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.     

Testing assumptions implicit in the use of the 15-second rule as an early predictor of whether an in-vehicle device produces unacceptable levels of distraction

Given the proliferation of in-vehicle technologies, techniques must be developed to ensure devices do not produce unacceptable levels of distraction. One approach is to use static time on task (e.g., the 15-second rule). However, this practice makes three critical assumptions: (1) static time on task predicts time on task while driving; (2) time on task measured in a hazard-free environment predicts time on task when drivers expect hazards; (3) time on task predicts perceived distraction, collisions, and driving errors. To test these assumptions, two tasks were compared in 32 drivers using a driving simulator. The tasks were manipulating controls of a radio/tape deck and dialling a hand-held cellular phone. Static time on task underestimated dynamic time on task, though the differences between tasks were roughly consistent across testing conditions, with the cellular task taking more time. Participants who expected hazards required slightly more time on task than those who did not, but the effect was only marginal (p=0.09) and consistent across tasks. Finally, the device with higher static time on task also produced significantly more lane deviations and perceived interference, though the predicted pattern of results did not emerge for collisions and hazard response time.     

Self-report measures of distractibility as correlates of simulated driving performance

The present study investigated the relationship between self-reported measures pertaining to attention difficulties and simulated driving performance while distracted. Thirty-six licensed drivers participated in a simulator driving task while engaged in a cell phone conversation. The participants completed questionnaires assessing their tendency toward boredom, cognitive failures, and behaviors associated with attention deficit and hyperactivity. Scores on these measures were significantly correlated with various driving outcomes (e.g., speed, lane maintenance, reaction time). Significant relationships were also found between one aspect of boredom proneness (i.e., inability to generate interest or concentrate) and self-reports of past driving behavior (moving violations). The current study may aid in the understanding of how individual differences in driver distractibility may contribute to unsafe driving behaviors and accident involvement. Additionally, such measures may assist in the identification of individuals at risk for committing driving errors due to being easily distracted. The benefits and limitations of conducting and interpreting simulation research are discussed.     

Young novice driver subtypes: Relationship to driving violations, errors and lapses

The present study aimed to identify, in a large Italian sample of young, novice drivers, specific subtypes of drivers on the basis of combinations of self-reported personality traits (i.e., driving anger, anxiety, angry hostility, excitement-seeking, altruism, normlessness and driving locus of control) and to evaluate their high-risk driving behaviors not only in terms of traffic rule violations and risk-taking behaviors, but also in terms of driving errors and lapses as measured by the Manchester Driver Behavior Questionnaire. Participants were 1008 high school students between the ages of 18 and 23 years, with valid driver's licenses. On the basis of a cluster analysis of the personality variables, three easily interpretable driver subgroups were identified (risky drivers, worried drivers and careful drivers) that differed on self-reported accident involvement, attitudes toward traffic safety and risk perception, as well as on driving violations, errors, and lapses. The inclusion of internal and external driving locus of control, variables not previously considered in similar cluster studies, provided a relevant contribution to the final cluster solution. Further, the use of the Driving Behavior Questionnaire permitted the differentiation between deliberate deviations from safe driving practices and mistakes due to misjudgments or lapses in attention. This distinction was critical for understanding the behavior of each of the three identified subgroups of drivers, and for planning interventions to promote safe driving.     

Navigational conversation impairs concurrent distance judgments

Dual-task performance as it relates to driving, such as tuning a radio or manipulating a cellular phone, forces drivers to divide their attention between the traffic demands and the in-car task. The present study investigated how concurrent spatial or non-spatial cognitive distractions mediated proximity judgments using vehicular stimuli. Utilizing a modified version of the task employed by [Elias, L.J., Robinson, B. in press. Drive on the right side of the road: perceptual asymmetries for judgments of automobile proximity. International Journal of Neuroscience.] the current study examined how mental navigation (spatial distraction) affected accuracy and response time for depth judgments on vehicular stimuli in each visual field. These were compared to a control condition in which no distraction was present, as well as when a semantic (non-spatial) distraction was present. We found that conversation of a navigational nature (i.e., spatial distraction) most negatively impacted accuracy and response time when processing dynamically changing vehicle proximity. Further, these deleterious effects appeared to be uniform throughout the visual field. Findings are related to driving while being distracted, with particular emphasis on the role of cerebral lateralization in dual-task performance.     

Does early training improve driving skills of young novice French drivers?

The aim of this research was to study drivers’ performances and divided attention depending on their initial training. The performances of young novice drivers who received early training, traditionally trained drivers and more experienced drivers were compared during a dual task consisting of a simulated car-following task and a number’ parity judgment task. It was expected that, due to their limited driving experience, the young novice drivers would have more difficulty in adequately distributing their attention between the two tasks. Poorer performances by novice drivers than experienced drivers were therefore expected. The results indicate that traditionally trained drivers had more difficulties in speed regulation and maintaining their position in the lane than drivers with early training and experienced drivers. Performance impairment linked to driving inexperience was also found in the secondary task. The results were interpreted regarding the attentional resources involved in driving with a secondary task and supported the positive effects of French early training.     

Cognitive load and detection thresholds in car following situations: safety implications for using mobile (cellular) telephones while driving

This study was aimed at investigating drivers’ ability to detect a car ahead decelerating, while doing mobile phone related tasks. Nineteen participants aged between 20 and 29 years, (2000–125 000 km driving experience) drove at 80 km/h, 50 m behind a lead car, on a 30 km section of motorway in normal traffic. During each trial the lead car started to decelerate at an average of 0.47 m/s² while the participant either looked at the car in front (control), continuously dialed series of three random integers on a numeric keypad (divided visual attention), or performed a memory and addition task (non-visual attention). The results indicated that drivers’ detection ability was impaired by about 0.5 s in terms of brake reaction time and almost 1 s in terms of time-to-collision, when they were doing the non-visual task whilst driving. This impairment was similar to when the drivers were dividing their visual attention between the road ahead and dialing numbers on the keypad. It was concluded that neither a hands-free option nor a voice controlled interface removes the safety problems associated with the use of mobile phones in a car.     

A parametric duration model of the reaction times of drivers distracted by mobile phone conversations

The use of mobile phones while driving is more prevalent among young drivers—a less experienced cohort with elevated crash risk. The objective of this study was to examine and better understand the reaction times of young drivers to a traffic event originating in their peripheral vision whilst engaged in a mobile phone conversation. The CARRS-Q advanced driving simulator was used to test a sample of young drivers on various simulated driving tasks, including an event that originated within the driver's peripheral vision, whereby a pedestrian enters a zebra crossing from a sidewalk. Thirty-two licensed drivers drove the simulator in three phone conditions: baseline (no phone conversation), hands-free and handheld. In addition to driving the simulator each participant completed questionnaires related to driver demographics, driving history, usage of mobile phones while driving, and general mobile phone usage history. The participants were 21–26 years old and split evenly by gender. Drivers’ reaction times to a pedestrian in the zebra crossing were modelled using a parametric accelerated failure time (AFT) duration model with a Weibull distribution. Also tested where two different model specifications to account for the structured heterogeneity arising from the repeated measures experimental design. The Weibull AFT model with gamma heterogeneity was found to be the best fitting model and identified four significant variables influencing the reaction times, including phone condition, driver's age, license type (provisional license holder or not), and self-reported frequency of usage of handheld phones while driving. The reaction times of drivers were more than 40% longer in the distracted condition compared to baseline (not distracted). Moreover, the impairment of reaction times due to mobile phone conversations was almost double for provisional compared to open license holders. A reduction in the ability to detect traffic events in the periphery whilst distracted presents a significant and measurable safety concern that will undoubtedly persist unless mitigated.     

Gap acceptance and risk-taking by young and mature drivers, both sober and alcohol-intoxicated, in a simulated driving task

A single-blind randomized study was conducted on young (18–21 years, n = 16) and mature (25–35 years, n = 16) drivers to assess how age, combined with a modest dose of alcohol (0.7 g/kg for males and 0.6 g/kg for females), influenced performance on a driving simulator. The driving tasks included detecting the presence of a vehicle on the horizon as quickly as possible, estimating the point on the road that an approaching vehicle would have passed by the participants’ vehicle (time-to-collision) and overtaking another vehicle against a steady stream of oncoming traffic. The results of the vehicle detection task showed that detection times were significantly slower with maturity, alcohol consumption and lower approaching vehicle speeds (50 kph), particularly on curved sections of road. Approaching vehicle speed was also found to significantly influence time-to-collision (TTC) judgments, such that faster approach speeds led to less underestimated (and therefore riskier) judgments of TTC than slower speeds. In the overtaking task, mature participants demonstrated impaired discrimination skills with varying approaching vehicle speeds, while young participants recorded significantly slower speeds while overtaking a vehicle, thus increasing the time that they spent in the opposing lane. In conclusion, young and mature drivers demonstrated pivotal differences in behavior in this study. Young drivers showed a greater tendency to engage in risky driving, while experienced drivers appeared to be more susceptible to perceptual influences. Overall, alcohol consumption impaired a driver's ability to divide attention, but had little effect on decision-making processes.     

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.     

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.     

Measurement of driver calibration and the impact of feedback on drivers’ estimates of performance

Recent studies focused on driver calibration show that drivers are often miscalibrated, either over confident or under confident, and the magnitude of this miscalibration changes under different conditions. Previous work has demonstrated behavioral and performance benefits of feedback, yet these studies have not explicitly examined the issue of calibration. The objective of this study was to examine driver calibration, i.e., the degree to which drivers are accurately aware of their performance, and determine whether feedback alters driver calibration. Twenty-four drivers completed a series of driving tasks (pace clocks, traffic light, speed maintenance, and traffic cones) on a test track. Drivers drove three different blocks around the test track: (1) baseline block, where no participants received feedback; (2) feedback block, where half of the participants received performance feedback while the other half received no feedback; (3) a no feedback block, where no participants received feedback. Results indicated that across two different calibration measures, drivers were sufficiently calibrated to the pace clocks, traffic light, and traffic cone tasks. Drivers were not accurately aware of their performance regarding speed maintenance, though receiving feedback on this task improved calibration. Proper and accurate measurements of driver calibration are needed before designing performance feedback to improve calibration as these feedback systems may not always yield the intended results.     

A meta-analysis of the effects of cell phones on driver performance

The empirical basis for legislation to limit cell phones while driving is addressed. A comprehensive meta-analysis of the effects of cell phones on driving performance was performed. A total of 33 studies collected through 2007 that met inclusion criteria yielded 94 effect size estimates, with a total sample size of approximately 2000 participants. The dependent variables of reaction time, lateral vehicle control, headway and speed and the moderating variables of research setting (i.e., laboratory, simulator, on-road), conversation target (passenger, cell phone) and conversation type (cognitive task, naturalistic) were coded. Reaction time (RT) to events and stimuli while talking produced the largest performance decrements. Handheld and hands-free phones produced similar RT decrements. Overall, a mean increase in RT of .25s was found to all types of phone-related tasks. Observed performance decrements probably underestimate the true behavior of drivers with mobile phones in their own vehicles. In addition, drivers using either phone type do not appreciably compensate by giving greater headway or reducing speed. Tests for moderator effects on RT and speed found no statistically significant effect size differences across laboratory, driving simulation and on-road research settings. The implications of the results for legislation and future research are considered.     

An observational study of driving distractions on urban roads in Spain

The present research investigated the prevalence of driver engagement in secondary tasks and whether there were any differences by age and gender, as well as day of the week and time of the day. Two independent researchers observed 6578 drivers at nine randomly selected urban locations in Girona, Spain. Nearly 20% of the drivers observed were engaged in some type of secondary task, with the most common being: conversing with a passenger (11.1%), smoking (3.7%) and talking on a handheld mobile phone (1.3%). Surprisingly there were no differences by gender, but there were age-related differences with younger drivers being more frequently observed engaged in a number of different types of secondary tasks while driving (i.e. drinking, talking on a handheld mobile phone, and texting or keying numbers). Logistic regression showed that younger drivers, and to a lesser extent middle-age drivers, were significantly more likely to be observed engaged in a technological distraction than older drivers. Conversely, non-technological distractions were significantly predicted by day of the week, time of the day and location. A substantial number of the drivers observed in this study were putting themselves at an increased risk of becoming involved in a crash by engaging in non-driving related tasks at the same time as driving. Furthermore, the higher crash rate among young drivers may be partially accounted for by their more frequent engagement in some types of secondary tasks while driving.     

The effects of driver training on simulated driving performance

Given that the beneficial effects of driver training on accident risk may not be an appropriate criterion measure, this study investigates whether professionally trained and experienced drivers exhibit safer driving behaviour in a simulated driving task compared with drivers without professional driver training. A sample of 54 police trained drivers and a sample of 56 non-police trained drivers were required to complete two tasks. Firstly to overtake a slow-moving bus on a hazardous stretch of single-lane road with bends and hills and secondly to follow a lead vehicle travelling at 55mph in a built-up section with a speed limit of 30mph. Results showed that in comparison with non-police trained drivers, police drivers were significantly less likely to cross the central division of the road at unsafe locations during the overtaking task and reduced their speed on approach to pedestrians at the roadside in the following task to a greater extent. Police drivers also adopted a more central lane position compared with non-police trained drivers on urban roads and at traffic lights during the following task. Driver group differences in simulated driving performance are discussed with reference to the implications for driver training assessment and skill development.     

Driver-initiated distractions: Examining strategic adaptation for in-vehicle task initiation

Today, drivers are faced with many in-vehicle activities that are potentially distracting. In many cases, they are not passive recipients of these tasks; rather, drivers decide whether or not (or how) to perform them. In this study, we examined whether drivers, given knowledge of the upcoming road demands, would strategically delay performing in-vehicle activities until demands were reduced. Twenty drivers drove an instrumented van around a closed track that was divided into sections of varying demands and difficulty. Drivers were asked to perform one of four in-vehicle tasks (e.g., phone conversation; read a text message; find an address; pick up an object on the floor); however, they were free to decide when to initiate these tasks, provided they finish them before a given deadline. Although drivers were fully aware of the relative demands of the road, they did not tend to strategically postpone tasks—a finding that was consistent across the different tasks (p > .05). Rather, drivers tended to initiate tasks regardless of the current driving conditions. This strategy frequently led to driving errors. Given the control that drivers have over many in-vehicle distractions, interventions that focus on strategic decisions and planning may have merit.     

An on-road assessment of cognitive distraction: impacts on drivers' visual behavior and braking performance

In this on-road experiment, drivers performed demanding cognitive tasks while driving in city traffic. All task interactions were carried out in hands-free mode so that the 21 drivers were not required to take their visual attention away from the road or to manually interact with a device inside the vehicle. Visual behavior and vehicle control were assessed while they drove an 8 km city route under three conditions: no additional task, easy cognitive task and difficult cognitive task. Changes in visual behavior were most apparent when performance between the No Task and Difficult Task conditions were compared. When looking outside of the vehicle, drivers spent more time looking centrally ahead and spent less time looking to the areas in the periphery. Drivers also reduced their visual monitoring of the instruments and mirrors, with some drivers abandoning these tasks entirely. When approaching and driving through intersections, drivers made fewer inspection glances to traffic lights compared to the No Task condition and their scanning of intersection areas to the right was also reduced. Vehicle control was also affected; during the most difficult cognitive tasks there were more occurrences of hard braking. Although hands-free designs for telematics devices are intended to reduce or eliminate the distraction arising from manual operation of these units, the potential for cognitive distraction associated with their use must also be considered and appropriately assessed. These changes are captured in measures of drivers' visual behavior.     

Texting while driving: Is speech-based text entry less risky than handheld text entry?

Research indicates that using a cell phone to talk or text while maneuvering a vehicle impairs driving performance. However, few published studies directly compare the distracting effects of texting using a hands-free (i.e., speech-based interface) versus handheld cell phone, which is an important issue for legislation, automotive interface design and driving safety training. This study compared the effect of speech-based versus handheld text entries on simulated driving performance by asking participants to perform a car following task while controlling the duration of a secondary text-entry task. Results showed that both speech-based and handheld text entries impaired driving performance relative to the drive-only condition by causing more variation in speed and lane position. Handheld text entry also increased the brake response time and increased variation in headway distance. Text entry using a speech-based cell phone was less detrimental to driving performance than handheld text entry. Nevertheless, the speech-based text entry task still significantly impaired driving compared to the drive-only condition. These results suggest that speech-based text entry disrupts driving, but reduces the level of performance interference compared to text entry with a handheld device. In addition, the difference in the distraction effect caused by speech-based and handheld text entry is not simply due to the difference in task duration.     

Lane heading difference: An innovative model for drowsy driving detection using retrospective analysis around curves

Driving while sleepy is a serious contributor to automobile accidents. Previous research has shown that drowsy drivers produce systematic errors (variability) in vehicle behavior which are detectable using vehicle monitoring technology. The current study developed a new methodological approach using a vehicle heading difference metric to detect drowsy driving more effectively than other more commonly used methods. Twenty participants completed a driving scenario as well as several measures of fatigue in five testing sessions across a night of sleep deprivation. Each simulated highway driving session lasted 20 min, and was analyzed for lateral lane position variability and vehicle heading difference variability with two statistical methods. Fatigue measures monitored reaction time, attention, and oculomotor movement. The results showed that examining lane heading difference using the absolute value of the raw data detected driving variability better across the night than other statistical models. The results from the fatigue measures indicated an increase in reaction time and response lapses, as well as a decrease in oculomotor reactivity across the night. These results suggest that in fatigued drivers the statistical model using the absolute value of lane heading could be an improved metric for drowsy driving detection that could accurately detect detriments in driving ability at lower levels of fatigue.     

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.