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1.
Appl Ergon ; 76: 113-121, 2019 Apr.
Article in English | MEDLINE | ID: mdl-30642515

ABSTRACT

Several innovative measures in traffic control applied in Europe have successfully improved the comfort and safety of cycling, among which is the green waves for cyclists. Consecutive traffic lights are synchronised to create a green wave, increasing comfort and decreasing waiting times and related deliberate red-light running. This study focused on exploring the user acceptance of green wave systems and the user evaluation of six distinct interface designs (i.e. numeric-based countdown, dot-based vertical countdown, dot-based clockwise countdown, LED line, LED road surface, on-bike speed indicator). Results indicate a preference for three systems: numeric-based countdown, LED line and LED road surface. Results also show a significant influence of nationality on the evaluation of the interfaces. Based on our findings, we argue that the numeric-based countdown represents the most promising option for future adaptive green wave implementations. The outcomes of the present study represent a useful evidence and guidance for researchers, designers and decision makers in the field of green waves, mobility and traffic safety.


Subject(s)
Accident Prevention , Bicycling , Built Environment , Safety , Accident Prevention/methods , Accidents, Traffic/prevention & control , Adolescent , Adult , Aged , Consumer Behavior , Female , Humans , Male , Middle Aged , Perception , Young Adult
2.
Int J Inj Contr Saf Promot ; 25(1): 70-77, 2018 Mar.
Article in English | MEDLINE | ID: mdl-28675090

ABSTRACT

This study investigates the direct and indirect effect of three types of unsafe behaviours (i.e. errors, generic violations and smartphone-specific violations) on the likelihood of near crashes and actual crashes among Italian cyclists. We considered smartphone-specific violations as a different unsafe behaviour subtype that enhances the probability of committing errors, thus increasing the likelihood of being involved in near crashes. Furthermore, we hypothesized that near crashes will predict actual crashes. Results revealed that errors predicted near crashes, whereas generic and smartphone-specific violations did not. Near crashes mediated the effect of errors on crashes. Moreover, smartphone-specific violations predicted crashes throughout its consecutive effects on errors and near crashes. These findings contribute to deepen our understanding of the relationship between cyclists' unsafe behaviours, near crashes and actual crashes. To our knowledge, the present study is the first that links errors to near crashes among cyclists.


Subject(s)
Accidents, Traffic/statistics & numerical data , Bicycling/statistics & numerical data , Dangerous Behavior , Safety , Smartphone , Adult , Age Factors , Aged , Aged, 80 and over , Bicycling/psychology , Female , Humans , Italy , Male , Middle Aged , Probability , Sex Factors , Surveys and Questionnaires , Young Adult
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