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Table 2 Characteristics of non-accident studies

From: Truck-bicycle safety: an overview of methods of study, risk factors and research needs

Study Type Aim Data collection Sample size Evaluation method Definition of conflict Truck type
Fenn et al., 2005 [24] Behavioural / Conflict Examine drivers’ experiences related to close proximity mirrors Postal survey 311 drivers Descriptive statistics Impression of close calls (barely avoiding an accident) not reported
FDS International (2010) [34] Behavioural Evaluate the behaviour related to roadside mirrors Interviews 51 drivers 20 cyclists Descriptive statistics not relevant Long goods vehicle
Frings et al., 2012 [35] Behavioural Examine gender differences in risk perception associated with various cycling maneuvers near trucks On-line questionnaire 4596 cyclists Variance analysis (ANOVA); chi-square analysis not relevant Truck over 3,5 t
Conway et al., 2013 [36] Conflict Assess cyclists’ exposure to multimodal conflict in urban on-street bicycle lanes Direct observations 50 h 35 sites 25 conflicts Bivariate correlation analyses To avoid a collision, cyclist must exit the bicycle lane or stop Trucks and vans
Twisk et al., 2013 [37] Behavioural Evaluate awareness programs by examining the decisions of young cyclists when in blind spot areas Table-top models Quasi-experimental design 62 cyclists Mixed design ANOVA not relevant not reported
Helman et al., 2013 [18] Behavioural Assessment of drivers’ tasks while turning left; assessment of driver errors Accompanied driving followed by short interviews 3 drivers Cognitive task analysis not relevant Construction vehicles
Milner et al., 2016 [38] Behavioural Study behaviour related to direct and indirect vision, Improve the understanding of visual processing Literature review, road user surveys, laboratory experiments 117 drivers 129 cyclists Descriptive statistics and qualitative analysis not relevant not reported
Mole & Wilkie, 2017 [39] Behavioural Examine whether mirrors delay driver responses Simulation of driving tasks 41 drivers Mixed model ANOVA not relevant not reported
Pitera et al., 2017 [40] Conflict Conduct safety evaluation of loading area located next to busy cycle street Observation with camera 100 h 1 site 2 conflicts Descriptive statistics Presence of an evasive action Delivery truck (excluding vans)
Behavioural Investigate road users’ understanding of a safety measure Intercept interviews Camera 39 cyclists 5 drivers not relevant
Richter & Sachs, 2017 [32] Behavioural Examine the driving and gaze behaviour when using turn-off assistant Simulation of routes 48 drivers Descriptive statistics not relevant Van, delivery truck, truck without trailer, semitrailer truck
Conflict Observe the behaviour and conflicts in right-turning maneuvers Observation with camera 129 h 43 sites 71 conflicts not reported
Abadi & Hurwitz, 2018 [17] Behavioural Investigate cyclists’ perceived level of comfort near urban loading zones Online questionnaire 342 cyclists Repeated-measures ANOVA, cluster analysis not relevant not reported
Pokorny et al., 2018 [41] Conflict Investigate cyclists’ involvement in conflicts with trucks (frequency, type and characteristics of conflicts) On-line questionnaire 631 cyclists Descriptive statistics, multinomial logistic regression A near collision, but due to the quick reactions of the cyclist and/or driver, accident averted Large road vehicle used for carrying or pulling goods or materials