Driving Fatigue in Professional Drivers: A Survey of Truck and Taxi Drivers

Meng, Fanchao; Li, Shuling; Cao, Lingzhi; Li, Musen; Peng, Qijia; Wang, Chunhui; Zhang, Weigang

doi:10.1080/15389588.2014.973945

Cited by 114 publications

(79 citation statements)

References 53 publications

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“…Various analysis techniques have been used by the researchers to study the effects of different lifestyle and sleep-related factors on the probability of drowsy driving and associated crash risk. For instance, Girotto et al (2016) and Sadeghniiat-haghighi et al (2016) used multinomial logistic regression and Häkkänen and Summala (2001), Meng et al (2015), Papadakaki et al (2008) and Tzamalouka et al (2005) used logistic regression. Chi-square test (Meng et al, 2015;Williamson & Friswell, 2013), Kruskal-Wallis test (Philip et al, 2002;Sabahiah et al, 2017), Spearmen correlation (Philip et al, 2002), factor analysis (McCartt et al, 2000;Sullman et al, 2002;Tsao, Chang, & Ma, 2017), multivariate analysis of covariance (MANCOVA) (Thompson & Stevenson, 2014) and Agent-Based Modeling (ABM) (Thompson et al, 2015) are also some of the commonly used analysis techniques.…”

Section: Previous Researchmentioning

confidence: 99%

“…In contrast to India, the previous studies across the globe have elucidated the dimensions of drowsiness problem among commercial or Heavy Vehicle (HV) drivers to some extent (Duke et al, 2010;Castillo-Manzano et al, 2016;Teoh et al, 2017;Meng et al, 2015;Kanazawa et al, 2006). Based on the literature, the major contributing factors to drowsiness problem among drivers are discussed in the following sub-sections.…”

Section: Previous Researchmentioning

confidence: 99%

“…Drowsy driving can lead to severe property damages, injuries and fatalities, but is usually under-reported (Anund et al, 2011;Sagberg, 1999;Tefft, 2012). Many previous studies have focused on drowsy driving problem among truck drivers which suggest driver demographics, lifestyle and work-rest patterns are the main factors that contribute to driver alertness (confer Table 1) (Duke et al, 2010;Castillo-Manzano et al, 2016;Teoh et al, 2017;Meng et al, 2015;Kanazawa et al, 2006;Papadakaki et al, 2008;Tzamalouka et al, 2005).…”

Section: Introductionmentioning

confidence: 99%

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Effects of driver work-rest patterns, lifestyle and payment incentives on long-haul truck driver sleepiness

Mahajan

Velaga

Kumar

et al. 2019

Transportation Research Part F: Traffic Psychology and Behaviou

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The aim of the study is to identify and model the role of payment incentives, driver work-rest patterns and other lifestyle habits influencing the drowsy driving behavior among long-haul truck drivers. To achieve this aim, this study targeted two main objectives: (1) to examine the significant differences between the groups of drowsy and non-drowsy drivers based on the opportunities of monetary incentives and (2) to examine the role of different factors: driver demographics, work-rest patterns, lifestyle and occupational characteristics particularly incentives associated with driving in causing driver sleepiness among Indian truck drivers. The study is based on interview responses from 453 long-haul truck drivers approached in three Indian cities-Mumbai, Indore and Nagpur. Initial principal component analysis of the responses related to financial incentives (occupational characteristics) resulted into two correlated factors: (i) willingness to earn extra payments if offered (WEP) and (ii) incentives available in the current driving experience (ICD) that influence driver work-rest patterns and alertness while driving. Kruskal-Wallis test showed a significant difference among the groups of sleepy and non-sleepy drivers due to these factors (WEP and ICD). Finally, a logistic regression model showed that long driving duration, working days per week, rest patterns, insufficient sleeping hours and history of violations were found significantly associated with drowsy driving among the long-haul truck drivers. Increase in consumption of caffeine and tobacco indicated reduction in driver alertness. According to the model results, the odds of drowsy driving were 77% less for drivers between 46-55 years compared to the young drivers (<25 years). Driving under the influence of financial incentives was observed to increase the odds of falling asleep by 1.58 times among the truck drivers. This was apparently the most interesting and intriguing result of the study indicating the need for further research on the influence of financial or socioeconomic motivations to sleepiness.

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Section: Previous Researchmentioning

confidence: 99%

Section: Previous Researchmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Effects of driver work-rest patterns, lifestyle and payment incentives on long-haul truck driver sleepiness

Mahajan

Velaga

Kumar

et al. 2019

Transportation Research Part F: Traffic Psychology and Behaviou

View full text Add to dashboard Cite

show abstract

“…Besides, drivers' vocation was another factor related to traffic violations and road crashes [48]. Professional drivers (such as taxi, bus, or truck drivers) had a high probability of traffic crashes due to a high exposure on road and the high possibility of fatigue driving [49]. Moreover, professional drivers may perform differently from nonprofessional drivers because of different levels of driving skills.…”

Section: Impacts Of Driver Characteristics On Driver Behaviormentioning

confidence: 99%

Exploring the Effects of Signs’ Design and In-Vehicle Audio Warning on Driver Behavior at Flashing-Light-Controlled Grade Crossings: A Driving Simulator-Based Study

Yang

Yan

Xue

et al. 2019

Journal of Advanced Transportation

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The complex environment at grade crossings and the severe collision consequences give rise to the concern of safety condition at crossings among traffic control authorities. Optimizing conventional devices and applying emerging technologies are worthwhile measures to improve the safety conditions at grade crossings. In this study, a flashing-light running (FLR) warning system was proposed to reduce crossing violation and improve performances of drivers at flashing-light-controlled grade crossings (FLCGCs). Forty-four fully licensed drivers aged between 30 and 48 years participated in a driving simulator study to investigate the efficacy of two countermeasures of the system: proposed design of signs and pavement markings (PSM) for grade crossing, and two-stage in-vehicle audio warning (IVAW) technology. A range of flashing light trigger timing and two foggy conditions were designed in this experiment to test the system applicability. Drivers’ gender and vocation were considered as well to examine drivers’ adaptation to the new proposed system. Five variables were collected and analyzed in this study to investigate the effectiveness of the system, i.e., drivers’ compliance, approaching mean speed, brake reaction time, deceleration, and red-to-crossing time. Results showed that drivers’ driving performances were improved in both PSM only condition and PSM + W condition. The FLR warning system could eliminate the negative effects of foggy weather and reduce gender differences in driver behaviors to some extent. These findings suggested that the FLR warning system has a potential to reduce the probability of grade crossing collisions.

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“…Many factors contributed to driving fatigue for taxi drivers, among which prolonged driving time was likely to be the most common and important [30]. Meng et al [31] found that the reason for the engagement in prolonged driving was neither a lack of awareness concerning the serious outcomes of fatigue driving nor poor detection of fatigue. e most probable reason was optimism bias, which led these professional drivers to think that fatigue was more serious for other drivers than for themselves and that they were effective in counteracting the effect of fatigue on their driving performance.…”

Section: Introductionmentioning

confidence: 99%

A Study on the Differences in Driving Skills of Chinese Bus and Taxi Drivers

Zhang

et al. 2019

Journal of Advanced Transportation

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Professional drivers constitute an important group of drivers who shoulder the responsibility of safely transporting passengers and cargo. Bus drivers and taxi drivers are an important part of the urban public transport system, and their driving safety affects road traffic safety. Therefore, the purpose of this paper is to explore the differences between bus drivers and taxi drivers in their driving behaviors and driving skills and to predict their traffic accident involvement based on these behaviors and skills. We conducted a field survey of 274 bus drivers and 178 taxi drivers in Hefei, China. The results revealed significant differences between bus drivers and taxi drivers in terms of violations, lack of concentration and technical driving skills. Aggression and violations had significant predictive effects on bus drivers’ traffic accident involvement, and memory lapses and a lack of safety consciousness had significant predictive effects on taxi drivers’ accident involvement.

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Driving Fatigue in Professional Drivers: A Survey of Truck and Taxi Drivers

Abstract: This study provides knowledge on truck and taxi drivers' characteristics in fatigue experience, fatigue attitude, and fatigue countermeasures, and these findings have practical implications for the fatigue management and education of professional drivers.

Cited by 114 publications

References 53 publications

Effects of driver work-rest patterns, lifestyle and payment incentives on long-haul truck driver sleepiness

Effects of driver work-rest patterns, lifestyle and payment incentives on long-haul truck driver sleepiness

Exploring the Effects of Signs’ Design and In-Vehicle Audio Warning on Driver Behavior at Flashing-Light-Controlled Grade Crossings: A Driving Simulator-Based Study

A Study on the Differences in Driving Skills of Chinese Bus and Taxi Drivers

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