by Marilyn Johnson, Stuart Newstead, Judith Charlton, and Jennifer Oxley, 2011
https://www.sciencedirect.com/science/article/pii/S0001457510002630
This is an abridged version of their full report. Please follow the link to see the data they collected in its entirety.
Abstract
This study determined the rate and associated factors of red light infringement among urban commuter cyclists. A cross-sectional observational study was conducted using a covert video camera to record cyclists at 10 sites across metropolitan Melbourne, Australia from October 2008 to April 2009. In total, 4225 cyclists faced a red light and 6.9% were non-compliant. The main predictive factor for infringement was direction of travel, cyclists turning left (traffic travels on the left-side in Australia) had 28.3 times the relative odds of infringement compared to cyclists who continued straight through the intersection. Presence of other road users had a deterrent effect with the odds of infringement lower when a vehicle travelling in the same direction was present (OR = 0.39, 95% CI 0.28–0.53) or when other cyclists were present (OR = 0.26, 95% CI 0.19–0.36). Findings suggest that some cyclists do not perceive turning left against a red signal to be unsafe and the opportunity to ride through the red light during low cross traffic times influences the likelihood of infringement.
4. Discussion
This study examined cyclist red light infringement, the rate and related factors and identified a number of behavioural and environmental predictors. Findings highlight that cyclists’ propensity to ride through intersections against a red light as a multivariate issue.
Travel direction, specifically turning left, was the greatest predictor of infringement. Cyclists may perceive turning left to be a relatively safe manoeuvre since they are exposed to fewer points of conflict from cross traffic and cross traffic did have a deterrent effect and the perception of safety and opportunity to infringe decreased as the cross traffic volume increased (Wang and Nihan, 2004). However, despite the perceived safety associated with turning left against a red light, this manoeuvre may lead to an increased risk of cyclist-pedestrian collisions as was experienced in the United States of America when the right turn on red was introduced (Preusser et al., 1982). Further analysis is needed to determine the role of direction of cross vehicular traffic.
No collisions were observed. While this may suggest that non-compliance is a safe behaviour, collisions are relatively rare events. More importantly, the potential repercussions of this behaviour go beyond the individual cyclist. Cyclist red light non-compliance is the most frequently cited behaviour at annoys drivers (O’Brien et al., 2002, Kidder, 2005, Fincham, 2006) and there is potential that this annoyance may influence the attitudes and behaviours of some drivers when they interact with cyclists, beyond the individual non-compliant rider observed. In addition, unpredictability is a key concern of drivers when interacting with cyclists on the road (Basford et al., 2002) and cyclist red light non-compliance is likely to increase driver perceptions of unpredictability and reduce driver confidence when interacting with cyclists.
The presence of other road users, cyclists and drivers, travelling in the same direction had a deterrent effect on infringement. Other road users may be a proxy measure for high traffic periods or it may have a direct deterrent effect or other cyclists may speak to cyclists and admonish a non-compliant cyclist. Further investigation of cyclist attitudes is needed to understand the influence of others on red light non-compliance.
Despite drivers’ perception that they can anticipate cyclists’ behaviour based on appearance and bicycle type (Basford et al., 2002, Walker, 2007), this analysis found these characteristics had no predictive value on cyclists’ likelihood of red light non-compliance.
Further, variations in non-compliance were also observed across the cycling facility types with cyclists more likely to be non-compliant at the centre sites than the standard or continuous sites. While there may be numerous reasons for this finding, for example differences in light phasing (left turn filter lights were available at the centre sites and not at other sites), or arrival time in the red light phase, these were not able to be determined from the observational data. More in-depth analysis is required to fully understand these contributing factors.
Finally, cyclists’ non-compliance was deliberately not compared to driver behaviour as the opportunity to infringe is different. Any driver who may intend to infringe is restricted by the lead vehicle in the lane, therefore no following drivers have an opportunity to infringe. This is not the case for cyclists. Every cyclist is able to ride between waiting vehicles or cyclists and can choose to be non-compliant at almost every intersection. While it is likely that the predilection to infringe at red lights varies when people are cycling compared to driving, the opportunity to infringe is more comparable to pedestrians than drivers. Further analysis is planned to compare the rates of non-compliance between cyclists and pedestrians.
5. Strengths and limitations
This study determined the rate, characteristics and risk factors of commuter cyclists’ red light infringement and provided an objective measure of actual cyclist behaviour and was not subject to behaviour modification or self-reporting bias. The multivariate analysis identified the impact of individual components on risk.
There were a number of study limitations. The infringement rate is not likely to be representative of all intersection types as observed sites had comparable traffic flow and complexity and are unlike less complex sites with no cross traffic (e.g. pedestrian crossings) or highly complex intersections with greater cross traffic volume. In addition, findings were for metropolitan commuter cyclists and may be comparable to cyclists in other urban areas however they may not represent non-urban riders or weekend behaviour.
Further, cyclist gender was determined by physical appearance and there is potential for some error in this subjective classification. It is also possible that factors that cannot be determined by observation, including age and socioeconomic factors, may contribute to the likelihood of non-compliance. Finally, cyclists are heterogeneous and findings may not relate to other types of riders.
6. Conclusion
The rate of red light non-compliance (7%) is lower than that found in previous studies have found and is not as widespread as reported in studies of drivers’ perception. This study provides a baseline rate of red light non-compliance and establishes the types of behaviour that might be targeted for behavioural change countermeasures, such as turning left. Further research directions may include investigating the rate of red light infringement at various intersection types or among different cyclist types such as training riders, bicycle couriers, recreational riders or children. In addition, investigations into cyclist red light non-compliance may address: driver attitudes and perceptions and influences on driver behaviour; the mechanism of the deterrent role of other cyclists and vehicles and; cyclists’ perceptions about the apparent safety of turning left and the potential implications on cyclist safety.
This article is important because it challenges the perceptions of drivers that all cyclists are lawless and reckless. It also indicates the most likely scenarios for a cyclist to break the law and when accidents can occur which is crucial for improving safety for everyone that shares the road.
