Elsevier

Safety Science

Volume 105, June 2018, Pages 167-177
Safety Science

The role of perceived competence and risk perception in cycling near misses

https://doi.org/10.1016/j.ssci.2018.02.013Get rights and content

Highlights

  • Overconfidence mediated the relation of control to avoidance of mixed traffic.

  • Control moderated the relation of risk perception to avoidance of mixed traffic.

  • Overconfidence, bicycle use, and avoidance of mixed traffic mediated the path from control to near misses.

Abstract

Cyclists’ crashes account for a relatively large proportion of road fatalities and this proportion is increasing. Research suggests that near misses can be used as surrogate measures of crashes, based on the assumption that they share common causes. Also, in the cycling domain, it has been suggested that near miss incidents may provide ‘early warnings’ of situations or behaviours that could lead to crashes. The aim of this study was to investigate the role played by perception of risk and control on the exposure to risky situations, such as the involvement in mixed traffic. We administered a questionnaire to 298 Italian cyclists measuring perceived competence (i.e. perceived control and overconfidence), risk perception of interactions with cars, bicycle use, avoidance of mixed traffic and recent experiences of near misses. Path analysis using Bayesian estimation showed that perceived control, mediated by overconfidence, had a positive indirect effect on bicycle use and a negative one on avoidance of mixed traffic, while it acted as a moderator in the relationship between risk perception of interaction with cars and avoidance of mixed traffic. Furthermore, the mediation paths revealed the indirect effects of perceived control on near misses through exposure. Results highlighted the importance of considering the role of individuals’ perception of their ability to cycle with regard to near misses and provided new insight on how cyclists regulate their behaviour, as well as how such behaviour leads to different safety outcomes. Results have implications regarding theory, infrastructure and the application of new safety technologies.

Introduction

Risk perception has been found to reduce risky behaviours and the probability of safety outcomes by behavioural adaptation both theoretically and empirically (Ba et al., 2016, Koornstra, 2009). Moreover, perceived competence, in the meaning of the perceived capabilities that one possesses over one task, has been also proposed to be part of the behavioural adaptation process influencing the level of difficulty associated with a task (Rudin-Brown and Jamson, 2013). Both risk perception and perceived competence are cognitive constructs of utmost importance when modelling road users’ behaviour due to their relationship with behavioural adaptation, nevertheless, there is lack of research addressing their influence on cyclists’ safety outcomes (i.e. near misses). Thus, the present study aims to shed light on the interactions between perceived competence and risk perception and their effect on cyclists’ involvement in risky situations and safety outcomes in cycling.

In the last decade, the amount of research investigating cycling safety has dramatically increased (e.g. Heydari et al., 2017, Jacobsen et al., 2016, Osama and Sayed, 2016, Prati et al., 2017b). Several reasons might be the source of such interest. First, even though cyclists represent a small minority in comparison with motorised vehicles (Prati et al., 2017), they account for a relatively large proportion of fatalities (ERSO, 2016). In fact, in 2014 there were 2112 cyclists' fatalities in the EU countries, which correspond to the 8.1% of all the road deaths (ERSO, 2016) showing an increase of 0.3% compared to 2013. In addition to this, infrastructure is usually not designed to provide cyclists with safety conditions comparable to other road users (e.g. car drivers), therefore, their level of protection is considerably lower (Wegman et al., 2012).

Fatality trends and other safety outcomes (e.g. the number of non-fatal crashes) vary along different EU countries. In Italy, according to the Italian National Institute of Statistics (ACI-ISTAT, 2015), on a total of 17,437 crashes involving at least one cyclist in 2015, 16,827 cyclists were injured and 252 died within 30 days following the crash. These data show a decrease of 3.2% in the injuries and of 7.7% in the fatalities compared to the previous year. In Italy, the mortality index (deaths every 100 accidents) for cyclists is 1.44, which is higher in comparison with the mortality index of car users (0.88).

In the safety domain, using Heinrich’s Safety Triangle model, accidents are on the pinnacle of the pyramid, whereas near misses are found below them being more frequent and less severe (e.g. Hamann and Peek-Asa, 2017). A near miss can be defined as an event that did not cause any harm and therefore has limited immediate impact. Near misses have been used as surrogate measures of crashes since they both have been found to share common causation (Wright and Van der Schaaf, 2004). Moreover, safety outcomes with lower severity (i.e. near misses) are more frequent, thus, more susceptible of being studied (Laureshyn et al., 2017). At a theoretical level, Güttinger (1982) proposed a model in which a conflict is defined as a set of initial conditions that, depending on the successfulness of the evasive action, either develop further into a collision or resolve without any consequences. This definition implies the existence of a continuum in which conflicts always precede crashes and with the possibility for the conflicts to develop either in a crash or in an avoided crash – near miss. In other words, this model can be interpreted in a way that a conflict is a set of circumstances that either results in a crash or not.

In the cycling domain, the relationship between near misses and crashes is yet to be understood. In accordance with Güttinger’s (1982) model, Aldred (2016) suggests that near miss incidents may provide ‘early warnings’ of situations or behaviour that could lead to crashes. Moreover, Aldred (2016) compared percentages of attribution of near misses and crashes in the study of Knowles’ et al. (2009) and found that they were very similar, giving support to the shared causation.

Despite these early studies, cycling near misses remain under-researched, regardless of their likely contribution to injury crashes (Aldred, 2016). Nevertheless, more and more innovative solutions and methodologies attempted to address such matter (i.e. Aldred and Crosweller, 2015, Westerhuis and De Waard, 2016). Some studies, such as Aldred and Crosweller (2015), and Joshi et al. (2001) in the UK, and Sanders (2015) in the San Francisco Bay Area, have also shown that near misses are a very common experience for cyclists. For example, using an online diary methodology, Aldred and Crosweller (2015) found that the 75% of participants experienced at least .75 incidents per cycled hour, with a median of 1.71 per hour. Similarly, using a self-reported questionnaire, Sanders (2015) showed that 86% of those who bicycle at least annually in this sample had experienced some type of near miss.

Exposure is of utmost importance when it comes to studying cycling safety. Research suggests that studies that intend to estimate the importance of factors other than exposure in crashes and injuries must control for exposure given to its overall effect on cycling safety and risk of crash and injury (Vanparijs et al., 2015). Moreover, its effect on crash and injury risk has been consolidated over the years by research (Carlin et al., 1995, Bacchieri et al., 2010).

In the present study, we consider exposure at two different levels: (1) exposure to cycling in general, that is to say, use of the bicycle; and (2) cycling in mixed traffic situations. The latter type of exposure allows for more opportunities for cyclists to interact with cars, which is of especial importance when considering risk. Evidence shows countries and cities with extensive bicycling facilities have the highest cycling modal split shares and the lowest fatality rates (Pucher, 2001, Pucher and Dijkstra, 2000). Those countries and cities without separate facilities have low modal split shares and much higher fatality rates (Buehler and Dill, 2016, Pucher and Dijkstra, 2000). However, in emerging cycling regions where cyclists are rapidly growing in number, cyclists are forced to share the road with motorised vehicles due to the underdevelopment of cycling infrastructure (e.g. Pucher et al., 2011). Cyclists in urban area may have to choose between (1) cycle within mixed traffic situations with shorter travel time, (2) cycle on bike lanes or segregated paths with a longer travel time, and (3) use other means of transport. The two latter options would imply avoiding mixed traffic and, therefore, the risk of conflicts with road users in it.

For this reason, in our model (Fig. 1) we hypothesise that, on the one hand, avoidance of cycling in mixed traffic will be negatively associated with the occurrence of near misses (Hypothesis 1). In other words, the more cyclists avoid mixed traffic situations, the lower the probability of being involved in a conflict (i.e. near miss), especially with vehicles generally involved in mixed traffic. On the other hand, concerning exposure to cycling in general and according to the aforementioned, we hypothesise a positive association between bicycle use and near misses (Hypothesis 2).

Risk-adaptation theory proposes that road traffic risk perception depends on fear and arousal (Koornstra, 2009). Cyclists feel most secure on road with cycle tracks and most at risk on roads with mixed traffic, while cycle lanes can be considered half way: less secure than cycle tracks, but considerably more secure than mixed traffic roads (Jensen et al., 2007). In particular, it has been shown that the presence and the size of motor vehicles (Aldred, 2016) increase cyclists’ feeling of being at risk. Moreover, previous experiences set up the adaptation level around which there is a range of indifference to risks (Koornstra, 2009). Such level and ranges vary between individuals; therefore, one can also expect variance in the degree of risk which cyclists incur depending on their own personal characteristics, leading to potential compensations (Koornstra, 2009, Wilde, 1982) in terms of strategic decisions (e.g. taking the bicycle over other means of transport, choosing one path to work instead of another) or driving behaviours (e.g. riding at a certain speed, committing violations or not, keeping safe or unsafe distance from other road users). This way, avoiding mixed traffic can be a strategy to cope with perceived risk (Chataway et al., 2014, Kaplan and Prato, 2016, O'Connor and Brown, 2010) which, as other forms of behavioural adaptation, might lead to a decrease of the objective probability of crash or events with potential hazards (Ba et al., 2016). Therefore, we hypothesised that risk perception regarding interaction with motorised vehicles will be positively associated with avoidance of mixed traffic (Hypothesis 3). In other words, the higher the perception of risk in interactions with motorised vehicles, the more cyclists will avoid mixed traffic situations.

Perceived competence in riding a bicycle can be considered as a form of control over one’s riding (Chaurand and Delhomme, 2013). Cristea and Gheorghiu (2016) found that perceived behavioural control over certain situation was a good predictor of the behavioural intention to take part in such situations. Perceived behavioural control refers to the individual’s perception of his or her ability to execute a given behaviour (Ajzen, 1991). According to this, people will likely choose to perform behaviours they think they will be capable of executing. The concept of perceived behavioural control is very similar to that of self-efficacy (Bandura, 1982) and it captures people’s perceived capability to execute a given behaviour, for example, travelling to work by bicycle (Lois et al., 2015). With that said, perceived control can be defined as a self-perception regarding the own capabilities and ability to control one’s own action to execute a given behaviour, in other words, how skilled and effective people perceive themselves to be given particular conditions. According to this framework it is reasonable to argue that perceived control will influence how much a person will engage in a certain behaviour. In the context of the present study, we hypothesise that increasing levels of perceived control will be positively associated with weekly rates of bicycle use (Hypothesis 4).

Previous studies have found that the perceived control over a driving situation predicts the disposition to take higher levels of risk (Horswill and McKenna, 1999). Moreover, people tend to better accept controllable rather than uncontrollable risks (Nordgren et al., 2007). Furthermore, in driving safety research, a reduced risk avoidance in road traffic has been found when drivers’ perception of control is higher (Horswill and McKenna, 1999, Windsor et al., 2008). Considering the inherent risk of involvement in mixed traffic and the decision to avoid mixed traffic situations as a coping strategy to reduce the perceived risk (Chataway et al., 2014, Kaplan and Prato, 2016, O'Connor and Brown, 2010), higher perceptions of control may influence cyclist’s behavioural intention to ride in a stressful traffic environment such as mixed traffic scenario (Kaplan and Prato, 2016, O'Connor and Brown, 2010). Therefore, we hypothesised that perceived control will be negatively associated with avoidance of mixed traffic (Hypothesis 5). In other words, the higher the perception of control, the more cyclists will be involved in mixed traffic, since they will avoid less.

Perceived control may be seen as a positive trait since it is associated with self-efficacy and performance therefore (Wohleber and Matthews, 2016). Nevertheless, Weinstein (1980) found that when thinking about future events, situations that were perceived as controllable led to motivational and cognitive factors that tended to increase the perceived likelihood that the given situation would unfold the way the person wanted, therefore, it would lead to unrealistic optimism (Weinstein, 1980). When such perception of control exceeds the real control a person has over the bicycle, it can be labelled overconfidence (Wohleber and Matthews, 2016). Thus, perception of control leading to unreasonable optimism can generate overconfidence regarding the future being linked to your control, in other words, to your skills and capability to control the situation and outcomes. Therefore, we hypothesised that perceived control will lead to overconfidence in the person’s skills because of unrealistic optimism (Hypothesis 6).

Moreover, in driving safety research, overconfidence has been found to be related to riskier behaviours among drivers (Hatfield and Fernandes, 2009, Wohleber and Matthews, 2016). Chaurand and Delhomme (2013) found that higher levels of overconfidence in one’s cycling skills were associated with lower risk perception. Thus, cyclists with higher overestimation of their own skills might see dangerous or hazardous situations, such as committing a violation, as relatively less risky. In addition, they will feel more capable to deal with them or to handle the potential consequences of external sources of risk, such as interaction with other road users. Therefore, perceiving oneself as more competent than one actually is, may lead to not avoiding situations that, otherwise, would be considered hazardous. Thus, we hypothesise that increasing levels of overconfidence will be associated with lower avoidance of mixed traffic (Hypothesis 7) as well as with a higher rate of bicycle use (Hypothesis 8). Based on the reasoning presented for hypothesis 6, we established that the relationship between perceived control and bicycle use is indirectly explained through overconfidence (Hypothesis 9) as it is the relationship between perceived control and avoidance of mixed traffic (Hypothesis 10). Finally, in order to further understand the relations between our variables, we expect to find an indirect effect of multiple mediators on the relationship between perceived control and near misses throughout the influence of overconfidence which in turn, will have an effect on near misses through the parallel mediators bicycle use and avoidance of mixed traffic (Hypothesis 11).

Research addressing perceived control and risk perception has mainly focused on their relationship, raising the need for investigating the possible effect of the latter on risk acceptance. Cordellieri’s et al. (2016) findings suggested that worrying about the risk might influence the reduction of hazardous behaviours. Based on the assumption that trusting one’s skills leads to unrealistic optimism (Weinstein, 1980), we propose that for people with high control over one’s own skills, there will be less worry about the risk even if the hazard is perceived equally risky. Thus, cyclists with higher levels of perceived control might base their decision to take part in the risky behaviour mainly for reasons other than the level of risk, because they might be less worried about such a risk. Therefore, we propose that, while risk perception might be a predictor of acceptance of the risk (i.e. interaction with mixed traffic), perceived control could play a relevant role in shaping the context in which risk perception is considered to be important when deciding to take such risk. That is, we hypothesise that with high levels of perceived control, risk perception will not play an important role in the prediction of acceptance of the risk, whereas, with lower levels of perceived control, the decision to engage in the risky behaviour will be made on the basis of risk perception. In other words, we hypothesise that the relationship between risk perception and avoidance of mixed traffic will be moderated by perception of control (Hypothesis 12).

Fig. 1 displays the hypothesised path model.

Section snippets

Procedure

Data were collected from December 10, 2015 to February 29, 2016 through an online questionnaire in Italian. To attempt to reduce the self-selection bias and to reach a wide variety of participants, we included groups targeting cyclists with all sorts of demographic characteristics and from different locations in Italy. Cyclists associations’ websites, Facebook groups, and forums were found using keywords (i.e. the Italian words for “cycling” “bicycle” “cyclists’ association”) on Google and on

Preliminary analyses

An exploratory factor analysis revealed that each item loaded on its respective factor, thus indicating the underlying processes creating correlations among items (Tabachnick and Fidell, 2013) that provides support for the discriminant validity of the scales. In other words, it has allowed for concluding that all the subscales are measuring different constructs, just as it was expected. Due to the violation of assumptions of normality distribution of all the model variables, we used Spearman

Discussion

The present study investigated the interactions between perceived competence and risk perception and their effect on cyclists’ involvement in risky situations and safety outcomes in cycling.

The results provided support for all the hypotheses except for Hypotheses 3, 4 and 5. Path analysis showed a significant positive association between bicycle use and near misses, thus supporting Hypothesis 2. This finding is in line with previous studies that highlighted a positive association between crash

Conclusion

The present research investigated the complex relationship between perceived control, perceived risk and the causal paths through which they influence near miss occurrence. The findings showed that perceived control increased overconfidence in one’s skills and this increased exposure to cycling and mixed traffic. As a result, perceived control affected (i.e. increasing) the occurrence of near misses through bicycle use and involvement in mixed traffic. Moreover, the relationship between

Acknowledgement

This work was supported by the European Commission under the Grant Project XCYCLE: contract number 635975. Co-funded by the Horizon 2020 Framework Programme of the European Union (2014–2020).

References (76)

  • M. Cristea et al.

    Attitude, perceived behavioral control, and intention to adopt risky behaviors

    Transportation Res. Part F: Traffic Psychol. Behav.

    (2016)
  • R. Elvik et al.

    Safety-in-numbers: A systematic review and meta-analysis of evidence

    Saf. Sci.

    (2017)
  • N. Guttman

    Persuasive appeals in road safety communication campaigns: Theoretical frameworks and practical implications from the analysis of a decade of road safety campaign materials

    Accid. Anal. Prev.

    (2015)
  • C.J. Hamann et al.

    Examination of adult and child bicyclist safety-relevant events using naturalistic bicycling methodology

    Accid. Anal. Prev.

    (2017)
  • J. Hatfield et al.

    The role of risk-propensity in the risky driving of younger drivers

    Accid. Anal. Prev.

    (2009)
  • S. Heydari et al.

    Using a flexible multivariate latent class approach to model correlated outcomes: A joint analysis of pedestrian and cyclist injuries

    Analytic Methods Accident Res.

    (2017)
  • S. Kaplan et al.

    “Them or Us”: Perceptions, cognitions, emotions, and overt behavior associated with cyclists and motorists sharing the road

    Int. J. Sustain. Transportation

    (2016)
  • M.J. Koornstra

    Risk-adaptation theory

    Transportation Res. Part F: Traffic Psychol. Behav.

    (2009)
  • A. Laureshyn et al.

    Cross-comparisson of three surrogate safety methods to diagnose cyclist safety problems at crossroads in Norway

    Accid. Anal. Prev.

    (2017)
  • D. Lois et al.

    Cycle commuting intention: A model based on theory of planned behaviour and social identity

    Transportation Res. Part F: Traffic Psychol. Behav.

    (2015)
  • J.P. O'Connor et al.

    Riding with sharks: Serious leisure cyclists' perceptions of sharing the road with motorists

    J. Sci. Med. Sport

    (2010)
  • A. Osama et al.

    Examining the impact of bike network indicators on cyclists safety using macro-level collision prediction models

    Accid. Anal. Prev.

    (2016)
  • G. Prati et al.

    Cyclists as a minority group?

    Transportation Res. Part F: Traffic Psychol. Behav.

    (2017)
  • J. Pucher et al.

    Bicycling renaissance in North America? An update and re-appraisal of cycling trends and policies

    Transportation Res. Part A: Policy Practice

    (2011)
  • R.L. Sanders

    Perceived traffic risk for cyclists: The impact of near miss and collision experiences

    Accid. Anal. Prev.

    (2015)
  • N. Sümer et al.

    Asymmetric relationship between driving and safety skills

    Accid. Anal. Prev.

    (2006)
  • J. Vanparijs et al.

    Exposure measurement in bicycle safety analysis: a review of the literature

    Accid. Anal. Prev.

    (2015)
  • F. Wegman et al.

    How to make more cycling good for road safety?

    Accid. Anal. Prev.

    (2012)
  • R.W. Wohleber et al.

    Multiple facets of overconfidence: implications for driving safety

    Transportation Res. Part F: Traffic Psychol. Behav.

    (2016)
  • L. Wright et al.

    Accident versus near miss causation: a critical review of the literature, an empirical test in the UK railway domain, and their implications for other sectors

    J. Hazard. Mater.

    (2004)
  • ACI-ISTAT, 2015. La statistica ISTAT-ACI: Tavole 2015. Retrieved on October 14th, 2016 from:...
  • R. Aldred et al.

    Cycling provision separated from motor traffic: A systematic review exploring whether stated preferences vary by gender and age

    Transport Rev.

    (2017)
  • A. Bandura

    Self-efficacy mechanism in human agency

    Am. Psychol.

    (1982)
  • J. Bonham et al.

    Cycling Futures

    (2015)
  • N.M. Bradburn et al.

    Answering autobiographical questions: the impact of memory and inference on surveys

    Science

    (1987)
  • P. Chapman et al.

    Forgetting near-accidents: the roles of culpability, severity and experience in the poor recall of dangerous driving situations

    Appl. Cognitive Psychol.

    (2000)
  • J. Cohen et al.

    Applied multiple regression/correlation analysis for the behavioral sciences

    (2003)
  • P. Cordellieri et al.

    Gender effects in young road users on road safety attitudes, behaviors and risk perception

    Front. Psychol.

    (2016)
  • Cited by (27)

    • Near miss management systems in the industrial sector: A literature review

      2022, Safety Science
      Citation Excerpt :

      As stated in the previous section, the aim is to analyze the adoption of NMS in the industrial sector (e.g. mining, manufacturing, construction, etc.): the analysis will be developed on theoretical studies discussing critical issues about NMSs, and, on studies that propose practical applications. It has to be noted that only studies which refer to the industrial sector will be included, although the concept of near miss is widely diffused in other sectors - such as healthcare and aeronautics – where, otherwise, different approaches are usually applied (Clark et al., 2012; Marín Puchades et al., 2018). Other inclusion criteria have been defined, considering only articles in English language, and limiting the research to papers from scientific journals, conference proceedings and books.

    View all citing articles on Scopus
    View full text