safety, but laws should be revised to reflect the premise that the number of collisions with vulnerable road users is determined largely by motorist behaviour.

KEY POINTS FROM THE STUDY

  • Where, or when, more people walk or bicycle, the less likely any of them are to be injured by motorists. There is safety in numbers.
  • Motorist behavior evidently largely controls the likelihood of collisions with people walking and bicycling.
  • Comparison of pedestrian and cyclist collision frequencies between communities and over time periods need to reflect the amount of walking and bicycling.
  • Efforts to enhance pedestrian and cyclist safety, including traffic engineering and legal policies, need to be examined for their ability to modify motorist behavior.
  • Policies that increase walking and bicycling appear to be an effective route to improving the safety of people walking and bicycling.

Australia

Robinson, 2005b used three data sets from Australia to yield results very similar to Jacobsen.

The average daily distance cycled in different Australian States in 1985-86 was compared with fatality rates. The mean per capita distance cycled in Western Australia was double that in New South Wales and the risk of fatality 35% less.

In Western Australia from 1982 to 1989 cycling almost doubled. During the same period, the number of cyclists admitted to hospital fell by 48% and reported fatal and serious injuries went down by 33%.

In the 1990s, the amount of cycling in Australia was greatly reduced following the passage of helmet laws. Estimates of the injury rate per cyclist suggest that the Safety in Numbers principle then worked in reverse. Pedestrian deaths and serious head injuries (DSHI) in Victoria fell by 74% due to road safety campaigns that ought also to have benefited cyclists. But the cycle helmet law introduced during the same period caused cycle use to fall by about 30% while DSHI for cyclists fell by only 57%, much less than for pedestrians. Thus despite, or because of, the helmet law, the risk of injury per cyclist relative to pedestrians increased as cycling numbers fell.

Bonham, Cathcart, Petkov and Lumb, 2006 matched cycle crash data with sites in South Australia where cycle counts had been undertaken. The period covered was 1999 to 2004. It was found that crashes increased as the number of cyclists rose, but not at lower rate. At intersections where crashes occurred, almost 70% of variability in those crashes was explained by the volume of cyclist trips.

Cycling in Sweden and walking in Canada

In Malmö, Sweden, Ekman, 1996 compared cyclist volumes against serious cycling crashes at 95 intersections. There was an inverse relationship between the number of cyclists and the number of crashes that involved cyclists.

Leden reported a non-linear relationship in two examinations of intersections. In a before and after study, he examined changes in numbers of bicyclists and collisions between motorists and bicyclists in response to changes in physical configuration at 45 non-signalized intersections between bicycle paths and roadways in Gothenburg, Sweden (Leden, Garder and Pulkkinen, 2000). The total number of collisions increased with the 0.4 power of the increasing use of the intersections by bicyclists.

Leden also examined police reported injuries to people walking at some 300 signalized intersections in Hamilton, Ontario, Canada (Leden, 2002). The number of collisions increased with the 0.32 to 0.67 power with increasing numbers of pedestrians. That is, where there were greater number of pedestrians, fewer pedestrians were involved in crashes.

Smeed's law

The concept of 'Safety in Numbers' is not new. It was first demonstrated in 1949 by Smeed, 1949 with regard to motor vehicle use when data from 62 countries showed that road fatalities per vehicle were lower in countries with more driving. The relationship - an exponential curve - has become known as Smeed's Law and has stood the test of time well, being verified in examinations of data across 42 years in the UK (Adams 1985) and 110 years in Australia (Knott 1994).

References

Adams 1985

Adams J, 1985. Smeed's Law, seatbelts and the Emperor's new clothes. In Schwing RC, ed Human behavior and traffic safety New York, pp 193-253.

BHRF, 1185

High life expectancy confirms low risk in cycling. .

Bonham, Cathcart, Petkov and Lumb, 2006

Bonham J, Cathcart S, Petkov J, Lumb P, . Safety in numbers: a strategy for cycling?. University of South Australia .

Ekman, 1996

Ekman L, 1996. On the treatment of flow in traffic safety analysis—a non-parametric approach applied on vulnerable road users. Lund, Sweden: Institutionen för Trafikteknik, Lunds Tekniska Högskola Bulletin 136.

Jacobsen, 2003

Jacobsen PL, 2003. Safety in numbers: more walkers and bicyclists, safer walking and bicycling. Injury Prevention 2003;9:205-209.

Knott 1994

Knott JW, 1994. Road traffic accidents in New South Wales, 1881 - 1991. Australian Economic History Review 1994;34:80-116.

Leden, 2002

Leden L, 2002. Pedestrian risk decrease with pedestrian flow. A case study based on data from signalised intersections in Hamilton, Ontario. Accident Analysis & Prevention 2002;34:457#64.

Leden, Garder and Pulkkinen, 2000

Leden L, Garder P, Pulkkinen U, 2000. An expert judgment model applied to estimating the safety effect of a bicycle facility. Accident Analysis & Prevention 2000 Jul;32(4):589-99.

Robinson, 2005b

Robinson DL, 2005. Safety in numbers in Australia: more walkers and bicyclists, safer walking and bicycling. Health Promotion Journal of Australia 2005;16:47-51.

Smeed, 1949

Smeed RJ, 1949. Some statistical aspects of road safety research. J R Stat Soc A 1949:1-34.

See also