Fig 4 - uploaded by Mette Møller
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Average speed [km/h] and lateral position [m] on the road segment after overtaking the cyclists. Lateral position describes the deviation from the centre with positive values referring to a deviation to the right. Error bars represent 95% confidence intervals.
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... the 3 x 3 mixed MANOVA we found a significant main effect of marking in average speed and lateral position, but not in SDLP, and no main effect for secondary task and no significant interaction in any of the dependent variables. Table 1 shows the results of the univariate test of the MANOVA. Fig. 4 shows the average speed and the mean lateral position for the three marking types during normal cycling. Cyclists seem to go a bit faster on the track with the line and slowest with the buffer. However, the difference is only marginal, and the effect size is rather weak. The stronger effect, in contrast, is found for lateral position. ...
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... Distracted cycling encompasses a range of behaviors that divert a cyclist's attention from the primary task of safe navigation, including but not limited to using smartphones, listening to music, conversing with fellow cyclists, or even daydreaming. Each of these secondary activities can significantly impair a cyclist's situational awareness and ability to respond to environmental hazards, thereby heightening the risk of crashes and injuries (Møller et al., 2024). While the adverse effects of distracted driving on road safety have been extensively studied (Islam, 2024;Stavrinos et al., 2013;Zhu et al., 2024), relatively scant attention has been devoted to understanding the nuances of distracted cycling and its impact on crash severity. ...
... Distraction impairs situational awareness, reaction time, and the ability to process environmental stimuli, all of which are critical for hazard avoidance (Mwakalonge and White, 2014;Useche et al., 2018). The cognitive load associated with multitasking hinders visual information processing and reduces cyclists' ability to respond appropriately to dynamic traffic conditions, thereby increasing their vulnerability (Møller et al., 2024;Mwakalonge and White, 2014). Furthermore, distraction influences risk perception and decision-making, often leading cyclists to underestimate potential risks (D'Addario & Donmez, 2019). ...
... Furthermore, distraction influences risk perception and decision-making, often leading cyclists to underestimate potential risks (D'Addario & Donmez, 2019). It also negatively impacts performance, with distracted cyclists exhibiting worse visual detection, larger variation in lateral position, slower fixation, and faster acceleration (De Waard et al., 2014;Jiang et al., 2021;Møller et al., 2024). Goldenbeld et al. (2012) and Useche et al. (2018) associated frequent device use with increased crash and near-crash involvement. ...
Cyclists are among the most vulnerable road users, increasingly subject to various sources of distraction, including the use of mobile phones and engagement in other tasks while navigating urban environments. Understanding and mitigating the impact of these distractions on cyclist safety is crucial. Despite the importance of this issue, the effect of distraction on injury severity in cycling crashes has not been extensively studied. This research analyzes four years of U.S. crash data (2019–2022) from the Crash Report Sampling System (CRSS) database, employing a hybrid framework that integrates CatBoost-based SHAP algorithm and the random parameters binary logit model with heterogeneity in means and variances (RPBL-HMV). The proposed approach confirms the significant role of cyclist distraction in crash injury severity. Subsequently, the analysis identifies several factors influencing the likelihood of severe injuries in distracted cyclist crashes. Crashes involving the front of motor vehicles, occurring in rural areas, on two-way roads, at higher speed limits, and during weekends were associated with a higher probability of severe injuries. Conversely, crashes at T-intersections, involving the side or rear of motor vehicles, where cyclists wore helmets, or during rush hour were linked to a reduced likelihood of severe injuries. Notably, interaction effects reveal nuanced patterns. For instance, while crossing roadway actions and rush hour periods individually decrease the likelihood of severe crashes, their combination increases the probability of such outcomes. The findings suggest targeted safety measures and policy interventions aimed at enhancing cyclist safety and promoting safer cycling environments by mitigating distraction-related risks.