驾驶过程中手机使用的补偿式行为

驾驶员在驾车过程中使用手机会造成驾驶分心,研究驾驶中的补偿行为有助于降低驾驶分心造成的危害。通过模拟驾驶探究驾驶行为和生理指标在是否使用手机、不同路段复杂程度、不同驾驶员类型中的差异,从而使驾驶员注意到驾驶中使用手机的危害并及时采取措施,弥补驾驶分心带来的危害。研究结果表明,使用手机主效应在各项指标中均呈现显著影响(P<0.001),驾驶员类型主效应在阅读短信行为中的踩刹车持续时间上存在显著影响(P<0.01),使用手机与驾驶员类型交互作用在接听电话行为的心率、阅读短信行为中的平均速度、踩刹车持续时间和心率上存在显著影响(P<0.05)。比起接听免提电话,阅读短信时采取补偿行为的幅度更大(P<0.05);驾驶员比学员采取补偿行为的幅度更大(P<0.05)。     

A rear-end collision risk assessment model based on drivers’ collision avoidance process under influences of cell phone use and gender—A driving simulator based study

Driver’s collision avoidance performance has a direct link to the collision risk and crash severity. Previous studies demonstrated that the distracted driving, such as using a cell phone while driving, disrupted the driver’s performance on road. This study aimed to investigate the manner and extent to which cell phone use and driver’s gender affected driving performance and collision risk in a rear-end collision avoidance process. Forty-two licensed drivers completed the driving simulation experiment in three phone use conditions: no phone use, hands-free, and hand-held, in which the drivers drove in a car-following situation with potential rear-end collision risks caused by the leading vehicle’s sudden deceleration. Based on the experiment data, a rear-end collision risk assessment model was developed to assess the influence of cell phone use and driver’s gender. The cell phone use and driver’s gender were found to be significant factors that affected the braking performances in the rear-end collision avoidance process, including the brake reaction time, the deceleration adjusting time and the maximum deceleration rate. The minimum headway distance between the leading vehicle and the simulator during the rear-end collision avoidance process was the final output variable, which could be used to measure the rear-end collision risk and judge whether a collision occurred. The results showed that although cell phone use drivers took some compensatory behaviors in the collision avoidance process to reduce the mental workload, the collision risk in cell phone use conditions was still higher than that without the phone use. More importantly, the results proved that the hands-free condition did not eliminate the safety problem associated with distracted driving because it impaired the driving performance in the same way as much as the use of hand-held phones. In addition, the gender effect indicated that although female drivers had longer reaction time than male drivers in critical situation, they were more quickly in braking with larger maximum deceleration rate, and they tended to keep a larger safety margin with the leading vehicle compared to male drivers. The findings shed some light on the further development of advanced collision avoidance technologies and the targeted intervention strategies about cell phone use while driving.     

Mobile phone use-effects of handheld and handsfree phones on driving performance

The study was concerned with effects of handsfree and handheld mobile phone dialling and conversation in simulated driving. In the main experiment dealing with conversation, 48 participants drove a distance of about 70 km on a route which led through urban and rural environments. In the dialling experiment, the participants drove a distance of 15 km on a rural two-lane road. The experimental design was mixed with phone mode as a between-subjects factor and phone use (yes/no) as a within-subjects factor. Performance on a peripheral detection task (PDT) while driving was impaired by dialling and conversation for both phone modes, interpreted as an increase in mental workload. Driving performance was impaired by dialling--lateral position deviation increased in a similar way for both phone modes. Conversation had, however, opposite effects--lateral position deviation decreased in a similar way for both phone modes. Driving speed decreased as an effect of dialling with the greatest effect for handsfree phone mode. Conversation also caused reduced speed, but only for handheld phone mode. The effects on speed can be interpreted as a compensatory effort for the increased mental workload. In spite of the compensatory behaviour, mental workload was still markedly increased by phone use. Subjective effects of dialling and conversation were also analysed. Most participants reported a speed decrease but no effect on lateral position deviation as an effect of dialling or conversation. In the conversation experiment, driving performance was rated better for handsfree than for handheld mode. In the dialling experiment, no difference between the two phone modes appeared.     

Engrossed in conversation: the impact of cell phones on simulated driving performance

The current study examined the effects of cognitively distracting tasks on various measures of driving performance. Thirty-six college students with a median of 6 years of driving experience completed a driving history questionnaire and four simulated driving scenarios. The distraction tasks consisted of responding to a signal detection task and engaging in a simulated cell phone conversation. Driving performance was measured in terms of four categories of behavior: traffic violations (e.g., speeding, running stop signs), driving maintenance (e.g., standard deviation of lane position), attention lapses (e.g., stops at green lights, failure to visually scan for intersection traffic), and response time (e.g., time to step on brake in response to a pop-up event). Performance was significantly impacted in all four categories when drivers were concurrently talking on a hands-free phone. Performance on the signal detection task was poor and not significantly impacted by the phone task, suggesting that considerably less attention was paid to detecting these peripheral signals. However, the signal detection task did interact with the phone task on measures of average speed, speed variability, attention lapses, and reaction time. The findings lend further empirical support of the dangers of drivers being distracted by cell phone conversations.     

How reinforcement sensitivity and perceived risk influence young drivers’ reported engagement in risky driving behaviors

Gray's reinforcement sensitivity theory (RST), implementing Carver and White's behavior inhibition system (BIS) and behavior approach system (BAS) scales, was used to predict reported engagement in 10 risky driving behaviors: speeding (2 levels), driving under the influence of alcohol, racing other vehicles, cell phone use (hand-held and hands free), tailgating, unsafe overtaking, driving while fatigued, and not wearing a seatbelt. Participants were 165 young male and female (n = 101) drivers aged 17–25 years who held a valid Australian driver's license. Effects of the explanatory variables and specific risk perceptions upon engagement in the reported risky driving behaviors were examined using SEM analyses. Also of interest was whether perceived risk mediated the relationship between the personality variables and reported engagement in risky driving behaviors. RST variables, negative reactivity, reward responsiveness and fun seeking, accounted for unique variance in young drivers’ perceived risk. Reward responsiveness and perceived risk accounted for unique variance in young drivers’ reported engagement in risky driving behaviors. Negative reactivity was completely mediated by perceived risk in its negative relationship with reported engagement. To better understand driving related risk decision making, future research could usefully incorporate drivers’ motivation systems. This has the potential to lead to more tailored approaches to identifying risk-prone drivers and provide information for the development and implementation of media campaigns and educational programs.     

In the eye of the beholder: A simulator study of the impact of Google Glass on driving performance

This study examined whether, and to what extent, driving is affected by reading text on Google Glass. Reading text requires a high level of visual resources and can interfere with safe driving. However, it is currently unclear if the impact of reading text on a head-mounted display, such as Google Glass (Glass), will differ from that found with more traditional head-down electronic devices, such as a dash-mounted smartphone. A total of 20 drivers (22–48 years) completed the Lane Change Test while driving undistracted and while reading text on Glass and on a smartphone. Measures of lateral vehicle control and event detection were examined along with subjective workload and secondary task performance. Results revealed that drivers’ lane keeping ability was significantly impaired by reading text on both Glass and the smartphone. When using Glass, drivers also failed to detect a greater number of lane change signs compared to when using the phone or driving undistracted. In terms of subjective workload, drivers rated reading on Glass as subjectively easier than on the smartphone, which may possibly encourage greater use of this device while driving. Overall, the results suggest that, despite Glass allowing drivers to better maintain their visual attention on the forward scene, drivers are still not able to effectively divide their cognitive attention across the Glass display and the road environment, resulting in impaired driving performance.     

Motorists' use of hand held cell phones in New Zealand: an observational study

Unlike many similar countries, New Zealand has no specific legislation restricting the use of cell phones in vehicles. Several factors suggest that legislation may be introduced in the near future. This study provided a benchmark for current cell phone use among motorists. A total of 8,700 drivers of cars were observed for cell phone use as they passed a fixed location in Auckland. Cell phone use was double that of an Australian city, where cell phones are banned. Use of a cell phone while driving was similarly likely in male and female drivers.     

To call or not to call—That is the question (while driving)

We studied whether decisions to engage in cell phone conversation while driving and the consequences of such decisions are related to the driver's age, to the road conditions (demands of the driving task), and to the driver's role in initiating the phone call (i.e. the driver as caller vs. as receiver). Two experiments were performed in a driving simulator in which driver age, road conditions and phone conversation, as a secondary task, were manipulated. Engagement in cell phone conversations, performance in the driving and the conversation tasks, and subjective effort assessment were recorded. In general, drivers were more willing to accept incoming calls than to initiate calls. In addition, older and younger drivers were more susceptible to the deleterious effects of phone conversations while driving than middle aged/experienced drivers. While older drivers were aware of this susceptibility by showing sensitivity to road conditions before deciding whether to engage in a call or not, young drivers showed no such sensitivity. The results can guide the development of young driver training programs and point at the need to develop context-aware management systems of in-vehicle cell phone conversations.     

Perceptual and attentional effects on drivers' speed selection at curves

This paper describes an experiment comparing the relative effectiveness of various types of warnings on drivers' speed selection at curves. The experiment compared three types of curve warnings across three different curve types in a driving simulator. All of the warnings worked reasonably well for severe curves (45 km/h), regardless of demands from a secondary (cell phone) task. For less demanding curves, only those warnings with a strong perceptual component (i.e., implicit cues) were effective in reducing drivers' curve speeds in the presence of the cell phone task. The design implications of these data appear straightforward; curve warnings that contain perceptual components or emphasise the physical features of the curve work best, particularly in cognitively demanding situations. The cell phone task added to driver workload and drivers became less responsive to primary task demands (i.e., speeds were elevated and reaction times were longer).     

Shifting attention across near and far spaces: Implications for the use of hands-free cell phones while driving

In three experiments, participants performed two tasks concurrently during driving. In the peripheral detection task, they responded manually to visual stimuli delivered through a LED placed on the internal rear mirror; in the conversation task, they were engaged in a conversation with a passenger, or through earphone-operated, loudspeaker-operated, or hand-held cell phones. Results showed that drivers were slower at responding to the visual stimuli when conversing through a hand-held cell phone or an earphone-operated cell phone than when conversing through a loudspeaker-operated cell phone or with a passenger. These results suggest that due to the brain coding the space into multiple representations, devices that make phone conversations taking place in the near, personal space make drivers slower at responding to visual stimuli, compared to devices that make the conversation occurring in a far space.     

Cell phone conversing while driving in New Zealand: prevalence, risk perception and legislation

This study investigated (i) the prevalence of conversing on a cell phone while driving in New Zealand, (ii) respondents’ perception of risk regarding this behaviour and (iii) attitudes towards legislation banning cell phone use while driving. In addition, the study examined the association between the prevalence of conversing on a cell phone and risk perception. Anonymous, self-reported, survey data was collected via the internet from 1057 drivers nationwide regarding the frequency of conversing on a cell phone, including hands-free and hand-held conversing, risk perception, views on legislation, and demographic information. A positive relationship was found between the frequency of conversing on a cell phone and risk perception; that is, as the frequency of conversing on a cell phone increased, the perceived risk of this behaviour decreased.     

Driver distraction: the effects of concurrent in-vehicle tasks, road environment complexity and age on driving performance

This paper presents the findings of a simulator study that examined the effects of distraction upon driving performance for drivers in three age groups. There were two in-vehicle distracter tasks: operating the vehicle entertainment system and conducting a simulated hands-free mobile phone conversation. The effect of visual clutter was examined by requiring participants to drive in simple and complex road environments. Overall measures of driving performance were collected, together with responses to roadway hazards and subjective measures of driver perceived workload. The two in-vehicle distraction tasks degraded overall driving performance, degraded responses to hazards and increased subjective workload. The performance decrements that occurred as a result of in-vehicle distraction were observed in both the simple and complex highway environments and for drivers in different age groups. One key difference was that older drivers traveled at lower mean speeds in the complex highway environment compared with younger drivers. The conclusions of the research are that both in-vehicle tasks impaired several aspects of driving performance, with the entertainment system distracter having the greatest negative impact on performance, and that these findings were relatively stable across different driver age groups and different environmental complexities.     

Impact of age and cognitive demand on lane choice and changing under actual highway conditions

Previous research suggests that drivers change lanes less frequently during periods of heightened cognitive load. However, lane changing behavior of different age groups under varying levels of cognitive demand is not well understood. The majority of studies which have evaluated lane changing behavior under cognitive workload have been conducted in driving simulators. Consequently, it is unclear if the patterns observed in these simulation studies carry over to actual driving. This paper evaluates data from an on-road study to determine the effects of age and cognitive demand on lane choice and lane changing behavior. Three age groups (20–29, 40–49, and 60–69) were monitored in an instrumented vehicle. The 40's age group had 147% higher odds of exhibiting a lane change than the 60's group. In addition, drivers in their 60's were less likely to drive on the leftmost lane compared to drivers in their 20's and 40's. These results could be interpreted as evidence that older adults adopt a more conservative driving style as reflected in being less likely to choose the leftmost lane than the younger groups and less likely to change lanes than drivers in their 40's. Regardless of demand level, cognitive workload reduced the frequency of lane changes for all age groups. This suggests that in general drivers of all ages attempt to regulate their behavior in a risk reducing direction when under added cognitive demand. The extent to which such self-regulation fully compensates for the impact of added cognitive demand remains an open question.     

Effects of practice, age, and task demands, on interference from a phone task while driving

Experimental research on the effects of cellular phone conversations on driving indicates that the phone task interferes with many driving-related functions, especially with older drivers. Unfortunately in past research (1) the dual task conditions were not repeated in order to test for learning, (2) the 'phone tasks' were not representative of real conversations, and (3) most often both the driving and the phone tasks were experimenter-paced. In real driving drivers learn to time-share various tasks, they can pace their driving to accommodate the demands of a phone conversation, and they can even partially pace the phone conversation to accommodate the driving demands. The present study was designed to better simulate real driving conditions by providing a simulated driving environment with repeated experiences of driving while carrying two different hands-free 'phone' tasks with different proximities to real conversations. In the course of five sessions of driving and using the phone, there was a learning effect on most of the driving measures. In addition, the interference from the phone task on many of the driving tasks diminished over time as expected. Finally, the interference effects were greater when the phone task was the often-used artificial math operations task than when it was an emotionally involving conversation, when the driving demands were greater, and when the drivers were older. Thus, the deleterious effects of conversing on the phone are very real initially, but may not be as severe with continued practice at the dual task, especially for drivers who are not old.     

Driving while conversing: Cell phones that distract and passengers who react

The research systematically compared the driving performance and conversational patterns of drivers speaking with in-car passengers, hands-free cell phones, and remote passengers who could see the driver's current driving situation (via a window into a driving simulator). Driving performance suffered during cell phone and remote passenger conversations as compared with in-car passenger conversations and no-conversation controls in terms of their approach speeds, reaction times, and avoidance of road and traffic hazards. Of particular interest was the phenomenon of conversation suppression, the tendency for passengers to slow their rates of conversation as the driver approached a hazard. On some occasions these passengers also offered alerting comments, warning the driver of an approaching hazard. Neither conversation suppression nor alerting comments were present during cell phone conversations. Remote passengers displayed low levels of alerting comments and conversation suppression, but not enough to avoid negative effects on driving performance. The data suggested that conversation modulation was a key factor in maintaining driving performance and that seeing the road and traffic was not sufficient to produce it. A second experiment investigated whether a cell phone modified to emit warning tones could alleviate some of the adverse effects typically associated with cell phone conversations. The modified cell phone produced discourse patterns that were similar to passenger conversations and driving performance nearly as good as that of drivers who were not conversing. This latter finding supported the argument that conversation modulation is a key ingredient in avoiding adverse effects of conversations with drivers, rather than the physical presence of an in-car passenger.     

Mental workload when driving in a simulator: Effects of age and driving complexity

Driving errors for older drivers may result from a higher momentary mental workload resulting from complex driving situations, such as intersections. The present study examined if the mental workload of young and older active drivers vary with the difficulty of the driving context. We adopted the probe reaction time (RT) technique to measure the workload while driving in a simulator. The technique provided clear instructions about the primary (driving) and secondary (RT) tasks. To avoid structural interference, the secondary task consisted of responding as rapidly as possible with a vocal response (“top”) to an auditory stimulus. Participants drove through a continuous 26.4-km scenario including rural and urban sections and probes (stimuli) were given in a baseline static condition and in three different driving contexts embedded into the overall driving scenario. Specifically, stimuli were given randomly when (a) driving on straight roads at a constant speed, (b) approaching intersections for which the driver had to stop the car, and (c) when overtaking a slower vehicle. Unless a driving error was made, drivers did not need any emergency responses. Reaction time was defined as the temporal interval between the auditory stimulus and the onset of the corresponding verbal response detected from the analog signal of a piezo-electric microphone fixed on a headset (ms accuracy). Baseline RTs were similar for both groups. Both groups showed longer RTs when driving and RTs increased as the complexity of the driving contexts increased (driving straights, intersections, overtaking maneuvers). Compared to younger drivers, however, older drivers showed longer RTs for all driving contexts and the most complex driving context (overtaking maneuvers) yielded a disproportionate increase. In conclusion, driving leads to a greater mental workload for the older drivers than for the younger drivers and this effect was exacerbated by the more complex driving context (overtaking maneuvers).     

Impact of distracted driving on safety and traffic flow

Studies have documented a link between distracted driving and diminished safety; however, an association between distracted driving and traffic congestion has not been investigated in depth. The present study examined the behavior of teens and young adults operating a driving simulator while engaged in various distractions (i.e., cell phone, texting, and undistracted) and driving conditions (i.e., free flow, stable flow, and oversaturation). Seventy five participants 16–25 years of age (split into 2 groups: novice drivers and young adults) drove a STISIM simulator three times, each time with one of three randomly presented distractions. Each drive was designed to represent daytime scenery on a 4 lane divided roadway and included three equal roadway portions representing Levels of Service (LOS) A, C, and E as defined in the 2000 Highway Capacity Manual. Participants also completed questionnaires documenting demographics and driving history. Both safety and traffic flow related driving outcomes were considered. A Repeated Measures Multivariate Analysis of Variance was employed to analyze continuous outcome variables and a Generalized Estimate Equation (GEE) Poisson model was used to analyze count variables. Results revealed that, in general more lane deviations and crashes occurred during texting. Distraction (in most cases, text messaging) had a significantly negative impact on traffic flow, such that participants exhibited greater fluctuation in speed, changed lanes significantly fewer times, and took longer to complete the scenario. In turn, more simulated vehicles passed the participant drivers while they were texting or talking on a cell phone than while undistracted. The results indicate that distracted driving, particularly texting, may lead to reduced safety and traffic flow, thus having a negative impact on traffic operations. No significant differences were detected between age groups, suggesting that all drivers, regardless of age, may drive in a manner that impacts safety and traffic flow negatively when distracted.     

Impact of mobile phone use on car-following behaviour of young drivers

Multitasking, such as the concurrent use of a mobile phone and operating a motor vehicle, is a significant distraction that impairs driving performance and is becoming a leading cause of motor vehicle crashes. This study investigates the impact of mobile phone conversations on car-following behaviour. The CARRS-Q Advanced Driving Simulator was used to test a group of young Australian drivers aged 18–26 years on a car-following task in three randomised phone conditions: baseline (no phone conversation), hands-free and handheld. Repeated measure ANOVA was applied to examine the effect of mobile phone distraction on selected car-following variables such as driving speed, spacing, and time headway. Overall, drivers tended to select slower driving speeds, larger vehicle spacings, and longer time headways when they were engaged in either hands-free or handheld phone conversations, suggesting possible risk compensatory behaviour. In addition, phone conversations while driving influenced car-following behaviour such that variability was increased in driving speeds, vehicle spacings, and acceleration and decelerations. To further investigate car-following behaviour of distracted drivers, driver time headways were modelled using Generalized Estimation Equation (GEE). After controlling for various exogenous factors, the model predicts an increase of 0.33 s in time headway when a driver is engaged in hands-free phone conversation and a 0.75 s increase for handheld phone conversation. The findings will improve the collective understanding of distraction on driving performance, in particular car following behaviour which is most critical in the determination of rear-end crashes.     

Effect of North Carolina's restriction on teenage driver cell phone use two years after implementation

A majority of states now restrict teenagers from using a mobile communication device while driving. The effect of these restrictions is largely unknown. In a previous study, we found North Carolina's teenage driver cell phone restriction had little influence on young driver behavior four months after the law took effect (Foss et al., 2009). The goal of the present study was to examine the longer-term effect of North Carolina's cell phone restriction. It was expected that compliance with the restriction would increase, as awareness of the restriction grew over time. Teenagers were observed at high schools in North Carolina approximately two years after the law was implemented. Observations were also conducted in South Carolina, which did not have a cell phone restriction. In both states, there was a broad decrease in cell phone use. A logistic regression analysis showed the decrease in cell phone use did not significantly differ between the two states. Although hand-held cell phone use decreased, there was an increase in the likelihood that drivers in North Carolina were observed physically manipulating a phone. Finally, a mail survey of teenagers in North Carolina showed awareness for the cell phone restriction now stands at 78% among licensed teens. Overall, the findings suggest North Carolina's cell phone restriction has had no long-term effect on the behavior of teenage drivers. Moreover, it appears many teenage drivers may be shifting from talking on a phone to texting.     

Differential impact of personality traits on distracted driving behaviors in teens and older adults

ObjectiveTo determine the impact of personality on distracted driving behaviors.MethodParticipants included 120 drivers (48 teens, 72 older adults) who completed the 45-item Big Five Personality questionnaire assessing self-reported personality factors and the Questionnaire Assessing Distracted Driving (QUADD) assessing the frequency of distracted driving behaviors. Associations for all five personality traits with each outcome (e.g., number of times texting on the phone, talking on the phone, and interacting with the phone while driving) were analyzed separately for teens and older adults using negative binomial or Poisson regressions that controlled for age, gender and education.ResultsIn teens, higher levels of openness and conscientiousness were predictive of greater reported texting frequency and interacting with a phone while driving, while lower levels of agreeableness was predictive of fewer reported instances of texting and interacting with a phone while driving. In older adults, greater extraversion was predictive of greater reported talking on and interacting with a phone while driving. Other personality factors were not significantly associated with distracted driving behaviors.ConclusionsPersonality traits may be important predictors of distracted driving behaviors, though specific traits associated with distracted driving may vary across age groups. The relationship between personality and distracted driving behaviors provides a unique opportunity to target drivers who are more likely to engage in distracted driving behavior, thereby increasing the effectiveness of educational campaigns and improving driving safety.