The authors regret that a mistake was made in Table 3 of the article. This table should read: [Table presented] The figures in bold, italic and red differ from the figures in the published article. As a result of these different values, the sixth sentence of the abstract should read: “S-pedelecs were much faster than conventional bicycles, amounting to a speed difference with conventional bicycles of 9.6 km/h in urban areas (M = 26.9 km/h vs. 17.3 km/h) and of 13.1 km/h in rural areas (M = 31.4 km/h vs. 18.3 km/h).” and the seventh sentence of the abstract should read: “The speed differences between pedelecs and conventional bicycles were much smaller: 2.8 km/h in urban areas (20.1 km/h vs 17.3 km/h) and 3.9 km/h in rural areas (22.2 km/h vs. 18.3 km/h). In the Discussion, Section 4.1. Comparison with previous studies on cycling speed characteristics, the second sentence of the second section should read: “Our study found similar patterns among Dutch riders. S-pedelecs were much faster than conventional bicycles, amounting to a speed difference in mean speeds in urban areas of 9.6 km/h (M = 26.9 km/h vs. 17.3 km/h) and in rural areas of 13.1 km/h (M = 31.4 km/h vs. 18.3 km/h). Values different from those in the published text are in bold, italic, and red. The authors would like to apologise for any inconvenience caused.

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To assess the potential impact of the higher speeds of pedal-assisted bicycles on safety, this study compared conventional bicycles, pedelecs and speed pedelecs (hereafter called s-pedelecs) on mean speeds, speed variability, harsh braking events (decelerations > 2 m/s), and mean speeds above the speed limit (MSAL) in rural and urban areas in the Netherlands Data were collected in daily traffic, while the legal maximum speed for speed-pedelecs was 25 km/h, and pedelecs and s-pedelecs shared the infrastructure with conventional bicycles. Data were collected, using two-wheelers equipped with accelerometers and GPS. Personality factors – sensation seeking and risk taking - were measured with surveys. Regular commuters used one of the three bicycle types for two weeks. Participant bias was intentionally included by allowing participants to select a bicycle type of their preference, resulting in 12 conventional bicycle riders (71 % women), 14 pedelec riders (67 % women) and 20 s-pedelec riders (25 % women). S-pedelecs were much faster than conventional bicycles, amounting to a speed difference with conventional bicycles of 10.4 km/h in urban areas (M =28.2 km/h vs. 17.8 km/h) and of 13.2 km/h in rural areas (M = 31.4 km/h vs. 18.2 km/h). The speed differences between pedelecs and conventional bicycles were much smaller: 2.3 km/h in urban areas (20.1 km/h vs 17.8 km/h) and 4 km/h in rural areas (22.2 km/h vs. 18.2 km/h). Compared to conventional bicycles, s-pedelecs varied their speed to a greater extent and also braked harshly more frequently, showing a greater need for speed adjustment. These adjustments were larger at higher speeds. In contrast, pedelecs did not differ from conventional bicycles on speed variation. MSAL for s-pedelec riders differed by gender. For men the MSAL was 87 % on urban sections and 91 % on rural sections. For women, the MSAL was lower, respectively 23 and 69 %. None of the personality factors were associated with speed variability, harsh braking or MSAL. However, sensation seeking was associated with higher mean speeds on all three bicycle types. To conclude, pedelecs and conventional bicycles are similar in speed patterns, whereas the speed patterns of s-pedelecs differ significantly from the former two. The safety implications are discussed.

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Research in different domains has shown that people categorize oneself and others as ingroup (“us”) and outgroup (“them”) members, resulting in group-based stereotyping and attribution errors that may adversely affect social behaviour. To determine whether such patterns also exist in road traffic, we conducted an experimental web-based survey using scenarios of unregulated traffic settings in which the type of other road user was varied (cyclist vs. car driver). We investigated whether road users who described themselves predominantly as either a car driver (N = 330) or a cyclist (N = 315) would (1) report having more in common with members of their respective ingroups than outgroups, (2) be more negative about their respective outgroup than ingroup in terms of their expectations about other road users, (3) make more dispositional and less circumstantial attributions about an outgroup member who failed to yield right of way than about an ingroup member, and (4) show more willingness to raise traffic fines for the outgroup than for the ingroup. Results showed both self-described car drivers and cyclists reported having more in common with their ingroup than with their outgroup. Self-described car drivers were also least inclined to expect to be given right of way by cyclists as compared to car drivers, while self-described cyclists were less inclined than self-described car drivers to expect car drivers to yield right of way. Self-described car drivers were more inclined to make dispositional attributions about cyclists’ rule breaking behaviour and less inclined to attribute these to circumstances compared to rule breaking on the part of car drivers, and were most inclined to disadvantage their outgroup compared to their ingroup in terms of raising traffic fines. Since dispositional attributions are more likely to lead people to behave aggressively, our findings suggest that cyclists, who are arguably among those most dependent on the goodwill and forgivingness of drivers of motorised vehicles, may be less likely to receive it. This means that although both self-described cyclists and car drivers may distinguish between ingroups and outgroups in traffic, this distinction may have much more complicated implications than the simple terms “us” and “them” might imply.@en

This study investigated cycling performance of middle-aged (30–45 years old; n = 30) versus older (65+ years; n = 31) participants during low-speed tasks for which stabilization skills are known to be important. Additionally, participants’ self-ratings of their cycling skills and performance were assessed. Participants rode once on a conventional bicycle and once on a pedelec, in counterbalanced order. Three standardized tasks were performed: (1) low-speed cycling, (2) acceleration from a standstill, and (3) shoulder check. During Tasks 1 and 3, the mean absolute steering angle (a measure of the cyclist's steering activity) and the mean absolute roll rate (a measure of the amount of angular movement of the frame) were significantly greater for older participants than for middle-aged participants. These large lateral motions among older cyclists may indicate a difficulty to control the inherently unstable system. Comparing the conventional bicycle and the pedelec, participants reached a 16 km/h threshold speed in Task 2 sooner on the pedelec, an effect that was most pronounced among the older participants. Correlations between skills assessed with the Cycling Skill Inventory and actual measures of cycling performance were mostly not statistically significant. This indicates that self-reported motor-tactical and safety skills are not strongly predictive of measures of actual cycling performance. Our findings add to the existing knowledge on self-assessment of cycling skills, and suggest that age-related changes in psychomotor and sensory functions pose hazards for cycling safety.

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