How do drivers behave during indecision zone maneuvers?

Xiong, Huimin; Narayanaswamy, Prabha; Bao, Shan; Flannagan, Carol A. C.; Sayer, James R.

doi:10.1016/j.aap.2015.04.023

Cited by 21 publications

(7 citation statements)

References 13 publications

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“…Cognitively, but not visually, demanding tasks of phone conversations did not influence visual attention in naturalistic or simulated settings (Farmer et al., ; Kingery et al., , ). Such cognitively distracting tasks did, however, cause young drivers to take incorrect exits (Gaspar et al., ), miss turns (Kass, Cole, & Stanny, ) and mirror checks (Pereira, Hamama, Dapzol, Bruyas, & Simões, ), pause excessively at stop signs (Reimer, Mehler, Coughlin et al., ; Reimer, Mehler, D'Ambrosio et al., ), and proceed through yellow light indicators (Xiong, Narayanaswamy, Bao, Flannagan, & Sayer, ). Conversing on phones slowed driver response time in three studies (Bellinger, Budde, Machida, Richardson, & Berg, ; Horberry, Anderson, Regan, Triggs, & Brown, ; Strayer & Drews, ), but not in a fourth (Narad et al., ).…”

Section: Resultsmentioning

confidence: 99%

Distracted Walking, Bicycling, and Driving: Systematic Review and Meta‐Analysis of Mobile Technology and Youth Crash Risk

et al. 2017

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This article examined the impact of mobile technology on young pedestrians, bicyclists, and drivers. A systematic search yielded 41 articles meeting inclusion criteria: peer-reviewed, published before February 1, 2016, behavioral outcome related to pedestrian, bicycling, or driving in the presence of mobile technology use, youth sample. Eleven studies were meta-analyzed to evaluate increased risk for crash/near-crash while distracted. Risk of bias and quality of research were assessed. Across methodologies, developmental stages, and type of distracting task, mobile technology use impairs youth safety on the road. Quality of evidence was low (pedestrian) to moderate (driving). Findings are discussed from the perspective of cognitive and visual distractions. Policy and behavioral efforts should continue to reduce mobile technology use in transportation settings.

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Section: Resultsmentioning

confidence: 99%

Distracted Walking, Bicycling, and Driving: Systematic Review and Meta‐Analysis of Mobile Technology and Youth Crash Risk

et al. 2017

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“…Some of these variables were tested through metaregression, including research setting, conversation type, and year of publication. Other studies used variables that did not fit with inclusion criteria, such as responses to being distracted while trying to stop at yellow lights (Ohlhauser, Boyle, Marshall, & Ahmad, 2011;Xiong, Narayanaswamy, Bao, Flannagan, & Sayer, 2016). However, many of these variables could not be quantitatively examined.…”

Section: Implications For Countermeasuresmentioning

confidence: 99%

Does Talking on a Cell Phone, With a Passenger, or Dialing Affect Driving Performance? An Updated Systematic Review and Meta-Analysis of Experimental Studies

Caird¹,

Simmons²,

Wiley³

et al. 2018

Hum Factors

143

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Objective An up-to-date meta-analysis of experimental research on talking and driving is needed to provide a comprehensive, empirical, and credible basis for policy, legislation, countermeasures, and future research. Background The effects of cell, mobile, and smart phone use on driving safety continues to be a contentious societal issue. Method All available studies that measured the effects of cell phone use on driving were identified through a variety of search methods and databases. A total of 93 studies containing 106 experiments met the inclusion criteria. Coded independent variables included conversation target (handheld, hands-free, and passenger), setting (laboratory, simulation, or on road), and conversation type (natural, cognitive task, and dialing). Coded dependent variables included reaction time, stimulus detection, lane positioning, speed, headway, eye movements, and collisions. Results The overall sample had 4,382 participants, with driver ages ranging from 14 to 84 years ( M = 25.5, SD = 5.2). Conversation on a handheld or hands-free phone resulted in performance costs when compared with baseline driving for reaction time, stimulus detection, and collisions. Passenger conversation had a similar pattern of effect sizes. Dialing while driving had large performance costs for many variables. Conclusion This meta-analysis found that cell phone and passenger conversation produced moderate performance costs. Drivers minimally compensated while conversing on a cell phone by increasing headway or reducing speed. A number of additional meta-analytic questions are discussed. Application The results can be used to guide legislation, policy, countermeasures, and future research.

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“…Distracted driving behaviours also change the decision-making ability of drivers at the intersections. Previous studies have shown that distracted drivers are less likely to stop when meeting the yellow light, which significantly increased the risk of crashes at the intersection [7,8]. particular driving distraction; however, there is a lack of comparative study on the motivation of different driving distraction behaviours.…”

Section: Literature Reviewmentioning

confidence: 99%

Exploration of Contributing Factors of Different Distracted Driving Behaviors

Shi

Peng

Xiao

2019

PROMET

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The motivation of this research is to explore the contributing factors of driving distraction and compare the contributing factors for three typical distracted driving behaviours: drinking water, answering a phone and using mobile phone application (APP) while driving. An online survey including a driving behaviour scale and the Theory of Planned Behaviour Questionnaire (TPB Questionnaire) was conducted to obtain data related to these driving distractions. An integral structural equation model based on the Theory of Planned Behaviour (TPB) was established to explain the factors causing three typical distracted behaviours, and the causes of differences for three typical distracted behaviours were compared. The result shows that the attitudes and perceived behaviour control are the main factors causing distracted behaviours, and the subjective norm has a significant impact on answering a phone while driving. The occurrence of a distracted driving behaviour is the consequence of behaviour intention and perceived behaviour control. These conclusions provide insights for implementing behaviour modification and traffic laws education. KEY WORDSdriving distraction; contributing factors; structural equation model; theory of planned behaviours;

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How do drivers behave during indecision zone maneuvers?

Cited by 21 publications

References 13 publications

Distracted Walking, Bicycling, and Driving: Systematic Review and Meta‐Analysis of Mobile Technology and Youth Crash Risk

Distracted Walking, Bicycling, and Driving: Systematic Review and Meta‐Analysis of Mobile Technology and Youth Crash Risk

Does Talking on a Cell Phone, With a Passenger, or Dialing Affect Driving Performance? An Updated Systematic Review and Meta-Analysis of Experimental Studies

Exploration of Contributing Factors of Different Distracted Driving Behaviors

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