The 100-Car Naturalistic Driving Study: Phase II - Results of the 100-Car Field Experiment

Dingus, Tom; Klauer, Sheila G.; Neale, V. L.; Petersen, A.; Lee, S. E.; Sudweeks, Jeremy; Pérez, Miguel Á.; Hankey, Jonathan M.; Ramsey, D.; Gupta, Subhadeep; Bucher, C.; Doerzaph, Z. R.; Jermeland, J.; Knipling, R. R.

doi:10.1037/e624282011-001

Cited by 623 publications

(563 citation statements)

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“…With more than 9.5 million Americans working overnight or rotating shifts and one-third of United States commutes exceeding 30 min, these results have implications for traffic and occupational safety. was involved in an estimated 21% of fatal crashes and 13% of crashes causing severe injury, consistent with earlier estimates that drowsy driving causes 20% of serious motor vehicle crash injuries resulting in hospitalization or death, and is associated with a four-to sixfold increase in crash/near-crash risk (1)(2)(3)(4). These data indicate that drowsiness is likely one of the most prevalent causes of preventable road crashes worldwide (5).…”

supporting

confidence: 84%

High risk of near-crash driving events following night-shift work

Lee

Howard

Horrey

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

169

119

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Night-shift workers are at high risk of drowsiness-related motor vehicle crashes as a result of circadian disruption and sleep restriction. However, the impact of actual night-shift work on measures of drowsiness and driving performance while operating a real motor vehicle remains unknown. Sixteen night-shift workers completed two 2-h daytime driving sessions on a closed driving track at the Liberty Mutual Research Institute for Safety: (i) a postsleep baseline driving session after an average of 7.6 ± 2.4 h sleep the previous night with no night-shift work, and (ii) a postnightshift driving session following night-shift work. Physiological measures of drowsiness were collected, including infrared reflectance oculography, electroencephalography, and electrooculography. Driving performance measures included lane excursions, near-crash events, and drives terminated because of failure to maintain control of the vehicle. Eleven near-crashes occurred in 6 of 16 postnight-shift drives (37.5%), and 7 of 16 postnight-shift drives (43.8%) were terminated early for safety reasons, compared with zero near-crashes or early drive terminations during 16 postsleep drives (Fishers exact: P = 0.0088 and P = 0.0034, respectively). Participants had a significantly higher rate of lane excursions, average Johns Drowsiness Scale, blink duration, and number of slow eye movements during postnight-shift drives compared with postsleep drives (3.09/min vs. 1.49/min; 1.71 vs. 0.97; 125 ms vs. 100 ms; 35.8 vs. 19.1; respectively, P < 0.05 for all). Night-shift work increases driver drowsiness, degrading driving performance and increasing the risk of near-crash drive events. With more than 9.5 million Americans working overnight or rotating shifts and one-third of United States commutes exceeding 30 min, these results have implications for traffic and occupational safety. drowsy driving | sleep | EEG | infrared oculography | fatigue

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supporting

confidence: 84%

High risk of near-crash driving events following night-shift work

Lee

Howard

Horrey

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

169

119

View full text Add to dashboard Cite

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“…This results in crash-frequency data that are non-negative integers, and suggests the application of count-data regression methods or other approaches that can properly account for the integer nature of the data. In the U.S., the National Strategic Highway Research Program initiated a series of studies in recent years with the objective of addressing many of the fundamental questions relating to crash causation and involvement (see for example Dingus et al 2006). These studies are based on naturalistic driving information, wherein a selected pool of drivers is observed over prolonged periods in terms of their crash, near-crash and incident involvements.…”

Section: Introductionmentioning

confidence: 99%

The statistical analysis of crash-frequency data: A review and assessment of methodological alternatives

Lord

Mannering

2010

Transportation Research Part A: Policy and Practice

979

739

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“…However, the results obtained in this example should be validated by further data from studies on noncritical driving behavior and critical events. A fruitful source of data was obtained from the 100-car study by Dingus et al, (2006).…”

Section: Resultsmentioning

confidence: 99%

“…However, the proportion of critical and noncritical traffic situations is strongly unbalanced. For example, the 100-car Naturalistic Driving Study carried out by the Virginia Tech Transportation Institute (VTTI) showed that within 12 to 13 months of data collection and an overall of 2,000,000 miles traveled, only 15 police-reported and 67 non-police-reported crashes, which included low "g" events such as striking or running over curbs and parking blocks (some vehicles were involved in multiple crashes), 761 near-crashes and 8,295 incidents occurred (Dingus et al, 2006). This leads to an incident rate of about 4.6*10 -3 incidents/mi.…”

Section: Introductionmentioning

confidence: 99%

Curve Negotiation: Identifying Driver Behavior Around Curves with the Driver Performance Database

Mikolajetz¹,

Henning

Tenzer³

et al. 2009

Proceedings of the 5th International Driving Symposium on Human Factors in Driver Assessment, Training, and Vehicle Design : Dr

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Summary:Approximately one quarter of all accidents outside city limits occur while driving around curves, where assistance systems could prevent the driver from negotiating curves with excessive speed. This study argues that the parameterizing of a Driving Assistant System could be realized with data from realistic, noncritical driving behavior offered by Naturalistic Driving Studies. The Driver Performance Database presented in this study provides a tool for observing normal, noncritical driving behavior. The Database contains results from road tests with an instrumented vehicle that were carried out on public road traffic on a predetermined route, which was precisely measured in advance. In addition to vehicle state parameters, we also collected data concerning the driving environment and physiological information. With the Driver Performance Database it is possible to generate different facets of human driving behavior in a descriptive and normative way, which is illustrated by driver behavior in curve negotiation.

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The 100-Car Naturalistic Driving Study: Phase II - Results of the 100-Car Field Experiment

Cited by 623 publications

References 0 publications

High risk of near-crash driving events following night-shift work

High risk of near-crash driving events following night-shift work

The statistical analysis of crash-frequency data: A review and assessment of methodological alternatives

Curve Negotiation: Identifying Driver Behavior Around Curves with the Driver Performance Database

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