Fluctuating Attentional Demand in a Simulated Driving Assessment: The Roles of Age and Driving Complexity

Stinchcombe, Arne; Gagnon, Sylvain; Zhang, J. Jane; Montembeault, Patricia; Bédard, Michel

doi:10.1080/15389588.2011.607479

Cited by 31 publications

(25 citation statements)

References 37 publications

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“…This is because there is a high number of school children generated from nearby secondary school, people coming back from work, and those going for shopping at the nearby shopping complex (mostly between age groups of 25-35 and 35-45 years old. This findings is in consistent to past findings [14]) which reported that when the complexity of a road is high especially during heavy traffic, the performance of drivers are low regardless of age groups which may contribute to greater chances of crash occurrence.…”

Section: Composite Road Environment Risk Index Vs Crash Datasupporting

confidence: 82%

Identification of Hazardous Road Sections: Crash Data versus Composite Index Method

Razelan¹,

Hussain²,

Hwa³

et al. 2014

IJET

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Abstract-In current road safety practices, the identification of hazardous road sections are normally based on crash data. However, the information provided by crash data may not be adequate to explain the causal factors that lead to a crash. Therefore, a different kind of road safety indicator that can extensively describe the actual road environment problems of a road section is considered essential. This paper considered fourteen road environment indicators based on their abilities to portray current road environment conditions and their potential towards road crash incidence. These indicators were collected using naturalistic driving technique within the 80-km road length connecting Kuantan and Maran town in the state of Pahang, Malaysia in which the composite road environment risk index was finally developed. This composite road environment risk index is found to be a useful proactive method to identify the potential problematic road sections that require urgent road improvement works as compared to the reactive crash data analysis method.Index Terms-Hazardous road sections, crash data, road environment, composite index, proactive method.

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Section: Composite Road Environment Risk Index Vs Crash Datasupporting

confidence: 82%

Identification of Hazardous Road Sections: Crash Data versus Composite Index Method

Razelan¹,

Hussain²,

Hwa³

et al. 2014

IJET

View full text Add to dashboard Cite

show abstract

“…The scenario was based on a simulated driving evaluation course developed by Weaver et al (2009) (see also Lemieux et al, 2014;Stinchcombe et al, 2011). Modifications were made to the original course in order to divide it into six road sections, each allowing the inclusion of any of the six challenging events described below and the counterbalancing of the sequence of events across scenarios.…”

Section: Simulated Scenariomentioning

confidence: 99%

Crash avoidance in response to challenging driving events: The roles of age, serialization, and driving simulator platform

Belanger

Gagnon

Stinchcombe

2015

Accident Analysis & Prevention

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“…When resource demands exceed resource availability, performance can be impaired [ 27 ]. Mental workload increases with driving complexity [ 29 , 30 ]. Therefore, when considering the context of a driving study, scenarios need to be designed with an appropriate level of difficulty and mental workload to identify subtle differences in driving behavior.…”

Section: Introductionmentioning

confidence: 99%

Driving simulator scenarios and measures to faithfully evaluate risky driving behavior: A comparative study of different driver age groups

et al. 2017

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To investigate the links between mental workload, age and risky driving, a cross-sectional study was conducted on a driving simulator using several established and some novel measures of driving ability and scenarios of varying complexity. A sample of 115 drivers was divided into three age and experience groups: young inexperienced (18–21 years old), adult experienced (25–55 years old) and older adult (70–86 years old). Participants were tested on three different scenarios varying in mental workload from low to high. Additionally, to gain a better understanding of individuals’ ability to capture and integrate relevant information in a highly complex visual environment, the participants’ perceptual-cognitive capacity was evaluated using 3-dimensional multiple object tracking (3D-MOT). Results indicate moderate scenario complexity as the best suited to highlight well-documented differences in driving ability between age groups and to elicit naturalistic driving behavior. Furthermore, several of the novel driving measures were shown to provide useful, non-redundant information about driving behavior, complementing more established measures. Finally, 3D-MOT was demonstrated to be an effective predictor of elevated crash risk as well as decreased naturally-adopted mean driving speed, particularly among older adults. In sum, the present experiment demonstrates that in cases of either extreme high or low task demands, drivers can become overloaded or under aroused and thus task measures may lose sensitivity. Moreover, insights from the present study should inform methodological considerations for future driving simulator research. Importantly, future research should continue to investigate the predictive utility of perceptual-cognitive tests in the domain of driving risk assessment.

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Fluctuating Attentional Demand in a Simulated Driving Assessment: The Roles of Age and Driving Complexity

Cited by 31 publications

References 37 publications

Identification of Hazardous Road Sections: Crash Data versus Composite Index Method

Identification of Hazardous Road Sections: Crash Data versus Composite Index Method

Crash avoidance in response to challenging driving events: The roles of age, serialization, and driving simulator platform

Driving simulator scenarios and measures to faithfully evaluate risky driving behavior: A comparative study of different driver age groups

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