A study has indicated that the major risk factors for cyclists are intersections, especially with poor visibility, poor road maintenance and other road users passing in front of the cyclist. However, the study involved a very limited sample with 16 cyclists (8 male, 8 female) riding instrumented bicycles for two weeks. The cyclists used the instrumented bicycles, instead of their own bikes, to carry out their normal cycling activities, such as commuting to work.
The instrumented bicycles were fitted with at least one forward video camera, two inertial measurement units, GPS, and two brake force sensors (one for each wheel). Data logging started automatically approximately two minutes after the cyclist began riding and stopped after two minutes without moving. Cyclists were asked to record any event which made them feel unsafe by pushing a button on the handlebars. Cyclists completed a pre-study questionnaire describing their riding habits and demographics. They also kept a trip diary reporting the purpose and duration of each ride and a post-study interview to describe any events that made them feel unsafe. Critical events were indicated when the cyclist pushed the button, reported something in the post-study interview or when inertial measurement indicated an event. Each of these potential events was verified and categorized by viewing the recorded video.
It is noted in the paper that previous research had shown that 70% of European cycle accidents do not involve another road user. However, most fatal accidents involve a motor vehicle. Due to the small sample size, these more serious types of collisions would not be expected to be encountered. Therefore near-collisions were used as surrogates. Identifying when such an incidence has occurred is somewhat subjective.
When an event was recorded it was also noted whether a number of factors were present. These were divided into environmental factors and threats. Environmental factors included: daylight; bike lane; asphalt; paved surface; slippery surface; holes in road surface; intersection; intersection with poor visibility; construction works; and a motor vehicle parked on the bike lane. Threats were defined as another road user crossing the cyclist’s path: light vehicle; heavy vehicle; pedestrian; bicycle; or animal.
The conclusion was that cycling close to an intersection increased the risk of a critical event by four times. This is increased to twelve times when there is poor visibility at the intersection, for example a building or hedge blocking the view. Holes in the road surface increased the risk by ten times and a pedestrian or cyclist crossing the riders path increased the risk by two times. Since most serious accidents involve a motor vehicle, and these are most likely at intersections with poor visibility, the most important advice seems to be for cyclists to improve their visibility, especially from the side.
Presently, the collection and analysis of naturalistic data is the most credited method for understanding road user behavior and improving traffic safety. Such methodology was developed for motorized vehicles, such as cars and trucks, and is still largely applied to those vehicles. However, a reasonable question is whether bicycle safety can also benefit from the naturalistic methodology, once collection and analyses are properly ported from motorized vehicles to bicycles. This paper answers this question by showing that instrumented bicycles can also collect analogous naturalistic data. In addition, this paper shows how naturalistic cycling data from 16 bicyclists can be used to estimate risk while cycling. The results show that cycling near an intersection increased the risk of experiencing a critical event by four times, and by twelve times when the intersection presented some form of visual occlusion (e.g.; buildings and hedges). Poor maintenance of the road increased the risk tenfold. Furthermore, the risk of experiencing a critical event was twice as large when at least one pedestrian or another bicyclist crossed the bicyclist’s trajectory. Finally, this study suggests the two most common scenarios for bicycle accidents, which result from different situations and thus require different countermeasures. The findings presented in this paper show that bicycle safety can benefit from the naturalistic methodology, which provides data able to guide development and evaluation of (intelligent) countermeasures to increase cycling safety.
Introducing naturalistic cycling data: What factors influence bicyclists’ safety in the real world?
Dozza, Marco (Chalmers University of Technology, Department of Applied Mechanics, Division of Vehicle Safety, Lindholmspiren 3, 41296 Gothenburg, Sweden); Werneke, Julia Source: Transportation Research Part F: Traffic Psychology and Behaviour, v 24, p 83-91, May 2014