Verbal and cognitive distractors in driving performance while using hands-free phones

This study investigated the effect of different types of distractions related to use of a hands-free phone on driving performance. The study used three types of verbal distractors: casual conversation, simple arithmetic number guessing, and number adding, in the phone conversation. 12 adults were instructed to follow a lead vehicle on a closed-course highway in a fixed-based driving simulator. The results showed that use of a hands-free cellular phone involving verbal and cognitive distractions impaired driving performance and skill. Types of distraction produced significantly different effects on several dependent variables: the driving speed, headway (distance between the lead car and the manipulated car), brake reaction time, and number of collisions with the lead car. In general, the higher the cognitive load involved in the dialogue, the worse the driving performance.     

A driving simulator study to assess driver performance during a car-following maneuver after switching from automated control to manual control

A review of the literature on autonomous vehicles has shown that they offer several benefits, such as reducing traffic congestion and emissions, and improving transport accessibility. Until the highest level of automation is achieved, humans will remain an important integral of the driving cycle, which necessitates to fully understand their role in automated driving. A difficult research topic involves an understanding of whether a period of automated driving is likely to reduce driver fatigue rather than increase the risk of distraction, particularly when drivers are involved in a secondary task while driving. The main aim of this research comprises assessing the effects of an automation period on drivers, in terms of driving performance and safety implications. A specific focus is set on the car-following maneuver. A driving simulator experiment has been designed for this purpose. In particular, each participant was requested to submit to a virtual scenario twice, with level-three driving automation: one drive consisting of Full Manual Control Mode (FM); the other comprising an Automated Control Mode (AM) activated in the midst of the scenario. During the automation mode, the drivers were asked to watch a movie on a tablet inside the vehicle. When the drivers had to take control of the vehicle, two car-following maneuvers were planned, by simulating a slow-moving vehicle in the right lane in the meanwhile a platoon of vehicles in the overtaking lane discouraged the passing maneuver. Various driving performances (speeds, accelerations, etc.) and surrogate safety measures (PET and TTC) were collected and analysed, focusing on car-following maneuvers. The overall results indicated a more dangerous behavior of drivers who were previously subjected to driving automation; the percentage of drivers who did not apply the brakes and headed into the overtaking lane despite the presence of a platoon of fast-moving vehicles with unsafe gaps between them was higher in AM drive than in FM drive. Conversely, for drivers who preferred to brake, it was noted that those who had already experienced automated driving, adopted a more careful behavior during the braking maneuver to avoid a collision. Finally, with regard to drivers who had decided to overtake the braking vehicle, it should be noted that drivers who had already experienced automated driving did not change their behavior whilst overtaking the stopped lead vehicle.     

Analysis of vehicle-based lateral performance measures during distracted driving due to phone use

Distracted driving due to mobile phone use has been identified as a major contributor to accidents; therefore, it is required to develop ways for detecting driver distraction due to phone use. Though prior literature has documented various visual behavioural and physiological techniques to identify driver distraction, comparatively little is known about vehicle based performance features which can identify driver’s distracted state during phone conversation and texting while driving. Therefore, this study examined the effects of simple conversation, complex conversation, simple texting and complex texting tasks on vehicle based performance parameters such as standard deviation of lane positioning, number of lane excursions, mean and standard deviation of lateral acceleration, mean and standard deviation of steering wheel angle and steering reversal rates (for 1°, 5° and 10° angle differences). All these performance measures were collected for 100 licensed drivers, belonging to three age groups (young, mid-age and old age), with the help of a driving simulator. Effects of all the phone use conditions and driver demographics (age, gender and phone use habits) on the measures were analysed by repeated measures ANOVA tests. Results showed that 1°, 5° SRRs are able to identify all the distracted conditions except for simple conversation; while, 10° SSR can detect all the distracted conditions (including simple conversation). The results suggest that 10° SRR can be included in intelligent in-vehicle devices in order to detect distraction and alert drivers of their distracted state. This can prevent mobile phone use during driving and therefore can help in reducing the road accidents due to mobile phone distractions.     

Driving distraction at night: The impact of cell phone use on driving behaviors among young drivers

Currently, young drivers are more likely than other drivers to use cell phones while driving at night, which has become a major cause of road crashes. However, limited attention has been given to distracted nighttime driving. Therefore, the aim of this study was to explore the interaction effect of cell phone use and time of day (daytime and nighttime) on young drivers’ car-following performance. Forty-three young drivers engaged in a driving simulator experiment with a within-subject design that included three distractions (no distraction, talking and texting on a cell phone) and two times of day. This paper applied non-parametric tests to analyze the data and obtained the following results: (1) the standard deviation of lane position (SDLP) did not significantly differ at either time of day under no distraction, but it was significantly higher at night on straight roads and large-radius curves after introducing distractions. In addition, participants drove faster and gave less headway on small-radius curves under both distractions at night; (2) texting significantly increased the SDLP, while there was less lateral variation during the talking tasks than under no distraction on simple road sections; and (3) compared with the experienced drivers, the novice drivers drove faster during the talking tasks on small-radius curves, but there was no significant difference between groups during the texting tasks. These findings provide both theoretical and practical implications for related policy makers to enhance traffic safety.     

The effect of the emotional state on driving performance in a simulated car-following task

Emotion is an important factor that influences driving behavior, but the mechanism is unclear. This research explored the effect of the emotional state on simulated driving behavior. Thirty-five licensed drivers participated in this study and completed a car-following task. The angry, happy and neutral states were manipulated during the task. The participants’ driving performance and risk perception were recorded under each emotional state. Trait anger and driving experience were also measured to explore the possible mediating effect. The results showed that the drivers in an angry or happy emotional state tended to maintain less time to collision and take a longer time to brake while following a lead vehicle than the drivers under the neutral condition, suggesting that drivers in emotional states are more dangerous those in neutral states. Moreover, the happy state rendered the drivers more dangerous, which manifested as a lower perceived accident risk than that among the drivers in the angry and neutral states. More specifically, experienced drivers in happy states performed worse with respect to vehicle lateral position control. Recommendations and implications for safety education and further research are discussed.     

Young driver distraction by text messaging: A comparison of the effects of reading and typing text messages in Chinese versus English

BackgroundReading and typing text messages while driving seriously impairs driving performance and are prohibited activities in many jurisdictions. Hong Kong is a bilingual society and many people write in both Chinese and English. As the input methods for text messaging in Chinese and English are considerably different, this study used a driving simulator approach to compare the effects of reading and typing Chinese and English text messages on driving performance.MethodThe driving performances of 26 participants were monitored under the following conditions: (1) no distraction, (2) reading and typing Chinese text messages, and (3) reading and typing English text messages. The following measures of driving performance were collected under all of the conditions: reaction time (RT), driving lane undulation (DLU), driving speed fluctuation (DSF), and car-following distance (CFD) between test and leading cars.ResultsRT, DLU, and DSF were significantly impaired by reading and typing both Chinese and English text messages. Moreover, typing text messages distracted drivers more than reading them. Although the Chinese text messaging input system is more complicated than the English system, the use of Chinese did not cause a significantly different degree of distraction.ConclusionBoth reading and typing text messages while driving should be prohibited regardless of whether Chinese or English is used.     

Using a multi-user driving simulator system to explore the patterns of vehicle fleet rear-end collisions occurrence under different foggy conditions and speed limits

Vehicle fleet rear-end collisions (FRECs) are an extremely fatal type of traffic collisions on freeway and they usually occur in foggy weather. This study aimed to explore the patterns of vehicle fleet rear-end collisions occurrence under different foggy conditions and speed limits on freeway. A multi-user driving simulator system was used to conduct the experiment and the driving behavior data were collected from eight participants. The experimental results showed that as the fog density increased, the length of vehicle fleet decreased significantly, and drivers tended to keep a more stable car-following distance. The fog weather and short vehicle gap prompted drivers to react faster and brake harder in respond to the leading vehicle’s brake. In spite of the compensational behaviors, more FRECs were observed under heavy fog condition. Lowering speed limit can significantly reduce the FRECs under foggy conditions. As the speed limits reduced, drivers’ brake response time and speed variance significantly reduced. The study also found that drivers’ brake response time was negatively correlated with their positions in the fleet. Drivers in the front positions of the fleet had a longer response time than drivers in the back positions and thus were more likely to encounter collisions. The study generated a better understanding of drivers’ behavioral pattern in a vehicle fleet and the patterns of vehicle fleet rear-end collisions occurrence. The findings also shed lights on the design of driver assistance system for complex driving situations such as freeway driving under adverse weather.     

Car following with an inertia-oriented driving technique: A driving simulator experiment

BackgroundFor many decades, car-following (CF) and congestion models have assumed a basic invariance: drivers’ default driving strategy is to keep the safety distance. The present study questions that Driving to keep Distance (DD) is a traffic invariance and, therefore, that the difference between the time required to accelerate versus decelerate must necessarily determine the observed patterns of traffic oscillations. Previous studies have shown that drivers can adopt alternative CF strategies like Driving to keep Inertia (DI) by following basic instructions. The present work aims to test the effectiveness of a DI course that integrates 4 tutorials and 4 practice sessions in a standard PC computer designed to learn more adaptive driving behaviors in dense traffic. Methods. Sixty-eight drivers were invited to follow a leading car that varied its speed on a driving simulator, then they took a DI course on a PC computer, and finally they followed a fluctuating leader again on the driving simulator. The study adopted a pretest-intervention-posttest design with a control group. The experimental group took the full DI course (tutorials and then simulator practice). The control group had access to the DI simulator but not to the tutorials. Results. All participating drivers adopted DD as the default CF mode on the pre-test, yielding very similar results. But after taking the full DI course, the experimental group showed significantly less accelerations, decelerations, and speed variability than the control group, and required greater CF distance, that was dynamically adjusted, spending less fuel in the post-test. A group of 8 virtual cars adopting DD required less space on the road to follow the drivers that took the DI course.     

Personality factors are associated with simulated driving outcomes across the driving lifespan

Research has shown that personality factors are related to driving safety. However, the majority of existing studies rely on self-report measures of driving behaviour and sample drivers from limited age ranges. This study sought to examine the relationship between personality and objective driving outcomes as assessed by a driving simulator in a sample of young, mid-aged, and older adults. A total of 114 active drivers completed personality questionnaires as well as a simulated driving assessment protocol. The results showed that: (1) Extraversion and neuroticism were significantly associated with driving simulator performance; (2) conscientiousness was significantly associated with driving performance among middle-aged adults; (3) sensation seeking was an important personality factor primarily for young drivers and was positively correlated with driving speed in the simulator. These results provide further support for the link between personality factors and driving performance, and suggest certain directions for future research.     

Distraction while driving: The case of older drivers

As the impairment of older drivers is especially found in perception and attention, one could assume that they are especially prone to distraction effects of secondary tasks performed while driving. The aim of the study was to examine the effect of age on driving performance as well as the compensation strategies of older drivers under distraction. 10 middle-aged and 10 older drivers drove in a simulator with and without a secondary task. To assess driving performance the Lane Change Task (Mattes, 2003) was used. This method aims at estimating driver demand while a secondary task is being performed, by measuring performance degradation on a primary driving-like task in a standardized manner. The secondary task – a self-developed computer-based version of “d2 Test of Attention” was presented both with and without time pressure. The results show that older participants’ overall driving performance (mean deviation from an ideal path) was worse in all conditions as compared to the younger ones. With regard to lane change reaction time both age groups were influenced by distraction in a comparable manner. However, when the lane keeping performance (standard deviation of the lateral position) was examined, the older participants were more affected than the younger ones. This pattern could be explained by compensation strategies of the older drivers. They focused on the most relevant part of the driving task, the lane change manoeuvres and were able to maintain their performance level in a similar way as did younger drivers. The driving performance of the older participants was not additionally impaired when the secondary task imposed time pressure. Overall, subjective rating of driving performance, perceived workload and perceived distraction was found to be similar for both age groups. The observed trends and patterns associated with distraction while driving should contribute to the further research or practical work regarding in-vehicle technologies and older drivers.     

Compensating for failed attention while driving

While operating a motor vehicle, drivers must pay attention to other moving vehicles and the roadside environment in order to detect and process critical information related to the driving task. Using a driving simulator, this study investigated the effects of an unexpected event on driver performance in environments of more or less clutter and under situations of high attentional load. Attentional load was manipulated by varying the number of neighboring vehicles participants tracked for lane changes. After baseline-driving behavior was established, the unexpected event occurred: a pedestrian ran into the driver’s path. Tracking-accuracy, brake initiation, swerving, and verbal report of the unexpected pedestrian were used to assess driver performance. All participants verbally reported noticing the pedestrian. However, analyses of driving behavior revealed differences in the reactions to the pedestrian: drivers braked faster and had significantly less deviation in their steering heading with a lower attentional load, and participants in low clutter environments had a larger overall change in velocity. This research advances the understanding of how drivers allocate attention between various stimuli and the trade-offs between a driver’s focus on an assigned task and external objects within the roadway environment. Moreover, the results of this research lend insight into how to construct roadway environments that encourage driver attention toward the most immediate and relevant information to reduce both vehicle-to-vehicle and vehicle-to-pedestrian interactions.     

Impact of Relevance and Distraction on Driving Performance and Visual Attention in a Simulated Driving Environment

Previous demonstrations of the impact of cellular phone conversations on visual attention when driving have primarily focused on attention to stimuli that are not relevant to driving. In contrast, we used a driving simulator and eye tracking to examine attention allocation across driving‐relevant and driving‐irrelevant items in the environment depending on whether drivers were distracted. Performance measures indicated that distraction negatively impacted vehicle control. However, driving relevance and the presence of distraction did not interact, suggesting that participants responded to potential hazards similarly in driving‐only and distraction conditions. In contrast, eye movement results indicated an interaction between distraction and relevance. Drivers attended more to driving‐relevant objects, and these objects showed smaller decrements in number of gazes in the distraction condition, compared with less relevant items. Even under distraction conditions, experienced drivers continued to attend to potential hazards, allocating less attention to billboards and roadway signage. Copyright © 2013 John Wiley & Sons, Ltd.     

The ability of young,middle-aged and older drivers to inhibit visual and auditory distraction in a driving simulator task

Driver distraction is one major cause of road traffic accidents. In order to avoid distraction-related accidents it is important to inhibit irrelevant stimuli and unnecessary responses to distractors and to focus on the driving task, especially when unpredictable critical events occur. Since inhibition is a cognitive function that develops until young adulthood and decreases with increasing age, young and older drivers should be more susceptible to distraction than middle-aged drivers. Using a driving simulation, the present study investigated effects of acoustic and visual distracting stimuli on responses to critical events (flashing up brake lights of a car ahead) in young, middle-aged, and older drivers. The task difficulty was varied in three conditions, in which distractors could either be ignored (perception-only), or required a simple response (detection) or a complex Go-/NoGo-response (discrimination). Response times and error rates to the critical event increased when a simultaneous reaction to the distractor was required. This distraction effect was most pronounced in the discrimination condition, in which the participants had to respond to some of the distracting stimuli and to inhibit responses to some other stimuli. Visual distractors had a stronger impact than acoustic ones. While middle-aged drivers managed distractor inhibition even in difficult tasks quite well (i.e., when responses to distracting stimuli had to be suppressed), response times of young and old drivers increased significantly, especially when distractor stimuli had to be ignored. The results demonstrate the high impact of distraction on driving performance in critical traffic situations and indicate a driving-related inhibition deficit in young and old drivers.     

Effectiveness of the compensatory strategy adopted by older drivers: Difference between professional and non-professional drivers

It has been a controversial issue for the effect of ageing population on driving safety. Apparently, drivers’ physiological and cognitive performances deteriorate with age. However, older drivers may compensate for the elevated risk by adjusting their behaviors, known as compensatory strategy. Despite the extensive research on this topic, the compensatory strategy of older professional drivers is not well understood since many studies focused on the differences in compensatory behavior between older and young drivers. Professional drivers tend to be more skillful and able to cope with the unfavorable driving environments, thus presenting a higher capability to mitigate the risk. This study attempts to examine the compensatory behavior and its safety effect amongst older professional drivers, as compared to those of older non-professional drivers, using the driving simulator approach. In the driving simulator experiment, participants were asked to follow a leading vehicle for one hour, and two sudden brake events were presented. 41 (mid-aged and older) drivers completed the driving tests. Each participant was required to complete a car-following test, either under high or low traffic flow conditions. Performance indicators include driving capability (i.e. lateral control, longitudinal control, and brake reaction time) and compensatory behavior (i.e. average speed, and time headway). Additionally, two modified traffic conflict measures: time exposed time-to-collision (TET) and time integrated time-to-collision (TIT) are applied to indicate the traffic conflict risk. The random parameter Tobit models were estimated to measure the association between conflict risk and driver attributes, and random intercept models were used to assess other driving performance indicators. Results show that despite the impaired lateral control performance and longer brake reaction time of older drivers, the likelihood of severe traffic conflict of older drivers is lower than that of mid-aged drivers. Furthermore, though both older professional and older non-professional drivers adopted longer time headway, the reduction in the risk of severe traffic conflict is more profound among the older professional drivers. Such findings suggest that older professional drivers are more capable of mitigating the possible collision risk by adopting the compensatory strategy, as compared to older non-professional drivers. This justifies the existence of compound effect by the compensatory strategy of older driver and better driving skills of professional driver. This research provides useful insights into driver training and management strategies for employers, as older drivers would become a major cohort in the transportation industry.     

Effects of distraction and experience on situation awareness and simulated driving

This study examined the impact of cell phone conversation on situation awareness and performance of novice and experienced drivers. Driving performance and situation awareness among novice drivers ages 14–16 (n = 25) and experienced drivers ages 21–52 (n = 26) were assessed using a driving simulator. Performance was measured by the number of driving infractions committed: speeding, collisions, pedestrians struck, stop signs missed, and centerline and road edge crossings. Situation awareness was assessed through a query method and through participants’ performance on a direction-following task. Cognitive distractions were induced through simulated hands-free cell phone conversations. The results indicated that novice drivers committed more driving infractions and were less situationally aware than their experienced counterparts. However, the two groups suffered similar decrements in performance during the cell phone condition. This study provides evidence of the detrimental effects of cell phone use for both novice and experienced drivers. These findings have implications for supporting driving legislation that limits the use of cell phones (including hands-free) in motor vehicles, regardless of the driver’s experience level.     

Effect of electronic device use while driving on cardiovascular reactivity

Motor vehicle collisions are the leading cause of death in people ages 5–34 in the US, and secondary task engagement, such as talking on a cell phone, is a leading contributor to motor vehicle collisions. The negative effects of secondary task engagement on driving performance has become a prominent recent topic of study given the increasing amount of time drivers engage in distracted driving. However, few studies have examined the effects of secondary task engagement while driving on health related outcomes such as cardiovascular reactivity. Cardiovascular reactivity, as measured by heart rate and blood pressure, has been used in previous studies as a means of measuring effort in task engagement as well as a means to predict cardiovascular disease and stroke. This study investigates the effect of secondary task (talking on a cell phone, texting, and driving with no task) while driving in a simulator on cardiovascular reactivity. Using difference scores between baseline (a period of inactivity) and stimulus (driving with no task and driving with secondary tasks), a repeated measures analysis of variance using a mixed model approach was used to determine the effect of secondary task on cardiovascular reactivity. Findings indicated that talking on a cell phone while driving significantly increased cardiovascular reactivity via heart rate and blood pressure compared to driving with no task. Texting while driving did not differ significantly from driving with no task. This study demonstrates the need for more research on the long term effects of secondary tasks while driving on cardiovascular reactivity and for assessing the risks associated with secondary task use while driving on developing cardiovascular disease or stroke.     

The effect of a simulated hearing loss on performance of an auditory memory task in driving

Hearing loss has been shown to exacerbate the effect of auditory distraction on driving performance in older drivers. This study controlled for the potentially confounding factor of age-related cognitive decrements, by applying a simulated hearing loss in young, normally hearing individuals. Participants drove a simulated road whilst completing auditory tasks under simulated hearing loss or normal hearing conditions. Measures of vehicle control, eye movements and auditory task performance were recorded. Results showed that performing the auditory tasks whilst driving resulted in more stable lateral vehicle control and a reduction in gaze dispersion around the road centre. These trends were not exacerbated by simulated hearing loss, suggesting no effect of hearing loss on vehicle control or eye movement patterns during auditory task engagement. However, a small effect of simulated hearing loss on the performance of the most complex auditory task was observed during driving, suggesting that the use of sound-based in-vehicle systems may be problematic for hearing impaired individuals. Further research incorporating a wider variety of driving scenarios and auditory tasks is required in order to confirm the findings of this study.     

The impact of cognitive functioning on driving performance of older persons in comparison to younger age groups: A systematic review

Older drivers are at a severely higher risk for motor vehicle crash involvement. Due to the global aging of the population, this increased crash risk has a significant impact on society, as well as on an older individual’s quality of life. For this reason, there is a need for understanding how normal age-related changes in cognition and underlying brain dynamics impact driving performance to identify the functional and neurophysiological biomarkers that could be used to design strategies to preserve or improve safe driving behavior in older persons. This review provides an overview of the literature on age-related changes in cognitive functioning and brain dynamics that impact driving simulator performance of healthy persons. A systematic literature search spanning the last ten years was conducted, resulting in 22 eligible studies. Results indicated that various aspects of cognition, most importantly executive function, complex attention, and dual tasking, were associated with driving performance, irrespective of age. However, there was a distinct age-related decline in cognitive and driving performance. Older persons had a more variable, less consistent driving simulator performance, such as more variable speed adaptation or less consistent lane keeping behavior. Only a limited number of studies evaluated the underlying brain dynamics in driving performance. Therefore, future studies should focus on implementing neuroimaging techniques to further unravel the neural correlates of driving performance.     

Physiological indicators of driver workload during car-following scenarios and takeovers in highly automated driving

This driving simulator study, conducted as a part of Horizon2020-funded L3Pilot project, investigated how different car-following situations affected driver workload, within the context of vehicle automation. Electrocardiogram (ECG) and electrodermal activity (EDA)-based physiological metrics were used as objective indicators of workload, along with self-reported workload ratings. A total of 32 drivers were divided into two equal groups, based on whether they engaged in a non-driving related task (NDRT) during automation (SAE Level 3) or monitored the drive (SAE Level 2). Drivers in both groups were exposed to two counterbalanced experimental drives, lasting ∼ 18 min each, of Short (0.5 s) and Long (1.5 s) Time Headway conditions during automated car-following (ACF), which was followed by a takeover that happened with or without a lead vehicle. Results showed that driver workload due to the NDRT was significantly higher than both monitoring the drive during ACF and manual car-following (MCF). Furthermore, the results indicated that a lead vehicle maintain a shorter THW can significantly increase driver workload during takeover scenarios, potentially affecting driver safety. This warrants further research into understanding safe time headway thresholds to be maintained by automated vehicles, without placing additional cognitive or attentional demands on the driver. Our results indicated that ECG and EDA signals are sensitive to variations in workload, which warrants further investigation on the value of combining these two signals to assess driver workload in real-time, to help future driver monitoring systems respond appropriately to the limitations of the driver, and predict their performance in the driving task, if and when they have to resume manual control of the vehicle after a period of automated driving.