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Traffic Injury Prevention Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/gcpi20
Driving Fatigue in Professional Drivers: A Survey of Truck and Taxi Drivers a
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Fanxing Meng , Shuling Li , Lingzhi Cao , Musen Li , Qijia Peng , Chunhui Wang & Wei Zhang
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State Key Laboratory of Automotive Safety and Energy, Department of Industrial Engineering, Tsinghua University, Beijing, China b
School of Management Engineering, Shandong Jianzhu University, Jinan, China
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National Key Laboratory of Human Factors Engineering, China Astronaut Research and Training Center, Beijing, China Accepted author version posted online: 30 Oct 2014.Published online: 09 Feb 2015.
Click for updates To cite this article: Fanxing Meng, Shuling Li, Lingzhi Cao, Musen Li, Qijia Peng, Chunhui Wang & Wei Zhang (2015) Driving Fatigue in Professional Drivers: A Survey of Truck and Taxi Drivers, Traffic Injury Prevention, 16:5, 474-483, DOI: 10.1080/15389588.2014.973945 To link to this article: http://dx.doi.org/10.1080/15389588.2014.973945
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Traffic Injury Prevention (2015) 16, 474–483 C Taylor & Francis Group, LLC Copyright ISSN: 1538-9588 print / 1538-957X online DOI: 10.1080/15389588.2014.973945
Driving Fatigue in Professional Drivers: A Survey of Truck and Taxi Drivers FANXING MENG1, SHULING LI1, LINGZHI CAO1,2, MUSEN LI1, QIJIA PENG1, CHUNHUI WANG3, and WEI ZHANG1 1
State Key Laboratory of Automotive Safety and Energy, Department of Industrial Engineering, Tsinghua University, Beijing, China School of Management Engineering, Shandong Jianzhu University, Jinan, China 3 National Key Laboratory of Human Factors Engineering, China Astronaut Research and Training Center, Beijing, China
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Received 22 February 2014, Accepted 3 October 2014
Objectives: Fatigue among truck drivers has been studied extensively; however, less is known regarding the fatigue experience of taxi drivers in heavily populated metropolitan areas. This study aimed to compare the differences and similarities between truck and taxi driver fatigue to provide implications for the fatigue management and education of professional drivers. Methods: A sample of 274 truck drivers and 286 taxi drivers in Beijing was surveyed via a questionnaire, which included items regarding work characteristics, fatigue experience, accident information, attitude toward fatigue, and methods of counteracting fatigue. Results: Driver fatigue was prevalent among professional drivers, and it was even more serious for taxi drivers. Taxi drivers reported more frequent fatigue experiences and were involved in more accidents. Among the contributing factors to fatigue, prolonged driving time was the most important factor identified by both driver groups. Importantly, the reason for the engagement in prolonged driving was neither due to the lack of awareness concerning the serious outcome of fatigue driving nor because of their poor detection of fatigue. The most probable reason was the optimism bias, as a result of which these professional drivers thought that fatigue was more serious for other drivers than for themselves, and they thought that they were effective in counteracting the effect of fatigue on their driving performance. Moreover, truck drivers tended to employ methods that require stopping to counteract fatigue, whereas taxi drivers preferred methods that were simultaneous with driving. Although both driver groups considered taking a nap as one of the most effective means to address fatigue, this method was not commonly used. Interestingly, these drivers were aware that the methods they frequently used were not the most effective means to counteract fatigue. Conclusions: 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. Keywords: fatigue, questionnaire, driving safety, professional drivers, occupational safety, traffic injury prevention
Introduction Driving is regarded as a skillful task that requires sustained attention and quick reactions. Fatigue in driving is often identified as a major contributing factor to road traffic accidents and has become a critical issue for road safety in many countries ˚ (Kecklund and Akerstedt 1993; McCartt et al. 2000; Philip et al. 2001; Williamson et al. 1996). Fatigue is associated with decreased physiological arousal, slowed sensorimotor functions, and impaired information processing, which can degrade drivers’ response to unusual, unexpected, or emergency
Associate Editor Rob Thomson oversaw the review of this article Address correspondence to Wei Zhang, State Key Laboratory of Automotive Safety and Energy, Department of Industrial Engineering, Shunde Building South 527, Tsinghua University, Beijing 100084, China. E-mail: [email protected]
situations (Kaplan and Prato 2012; Moore and Brooks 2000; Tzamalouka et al. 2005; Williamson et al. 1996). An analysis of comprehensive accidents estimates that fatigue is involved in between 10 and 20% of serious accidents (Fletcher et al. 2005; Horne and Reyner 1995; Karrer and Roetting 2007; Maycock 1997; Sagberg 1999). However, official statistics often underestimate this effect (Karrer and Roetting 2007) because drivers involved in crashes may sometimes fail to recognize or acknowledge the effects of fatigue (Gander et al. 2006). In previous studies, the terms fatigue and sleepiness (or drowsiness) were used interchangeably and inconsistently (Merat and Jamson 2013). The American Sleep Disorders Association (2005) defined sleepiness as a state in which an individual experiences difficulty in maintaining alertness and wakefulness (cited in Phipps-Nelson et al. 2011), and it can also be described as “the urge to fall asleep” as the result of a biological need (Beirness et al. 2004). Fatigue, on the other hand, a state that is manifested during prolonged performance
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Table 1. Similarities and differences in work characteristics of truck drivers and taxi drivers Truck drivers Similarities
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Differences
Taxi drivers
Potential sleep loss Prolonged driving periods and long distances Circadian rhythm disruption High time pressure Monotonous driving journeys Constantly changing environment Low task workload High task workload Limited places to stop and rest Relatively high autonomy to rest
of a task (Findley et al. 1999), is defined as “a disinclination to continue performing the task at hand” (Brown 1994; p. 302). Although fatigue and sleepiness have different causes and are governed by different mechanisms, they are usually considered together in driving tasks because they are inextricably linked and have similar effects on the impairments of driving performance (Merat and Jamson 2013; Vanlaar et al. 2008). Thus, the National Aeronautics and Space Administration defined fatigue as a general term commonly used to refer to the experience of being “sleepy,” “tired,” or “exhausted” (cited in Dalziel and Job 1997). There are 2 important forms of driving fatigue: first, the fatigue caused by driving per se, especially during a prolonged period (Crawford 1961), which is also called “time-to-task” fatigue (Adams-Guppy and Guppy 2003); the second form is fatigue from other sources, including sleep loss, circadian rhythm disruption, and other works performed before driving (Crawford 1961), which is also called “carry-over” fatigue (Adams-Guppy and Guppy 2003). The present study focused on the “time-to-task” fatigue, which was generally defined as being sleepy, tired, bored, unable to concentrate, unable to sustain attention, and being mentally slow (see Friswell and Williamson 2013). Driving fatigue has been commonly considered to be more serious in professional drivers (Fort et al. 2013), such as truck drivers and taxi drivers. Truck and taxi drivers are vulnerable to fatigue mainly because they are both involved in potential sleep loss, prolonged driving periods and distance, and circadian rhythm disruption, combined with relatively high time pressure journeys (see Table 1; Dalziel and Job 1997; McCartt ¨ et al. 2010). Profeset al. 2000; Morrow and Crum 2004; Oz sional drivers were reportedly 49% more likely to be involved in crashes than the general public after controlling driving exposure (see Lynn and Lockwood 1998). In a survey of truck drivers, 47.1% of the survey respondents had fallen asleep behind the wheel (McCartt et al. 2000). A more recent study reported by a European crash investigation study showed that 18.6% of single truck accidents involved overfatigue/falling asleep (International Road Transport Union 2007). For taxi drivers, a survey in Australia found that 67% of taxi drivers drove at least 50 h per week, and the time off in long shifts (up to 12 hours) was often as short as 37 min (Dalziel and Job 1997). Nevertheless, the 2 driver groups also have different driving experiences. Truck drivers frequently drive on long, monotonous, high-speed highways (Larue et al. 2011; McCartt et al. 2000; Sallinen et al. 2004; Thiffault and Bergeron 2003). The journey is usually uneventful, and the driving
task demand is relatively low. In contrast, taxi drivers primarily drive in urban road environments with long driving hours and high mental workload. The driving involves a constantly changing scenario and plenty of potential hazards. These drivers have to negotiate urban traffic, prevent collisions with other road users, respond to passenger conversations, and remember the route to the destination (Dalziel and Job 1997). These tasks are tiring and have a heavier load on attention and cognitive resources. In addition, truck drivers usually have limited autonomy over their rest schedules due to the lack of appropriate places to stop on highways and tight delivery schedules (Williamson and Friswell 2013), whereas taxi drivers may have relatively high autonomy within their driving tasks to take breaks, although they are also restricted by whether there are passengers in the car. The difference in work characteristics between truck drivers and taxi drivers may determine the potential difference in their fatigue experience, fatigue attitude, and corresponding fatigue countermeasures. Various studies have been conducted to understand the nature of driving fatigue and its relationship to traffic safety among truck drivers (Arnold et al. 1997; Gander et al. 2005, 2006; Kircher and Andersson 2013); surprisingly, however, little research focuses on driving fatigue among taxi drivers (Dalziel and Job 1997; Firestone et al. 2009), not to mention making comparisons between taxi drivers and other driver groups. Taxis play an important role in metropolitan areas in China. For example, Beijing, as the capital of China and with a population of more than 20,000,000 people, has approximately 100,000 registered taxis. Due to their much higher exposure on the road than regular vehicles, taxis contribute to approximately 3.5% of on-road accidents in traffic (CRTIS 2012). However, taxi drivers’ net income heavily depends on their driving time and distance every day. They need to pay a relatively high fixed license fee to a taxi company as well as other variable costs, such as gas, maintenance, etc. Therefore, many taxi drivers usually work for a long time each day to earn more money. Currently, little is known about Chinese taxi drivers regarding their fatigue experience. The aim of this study is to help fill such information gaps and to compare the similarities and differences between truck drivers’ and taxi drivers’ fatigue, which may provide implications for the fatigue management and education of professional drivers. First, this study surveyed the work characteristics and fatigue experience of truck and taxi drivers, showing the situation of driving fatigue among Chinese professional drivers. Second, according to the theory of planned behavior (see Ajzen 1988, 1991), people’s behavior is affected by their attitude. Therefore, this study further investigated the attitude of Chinese professional drivers toward driving fatigue. Finally, the methods used by drivers to manage fatigue are important to suppress the influence of fatigue on driving safety (see Gershon et al. 2009, 2011; Nordbakke and Sagberg 2007), the present study investigated the patterns of fatigue countermeasures used by Chinese truck and taxi drivers in order to counteract fatigue and evaluated the perceived effectiveness of these methods. We hypothesized that there would be significant difference in the fatigue experience and fatigue countermeasures between truck and taxi drivers because of
476 their different work characteristics; in additon, the 2 driver groups should hold similar attitudes toward fatigue because they were both considered to be heavily exposed to driving fatigue.
Method
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Sample and Procedure Questionnaires were randomly collected from 300 truck drivers and 300 taxi drivers in Beijing. Most of the truck drivers were recruited from the 5 largest logistic areas in Beijing, where these drivers transport cargo between Beijing and other provinces. The taxi drivers were recruited at the Beijing airport, where many taxi drivers wait for passengers and drive them to the city center. All of the drivers participated in the study by their own agreement, and they were assured of anonymity and confidentiality. Refusals were quite rare in each group and the response rate was more than 95% in both groups. All of the questionnaires were completed by face-toface interviews; the interviewer’s role was limited to the supply of clarification if needed. Before the administration of the questionnaire, each driver received detailed information about the purpose of the study and an explanation of how to fill out the questionnaire as well as the potential benefits from the project’s findings and the right to deny participation or withdraw at any time. The questionnaire required approximately 20 min to complete. Each participant who completed the questionnaire was given a gift for their participation. The experiment was conducted in accordance with the ethical guidelines laid down by the Department of Industrial Engineering, Tsinghua University. Questionnaires A detailed questionnaire was developed for truck and taxi drivers separately by consulting with truck drivers, taxi drivers, and experts in the area of driving safety. Most questions in these 2 questionnaires were identical, except for some jobspecific questions. The questionnaires can be divided into 5 sections as follows: 1. Drivers’ demographic and background characteristics, including information about gender, age, height, weight, education level, and residence area as well as information concerning driving experience (such as years of professional driving experience, annual driving distance, and employment types). The employment type of truck drivers could be classified as owners or employees. Three employment types were commonly used in Chinese taxi companies, including short shifts (2 taxi drivers shared a car, and each one had 12 h of working time available each day), long shifts (2 taxi drivers shared a car, and each used the car every other day), and whole shifts (one taxi driver operated a car, and the driver could schedule the work time freely). 2. Drivers’ work characteristics in the most recent month, including the typical number of working days per week,
Meng et al. typical driving hours per week, typical driving distance per week, and the typical sleeping hours in a day. 3. Drivers’ fatigue experience, measured by the fatigue onset time while driving, consecutive driving hours before taking a break (as well as the average break duration), fatigue frequency among themselves and their peers (both using a 5-point Likert scale, with 1 representing never and 5 representing always). The participants were also required to report any accident details in the previous 12 months (including accident times, whether fatigue was the cause, and their driving hours before the accident). 4. Drivers’ attitudes toward fatigue, measured by 3 items, including their views about the effect of fatigue on driving performance (with a 5-point Likert scale, with 1 representing no adverse effect at all and 5 representing extremely adverse effect), how fatigue affects their driving performance, and possible reasons causing them to experience fatigue while driving. 5. Drivers’ methods to manage fatigue. Seventeen types of commonly used methods to counteract driving fatigue were listed, and these methods were collected from other related studies (see Gershon et al. 2011) and from consulting with experienced drivers. The drivers graded the usage frequency and perceived effectiveness of each method on a 5-point Likert scale. For usage frequency, 1 represented never and 5 represented always; for perceived effectiveness, 1 represented not effective at all and 5 represented very effective. Statistical Analyses The descriptive statistic analysis was first performed to investigate the similarities and differences between the fatigue among truck and taxi drivers. Additionally, a logistic regression analysis was performed in order to assess the relationship between drivers’ fatigue experience and other variables, including demographic information, working characteristic, and attitudes toward fatigued driving. An independent-sample t test was used for the comparison of continuous variables and the score data of the Likert scales. Chi-square tests were used for group comparison on categorical measures. A two-side P value of less than .05 was considered to indicate statistical significance.
Results Demographic Information In total, 274 and 286 valid questionnaires were collected from truck and taxi drivers, respectively. Table 2 provides the demographic information for truck and taxi driver groups. Among the participants, most of the drivers were male (truck drivers, 97.1%; taxi drivers, 98.7%). The ages of the truck drivers ranged from 18 to 65 years (M = 36.4, SD = 7.7), and the age range of taxi drivers was from 24 to 60 years (M = 43.8, SD = 7.4). The taxi drivers were significantly older than the truck drivers (P < .001). The 2 groups had similar body mass indexes (truck driver, M = 25.1, SD = 3.2; taxi driver, M = 26.0, SD = 3.9; P = .32). They had been driving a truck or
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Table 2. Demographic information on the surveyed truck drivers (n = 274) and taxi drivers (n = 286)
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Truck driver Gender Male 266 (97.1%) Female 8 (2.9%) Age 18–29 54 (19.7%) 30–39 124 (45.3%) 40–49 77 (28.1%) ≥50 19 (6.9%) Body mass index (kg/m2) M = 25.1 (SD = 3.2)a Time as a professional driver Less than 5 years 62 (22.6%) 5 to 9 years 88 (32.1%) 10 to 14 years 67 (24.5%) 15 to 19 years 29 (10.6%) 20 years or more 28 (10.2%) Annual driving distance (kilometers) less than 50,000 27 (9.9%) 50,000 to 74,999 30 (10.9%) 75,000 to 99,999 21 (7.7%) 100,000 to 124,999 89 (32.5%) 125,000 or more 107 (39.1%) Education level Primary school 24 (8.8%) Junior school or equivalentb 164 (59.9%) Senior school or equivalentc 81 (29.6%) University or higher 5 (1.8%) Employment type Owner-operator: 42 (15.3%) Employee-operator: 232 (84.7%)
Residence area
From 18 provinces
Taxi driver 282 (98.6%) 4 (1.4%) 11 (3.8%) 61 (21.3%) 143 (50.0%) 71(24.8%) M = 26.0 (SD = 3.9) 60 (21.0%) 89 (31.1%) 75 (26.2%) 29 (10.1%) 33 (11.5%) 21 (7.3%) 84 (29.4%) 65 (22.7%) 73 (25.5%) 43 (15.0%) 5 (1.7%) 119 (41.6%) 146 (51.0%) 16 (5.6%) Short shift: 18 (6.3%) Long shift: 83 (29.0%) Whole shift: 185 (64.6%) Beijing
= mean, SD = standard deviation. includes secondary specialized school. cAlso includes junior college and secondary vocational school. aM
bAlso
a taxi for 9.2 (SD = 6.2) and 9.9 (SD = 6.2) years, respectively, with no significant difference (P = .15). A majority of the truck drivers (90.0%) and the taxi drivers (92.7%) drove more than 50,000 km per year. With regard to education, most truck drivers and taxi drivers had junior or senior middle school certificates. Most of the truck drivers were employeeoperators (84.6%). For the taxi drivers, short-shift, long-shift, and whole-shift drivers accounted for 6.3, 29.0, and 64.6% of respondents, respectively. The truck drivers resided in 18 out of 30 Chinese mainland provinces, autonomous regions, and municipalities, and all of the taxi drivers resided in Beijing. Because almost all of the participants in truck and taxi driver groups were male, data for the female participants were excluded in the following analyses. Work Characteristics The 2 driver groups had a similar number of working days per week (truck drivers, M = 5.4, SD = 1.8; taxi drivers, M = 5.6, SD = 1.3; p = .398). Approximately one third (33.5%) of truck drivers and one quarter (24.2%) of taxi drivers worked 7 days per week. On average, taxi drivers drove significantly more hours per week than truck drivers (truck drivers,
M = 50.2, SD = 25.5; taxi drivers, M = 67.7, SD = 19.7; P < .001). Approximately one third (32.4%) of truck drivers and approximately two thirds (68.5%) of taxi drivers worked for 60 or more hours per week. Truck drivers drove a significantly longer distance per week on average (M = 3,078.7 km, SD = 2,032.6 km) than taxi drivers (M = 1,536.7 km, SD = 504.7 km; P < .001), which was likely because truck drivers usually drove at a higher speed on highways than taxi drivers, who usually drove in cities. On average, truck drivers and taxi drivers had similar sleeping hours per day (truck drivers, M = 7.4, SD = 1.6; taxi drivers, M = 7.3, SD = 1.6; P = .314). Fatigue Experience The truck drivers reported that fatigue occurred after 4.7 h (SD = 2.5) of consecutive driving, whereas for taxi drivers, the average of onset of fatigue time was 5.5 h (SD = 2.7). The typical time to fatigue onset was significantly shorter among truck drivers than among taxi drivers (P < .001). On average, truck drivers reported that they would drive for 4.3 h (SD = 2.1) before taking a 41.3 min (SD = 44.5) rest, and taxi drivers would take a 27 min (SD = 19.0) break after driving for 3.8 consecutive hours (SD = 2.0). More than one fifth of truck drivers (22.0%) and taxi drivers (23.7%) would continuously drive for 6 h or more before taking a break. Truck and taxi drivers were required to evaluate the frequency of their own fatigue and that of their peers separately. On average, taxi drivers experienced greater fatigue in daily driving (M = 3.66, SD = 0.98) than truck drivers (M = 3.26, SD = 1.05; P < .001). Approximately 38% of truck drivers reported that they “often” or “always” experienced fatigue while driving, which was significantly lower than that of taxi drivers (59.5%, χ 2 = 25.8, P < .001). When required to evaluate other drivers’ fatigue frequency in their peers, truck drivers and taxi drivers rated an average score of 3.88 (SD = 0.87) and 4.47 (SD = 0.71), respectively. Both groups rated a significantly higher score for the fatigue frequency of their peers than their own (both P < .001). Specifically, 51.7% of the truck drivers and 60.5% of the taxi drivers thought that driving fatigue occurred more frequently for their peers than for themselves.
Accidents Detail Both groups were required to report the details of their accidents over the previous 12 months. Twenty-five truck drivers (9.4%) reported that they were involved in at least one accident, of which 19 truck drivers (7.1%) were involved in one accident and 6 truck drivers (2.3%) were involved in 2 accidents. The 25 truck drivers identified fatigue as a main contributory cause in 5 out of the 31 accidents (16.1%). In the 5 fatiguerelated accidents, the drivers reported that they had driven for an average of 8.2 h (SD = 2.9) before the accident occurred, whereas in the other 26 accidents, the drivers reported that they had driven for an average of 2.3 h (SD = 1.5) before the accident occurred, which was significantly shorter than that in fatigue-related accidents (P < .001). Fifty-four taxi drivers (19.1%; short shift: 1, long shift: 21, whole shift: 32) reported that they were involved in at least
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478 one accident, and the percentage of accident occurrence was significantly higher than that in truck drivers (χ 2 = 8.85, P = .003). Thirty-five taxi drivers (12.4%) reported that they were involved in one accident, and 19 taxi drivers (6.7%) reported that they were involved in 2 accidents. Among the 73 accidents, fatigue was reported as a main contributory cause in 22 accidents (30.1%) by taxi drivers. In the 22 fatigue-related accidents, it was reported that the driver had driven for an average of 9.3 h (SD = 4.4) before the accident occurred, whereas in the other 51 accidents, it was reported that the driver had driven for an average of 4.7 h (SD = 2.8) before the accident occurred, which was significantly lower than that in fatigue-related accidents (P < .001). Among the 73 accidents, taxi drivers on short shifts, long shifts, and whole shifts reported 1 (1.4%), 30 (41.1%), and 42 (57.5%) accidents, respectively. When considering the proportion that the 3 types of taxi drivers accounted for in the survey sample (6.3, 29.0, 64.6%, respectively), long-shift taxi drivers were involved in more accidents (accounting for 29.0% in the survey sample but 41.1% in the sample involved in accidents), although the chi-square test comparing the data of long-shift taxi drivers with the combined data of short-shift and whole-shift drivers only showed a marginal significance, χ 2(1) = 3.15, P = .076. Attitude Toward Fatigue Both driver groups were asked to rate the effect of fatigue on their driving performance. Truck and taxi drivers held a similar view that fatigue had a serious adverse effect on their driving performance, and there was no significant difference between the scores rated by the 2 groups (truck drivers, M = 4.40, SD = 0.75; taxi drivers, M = 4.46, SD = 0.77; P = .531). In particular, 54.8% of the truck drivers and 57.5% of the taxi drivers thought fatigue had an “extremely adverse effect.” When asked how fatigue affected their driving performance, both truck and taxi drivers identified slow reactions (72.8 and 82.1%, respectively) and poor awareness of traffic (53.9 and 68.9%, respectively) as the most common impairments as a result of fatigue (see Figure 1). In addition, 45.3% truck drivers reported that fatigue led to poor lateral control, and more than half (52.4%) of the taxi drivers thought that fatigue made them drive slowly, which was also reported by a large proportion of truck drivers (44.4%). Some factors were also identified as the contributors to drivers’ fatigue by the 2 driver groups (see Figure 2). Prolonged driving time was cited as the most important contributor to fatigue by both truck and taxi drivers (44.7 and 79.8%, respectively). In addition, more than one third (34.1%) of truck drivers reported short sleep time as a main contributing factor, and more than half (57.8%) of the taxi drivers thought that heavy traffic made them experience fatigue.
Meng et al.
Fig. 1. Effects of driving fatigue on driving performance.
the commonly used countermeasures for the 2 driver groups differed from each other (see Table 3). The 3 most frequently used countermeasures reported by truck drivers were stopping the vehicle and exercising (M = 3.34, SD = 1.10), opening the windows (M = 3.32, SD = 1.03), and washing their face (M = 3.21, SD = 1.03). For taxi drivers, opening the windows was also one of the most frequently used methods (M = 3.75, SD = 1.07) and the other 2 methods were different from those used by truck drivers, including listening to the radio (M = 3.43, SD = 1.34) and drinking water (M = 3.35, SD = 1.39). Other countermeasures, such as eating snacks, drinking coffee or energy drinks, and singing a song were used more frequently by truck drivers than by taxi drivers. Taxi drivers used talking with a passenger more frequently than truck drivers, probably because taxi drivers carried passengers more often than truck drivers. In terms of the perceived effectiveness, truck drivers reported that taking a short nap (M = 3.53, SD = 1.19), stopping the vehicle and exercising (M = 3.38, SD = 1.04), and washing their face (M = 3.21, SD = 0.96) were the most effective countermeasures. Taxi drivers perceived stopping the vehicle and exercising (M = 3.75, SD = 1.39), opening the window (M = 3.72, SD = 1.33), and taking a short nap (M = 3.61, SD = 1.57) to be the most effective methods. Although stopping to take a nap was not included in the list of the 3 most commonly
Countermeasures to Fatigue A list of 17 predefined countermeasures to cope with driving fatigue was presented to the 2 groups, and the respondents were required to rate the usage frequency and perceived effectiveness of each countermeasure. The results showed that
Fig. 2. Reasons that induce driving fatigue.
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Table 3. Usage frequency (1 = never, 5 = always) and perceived effectiveness (1 = not helpful at all, 5 = very helpful) of different fatigue countermeasures
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Usage frequency
Perceived effectiveness
Countermeasures
Truck
Taxi
P value
Truck
Taxi
P value
Taking a short nap Stopping the vehicle and exercising Eating some snacks Drinking coffee or energy drink Drinking water Smoking Opening the car windows Listening to the radio Listening to music Talking on the cellular phone Talking with a passenger Washing face Changing the seat position Watching the view Thinking personal thoughts Singing a song Shaking head
3.15 3.34 3.09∗ 2.64∗ 3.00 3.03∗ 3.32 2.92 2.33∗ 2.26∗ 2.51 3.21∗ 2.46∗ 2.29 2.05∗ 2.52∗ 2.65
3.03 3.34 1.98 1.99 3.35∗ 2.70 3.75∗ 3.43∗ 1.70 1.91 2.87∗ 2.44 2.06 2.51 1.72 1.92 2.75
.397 .834
Traffic Injury Prevention Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/gcpi20
Driving Fatigue in Professional Drivers: A Survey of Truck and Taxi Drivers a
a
ab
a
a
c
Fanxing Meng , Shuling Li , Lingzhi Cao , Musen Li , Qijia Peng , Chunhui Wang & Wei Zhang
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a
State Key Laboratory of Automotive Safety and Energy, Department of Industrial Engineering, Tsinghua University, Beijing, China b
School of Management Engineering, Shandong Jianzhu University, Jinan, China
c
National Key Laboratory of Human Factors Engineering, China Astronaut Research and Training Center, Beijing, China Accepted author version posted online: 30 Oct 2014.Published online: 09 Feb 2015.
Click for updates To cite this article: Fanxing Meng, Shuling Li, Lingzhi Cao, Musen Li, Qijia Peng, Chunhui Wang & Wei Zhang (2015) Driving Fatigue in Professional Drivers: A Survey of Truck and Taxi Drivers, Traffic Injury Prevention, 16:5, 474-483, DOI: 10.1080/15389588.2014.973945 To link to this article: http://dx.doi.org/10.1080/15389588.2014.973945
PLEASE SCROLL DOWN FOR ARTICLE Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content. This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. Terms & Conditions of access and use can be found at http:// www.tandfonline.com/page/terms-and-conditions
Traffic Injury Prevention (2015) 16, 474–483 C Taylor & Francis Group, LLC Copyright ISSN: 1538-9588 print / 1538-957X online DOI: 10.1080/15389588.2014.973945
Driving Fatigue in Professional Drivers: A Survey of Truck and Taxi Drivers FANXING MENG1, SHULING LI1, LINGZHI CAO1,2, MUSEN LI1, QIJIA PENG1, CHUNHUI WANG3, and WEI ZHANG1 1
State Key Laboratory of Automotive Safety and Energy, Department of Industrial Engineering, Tsinghua University, Beijing, China School of Management Engineering, Shandong Jianzhu University, Jinan, China 3 National Key Laboratory of Human Factors Engineering, China Astronaut Research and Training Center, Beijing, China
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Received 22 February 2014, Accepted 3 October 2014
Objectives: Fatigue among truck drivers has been studied extensively; however, less is known regarding the fatigue experience of taxi drivers in heavily populated metropolitan areas. This study aimed to compare the differences and similarities between truck and taxi driver fatigue to provide implications for the fatigue management and education of professional drivers. Methods: A sample of 274 truck drivers and 286 taxi drivers in Beijing was surveyed via a questionnaire, which included items regarding work characteristics, fatigue experience, accident information, attitude toward fatigue, and methods of counteracting fatigue. Results: Driver fatigue was prevalent among professional drivers, and it was even more serious for taxi drivers. Taxi drivers reported more frequent fatigue experiences and were involved in more accidents. Among the contributing factors to fatigue, prolonged driving time was the most important factor identified by both driver groups. Importantly, the reason for the engagement in prolonged driving was neither due to the lack of awareness concerning the serious outcome of fatigue driving nor because of their poor detection of fatigue. The most probable reason was the optimism bias, as a result of which these professional drivers thought that fatigue was more serious for other drivers than for themselves, and they thought that they were effective in counteracting the effect of fatigue on their driving performance. Moreover, truck drivers tended to employ methods that require stopping to counteract fatigue, whereas taxi drivers preferred methods that were simultaneous with driving. Although both driver groups considered taking a nap as one of the most effective means to address fatigue, this method was not commonly used. Interestingly, these drivers were aware that the methods they frequently used were not the most effective means to counteract fatigue. Conclusions: 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. Keywords: fatigue, questionnaire, driving safety, professional drivers, occupational safety, traffic injury prevention
Introduction Driving is regarded as a skillful task that requires sustained attention and quick reactions. Fatigue in driving is often identified as a major contributing factor to road traffic accidents and has become a critical issue for road safety in many countries ˚ (Kecklund and Akerstedt 1993; McCartt et al. 2000; Philip et al. 2001; Williamson et al. 1996). Fatigue is associated with decreased physiological arousal, slowed sensorimotor functions, and impaired information processing, which can degrade drivers’ response to unusual, unexpected, or emergency
Associate Editor Rob Thomson oversaw the review of this article Address correspondence to Wei Zhang, State Key Laboratory of Automotive Safety and Energy, Department of Industrial Engineering, Shunde Building South 527, Tsinghua University, Beijing 100084, China. E-mail: [email protected]
situations (Kaplan and Prato 2012; Moore and Brooks 2000; Tzamalouka et al. 2005; Williamson et al. 1996). An analysis of comprehensive accidents estimates that fatigue is involved in between 10 and 20% of serious accidents (Fletcher et al. 2005; Horne and Reyner 1995; Karrer and Roetting 2007; Maycock 1997; Sagberg 1999). However, official statistics often underestimate this effect (Karrer and Roetting 2007) because drivers involved in crashes may sometimes fail to recognize or acknowledge the effects of fatigue (Gander et al. 2006). In previous studies, the terms fatigue and sleepiness (or drowsiness) were used interchangeably and inconsistently (Merat and Jamson 2013). The American Sleep Disorders Association (2005) defined sleepiness as a state in which an individual experiences difficulty in maintaining alertness and wakefulness (cited in Phipps-Nelson et al. 2011), and it can also be described as “the urge to fall asleep” as the result of a biological need (Beirness et al. 2004). Fatigue, on the other hand, a state that is manifested during prolonged performance
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Table 1. Similarities and differences in work characteristics of truck drivers and taxi drivers Truck drivers Similarities
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Differences
Taxi drivers
Potential sleep loss Prolonged driving periods and long distances Circadian rhythm disruption High time pressure Monotonous driving journeys Constantly changing environment Low task workload High task workload Limited places to stop and rest Relatively high autonomy to rest
of a task (Findley et al. 1999), is defined as “a disinclination to continue performing the task at hand” (Brown 1994; p. 302). Although fatigue and sleepiness have different causes and are governed by different mechanisms, they are usually considered together in driving tasks because they are inextricably linked and have similar effects on the impairments of driving performance (Merat and Jamson 2013; Vanlaar et al. 2008). Thus, the National Aeronautics and Space Administration defined fatigue as a general term commonly used to refer to the experience of being “sleepy,” “tired,” or “exhausted” (cited in Dalziel and Job 1997). There are 2 important forms of driving fatigue: first, the fatigue caused by driving per se, especially during a prolonged period (Crawford 1961), which is also called “time-to-task” fatigue (Adams-Guppy and Guppy 2003); the second form is fatigue from other sources, including sleep loss, circadian rhythm disruption, and other works performed before driving (Crawford 1961), which is also called “carry-over” fatigue (Adams-Guppy and Guppy 2003). The present study focused on the “time-to-task” fatigue, which was generally defined as being sleepy, tired, bored, unable to concentrate, unable to sustain attention, and being mentally slow (see Friswell and Williamson 2013). Driving fatigue has been commonly considered to be more serious in professional drivers (Fort et al. 2013), such as truck drivers and taxi drivers. Truck and taxi drivers are vulnerable to fatigue mainly because they are both involved in potential sleep loss, prolonged driving periods and distance, and circadian rhythm disruption, combined with relatively high time pressure journeys (see Table 1; Dalziel and Job 1997; McCartt ¨ et al. 2010). Profeset al. 2000; Morrow and Crum 2004; Oz sional drivers were reportedly 49% more likely to be involved in crashes than the general public after controlling driving exposure (see Lynn and Lockwood 1998). In a survey of truck drivers, 47.1% of the survey respondents had fallen asleep behind the wheel (McCartt et al. 2000). A more recent study reported by a European crash investigation study showed that 18.6% of single truck accidents involved overfatigue/falling asleep (International Road Transport Union 2007). For taxi drivers, a survey in Australia found that 67% of taxi drivers drove at least 50 h per week, and the time off in long shifts (up to 12 hours) was often as short as 37 min (Dalziel and Job 1997). Nevertheless, the 2 driver groups also have different driving experiences. Truck drivers frequently drive on long, monotonous, high-speed highways (Larue et al. 2011; McCartt et al. 2000; Sallinen et al. 2004; Thiffault and Bergeron 2003). The journey is usually uneventful, and the driving
task demand is relatively low. In contrast, taxi drivers primarily drive in urban road environments with long driving hours and high mental workload. The driving involves a constantly changing scenario and plenty of potential hazards. These drivers have to negotiate urban traffic, prevent collisions with other road users, respond to passenger conversations, and remember the route to the destination (Dalziel and Job 1997). These tasks are tiring and have a heavier load on attention and cognitive resources. In addition, truck drivers usually have limited autonomy over their rest schedules due to the lack of appropriate places to stop on highways and tight delivery schedules (Williamson and Friswell 2013), whereas taxi drivers may have relatively high autonomy within their driving tasks to take breaks, although they are also restricted by whether there are passengers in the car. The difference in work characteristics between truck drivers and taxi drivers may determine the potential difference in their fatigue experience, fatigue attitude, and corresponding fatigue countermeasures. Various studies have been conducted to understand the nature of driving fatigue and its relationship to traffic safety among truck drivers (Arnold et al. 1997; Gander et al. 2005, 2006; Kircher and Andersson 2013); surprisingly, however, little research focuses on driving fatigue among taxi drivers (Dalziel and Job 1997; Firestone et al. 2009), not to mention making comparisons between taxi drivers and other driver groups. Taxis play an important role in metropolitan areas in China. For example, Beijing, as the capital of China and with a population of more than 20,000,000 people, has approximately 100,000 registered taxis. Due to their much higher exposure on the road than regular vehicles, taxis contribute to approximately 3.5% of on-road accidents in traffic (CRTIS 2012). However, taxi drivers’ net income heavily depends on their driving time and distance every day. They need to pay a relatively high fixed license fee to a taxi company as well as other variable costs, such as gas, maintenance, etc. Therefore, many taxi drivers usually work for a long time each day to earn more money. Currently, little is known about Chinese taxi drivers regarding their fatigue experience. The aim of this study is to help fill such information gaps and to compare the similarities and differences between truck drivers’ and taxi drivers’ fatigue, which may provide implications for the fatigue management and education of professional drivers. First, this study surveyed the work characteristics and fatigue experience of truck and taxi drivers, showing the situation of driving fatigue among Chinese professional drivers. Second, according to the theory of planned behavior (see Ajzen 1988, 1991), people’s behavior is affected by their attitude. Therefore, this study further investigated the attitude of Chinese professional drivers toward driving fatigue. Finally, the methods used by drivers to manage fatigue are important to suppress the influence of fatigue on driving safety (see Gershon et al. 2009, 2011; Nordbakke and Sagberg 2007), the present study investigated the patterns of fatigue countermeasures used by Chinese truck and taxi drivers in order to counteract fatigue and evaluated the perceived effectiveness of these methods. We hypothesized that there would be significant difference in the fatigue experience and fatigue countermeasures between truck and taxi drivers because of
476 their different work characteristics; in additon, the 2 driver groups should hold similar attitudes toward fatigue because they were both considered to be heavily exposed to driving fatigue.
Method
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Sample and Procedure Questionnaires were randomly collected from 300 truck drivers and 300 taxi drivers in Beijing. Most of the truck drivers were recruited from the 5 largest logistic areas in Beijing, where these drivers transport cargo between Beijing and other provinces. The taxi drivers were recruited at the Beijing airport, where many taxi drivers wait for passengers and drive them to the city center. All of the drivers participated in the study by their own agreement, and they were assured of anonymity and confidentiality. Refusals were quite rare in each group and the response rate was more than 95% in both groups. All of the questionnaires were completed by face-toface interviews; the interviewer’s role was limited to the supply of clarification if needed. Before the administration of the questionnaire, each driver received detailed information about the purpose of the study and an explanation of how to fill out the questionnaire as well as the potential benefits from the project’s findings and the right to deny participation or withdraw at any time. The questionnaire required approximately 20 min to complete. Each participant who completed the questionnaire was given a gift for their participation. The experiment was conducted in accordance with the ethical guidelines laid down by the Department of Industrial Engineering, Tsinghua University. Questionnaires A detailed questionnaire was developed for truck and taxi drivers separately by consulting with truck drivers, taxi drivers, and experts in the area of driving safety. Most questions in these 2 questionnaires were identical, except for some jobspecific questions. The questionnaires can be divided into 5 sections as follows: 1. Drivers’ demographic and background characteristics, including information about gender, age, height, weight, education level, and residence area as well as information concerning driving experience (such as years of professional driving experience, annual driving distance, and employment types). The employment type of truck drivers could be classified as owners or employees. Three employment types were commonly used in Chinese taxi companies, including short shifts (2 taxi drivers shared a car, and each one had 12 h of working time available each day), long shifts (2 taxi drivers shared a car, and each used the car every other day), and whole shifts (one taxi driver operated a car, and the driver could schedule the work time freely). 2. Drivers’ work characteristics in the most recent month, including the typical number of working days per week,
Meng et al. typical driving hours per week, typical driving distance per week, and the typical sleeping hours in a day. 3. Drivers’ fatigue experience, measured by the fatigue onset time while driving, consecutive driving hours before taking a break (as well as the average break duration), fatigue frequency among themselves and their peers (both using a 5-point Likert scale, with 1 representing never and 5 representing always). The participants were also required to report any accident details in the previous 12 months (including accident times, whether fatigue was the cause, and their driving hours before the accident). 4. Drivers’ attitudes toward fatigue, measured by 3 items, including their views about the effect of fatigue on driving performance (with a 5-point Likert scale, with 1 representing no adverse effect at all and 5 representing extremely adverse effect), how fatigue affects their driving performance, and possible reasons causing them to experience fatigue while driving. 5. Drivers’ methods to manage fatigue. Seventeen types of commonly used methods to counteract driving fatigue were listed, and these methods were collected from other related studies (see Gershon et al. 2011) and from consulting with experienced drivers. The drivers graded the usage frequency and perceived effectiveness of each method on a 5-point Likert scale. For usage frequency, 1 represented never and 5 represented always; for perceived effectiveness, 1 represented not effective at all and 5 represented very effective. Statistical Analyses The descriptive statistic analysis was first performed to investigate the similarities and differences between the fatigue among truck and taxi drivers. Additionally, a logistic regression analysis was performed in order to assess the relationship between drivers’ fatigue experience and other variables, including demographic information, working characteristic, and attitudes toward fatigued driving. An independent-sample t test was used for the comparison of continuous variables and the score data of the Likert scales. Chi-square tests were used for group comparison on categorical measures. A two-side P value of less than .05 was considered to indicate statistical significance.
Results Demographic Information In total, 274 and 286 valid questionnaires were collected from truck and taxi drivers, respectively. Table 2 provides the demographic information for truck and taxi driver groups. Among the participants, most of the drivers were male (truck drivers, 97.1%; taxi drivers, 98.7%). The ages of the truck drivers ranged from 18 to 65 years (M = 36.4, SD = 7.7), and the age range of taxi drivers was from 24 to 60 years (M = 43.8, SD = 7.4). The taxi drivers were significantly older than the truck drivers (P < .001). The 2 groups had similar body mass indexes (truck driver, M = 25.1, SD = 3.2; taxi driver, M = 26.0, SD = 3.9; P = .32). They had been driving a truck or
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Table 2. Demographic information on the surveyed truck drivers (n = 274) and taxi drivers (n = 286)
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Truck driver Gender Male 266 (97.1%) Female 8 (2.9%) Age 18–29 54 (19.7%) 30–39 124 (45.3%) 40–49 77 (28.1%) ≥50 19 (6.9%) Body mass index (kg/m2) M = 25.1 (SD = 3.2)a Time as a professional driver Less than 5 years 62 (22.6%) 5 to 9 years 88 (32.1%) 10 to 14 years 67 (24.5%) 15 to 19 years 29 (10.6%) 20 years or more 28 (10.2%) Annual driving distance (kilometers) less than 50,000 27 (9.9%) 50,000 to 74,999 30 (10.9%) 75,000 to 99,999 21 (7.7%) 100,000 to 124,999 89 (32.5%) 125,000 or more 107 (39.1%) Education level Primary school 24 (8.8%) Junior school or equivalentb 164 (59.9%) Senior school or equivalentc 81 (29.6%) University or higher 5 (1.8%) Employment type Owner-operator: 42 (15.3%) Employee-operator: 232 (84.7%)
Residence area
From 18 provinces
Taxi driver 282 (98.6%) 4 (1.4%) 11 (3.8%) 61 (21.3%) 143 (50.0%) 71(24.8%) M = 26.0 (SD = 3.9) 60 (21.0%) 89 (31.1%) 75 (26.2%) 29 (10.1%) 33 (11.5%) 21 (7.3%) 84 (29.4%) 65 (22.7%) 73 (25.5%) 43 (15.0%) 5 (1.7%) 119 (41.6%) 146 (51.0%) 16 (5.6%) Short shift: 18 (6.3%) Long shift: 83 (29.0%) Whole shift: 185 (64.6%) Beijing
= mean, SD = standard deviation. includes secondary specialized school. cAlso includes junior college and secondary vocational school. aM
bAlso
a taxi for 9.2 (SD = 6.2) and 9.9 (SD = 6.2) years, respectively, with no significant difference (P = .15). A majority of the truck drivers (90.0%) and the taxi drivers (92.7%) drove more than 50,000 km per year. With regard to education, most truck drivers and taxi drivers had junior or senior middle school certificates. Most of the truck drivers were employeeoperators (84.6%). For the taxi drivers, short-shift, long-shift, and whole-shift drivers accounted for 6.3, 29.0, and 64.6% of respondents, respectively. The truck drivers resided in 18 out of 30 Chinese mainland provinces, autonomous regions, and municipalities, and all of the taxi drivers resided in Beijing. Because almost all of the participants in truck and taxi driver groups were male, data for the female participants were excluded in the following analyses. Work Characteristics The 2 driver groups had a similar number of working days per week (truck drivers, M = 5.4, SD = 1.8; taxi drivers, M = 5.6, SD = 1.3; p = .398). Approximately one third (33.5%) of truck drivers and one quarter (24.2%) of taxi drivers worked 7 days per week. On average, taxi drivers drove significantly more hours per week than truck drivers (truck drivers,
M = 50.2, SD = 25.5; taxi drivers, M = 67.7, SD = 19.7; P < .001). Approximately one third (32.4%) of truck drivers and approximately two thirds (68.5%) of taxi drivers worked for 60 or more hours per week. Truck drivers drove a significantly longer distance per week on average (M = 3,078.7 km, SD = 2,032.6 km) than taxi drivers (M = 1,536.7 km, SD = 504.7 km; P < .001), which was likely because truck drivers usually drove at a higher speed on highways than taxi drivers, who usually drove in cities. On average, truck drivers and taxi drivers had similar sleeping hours per day (truck drivers, M = 7.4, SD = 1.6; taxi drivers, M = 7.3, SD = 1.6; P = .314). Fatigue Experience The truck drivers reported that fatigue occurred after 4.7 h (SD = 2.5) of consecutive driving, whereas for taxi drivers, the average of onset of fatigue time was 5.5 h (SD = 2.7). The typical time to fatigue onset was significantly shorter among truck drivers than among taxi drivers (P < .001). On average, truck drivers reported that they would drive for 4.3 h (SD = 2.1) before taking a 41.3 min (SD = 44.5) rest, and taxi drivers would take a 27 min (SD = 19.0) break after driving for 3.8 consecutive hours (SD = 2.0). More than one fifth of truck drivers (22.0%) and taxi drivers (23.7%) would continuously drive for 6 h or more before taking a break. Truck and taxi drivers were required to evaluate the frequency of their own fatigue and that of their peers separately. On average, taxi drivers experienced greater fatigue in daily driving (M = 3.66, SD = 0.98) than truck drivers (M = 3.26, SD = 1.05; P < .001). Approximately 38% of truck drivers reported that they “often” or “always” experienced fatigue while driving, which was significantly lower than that of taxi drivers (59.5%, χ 2 = 25.8, P < .001). When required to evaluate other drivers’ fatigue frequency in their peers, truck drivers and taxi drivers rated an average score of 3.88 (SD = 0.87) and 4.47 (SD = 0.71), respectively. Both groups rated a significantly higher score for the fatigue frequency of their peers than their own (both P < .001). Specifically, 51.7% of the truck drivers and 60.5% of the taxi drivers thought that driving fatigue occurred more frequently for their peers than for themselves.
Accidents Detail Both groups were required to report the details of their accidents over the previous 12 months. Twenty-five truck drivers (9.4%) reported that they were involved in at least one accident, of which 19 truck drivers (7.1%) were involved in one accident and 6 truck drivers (2.3%) were involved in 2 accidents. The 25 truck drivers identified fatigue as a main contributory cause in 5 out of the 31 accidents (16.1%). In the 5 fatiguerelated accidents, the drivers reported that they had driven for an average of 8.2 h (SD = 2.9) before the accident occurred, whereas in the other 26 accidents, the drivers reported that they had driven for an average of 2.3 h (SD = 1.5) before the accident occurred, which was significantly shorter than that in fatigue-related accidents (P < .001). Fifty-four taxi drivers (19.1%; short shift: 1, long shift: 21, whole shift: 32) reported that they were involved in at least
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478 one accident, and the percentage of accident occurrence was significantly higher than that in truck drivers (χ 2 = 8.85, P = .003). Thirty-five taxi drivers (12.4%) reported that they were involved in one accident, and 19 taxi drivers (6.7%) reported that they were involved in 2 accidents. Among the 73 accidents, fatigue was reported as a main contributory cause in 22 accidents (30.1%) by taxi drivers. In the 22 fatigue-related accidents, it was reported that the driver had driven for an average of 9.3 h (SD = 4.4) before the accident occurred, whereas in the other 51 accidents, it was reported that the driver had driven for an average of 4.7 h (SD = 2.8) before the accident occurred, which was significantly lower than that in fatigue-related accidents (P < .001). Among the 73 accidents, taxi drivers on short shifts, long shifts, and whole shifts reported 1 (1.4%), 30 (41.1%), and 42 (57.5%) accidents, respectively. When considering the proportion that the 3 types of taxi drivers accounted for in the survey sample (6.3, 29.0, 64.6%, respectively), long-shift taxi drivers were involved in more accidents (accounting for 29.0% in the survey sample but 41.1% in the sample involved in accidents), although the chi-square test comparing the data of long-shift taxi drivers with the combined data of short-shift and whole-shift drivers only showed a marginal significance, χ 2(1) = 3.15, P = .076. Attitude Toward Fatigue Both driver groups were asked to rate the effect of fatigue on their driving performance. Truck and taxi drivers held a similar view that fatigue had a serious adverse effect on their driving performance, and there was no significant difference between the scores rated by the 2 groups (truck drivers, M = 4.40, SD = 0.75; taxi drivers, M = 4.46, SD = 0.77; P = .531). In particular, 54.8% of the truck drivers and 57.5% of the taxi drivers thought fatigue had an “extremely adverse effect.” When asked how fatigue affected their driving performance, both truck and taxi drivers identified slow reactions (72.8 and 82.1%, respectively) and poor awareness of traffic (53.9 and 68.9%, respectively) as the most common impairments as a result of fatigue (see Figure 1). In addition, 45.3% truck drivers reported that fatigue led to poor lateral control, and more than half (52.4%) of the taxi drivers thought that fatigue made them drive slowly, which was also reported by a large proportion of truck drivers (44.4%). Some factors were also identified as the contributors to drivers’ fatigue by the 2 driver groups (see Figure 2). Prolonged driving time was cited as the most important contributor to fatigue by both truck and taxi drivers (44.7 and 79.8%, respectively). In addition, more than one third (34.1%) of truck drivers reported short sleep time as a main contributing factor, and more than half (57.8%) of the taxi drivers thought that heavy traffic made them experience fatigue.
Meng et al.
Fig. 1. Effects of driving fatigue on driving performance.
the commonly used countermeasures for the 2 driver groups differed from each other (see Table 3). The 3 most frequently used countermeasures reported by truck drivers were stopping the vehicle and exercising (M = 3.34, SD = 1.10), opening the windows (M = 3.32, SD = 1.03), and washing their face (M = 3.21, SD = 1.03). For taxi drivers, opening the windows was also one of the most frequently used methods (M = 3.75, SD = 1.07) and the other 2 methods were different from those used by truck drivers, including listening to the radio (M = 3.43, SD = 1.34) and drinking water (M = 3.35, SD = 1.39). Other countermeasures, such as eating snacks, drinking coffee or energy drinks, and singing a song were used more frequently by truck drivers than by taxi drivers. Taxi drivers used talking with a passenger more frequently than truck drivers, probably because taxi drivers carried passengers more often than truck drivers. In terms of the perceived effectiveness, truck drivers reported that taking a short nap (M = 3.53, SD = 1.19), stopping the vehicle and exercising (M = 3.38, SD = 1.04), and washing their face (M = 3.21, SD = 0.96) were the most effective countermeasures. Taxi drivers perceived stopping the vehicle and exercising (M = 3.75, SD = 1.39), opening the window (M = 3.72, SD = 1.33), and taking a short nap (M = 3.61, SD = 1.57) to be the most effective methods. Although stopping to take a nap was not included in the list of the 3 most commonly
Countermeasures to Fatigue A list of 17 predefined countermeasures to cope with driving fatigue was presented to the 2 groups, and the respondents were required to rate the usage frequency and perceived effectiveness of each countermeasure. The results showed that
Fig. 2. Reasons that induce driving fatigue.
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Table 3. Usage frequency (1 = never, 5 = always) and perceived effectiveness (1 = not helpful at all, 5 = very helpful) of different fatigue countermeasures
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Usage frequency
Perceived effectiveness
Countermeasures
Truck
Taxi
P value
Truck
Taxi
P value
Taking a short nap Stopping the vehicle and exercising Eating some snacks Drinking coffee or energy drink Drinking water Smoking Opening the car windows Listening to the radio Listening to music Talking on the cellular phone Talking with a passenger Washing face Changing the seat position Watching the view Thinking personal thoughts Singing a song Shaking head
3.15 3.34 3.09∗ 2.64∗ 3.00 3.03∗ 3.32 2.92 2.33∗ 2.26∗ 2.51 3.21∗ 2.46∗ 2.29 2.05∗ 2.52∗ 2.65
3.03 3.34 1.98 1.99 3.35∗ 2.70 3.75∗ 3.43∗ 1.70 1.91 2.87∗ 2.44 2.06 2.51 1.72 1.92 2.75
.397 .834
