Adult Pedestrian Behavior When Accompanying Children on the Route to School

Pfeffer, Karen; Fagbemi, H. P.; Stennet, S.

doi:10.1080/15389580903548576

Cited by 20 publications

(6 citation statements)

References 25 publications

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“…The result is in support of similar empirical results reported by Rosenbloom et al (2004) and Pfeffer et al (2010). This is partly because older pedestrians have stronger risk consciousness of traffic violations.…”

Section: Effects Of Personal Characteristicssupporting

confidence: 91%

Computational Intelligence for Traffic and Mobility

Wang¹,

Wets²

2013

Atlantis Computational Intelligence Systems

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Aims and scope of the seriesThe series 'Atlantis Computational Intelligence Systems' aims at covering state-of-theart research and development in all fields where computational intelligence is investigated and applied. The series seeks to publish monographs and edited volumes on foundations and new developments in the field of computational intelligence, including fundamental and applied research as well as work describing new, emerging technologies originating from computational intelligence research. Applied CI research may range from CI applications in the industry to research projects in the life sciences, including research in biology, physics, chemistry and the neurosciences.All books in this series are co-published with Springer.For more information on this series and our other book series, please visit our website at:www.atlantis-press.com PrefaceAdvances in mobility are most clearly illustrated by the spread of motorized traffic and transport, the development of the transportation industry, including vehicle manufacturing and its associated infrastructure. These developments represent one of the main challenges for information science and intelligent technology. The discipline of Intelligent Transportation System (ITS) is widely applied to solve transportation problems including congestion, accidents and pollution emissions.Since our daily life and work are closely related to traffic and mobility, traffic demand has increased dramatically. Following this increase, we additionally have to balance the increasing desire for mobility and efficiency with the societal concerns about traffic problems. Today's traffic demand is predominantly served by individual motorized vehicles, which are the primary means of transportation. As the traffic demand has continuously grown faster than the construction of infrastructure over the last decades, traffic congestion has become a severe problem in many countries. Meanwhile, as vehicle speed is increasing, traffic safety has also become an important and socially relevant topic, which has impact on social and economic developments. Additionally, the environmental impact and energy consumption caused by traffic systems also arouse great public concern.The engineers and scientists in different areas are seeking solutions as to how the traffic system could be used more efficiently and how operations could be improved by using new technologies and new methodologies. Recently, computational intelligence methods have received considerable attention regarding their potential as a powerful technique for traffic and mobility problems. Computational Intelligence (CI) is the study of adaptive mechanisms enabling or facilitating intelligent behaviour in complex and changing environments. As such, CI combines artificial neural networks, evolutionary computing, swarm intelligence and fuzzy systems. The characteristic of 'intelligence' is usually attributed to v vi Computational Intelligence for Traffic and Mobility humans. The concept of intelligence is directly linked to reasoning and...

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Section: Effects Of Personal Characteristicssupporting

confidence: 91%

Computational Intelligence for Traffic and Mobility

Wang¹,

Wets²

2013

Atlantis Computational Intelligence Systems

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“…Parents tend to believe their children are safe pedestrians and allow their children to walk alone on streets, despite the fact that they recognize the limitations of child pedestrian skills. [48][49][50] They also do not spend significant time teaching their children safe pedestrian skills 49,51 or modeling safe pedestrian skills for their children 52 (though see other work 53 for contradictory data on modeling).…”

Section: Social Influencesmentioning

confidence: 99%

Child Pedestrian Injury

Schwebel

Davis

O’Neal

2011

American Journal of Lifestyle Medicine

100

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Pedestrian injury is among the leading causes of pediatric death in the United States and much of the world. This paper is divided into two sections. First, we review the literature on behavioral risk factors for child injury. Cognitive and perceptual development risks are discussed. The roles of distraction, temperament and personality, and social influences from parents and peers are presented. We conclude the first section with brief reviews of environmental risks, pedestrian safety among special populations, and the role of sleep and fatigue on pediatric pedestrian safety. The second section of the review considers child pedestrian injury prevention strategies. Categorized by mode of presentation, we discuss parent instruction strategies, school-based instruction strategies (including crossing guards), and streetside training techniques. Technologybased training strategies using video, internet, and virtual reality are reviewed. We conclude the section on prevention with discussion of community-based interventions.

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“…The second part is devoted to the Motorcycle Rider Behavior Questionnaire (MRBQ), to the motives for riding a motorcycle and to the Bem Sex-Role Inventory (BSRI) (Bem, 1974;Fontayne et al, 2000;Pfeffer, Fagbemi, & Stennet, 2010).…”

Section: Methodsmentioning

confidence: 99%

Conformity to gender stereotypes, motives for riding and aberrant behaviors of French motorcycle riders

Coquelet

Granié²,

Griffet

2018

Journal of Risk Research

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As sex differences are very pronounced in motorcycle crashes, both in terms of number and severity, the present study aims to determine the relationship between gender, motives for riding a motorcycle, and risk-taking behaviors among motorcyclists. Declared aberrant behaviors, conformity to gender stereotypes and motives to ride a motorcycle were investigated among 2,262 riders of heavy motorcycles, through an Internet survey. Ages ranged from 18 to 78 years, 10.5% of the respondents were women. Results revealed the new scale on motives for riding a motorcycle was effective and allowed to show that competition motives were associated to masculinity, low femininity and youth. They also showed that maleness, masculinity, youth and competition motives were predictors of violations and femaleness and low masculinity were predictors of lapses. Furthermore, competition motives were also mediators between masculinity and aberrant behaviors, except for personal protective equipment negligence. This study gives new knowledge on the relationship between conformity to gender stereotypes, motivations and the behaviors of riders of heavy motorcycles. Results can be useful for adapting prevention campaigns to the small subgroups that are the more at risk in the motorcyclists' population.

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Adult Pedestrian Behavior When Accompanying Children on the Route to School

Cited by 20 publications

References 25 publications

Computational Intelligence for Traffic and Mobility

Computational Intelligence for Traffic and Mobility

Child Pedestrian Injury

Conformity to gender stereotypes, motives for riding and aberrant behaviors of French motorcycle riders

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