Abstract:The use of assistance systems aimed at reducing road fatalities is spreading, especially for car drivers, but less effort has been devoted to developing and testing similar systems for powered two-wheelers (PTWs). Considering that over speeding represents one of the main causal factors in road crashes and that riders are more vulnerable than drivers, in the present study we investigated the effectiveness of an assistance system which signaled speed limit violations during a simulated moped-driving task, in opt… Show more
“…Concerning the cluster analysis, a non-hierarchical k -means cluster analysis was performed on the z -scores of the driving parameters, using the centroids identified in a previous visual feedback study as a reference. In fact, the present study represents the second part of previous research conducted with the same HRT simulator intended to investigate the effectiveness of an alert system that provided simultaneous visual feedback when the speed limit was exceeded during a driving simulation and the persistence of its effect over a period of one month ( Tagliabue et al, 2021 ). The aim of the cluster analysis was to identify prudent and imprudent drivers, as in the reference study.…”
The aim of the present study is to investigate the relation between self-reported aberrant behaviors as measured by using the Italian version of the Manchester Driver Behavior Questionnaire (DBQ) and actual driving performance during a virtual simulation, focusing particularly on over-speeding. Individual variables are considered based on participants’ behavior, and driving styles are derived from both the self-report questionnaire and the kinematic variables obtained through a moped simulator after the simulated driving task. The experiment was carried out on an Italian sample of 79 individuals aged between 18 and 35 who had to drive throughout virtual road environments. A cluster analysis of the kinematic variables provided by the simulator was used to individuate two different groups of drivers: 45 fell into the cluster named “Prudent” and 34 participants fell into the “Imprudent” cluster. The Prudent participants were characterized by lower acceleration, lower speed, better overall evaluations, and a smaller number of accidents. Correlations showed that self-report responses correlated positively with performance variables in terms of acceleration, speed, and over-speeding. Furthermore, the results from a MANOVA supported and complemented this evidence by emphasizing the usefulness of the integrated approach employed. Overall, these results reflect the suitability of experimental sample-splitting into two clusters, pointing out the appropriateness and relevance of self-report DBQ use with particular emphasis on Ordinary Violations and Lapses. The integrated use of the driving simulator and the self-report DBQ instrument with reference to driving behavior made it possible to support previous theoretical considerations regarding the relations between on-road aberrant behaviors and over-speeding behaviors. It also enabled the addition of evidence on the effectiveness of the simulator in detecting drivers’ actual performance. These results are relevant to allow the integration of useful information to expand intervention and training designs that can be used to reduce risky behavior and promote road safety.
“…Concerning the cluster analysis, a non-hierarchical k -means cluster analysis was performed on the z -scores of the driving parameters, using the centroids identified in a previous visual feedback study as a reference. In fact, the present study represents the second part of previous research conducted with the same HRT simulator intended to investigate the effectiveness of an alert system that provided simultaneous visual feedback when the speed limit was exceeded during a driving simulation and the persistence of its effect over a period of one month ( Tagliabue et al, 2021 ). The aim of the cluster analysis was to identify prudent and imprudent drivers, as in the reference study.…”
The aim of the present study is to investigate the relation between self-reported aberrant behaviors as measured by using the Italian version of the Manchester Driver Behavior Questionnaire (DBQ) and actual driving performance during a virtual simulation, focusing particularly on over-speeding. Individual variables are considered based on participants’ behavior, and driving styles are derived from both the self-report questionnaire and the kinematic variables obtained through a moped simulator after the simulated driving task. The experiment was carried out on an Italian sample of 79 individuals aged between 18 and 35 who had to drive throughout virtual road environments. A cluster analysis of the kinematic variables provided by the simulator was used to individuate two different groups of drivers: 45 fell into the cluster named “Prudent” and 34 participants fell into the “Imprudent” cluster. The Prudent participants were characterized by lower acceleration, lower speed, better overall evaluations, and a smaller number of accidents. Correlations showed that self-report responses correlated positively with performance variables in terms of acceleration, speed, and over-speeding. Furthermore, the results from a MANOVA supported and complemented this evidence by emphasizing the usefulness of the integrated approach employed. Overall, these results reflect the suitability of experimental sample-splitting into two clusters, pointing out the appropriateness and relevance of self-report DBQ use with particular emphasis on Ordinary Violations and Lapses. The integrated use of the driving simulator and the self-report DBQ instrument with reference to driving behavior made it possible to support previous theoretical considerations regarding the relations between on-road aberrant behaviors and over-speeding behaviors. It also enabled the addition of evidence on the effectiveness of the simulator in detecting drivers’ actual performance. These results are relevant to allow the integration of useful information to expand intervention and training designs that can be used to reduce risky behavior and promote road safety.
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