The prevalence of, and factors associated with, serious crashes involving a distracting activity

McEvoy, Suzanne; Stevenson, Mark; Woodward, Mark

doi:10.1016/j.aap.2006.09.005

Cited by 129 publications

(69 citation statements)

References 13 publications

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“…sending a text message compared to placing a call) may have an effect, both on driving performance and also a driver's willingness to engage with their phone. The main focus of research in this area has been around hands free and hand held calling ( [18], [15], [19] and [20]). However, there is a paucity of research regarding willingness to engage.…”

Section: Of How the Use Of That Device Interferes With Driving And Thmentioning

confidence: 99%

Drivers’ willingness to engage with their mobile phone: the influence of phone function and road demand

Hancox

Richardson

Morris

2013

IET Intelligent Transport Systems

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Section: Of How the Use Of That Device Interferes With Driving And Thmentioning

confidence: 99%

Drivers’ willingness to engage with their mobile phone: the influence of phone function and road demand

Hancox

Richardson

Morris

2013

IET Intelligent Transport Systems

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“…McEvoy et al [15] reports that 13.6% of all accidents were caused by distracted driving whereas USDOT [1] has estimated 17% of all accidents were caused by distracted driving. Agencies have the option of choosing one of these numbers for their analysis of accidents.…”

Section: Analysis Modulementioning

confidence: 99%

“…follow the approach of McEvoy et al [15] who reports that 13.6% of all accidents are caused by driver distraction. The accident database generated from police reports are examined to determine the locations experiencing higher accidents and subsequently establish causes of accidents including distraction related factors.…”

Section: Data Collection Modulementioning

confidence: 99%

Research framework for studying public transit bus driver distraction

D'Souza

Maheshwari

2013

WIT Transactions on the Built Environment

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Over 3,000 people are killed and 400,000 injured annually in the US due to motor vehicle crashes involving a distracted driver. In the case of passenger vehicles, most of the distraction is within the control of the driver. However, for public transit vehicles, some distractions are caused by factors beyond the driver's control such as operating the fare box or attending to passengers. Research on the distraction of transit bus drivers is very limited, although injuries from transit vehicle accidents are generally higher because buses usually carry many passengers. This paper proposes a modular research framework for conducting a driver distraction study for transit buses. The research framework provides standardized methodologies structured into four modules -Data Collection, Analysis, Validation and Result Interpretation. The Data Collection module consists of approaches for collecting data from accident databases, surveys, and route observation. The Analysis module provide methods for classification of distracting activities, and development of statistical models that construct relationships between high risk distracting activities and driver attributes and external factors. The Validation module presents simple observation and discussion methods to sophisticated simulation techniques to check the model results. The final module contains guidelines for Results Interpretation and Usage. The framework's standardized techniques are expected to reduce the overall time and cost of conducting a transit bus driver distraction study.

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“…This is not only happening in this country but also worldwide, as road traffic injury is the eleventh leading cause of death, and over one million people are killed every year in road crashes [2]. A previous study showed that human errors are the major contributing factor in approximately 90% of road traffic accidents [3]; driver distraction is a significant contributor to road traffic accidents [4,5]. Naturalistic driving studies have demonstrated that drivers have a tendency to spend a vast amount of driving time doing secondary tasks.…”

Section: Introductionmentioning

confidence: 99%

Measurement of Driver Distraction in Malaysia’s Traffic Environment: A Driving Simulator Study

Siam¹,

Isa²,

Borhan³

et al. 2015

J. Mech. Eng. Sci.

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The Malaysian Institute of Road Safety Research has embarked on the development of a fixed-based driving simulator that can be reconfigured easily to suit various road safety research requirements. The objective of this study is to measure driver distraction in terms of participants' response time for different road conditions and secondary tasks using a driving simulator. Three different simulation routes were designed in the study-expressway, off-ramp, and curved road. Thirty participants took part in the study. Two types of detection response task were used in the study-tactile and visual. Recall number, surrogate reference task, navigation, and texting were used as secondary tasks. The results showed that in terms of road segments, both types of detection response task were found to be sensitive; longer response times were observed for more demanding off-ramp and curved road sections when compared with expressway. Furthermore, for secondary tasks, the participants took longer to respond to both stimuli, particularly for the more difficult task followed by an easier task. In general, response times increased as a function of road segments as well as exposure to secondary tasks.Keywords: Driving simulator; driver distraction; response time; secondary task; road safety. INTRODUCTIONIn 2012, 6,917 fatalities were recorded in Malaysia due to road crashes, with an average of 18 people killed every day [1]. This is not only happening in this country but also worldwide, as road traffic injury is the eleventh leading cause of death, and over one million people are killed every year in road crashes [2]. A previous study showed that human errors are the major contributing factor in approximately 90% of road traffic accidents [3]; driver distraction is a significant contributor to road traffic accidents [4,5]. Naturalistic driving studies have demonstrated that drivers have a tendency to spend a vast amount of driving time doing secondary tasks. According to research, approximately 23% of all crashes and near-crashes were caused by distraction due to secondary tasks [6]. Driving performance begins to deteriorate when drivers fail to allocate sufficient attention to the driving task at critical moments, because they are engaged in another task, thereby resulting in an impairment of the ability to drive safely and effectively [7,8]. One of the prominent tools to study human-related issues specifically for driver distraction is a driving simulator. It is able to simulate a virtual driving environment and resemble real driving conditions [9][10][11]. The advantages of

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The prevalence of, and factors associated with, serious crashes involving a distracting activity

Cited by 129 publications

References 13 publications

Drivers’ willingness to engage with their mobile phone: the influence of phone function and road demand

Drivers’ willingness to engage with their mobile phone: the influence of phone function and road demand

Research framework for studying public transit bus driver distraction

Measurement of Driver Distraction in Malaysia’s Traffic Environment: A Driving Simulator Study

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