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Abstract

Our research examined the effects of hands-free cell-phone conversations on simulated driving. We found that even when participants looked directly at objects in the driving environment, they were less likely to create a durable memory of those objects if they were conversing on a cell phone. This pattern was obtained for objects of both high and low relevance, suggesting that very little semantic analysis of the objects occurs outside the restricted focus of attention. Moreover, in-vehicle conversations do not interfere with driving as much as cell-phone conversations do, because drivers are better able to synchronize the processing demands of driving with in-vehicle conversations than with cell-phone conversations. Together, these data support an inattention-blindness interpretation wherein the disruptive effects of cell-phone conversations on driving are due in large part to the diversion of attention from driving to the phone conversation.

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... Drivers' mood changes thought stress that has been studied to understand its impacts on driving as a whole [16,[22][23][24][25][26]. The mood that impacts drivers' attention is an important parameter for safe driving [27][28][29][30][31][32][33]. Thus, it is very crucial to figure out or measure the stress level of the drivers. ...
... Inattention is responsible for unsafe driving, and the percentage sometimes goes beyond 25% [33,59]. On the other hand, conversation in mobile phones, concentrating on mobile phone-based activities, cognitive involvement in conversation, roadside advertisements, etc. has a direct correlation with distraction [8,9,[28][29][30]. Apart from that, drivers' mood and personality have a major effect on the driving behavior and experiences [16,22,23]. ...
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Driving stress can impact the driving performance that has an impact on the overall driving experiences. It is a vital area to focus on when the traffic scenario is challenging in terms of having traffic congestion, unruly drivers, and a lack of law enforcement. In Bangladesh, these issues are frequent on the roads. That is why we looked at self-reported stress scores of professional drivers, their personality analysis and conducted mixed-method (quantitative and qualitative) user studies that provided us a clear indication of driving stress. Then the findings motivated us to design and develop a low-cost real-time stress measurement wearable through human-centered computing, users’ feedback, and experiences. This wearable unit can understand bodily stress from physiological factors using Heart Rate Variability along with road conditions. This technology can help in supporting drivers in increasing self-awareness regarding driving stress, which will have a positive impact on drivers’ wellbeing and overall driving performance.
... Since talking on a phone while driving became increasingly popular, the attentional domain of divided attention is frequently discussed in driving studies (e.g., Becic et al., 2010;McCartt et al., 2006;Strayer and Drews, 2007;Strayer and Drews, 2004;Strayer et al., 2003aStrayer et al., , 2003bStrayer and Johnston, 2001). For example, Strayer and Johnston (2001) show that cell phone conversations but not simply holding a cell phone or listening to audiobooks interferes with detection of traffic lights. ...
... For example, Strayer and Johnston (2001) show that cell phone conversations but not simply holding a cell phone or listening to audiobooks interferes with detection of traffic lights. Additional eye-tracking data indicate a reduced attention to foveal information when talking on a cell phone (Strayer and Drews, 2007). In addition, studies show a relation between deficits in divided attention of older adults and poorer performance on a driving test (De Raedt and Ponjaert-Kristoffersen, 2000), increased crash involvement (Owsley et al., 1998), as well as a reduced recognition of road signs (Chaparro et al., 2005). ...
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Converging evidence from numerous previous studies highlights the relevance of attention in driving. However, these studies mostly conclude from respective situations or use complex tests that tap into further cognitive processes. Aiming a better understanding of specific attentional domains, we investigated the relation between visual selective attention, auditory selective attention, visual divided attention, switching attentional demands, switching between attributes, switching between rules, vigilance and driving performance in a driving simulator. Furthermore, we tested three-way interaction effects with respective attentional domains, inhibition and working memory. In the present study, 123 participants completed a driving scenario as well as commonly used measures of attention (SwAD-task, Oddball-task, MCST, TMT-B, D2), inhibition (Go/NoGo-task), and working memory (visual digit-span-task). Findings indicate no correlations between the tested attentional domains and driving performance. Furthermore, we found no interaction effects with the attentional domains and the two factors of inhibition and working memory on simulator driving performance. The present findings suggest no possibility to transfer findings from specific attentional domains, as well as the used measures for inhibition, and working memory to peoples' simulator driving performance. Along with previous findings we suggest using rather context-specific tasks than basic neuropsychological measures to quantify specific attentional domains, in order to predict peoples' driving performance.
... In this scenario, drivers simultaneously operate and control the movement of a vehicle on a roadway (Fuller, 2005), and exchange verbal information with an interlocutor (Levinson & Torreira, 2015). As demands of the driving and verbal tasks increase, the ability of drivers to divide attention between tasks may degrade (Becic et al., 2010;Strayer & Drews, 2007;Strayer, Biondi, et al., 2017;; this can result in an increased risk for fatal car crashes (National Center for Statistics and Analysis, 2021). ...
... In both experiments, we found that performance on the tracking task was worse overall in conditions in which a verbal task was present compared to when there was no verbal task. This result replicates previous findings about interference between conversation and driving (Strayer & Drews, 2007;. ...
Article
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We report results from a driving simulator paradigm we developed to test the fine temporal effects of verbal tasks on simultaneous tracking performance. A total of 74 undergraduate students participated in two experiments in which they controlled a cursor using the steering wheel to track a moving target and where the dependent measure was overall deviation from target. Experiment 1 tested tracking performance during slow and fast target speeds under conditions involving either no verbal input or output, passive listening to spoken prompts via headphones, or responding to spoken prompts. Experiment 2 was similar except that participants read written prompts overlain on the simulator screen instead of listening to spoken prompts. Performance in both experiments was worse during fast speeds and worst overall during responding conditions. Most significantly, fine scale time-course analysis revealed deteriorating tracking performance as participants prepared and began speaking and steadily improving performance while speaking. Additionally, post-block survey data revealed that conversation recall was best in responding conditions, and perceived difficulty increased with task complexity. Our study is the first to track temporal changes in interference at high resolution during the first hundreds of milliseconds of verbal production and comprehension. Our results are consistent with load-based theories of multitasking performance and show that language production, and, to a lesser extent, language comprehension tap resources also used for tracking. More generally, our paradigm provides a useful tool for measuring dynamical changes in tracking performance during verbal tasks due to the rapidly changing resource requirements of language production and comprehension.
... The capacity limitations of working memory mean that without the rehearsal of received sensory information, the processing of information is restricted (van Merrienboer & Sweller, 2010). This can lead to an attentional bottleneck where attending to one element of information causes other cognitive processes, and the associated information, to be neglected (Strayer & Drews, 2007). ...
... Controlled processing is needed to complete cognitive tasks that require attention and the management of information (Bargh, 1984). However, this type of processing is slow and effortful and relies on our limited attention capacity (Strayer & Drews, 2007). High levels of focused attention can be accomplished with effort (Bargh, 1984;Schneider & Shiffrin, 1977), but errors occur if an individual cannot meet the mental demands required to effectively complete the tasks (Paas & van Merrienboer, 1993). ...
Article
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Purpose. Although investigative interviewers receive training in interviewing techniques, they often fail to comply with recommended practices. Interviewers are required to actively listen, accurately remember information, think of questions to ask, make judgements, and seek clarification, whilst conducting interviews with witnesses, victims, or suspects. The current study examined the impact of increased cognitive load on mock interviewers' recall of a witness's account. Method. Participants took the role of an investigative interviewer in one of three conditions, high cognitive load (HCL), moderate cognitive load (MCL), or no cognitive load (NCL). Participants watched a video-recorded free narrative of a child witness during which they followed condition-relevant task instructions. Each participant rated their perceived cognitive load during their task and then recalled (free and cued recall) the content of the witness's account. Results. Participants in the HCL and MCL conditions perceived higher cognitive load and demonstrated poorer performance on the free recall task than those in the NCL condition. Participants in the HCL condition demonstrated poorer performance on the cued recall task compared to participants in the NCL condition.
... For example, drivers show increased errors in detection of traffic lights when making a conversation on the cell phone but not when simply holding the phone or listening to audiobooks while driving, which contrasts with reported findings on effects of its mere presence (Strayer and Johnston, 2001). Additional eye-tracking data indicate a reduced attention to foveal information when simultaneously talking on a cell phone, compared to solely driving (Strayer and Drews, 2007). In situations of walking while interacting with a smartphone, participants show a deteriorate awareness of roadside surroundings as well as decreased auditory attention. ...
... However, there are no previous findings regarding long-term effects of smartphone usage on inhibitory control. from various smartphone studies (Caird et al., 2008;Chang and Tang, 2015;Pielot et al., 2014;Sahami Shirazi et al., 2014;Stothart et al., 2015;Strayer and Drews, 2007;Ward et al., 2017). For example, within a recent study, illustrate the interruption potential, by showing an average of 49.05 smartphone screen unlocks every day. ...
Article
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The smartphone has become ubiquity in everyday life. Today, it is no longer the question of what these devices are capable of, but rather on related effects of using it. During recent years, studies increasingly focused on smartphone-related effects on cognitive functions, however, existing findings are limited. Therefore, the present manuscript aims to provide an overview of previous findings but also to highlight existing gaps in the field of smartphone-related effects on attention, inhibition, and working memory. We provide a hypothetical model assuming a differentiation between immediate and long-term effects of smartphone use on respective cognitive functions. It also describes the relations between attention, working memory, and inhibition, which have been extensively studied in the past. The model further suggests a quantification of smartphone usage based on different quantitative parameters, such as usage time, usage frequency, used applications, and received notifications. In addition, individual attributes and situational factors are highlighted as directly influencing attention, inhibition, and working memory, but also moderating smartphone-related effects on respective cognitive functions. Until now, there are many unresolved questions regarding the effects of smartphone usage on specific cognitive functions. However, until these are clarified, and despite a growing literature on adverse effects, it should be kept in mind that a general smartphone use may also have beneficial effects on certain processes of attention, inhibition, and working memory.
... It is now well established that using a mobile phone while driving will compromise driving performance and consequently increase crash risk, including talking and text messaging [11][12][13][14][15][16]. For instance, a number of previous studies have confirmed that communication behavior involving mobile phone use while driving significantly increases cognitive workload [13,17,18]. With regard to mobile phone conversation while driving, it is associated with attention blindness [19], decreased reaction time [11]. ...
... With regard to distracted drivers, LaVoie et al. [23] indicated that social distance is a key factor in talking and text messaging while driving. Their results indicated that teens (15)(16)(17)(18) year-olds) were more likely to talk with parents while driving, while adults (40-60 year-olds) were more likely to talk with their spouse. With regard to text messaging, the results indicated that teens were more likely to text with friends rather than girlfriend/boyfriend or parent, while adults said that they were more likely to text with friends or their children while driving [23]. ...
Article
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Pedestrian safety is alarming worldwide, and it is well validated that distracted walking/crossing involving mobile phone use would significantly compromise pedestrian safety. Some existing studies demonstrated that distracted pedestrians would spend more time to cross street, miss more safe opportunities to cross and pay less attention to the road environment, etc. As a result, they are more likely to be hit by an oncoming vehicle. Specifically, with respect to the distraction results from mobile phone use for communication in road user groups, previous research has examined the relationship between social networks and mobile phone use among drivers and motorcyclists. However, very little similar research was found in the field of pedestrian study. This study performed an online survey to investigate with whom pedestrians were most likely to communicate with while crossing street in a Chinese sample. The association between social networks and self-reported injury/ near miss event was also examined. To provide an insight into the difference in communication pattern between scenarios, the results were compared with the patterns while driving, motorcycling and the general patterns. Results indicate that pedestrians are most likely to communicate with friends (31.2%), followed by spouses (24.5%). Additionally, participants who frequently talk to parents/children have a greater likelihood of being involved in injury/ near miss events than those talk to the others. Compared with the prevalence of mobile phone use among drivers and motorcyclists reported in previous studies, mobile phone use is more prevalent among pedestrians, especially as they are more likely to communicate with colleagues. In sum, the results demonstrate that social networks play an important role in mobile phone use during street crossing, and pedestrians are more likely to communicate with people who are socially closest to them. The effect of social networks on mobile phone use (especially for communication) among pedestrians should be considered in the development of traffic safety countermeasures.
... Therefore, engaging in mind wandering lessens the ability to process information regarding the external environment. Decreased awareness of the external environment could result in dangerous consequences, such as inattentional blindness while driving (Strayer & Drews, 2007). Mason and colleagues (2007) found mind wandering continues during easy and familiar tasks and decreases as tasks become less familiar or more difficult. ...
... Most literature on multitasking while driving revolves around the use of mobile phones. Strayer and Drews (2007) affirm that talking on the mobile phone disrupts attention from the driving task and that these drivers are not as aware of the environment around them. A meta-analysis of 33 studies concludes that the reaction time is slower when talking on the phone than when not (Caird et al., 2008). ...
Article
The use of smartwatches raises a number of questions about their potential for distraction in situations where sustained attention is paramount, like driving a motor vehicle. Our research examines distraction caused by smartwatch use in comparison to mobile phone use while driving. It also studies the difference in distractions caused by inbound text messages versus inbound voice messages, and outbound replies through text messages versus outbound voice replies. A within-subject experiment was conducted in a driving simulator where 31 participants received and answered text messages under four conditions: they received notifications (1) on a mobile phone, (2) on a smartwatch, and (3) on a speaker, and then responded orally to these messages. They also (4) received messages in a “texting” condition where they had to reply through text to the notifications. Eye tracking gaze distribution results show that participants were more distracted in the smartwatch condition than in the mobile phone condition, they were less distracted in the speaker condition than in the phone condition, and they were more distracted in the texting condition than in any of the others. The participants’ driving performance remained the same in all conditions except in the texting condition, wherein it became worse. Eye tracking and pupillometry results suggest that participants’ mental workload might be lower in the texting condition than in the other three conditions, although this result might be caused by a higher number of glances at the device in that condition. This study contributes to a better understanding of the distraction potential of smartwatches as well as identifying vocal assistants as the least distracting way of communicating while driving a vehicle. Industry leaders could become a key factor in informing the public of the smartwatch’s potential for distraction.
... Yet, years of fundamental and applied psychology research have firmly established that Dual-Tasking (DT) leads to a decrement in performance, called the DT interference effect or DT cost : more errors and slower responses (Welford, 1952;Pashler, 1994;Huestegge et al, 2014). Unsurprisingly, this emerging societal trend has raised serious concerns in various fields, ranging from education to road safety (Strayer & Drews, 2007;Zheng et al, 2014, Pashler et al, 2013. ...
Preprint
Dual-tasking is extremely prominent nowadays, despite ample evidence that it comes with a performance cost: the Dual-Task (DT) cost. Neuroimaging studies have established that tasks are more likely to interfere if they rely on common brain regions, but the precise neural origin of the DT cost has proven elusive so far, mostly because fMRI does not record neural activity directly and cannot reveal the key effect of timing, and how the spatio-temporal neural dynamics of the tasks coincide. Recently, DT electrophysiological studies in monkeys have recorded neural populations shared by the two tasks with millisecond precision to provide a much finer understanding of the origin of the DT cost. We used a similar approach in humans, with intracranial EEG, to assess the neural origin of the DT cost in a particularly challenging naturalistic paradigm which required accurate motor responses to frequent visual stimuli (task T1) and the retrieval of information from long-term memory (task T2), as when answering passengers’ questions while driving. We found that T2 elicited neuroelectric interferences in the gamma-band (>40 Hz), in key regions of the T1 network including the Multiple Demand Network. They reproduced the effect of disruptive electrocortical stimulations to create a situation of dynamical incompatibility, which might explain the DT cost. Yet, participants were able to flexibly adapt their strategy to minimize interference, and most surprisingly, reduce the reliance of T1 on key regions of the executive control network – the anterior insula and the dorsal anterior cingulate cortex – with no performance decrement. HIGHLIGHTS - First direct evidence in humans of neural interferences between two tasks. - First explanation of the Dual-Task cost at the neural level in humans. - First Dual-Tasking study with intracranial EEG in naturalistic conditions.
... The dynamics of driving a vehicle while performing a non-driving-related task (NDRT) is an area of critical importance for human-factors investigations of crash risk (e.g., [1][2][3]), user interface design (e.g., [4]), and behavior when automated support systems are engaged (e.g., [5,6]). Though several studies have shown an increase in driver distraction during various NDRTs (e.g., [7]), engagement in NDRTs is relatively common while crashes are still relatively rare [8]-this apparent paradox can potentially be better understood by looking at the interplay between NDRT behaviors and the conditions under which they occur. There are many factors that may influence drivers' decisions to engage in NDRTs in real world conditions, including traffic, weather, road type and vehicle speed, which has long been believed to be an important variable [9]. ...
Article
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Non-driving-related tasks (NDRTs) have the potential to affect safety in a number of ways, but the conditions under which drivers choose to engage in NDRTs has not been extensively studied. This analysis considers naturalistic driving data in which drivers were recorded driving and engaging in NDRTs at will for several weeks. Using human-annotated video captured from vehicle cabins, we examined the probabilities with which drivers engaged in NDRTs, and we examined the relationship between vehicle speed and NDRT probability, with the goal of modeling NDRT probability as a function of speed and type of NDRT observed. We found that tasks that contain significant visual and manual components, such as phone manipulation, show strong sensitivity to vehicle speed, while other tasks, such as phone conversation, show no effects of vehicle speed. These results suggest that there are systematic relationships between NDRT patterns and vehicle speed, and that the nature of these relationships is sensitive to the demands of the NDRT. The relationship between speed and NDRT probability has implications for understanding the effects of NDRTs on safety, but also for understanding how drivers may differ in terms of the strategies they employ to modulate their NDRT behaviors based upon driving demands.
... DSM systems have traditionally been applied during manual driving scenarios to detect fatigue and inattention. Situations such as night-time driving (Phipps-Nelson et al., 2011), prolonged driving (Finkleman, 1994), and extreme temperatures (Xianglong et al., 2018) can induce fatigue; whereas mobile phones (Strayer and Drews, 2007), in-vehicle systems (Arexis et al., 2017), and eating (Tay and Knowles, 2004) can induce inattention. In a manual driving scenario, a DSM system can use remote sensors to monitor fatigue behaviors such as prolonged eyelid closures and yawning. ...
Article
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Driving cessation for some older adults can exacerbate physical, cognitive, and mental health challenges due to loss of independence and social isolation. Fully autonomous vehicles may offer an alternative transport solution, increasing social contact and encouraging independence. However, there are gaps in understanding the impact of older adults' passive role on safe human-vehicle interaction, and on their well-being. 37 older adults (mean age ± SD = 68.35 ± 8.49 years) participated in an experiment where they experienced fully autonomous journeys consisting of a distinct stop (an unexpected event versus an expected event). The autonomous behavior of the vehicle was achieved using the Wizard of Oz approach. Subjective ratings of trust and reliability, and driver state monitoring including visual attention strategies (fixation duration and count) and physiological arousal (skin conductance and heart rate), were captured during the journeys. Results revealed that subjective trust and reliability ratings were high after journeys for both types of events. During an unexpected stop, overt visual attention was allocated toward the event, whereas during an expected stop, visual attention was directed toward the human-machine interface (HMI) and distributed across the central and peripheral driving environment. Elevated skin conductance level reflecting increased arousal persisted only after the unexpected event. These results suggest that safety-critical events occurring during passive fully automated driving may narrow visual attention and elevate arousal mechanisms. To improve in-vehicle user experience for older adults, a driver state monitoring system could examine such psychophysiological indices to evaluate functional state and well-being. This information could then be used to make informed decisions on vehicle behavior and offer reassurance during elevated arousal during unexpected events.
... Cell phone distraction represents a national safety concern, particularly with texting while driving (Strayer & Drews, 2007). The nature of cell phone distraction has been studied extensively, equating this distraction to failures of visual attention (Harbluk, Noy, Trbovich, & Eizenman (2007). ...
Conference Paper
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Within this study, facial expressions before, during, and after completion of a texting demand while driving were measured using Noldus Face Reader. Measurements were taken during naturalistic or real-life driving conditions, offering enhanced ecological validity for the present study. There was not a significant effect for means across seven emotional states before, during, and after completion of a texting demand, specifically Anger, Neutral, Happy, Sad, Surprised, Scared, and Disgusted using ANOVA. However, for Valence, mean differences were statistically significant. Additional analyses did suggest statistically-significant differences in Anger and Valence before and during texting distraction periods, and there were significant differences in Anger, Sad, and Valence before and after a texting-based distraction. Results propose that rumination on some negative thoughts and emotions occurs in the context of driving and texting for some negative emotions but not for others. In contrast, contemplation on positive thoughts does not vary regarding the presence or absence of a texting demand. Such rumination may explain why texting while driving has been associated with deterioration of driving performance. This argument should be developed in additional research.
... Extensive research has shown that multitasking while driving has a negative impact on driving performance: it increases reaction times (Saifuzzaman et al., 2015;Strayer & Drew, 2004), affects lane position and vision, (Saifuzzaman et al., 2015;Stavrinos et al., 2013;Wright & Chouinard, 2019) and fluctuation of speed (Strayer & Drews, 2007). Recently, in a systematic review, Palmiero and colleagues (2019) showed how the brain activations associated with driving decrease when a secondary task is added. ...
Article
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Road traffic accidents have emerged as an important public health issue. In 2019, the 27 EU Member States reported more than 22,800 road fatalities. In Italian context, 3,173 people were killed in road accidents, whose 13.89% were under 25. Driving distraction is the leading cause of driving accidents (ISTAT in Road Accident 2019, 2020), particularly due to the driver engagement in secondary tasks, such as smartphone usage. Although many studies have investigated the effects of mobile phone use when driving, few have studied the psychological variables underlying such behaviors. Therefore, the reasons why people take these risk behaviors, in particular young drivers, are still unclear. This study attempts to investigate the effects of certain variables—such as attitude toward multitasking, risk perception, self-efficacy, sensation seek- ing—on using a mobile phone while driving. Data for this study were collected from different Italian High Schools; 1498 young drivers. (43.3% females) completed a driving survey (age 14–21; M = 17.11 and DS = 1.52). We found the aptitude for using a mobile phone while driving is largely explained by the variables that we have considered. Furthermore, multi-group analyses showed that, although multitasking while driving is common for all teenagers.
... 1. the study of human factors involved in the driving tasks (Ericson et al., 2014), 2. the influence of mood altering substances such as alcohol and drugs (Liguori and Robinson, 2001;Brookhuis et al., 2004), 3. the study of driving performance of special populations such as the elderly, or young drivers (Lee et al., 2003;Brouwer et al., 1991), 4. the design and assessment of in-vehicle systems like GPS (Horberry et al., 2006), 5. the effects of distracted driving (Strayer and Drews, 2007), 6. the impact of roadway geometric designs on driver behavior (Ben-Bassat and Shinar, 2011), and 7. and the study of motorcyclists lane position as a factor in right-of-way violation (Sager et al., 2014), among numerous others. ...
Article
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The long and tragic history of bicycle/vehicle collisions has led to calls for legislative action to provide greater safety for bicyclists on the roadways. In the United States, “Three-foot bicycle passing laws,” are among the most common. In general, these laws require motor vehicles overtaking or passing bicyclists to do so by providing a minimum of 3 ft of lateral separation. The goal of this paper was to investigate how these laws substantively affect driver behavior. In this paper, a driving simulator was used to quantify the overtaking behavior, in terms of lateral overtaking distance and speed, of drivers in the vicinity of bicyclists. Study participants included drivers both aware and unaware of these laws. The research also examined the behavior of participants under varying traffic conditions. The results showed a tendency of drivers to provide more than the three-foot minimum requirement. This was true for both sets of “aware” and “unaware” drivers. Overall, this research suggests that drivers in the simulated environment tended to behave similarly regardless of prior knowledge of the three-foot law requirements. Materially, the research failed to identify a significant distinction between the two groups of participants under a range of traffic conditions.
... The effects of typing and reading on road safety have been studied in simulators (Rudin- Brown et al., 2013;Stavrinos et al., 2013;Yannis et al., 2014) as well as in closed tracks (Owens et al., 2011;Yager, 2013, Yager et al., 2012. Selecting music on portable music-players (e.g. the iPod) led reduced car-following speed and to lateral deviation from lane center, comparable to that caused by dialing on the mobile phone (Salvucci et al., 2007).On PC-controlled simulated driving, it was found that increased background music led to increased driving speed, speed estimate and increased number of virtual traffic violations such as disregard of traffic lights, lane crossings and collisions (Brodsky, 2001).Mobile phone conversations place have have qualitatively heavier impact upon the driver than that of other auditory/verbal/vocal tasks such as in-vehicle conversations do not interfere with driving as much as cell-phone conversations do (Strayer and Drews, 2007). The probability of mobile phone use was found to be negatively associated with the excess fo speed limits and the number of harsh events (Papadimitriou et al., 2019). ...
... In its graphical presentation, nodes represent random variables and links illustrate relationships and conditional dependencies between variables [21]. The BN's learning procedure employs a training dataset, derived from actual events, to identify the possible connections between nodes to be used for future prediction of unseen data [5]. ...
... Indications suggest that with these technologies, the incidence of distraction-related crashes have escalated and left the driver worse off . Behaviours that contribute to driver inattention and distraction also include eating and drinking while driving, interaction with passengers (Just, 2008), passenger influences (Strayer, 2007 and listening to music (Ünäl, 2012). Inattentiveness while driving is difficult to determine, due to the fact that fatigue, drowsiness and highway hypnosis are also considered as inattentive driving and difficult to observe , Stelling, 2012. ...
Preprint
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The research paper investigates the use of mobile devices (MDs) on South African roads. The advent of technological advancement has become a prevalent force within society as it has shaped the behaviour and psychology of motorists' on our road. The MD is a popular gadget amongst all motorists. Unfortunately, it has created a very unconducive environment for safe driving as motorist are distracted leading to impaired response time of reflexes and poor attention of the road. Despite law enforcement prohibiting the use of the MD while driving motorist still continue behaviour. The research paper has already illicit findings to address the discourse and solving a social problem. Working professionals in the age category 25-34 and 35-49 years old are frequent users of MDs while driving likely due to work pressures and limited time constraints. The removal of the MD is not the solution but rather to integrate the MD with the car. Boredom is the root cause for mobile use while driving. Though having company in the car mitigate the use of the MD. People who MD with greater purpose (professionals, business people) are also more likely to be alone in the car which exacerbates the behaviour.
... In driving, neuroergonomic research of workload may be aspired by different purposes and context, and lead to different contributions. First, it can enable the objective assessment of cognitive demand for certain driving tasks, including the primary and the secondary (Kohlmorgen et al., 2007;Strayer & Drews, 2007), or driving environment (Kim, Jeong, Jung, Park, & Jung, 2013). In (Lei & Roetting, 2011), the frontal theta and the parietal-alpha activation in EEG data were correlated with perceived mental workload. ...
Chapter
The state-of-the-art vehicle automation and navigation technologies promise to augment or even replace diverse human functions in driving. For safety assurance on roadways, vehicles need to be informed about the humans (not only their presence but also mental states) in and around the vehicle. Yet, the uncertainties of drivers’ mental states under varying traffic situations make it difficult to provide such information. In this regard, neuroergonomics have potential to help bridge human and automation toward the next level of integration. In this chapter, we aim to provide an appreciation of neuroergonomic application to driving and navigation, with an emphasis on drivers’ cognitive tasks and performance. Particularly, the four main cognitive constructs associated with driving—attention, situation awareness (SA), intent, and mental workload—are reviewed in terms of their theoretical foundations and recent applications in neuroergonomic studies. The effects of special demographic population and environmental selection for such study are also discussed. To the readers who are interested in understanding the effects of next-generation vehicle technologies on humans or who aspire for the breakthrough in neuroergonomics for new driving and navigation technology, this chapter may provide a useful source.
... On top of that, we perform additional tasks unrelated to the main driving activity: talking to the co-driver or illegally using the cell phone are just two examples. The negative consequences resulting from such multitasking are well documented (Strayer and Drews 2007). Costs occurring from distraction while driving can be longer reaction times in braking, impaired lateral steering control and, related to this, more crashes with other cars or objects Communicated by Melvyn A. Goodale . ...
Article
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The study examined the impact of visual predictability on dual-task performance in driving and tracking tasks. Participants (N = 27) performed a simulated driving task and a pursuit tracking task. In either task, visual predictability was manipulated by systematically varying the amount of advance visual information: in the driving task, participants drove at night with low beam, at night with high beam, or in daylight; in the tracking task, participants saw a white line that specified the future target trajectory for 200, 400 or 800 ms. Concurrently with driving or tracking, participants performed an auditory task. They had to discriminate between two sounds and press a pedal upon hearing the higher sound. Results show that in general, visual predictability benefited driving and tracking; however, dual-task driving performance was best with highest visual predictability (daylight), dual-task tracking performance was best with medium visual predictability (400 ms). Braking/reaction times were higher in dual tasks compared to single tasks, but were unaffected by visual predictability, showing that its beneficial effects did not transfer to the auditory task. In both tasks, manual accuracy decreased around the moment the foot pressed the pedal, indicating interference between tasks. We, therefore, conclude that despite a general beneficial impact of predictability, the integration of visual information seems to be rather task specific, and that interference between driving and audiomotor tasks, and tracking and audiomotor tasks, seems comparable.
... Distracted driving may also reduce the proficiency of the traffic network by increasing the headway between vehicles unreasonably [73]. Studies about distracted driving showed that talking on a hand-held cell phone while driving harms the drivers' capability to sustain their speed and location on the road [14], [74]; texting while driving increases reaction times to push the brake and increases the variability of lane changing with no change in speed [58], [67]. ...
... This finding is consistent with literature showing the negative impact of high cognitive workload on primary task performance and response times. In the studies by Biondi, Strayer, and colleagues, for example, greater driver cognitive workload induced by performing concurrent mental activities resulted in slower responses in a braking task (Rossi et al., 2012;Strayer et al., 2006) and overall lower driving accuracy Strayer & Drews, 2007). ...
Article
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Objective This study investigates the effect of cognitive overload on assembly task performance and muscle activity. Background Understanding an operator’s cognitive workload is an important component in assessing human–machine interaction. However, little evidence is available on the effect that cognitive overload has on task performance and muscle activity when completing manufacturing tasks. Method Twenty-two volunteers completed an assembly task while performing a secondary cognitive task with increasing levels of demand ( n-back). Performance in the assembly task (completion times, accuracy), muscle activity recorded as integrated electromyography (EMG), and self-reported workload were measured. Results Results show that the increasing cognitive demand imposed by the n-back task resulted in impaired assembly task performance, overall greater muscle activity, and higher self-reported workload. Relative to the control condition, performing the 2-back task resulted in longer assembly task completion times (+10 s on average) and greater integrated EMG for flexor carpi ulnaris, triceps brachii, biceps brachii, anterior deltoid, and pectoralis major. Conclusion This study demonstrates that working under high cognitive load not only results in greater muscle activity, but also affects assembly task completion times, which may have a direct effect on manufacturing cycle times. Application Results are applicable to the assessment of the effects of high cognitive workload in manufacturing.
... MPUWD is thought to increase cognitive load (e.g., interacting with the hardware and software, people, and other media) making it difficult to attend to the primary task of driving (Strayer and Drews, 2007). Phone conversations lack the visual cues inherent to face-to-face communication and have degraded auditory information; text messages have even less auxiliary information. ...
... On the other hand, there is empirical evidence that resource allocation policy can be influenced, and consequently that resources can be unevenly distributed among tasks. For instance, instructing participants to put more emphasis on one vs. the other task (Lehle and Hubner 2009;Tsang 2006), different perceptions of potential outcome value and the saliency of tasks (Schmidt and Dolis 2009;Wickens et al. 2003Wickens et al. , 2015Wickens and Colcombe 2007), or distractions during dual-task execution (Strayer and Drews 2007) can impact resource allocation policy. However, these studies do not report what implications such an allocation policy might have for the other task which is why further attention should be given to potential drivers of resource reduction and allocation in order to optimize dual-task behavior (Salvucci and Taatgen 2008;Tombu and Jolicoeur 2003). ...
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The aim of this study was to examine the impact of predictability on dual-task performance by systematically manipulating predictability in either one of two tasks, as well as between tasks. According to capacity-sharing accounts of multitasking, assuming a general pool of resources two tasks can draw upon, predictability should reduce the need for resources and allow more resources to be used by the other task. However, it is currently not well understood what drives resource-allocation policy in dual tasks and which resource allocation policies participants pursue. We used a continuous tracking task together with an audiomotor task and manipulated advance visual information about the tracking path in the first experiment and a sound sequence in the second experiments (2a/b). Results show that performance predominantly improved in the predictable task but not in the unpredictable task, suggesting that participants did not invest more resources into the unpredictable task. One possible explanation was that the re-investment of resources into another task requires some relationship between the tasks. Therefore, in the third experiment, we covaried the two tasks by having sounds 250 ms before turning points in the tracking curve. This enabled participants to improve performance in both tasks, suggesting that resources were shared better between tasks.
... Cognitive distraction can also be measured through a variety of driver-based, physiological indicators. Among these, brain activity [185] and pupil diameter may be the most convincing. Studies of EDA and HR show only weak relationships between these indicators and cognitive distraction [61]. ...
Article
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Road vehicle accidents are mostly due to human errors, and many such accidents could be avoided by continuously monitoring the driver. Driver monitoring (DM) is a topic of growing interest in the automotive industry, and it will remain relevant for all vehicles that are not fully autonomous, and thus for decades for the average vehicle owner. The present paper focuses on the first step of DM, which consists of characterizing the state of the driver. Since DM will be increasingly linked to driving automation (DA), this paper presents a clear view of the role of DM at each of the six SAE levels of DA. This paper surveys the state of the art of DM, and then synthesizes it, providing a unique, structured, polychotomous view of the many characterization techniques of DM. Informed by the survey, the paper characterizes the driver state along the five main dimensions-called here "(sub)states"-of drowsiness, mental workload, distraction, emotions, and under the influence. The polychotomous view of DM is presented through a pair of interlocked tables that relate these states to their indicators (e.g., the eye-blink rate) and the sensors that can access each of these indicators (e.g., a camera). The tables factor in not only the effects linked directly to the driver, but also those linked to the (driven) vehicle and the (driving) environment. They show, at a glance, to concerned researchers, equipment providers, and vehicle manufacturers (1) most of the options they have to implement various forms of advanced DM systems, and (2) fruitful areas for further research and innovation.
... When the ego vehicle was 150 m before the center of the intersection, a test assistant in the ego vehicle arranged secondary tasks for the participants, and these tasks were divided into three types of secondary tasks [29]: one-back, two-back [30], and clock tasks. ese chosen surrogate secondary tasks consumed the drivers' cognition and easily distracted them, and they were also easy to implement. ...
Article
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Distracted driving has become a growing traffic safety concern. With advances in autonomous driving and connected vehicle technology, a mixture of various types of intelligent vehicles will become normal in the near future, while more factors that may cause driver cognitive distraction are emerging. However, there are rarely studies on distracted driving in mixed traffic environments. To fill this gap, we conducted a natural driving experiment with three representative events at a nonsignalized intersection in a mixed traffic environment and proposed a novel method of identifying cognitive distraction based on bidirectional long short-term memory (Bi-LSTM) with attention mechanism. Forty participants were recruited for each event, who completed three different cognitive distraction experiments induced by three different secondary tasks in contrast with a normal driving process when passing a nonsignalized intersection. Related driving performance and eye movement data were collected to train and test the Bi-LSTM with attention mechanism model. Compared with the support vector machine (SVM) model, its recognition accuracy rate is 94.33%, which is 3.83% higher than that of the SVM in the total event, which has reasonable applicability for distraction recognition in a mixed traffic environment. Potential applications of this model include distraction alarm and autonomous driving assistance systems, which could avoid road traffic accidents.
... On PC-controlled simulated driving, it was found that increased background music led to increased driving speed, speed estimate and increased number of virtual traffic violations such as disregard of traffic lights, lane crossings and collisions (Brodsky, 2001). Mobile phone conversations have qualitatively heavier impact upon the driver than that of other auditory/ verbal/vocal tasks such as in-vehicle conversations (Strayer and Drews, 2007). The probability of mobile phone use was found to be negatively associated with the excess of speed limits and the number of harsh events (Papadimitriou et al., 2019). ...
Article
Risk-taking behavior is often held responsible for increased crash involvement. We designed and undertook a face-to-face road survey (N = 459) in order to explore incident involvement history, driving attitudes and perceived risk among e-scooter users is Paris, France. Three risk factors were specifically explored: (i) riding after having consumed alcohol, (ii) riding after having consumed drugs, and (iii) using the smartphone while riding. The relationship between these factors and user attributes (such as age and gender) and travel behavior (such as frequency of e-scooter usage and trip duration) was examined using logit and mixed logit specifications and a structural equation model. Empirical evidence suggests that it is more likely for young and male riders to develop risky behaviors. Longer trip durations seem to be associated with risk-taking behaviors.
... The cognitive limitation also increases due to the lack of capability of not reading the information on a smartphone properly. The use of a smartphone while driving results in inattention blindness because drivers are unable to see up to 50% of the road-related information [32,33]. ...
... Therefore, additional monitoring techniques need to be introduced. It has been shown that identifying external objects, like mobile phones [16], coffee cups, and overall driver posture classification and facial features extraction is of great importance for driver's general distraction drowsiness level estimation. There is evidence that drowsiness is likely to happen between 6:00 a.m. and 9:00 a.m., and the first hour of a human's work shift [17]. ...
... Cognitive distraction can also be measured through a variety of driver-based, physiological indicators. Among these, brain activity (210) and pupil diameter may be the most convincing. Studies of EDA and HR show only weak relationships between these indicators and cognitive distraction (244). ...
Preprint
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Road-vehicle accidents are mostly due to human errors, and many such accidents could be avoided by continuously monitoring the driver. Driver monitoring (DM) is a topic of growing interest in the automotive industry, and it will remain relevant for all vehicles that are not fully autonomous, and thus for decades for the average vehicle owner. The present paper focuses on the first step of DM, which consists in characterizing the state of the driver. Since DM will be increasingly linked to driving automation (DA), this paper presents a clear view of the role of DM at each of the six SAE levels of DA. This paper surveys the state of the art of DM, and then synthesizes it, providing a unique, structured, polychotomous view of the many characterization techniques of DM. Informed by the survey, the paper characterizes the driver state along the five main dimensions--called here "(sub)states"--of drowsiness, mental workload, distraction, emotions, and under the influence. The polychotomous view of DM is presented through a pair of interlocked tables that relate these states to their indicators (e.g., the eye-blink rate) and the sensors that can access each of these indicators (e.g., a camera). The tables factor in not only the effects linked directly to the driver, but also those linked to the (driven) vehicle and the (driving) environment. They show, at a glance, to concerned researchers, equipment providers, and vehicle manufacturers (1) most of the options they have to implement various forms of advanced DM systems, and (2) fruitful areas for further research and innovation.
... Interacting with a smartphone 1 (e.g., reading or writing a message) can quite obviously lead to visual/manual distraction that impairs drivers' performance (Caird et al., 2008(Caird et al., , 2014Dumitru et al., 2018;Ortiz et al., 2018). But smartphones might also produce cognitive distraction with comparable effects on drivers' performance and road safety (Strayer, 2015) although the driver's eyes are on the roadway and his/her hands are on the steering wheel (Strayer et al., 2003;Strayer and Drews, 2007). Indeed, in laboratory settings, it has been demonstrated that receiving a notification on a smartphone significantly disrupted performance on attention-demanding tasks, even when the participants did not directly interact with their device (Stothart et al., 2015). ...
Article
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Smartphones are particularly likely to elicit driver distraction with obvious negative repercussions on road safety. Recent selective attention models lead to expect that smartphones might be very effective in capturing attention due to their social reward history. Hence, individual differences in terms of Fear of Missing Out (FoMO) – i.e., of the apprehension of missing out on socially rewarding experiences – should play an important role in driver distraction. This factor has already been associated with self-reported estimations of greater attention paid to smartphones while driving, but the potential link between FoMO and smartphone-induced distraction has never been tested empirically. Therefore, we conducted a preliminary study to investigate whether FoMO would modulate attentional capture by reward distractors displayed on a smartphone. First, participants performed a classical visual search task in which neutral stimuli (colored circles) were associated with high or low social reward outcomes. Then, they had to detect a pedestrian or a roe deer in driving scenes with various levels of fog density. The social reward stimuli were displayed as distractors on the screen of a smartphone embedded in the pictures. The results showed a significant three-way interaction between FoMO, social reward distraction, and task difficulty. More precisely, under attention-demanding conditions (i.e., high-fog density), individual FoMO scores predicted attentional capture by social reward distractors, with longer reaction times (RTs) for high rather than low social reward distractors. These results highlight the importance to consider reward history and FoMO when investigating smartphone-based distraction. Limitations are discussed, notably regarding our sample characteristics (i.e., mainly young females) that might hamper the generalization of our findings to the overall population. Future research directions are provided.
Article
Background: Globally, every 25 seconds, a person dies in a motor vehicle crash (MVC) and 58 people get injured. Adding to the rising distracted-driving rates is the rapid growth of the number of cars in circulation globally. This study examined the proportion of distracted drivers among patients attending orthopaedic fracture clinics, as well as associated factors. Methods: In this large, multicenter, cross-sectional study, we recruited 1,378 patients across 4 Canadian fracture clinics. Eligible patients completed an anonymous questionnaire about distracted driving. We calculated the percentages of specific distractions. Using questionnaire responses and published crash risk odds ratios (ORs), patients were grouped as distraction-prone and distraction-averse. Regression analyses to determine the association of demographic characteristics with distracting behaviors and the odds of being in a distraction-related crash were performed. Results: In total, 1,358 patients (99.7%) self-reported distracted driving. Prevalent distractions included talking to passengers (98.7%), distractions outside the vehicle (95.5%), listening to the radio (97.6%), adjusting the radio (93.8%), and daydreaming (61.2%). Of the 1,354 patients who acknowledged mobile phone distractions, 889 (65.7%) accepted phone calls and continued driving, 675 (49.8%) read electronic messages, and 475 (35.1%) sent electronic messages. Younger age (OR, 0.94 [95% confidence interval (CI), 0.91 to 0.97]; p < 0.001) and household incomes of $80,000 to <$100,000 (OR, 1.92 [95% CI, 1.17 to 3.14]; p = 0.01) and ≥$100,000 (OR, 2.48 [95% CI, 1.57 to 3.91]; p < 0.001) were associated with being in the distraction-prone group. Distraction-prone patients were twice as likely to be in a distraction-related MVC (OR, 1.98 [95% CI, 1.43 to 2.74]; p < 0.001). Of 113 drivers who sustained injuries from MVCs, 20 (17.7%) acknowledged being distracted. Of 729 patients who reported being the driver in a previous MVC in their lifetime, 226 (31.0%) confirmed being distracted. Conclusions: This survey-based study showed that driving distractions were near universally acknowledged. The pervasiveness of distractions held true even when only the more dangerous distractions were considered. One in 6 patients in MVCs reported being distracted in their current crash, and 1 in 3 patients disclosed being distracted in an MVC during their lifetime.
Chapter
Digital distractions are an important and prevalent aspect of college students' lives. Using a self-regulated learning perspective, this chapter provides an in-depth understanding of students' digital distractions in academic settings and highlights how college instructors can empower their students to manage digital distractions and self-regulate their own learning. In particular, the chapter discusses both the causes and consequences of engaging in digital distractions with a focus on the impact of multitasking. In addition, the chapter argues that students' engagement in digital distractions is closely connected to their motivation and emotions. This chapter highlights how college students can regulate their digital distractions throughout the learning process during each phase of self-regulated learning. Finally, the chapter reviews the ways college instructors can support students' management of distractions through their instructional approaches.
Article
Ubiquitous mobile technology is part of contemporary life, bringing with it the potential for distraction and reduction in performance associated with multitasking. The predisposition toward dysfunctional multitasking may be shaped in part by beliefs that individuals hold about memory and attention. The issue is particularly pressing for college students, given established links between distraction, multitasking and learning. This project assessed the impact of an online learning module on beliefs about attention, memory, and learning in college students. It also contrasted these beliefs in a college and non‐college community sample. Significant reductions in counterproductive beliefs were associated with completing the module; counterproductive beliefs were also no more prevalent in the college vs. the non‐college sample. Our findings suggest that brief online modules are a practical way to address counterproductive beliefs related to multitasking with technology, and add to the literature on metacognition, attention and multitasking in college and non‐college populations. This article is protected by copyright. All rights reserved.
Article
Commuting is a central activity of life that cuts across industries and occupations. Because a large majority of employees commute to work, organizational scholars have long been interested in the relevance of commuting to organizational life. This interest forms the foundation of a research tradition to understand commuting spillover, which reflects inter‐relationships between commuting and work experiences. Unfortunately, commuting spillover investigations have historically been fractured across publications in the management, psychology, transportation, and ergonomics communities, impeding understanding of the nature and implications of commuting spillover for organizational stakeholders. We conduct a systematic review to identify what is known and unknown about commuting spillover, attending to both between‐ and within‐person approaches to studying this process. This effort yields five major conclusions emerging from the commuting spillover literature, as well as the identification of two frequently investigated topics that have yielded few clear findings within this research base. This knowledge synthesis is used to develop an agenda for the next wave of commuting spillover research that aims to extend this research base while resolving inconsistencies observed in past research. We conclude with calls for methodological advancement and theory development on the commuting spillover topic.
Article
Aviation places significant demands on pilots' perceptual and attentional capacities. The avoidance of other objects both on the ground and in the air is critical to safe flight. Research on automobile driving has revealed the occurrence of ‘inattentional blindness’ (IB) whereby objects clearly located within the visual field may not detected when drivers are concurrently engaged in another attention capturing task such as a cellphone conversation. Almost no comparable research has been conducted within the aviation domain despite the significance of both ground-based and mid-air collisions. The present study was designed to investigate the effects of diverting attentional resources away from the primary task of safely flying a simulated light aircraft from takeoff to cruising. Flight naïve students were trained to proficiency in a flight-simulator and flew two simulated flights with and without a competing attentional task. Detection of a variety of objects placed in the background was measured. The results showed that when distracted by an engaging cellphone conversation novice pilots failed to detect many of the objects located within the visual scene. Recognition accuracy was greater when pilots' attention was not diverted elsewhere. There was a reduction in time spent looking at some key flight instruments but not on others. Inattentional blindness poses significant flight safety risks and further research into both the stimulus and perceiver characteristics that promote or reduce inattentional blindness would be of significant benefit to aviation safety.
Article
Distracted driving is known to be one of the main causes of crashes in the United States, accounting for about 40% of all crashes. Drivers’ situational awareness, decision-making, and driving performance are impaired as a result of temporarily diverting their attention from the primary task of driving to other unrelated tasks. Detecting driver distraction would help in adapting the most effective countermeasures. To tackle this problem, we employed a random forest (RF) classifier, one of the best classifiers that has attained promising results for a wide range of problems. Here, we trained RF using the data collected from a driving simulator, in which 92 participants drove under six different distraction scenarios of handheld calling, hands-free calling, texting, voice command, clothing, and eating/drinking on four different road classes (rural collector, freeway, urban arterial, and local road in a school zone). Various driving performance measures such as speed, acceleration, throttle, lane changing, brake, collision, and offset from the lane center were investigated. Using the RF method, we achieved 76.5% prediction accuracy on the independent test set, which is over 8.2% better than results reported in previous studies. We also obtained a 76.6% true positive rate, which is 14% better than those reported in previous studies. Such results demonstrate the preference of RF over other machine learning methods to identify driving distractions.
Article
This paper presents a novel soft vibrotactile interface with a wide acceleration bandwidth that can be applied to a curved surface, such as a steering wheel. This haptic interface utilizes the surface charge-inducing characteristic of polyvinyl chloride (PVC) gel and adopts a design where hydraulic pressure is induced upon actuation. This working principle significantly increases the output force of the device, which enables a high-performance haptic interface. In addition, the small contact angle due to its curved shape was analyzed as an important parameter for high-frequency performance. Results showed that the proposed haptic interface can generate sufficient acceleration performance (>3 G) over a broad frequency range (90700 Hz) with a maximum value near 6 G. Due to this high performance, user test participants could certainly feel the generated vibration with a sensation level of 22.544.8 dB from 10360 Hz at 3 kV.
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Dual-tasking is extremely prominent nowadays, despite ample evidence that it comes with a performance cost: the Dual-Task (DT) cost. Neuroimaging studies have established that tasks are more likely to interfere if they rely on common brain regions, but the precise neural origin of the DT cost has proven elusive so far, mostly because fMRI does not record neural activity directly and cannot reveal the key effect of timing, and how the spatio-temporal neural dynamics of the tasks coincide. Recently, DT electrophysiological studies in monkeys have recorded neural populations shared by the two tasks with millisecond precision to provide a much finer understanding of the origin of the DT cost. We used a similar approach in humans, with intracranial EEG, to assess the neural origin of the DT cost in a particularly challenging naturalistic paradigm which required accurate motor responses to frequent visual stimuli (task T1) and the retrieval of information from long-term memory (task T2), as when answering passengers’ questions while driving. We found that T2 elicited neuroelectric interferences in the gamma-band (>40 Hz), in key regions of the T1 network including the Multiple Demand Network. They reproduced the effect of disruptive electrocortical stimulations to create a situation of dynamical incompatibility, which might explain the DT cost. Yet, participants were able to flexibly adapt their strategy to minimize interference, and most surprisingly, reduce the reliance of T1 on key regions of the executive control network-the anterior insula and the dorsal anterior cingulate cortex-with no performance decrement.
Article
Mind wandering is a common phenomenon in our daily lives, especially in routine tasks such as driving familiar routes. Some evidence suggests that there are detrimental effects of mind wandering on driving performance, but limited research has been conducted to examine the influence of mind wandering on a driver’s attentional processing of relevant or irrelevant information. More specifically, it is unclear as to whether the effects of mind wandering depend on the task relevancy of information presented in the visual field. The current study expands literature on mind wandering during driving using eye tracking to measure driver visual processing of relevant/irrelevant signage information in a simulated driving task while drivers reported their mental states. Preliminary results showed no significant differences in frequency and duration of glances to roadway information based on the mental state of the individual as well as the task relevancy of the information. Implications and future directions are discussed.
Conference Paper
Distracted driving is known to be one of the core contributors to crashes in the US, accounting for about 40% of all crashes. Drivers’ situational awareness, decision-making, and driving performance are impaired due to temporarily diverting their attention from the primary task of driving to other tasks not related to driving. Detecting driver distraction would help in adapting the most effective countermeasures. To find the best strategies to overcome this problem, we developed a Bayesian Network (BN) distracted driving prediction model using a driving simulator. In this study, we use a Bayesian Network classifier as a powerful machine learning algorithm on our trained data (80%) and tested (20%) with the data collected from a driving simulator, in which the 92 participants drove six scenarios of hand-held calling, hands-free calling, texting, voice command, clothing, and eating/drinking on four different road classes (rural collector, freeway, urban arterial, and local road in a school zone). Various driving performances such as speed, acceleration, throttle, lane changing, brake, collision, and offset from the lane center were investigated. Here we investigated different optimization models to build the best BN in which a Genetic Search Algorithm obtained the best performance. As a result, we achieved a 67.8% prediction accuracy using our model to predict driver distraction. We also achieved a 62.6% true positive rate, which demonstrates the ability of our model to correctly predict distractions.
Conference Paper
A large percentage of drivers like listening to music, radio, or talking to passengers while driving, especially phoning in recent days, even if they use bluetooth earphones or car phone instead of holding the phones by hand. However, such extra cognitive workload will have an impact on drivers’ driving performance. In this study, a driving simulator based experiment was designed to find out drivers’ performance under smooth car-following drive and critical situations. In this experiment, 24 participants (male = 13, female = 11) were required to drive the same city road route twice, with and without extra cognitive workload. Driving performance is measured in driving safety and stability with several indicators. While smooth following the lead vehicle, drivers’ operations are probably not change, however, their risk perception have been increased. Once critical situations happen, extra workload put drivers into a more dangerous and higher risk to collision circumstances. Most of the stability metrics show significant difference between drives with and without extra workload. It is hypothesized that extra workload makes drivers distracted so that they need to adjust velocity and position more frequently.
Chapter
This paper studies the impact of different types of secondary tasks on older drivers’ driving safety. The study used a dual-task experimental design, the older participants need to perform three different secondary tasks while performing driving tasks on the simulated driver, including touch tasks, reading tasks, and conversation tasks. The study collected various metrics of older drivers in various distraction types of tasks, such as vehicle position, speed, acceleration, brake pedal force, distraction times and reaction time to emergencies. Results showed that the touch task has the longest reaction time and the most possibility of collision; the reading task has the largest lane offset and lateral acceleration. The indicators of the conversation task perform better than the other two tasks.
Chapter
Die Primärmobilität stellt einen der wichtigsten Faktoren zur Aufrechterhaltung von Lebensqualität und Selbstständigkeit älterer Menschen dar. Dabei werden aufgrund der zunehmenden Komplexität des Straßenverkehrs zunehmend höhere Anforderungen an die Aufmerksamkeit, Konzentration und Informationsverarbeitung aller Verkehrsteilnehmenden gestellt. Den steigenden Anforderungen an kognitive Fähigkeiten steht eine altersbedingte Abnahme kognitiver Leistungen gegenüber.
Article
Talking on a cell phone can impair driving performance, but the dynamics of this effect are not fully understood. We examined the effects of leaving a voicemail message on driving when there are critical driving targets to attend to (crosswalks and pedestrians). Participants engaged in an ecologically-valid “voicemail” task while navigating a virtual environment using a driving simulator. We also examined the potential weakening or strengthening of effects of leaving a voicemail message on driving as the familiarity and predictability of critical targets changed. Participants completed four experimental runs through the same driving environment in a driving simulator. There were two crosswalks, one with a pedestrian entering the roadway and one without a pedestrian and the location of the pedestrian was predictable (the same pedestrian consistently used the same crosswalk) for the first three runs and then unpredictable for the fourth. Half of the participants left voicemail messages using a hands-free headset, while the other half drove in silence. Leaving a voicemail message increased steering deviation and velocity. Drivers who were leaving a voicemail message decelerated for pedestrians in the roadway to a similar speed as drivers who were not leaving a voicemail message, but they were delayed in braking. Drivers who were leaving a voicemail message also had worse memory for roadway landmarks. These effects were relatively stable across runs through the same driving environment, suggesting that familiarity and predictability did not impact the effects of leaving a voicemail message while driving. Therefore, leaving a voicemail message leads to poorer driving behavior; faster speed, variable steering, and worse memory for roadway landmarks. Interestingly, although drivers who were leaving a voicemail message were slower to react to local targets, they slowed as much as drivers who were not leaving a voicemail message and familiarity with the driving environment did not impact the effects of leaving a voicemail message on driving.
Book
This book focuses on judgment and decision-making from an embodied cognition perspective that is how our bodies influence how we think, decide, and act. I coined the term embodied choices for the fact that indeed the body plays a major role in our daily choices, even often as an unnoticed player. Understanding judgment and decision-making without being embodied has been advanced mainly in isolation within cognitive psychology, and the movement science played no role. Recently, this has changed. Rather than viewing observable actions as merely the outcome of some mental processes the bidirectional interactions of mind and body as a coherent system became a new paradigm in cognitive sciences. The book is structured in 13 chapters that use scientific findings on how people decide in daily situations, lab experiments spanning from millisecond, based on our intuitions or long-term decisions, from whom to marry to what to do next in life. In simple words, examples from research as well as individual or group choices are presented to explain how our movements, our current body postures, or our gut feelings affect our choices. Examples will cover decisions based on experience and when we make them the first time. I hope that this book will increase our acknowledgment of embodied choices and how to trust them.
Chapter
This paper presents the results of mobile application which helps in preventing mobile phone accidents to the great extent. An electronic circuit (Transmitter and Receiver block) also designed to detect the driver’s mobile phone automatically once he or she starts the vehicle and the circuit will switch OFF and then ON the mobile phone without human intervention with the help of 5 pin relay in order to start the application automatically. The authors further extend the research by comparing the obtained results after installing this application with a recent study of the US National Safety Council, conducted on 2010. The authors also show how far this application helps in reducing economic losses in India.
Article
Divided attention may be more important than ever to comprehend, given ubiquitous distractors in modern living. In humans, concern has been expressed about the negative impact of distraction in education, the home, and the workplace. While acetylcholine supports divided attention, in part via muscarinic receptors, little is known about the specific muscarinic subtypes that may contribute. We designed a novel, high-response rate test of auditory sustained attention, in which rats complete variable-ratio runs on one of two levers, rather than emitting a single response. By doing this, we can present a secondary visual distractor task during some trials, for which a correct nosepoke response is reinforced with a more palatable food pellet. The nonspecific muscarinic antagonist scopolamine impaired performance, and slowed and reduced lever press activity. We then explored antagonists that preferentially block the M1 and M4 subtypes, because these receptors are potential therapeutic targets for cognitive enhancers. Telenzepine, an M1-preferring antagonist, impaired divided attention performance, but not performance of the attention task without distraction. Telenzepine also had fewer nonspecific effects than scopolamine. In contrast, the M4-preferring antagonist tropicamide had no effects. Analysis of overall behavior also indicated that accuracy in the main attention task decreased as a function of engagement with the distractor task. These results implicate the M1 receptor in divided attention.
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Recently, some studies revealed that transcranial direct current stimulation (tDCS) reduces dual-task interference. Since there are countless combinations of dual-tasks, it remains unclear whether stable effects by tDCS can be observed on dual-task interference. An aim of the present study was to investigate whether the effects of tDCS on dual-task interference change depend on the dual-task content. We adopted two combinations of dual-tasks, i.e., a word task while performing a tandem task (word-tandem dual-task) and a classic Stroop task while performing a tandem task (Stroop-tandem dual-task). We expected that the Stroop task would recruit the dorsolateral prefrontal cortex (DLPFC) and require involvement of executive function to greater extent than the word task. Subsequently, we hypothesized that anodal tDCS over the DLPFC would improve executive function and result in more effective reduction of dual-task interference in the Stroop-tandem dual-task than in the word-tandem dual-task. Anodal or cathodal tDCS was applied over the DLPFC or the supplementary motor area using a constant current of 2.0 mA for 20 min. According to our results, dual-task interference and the task performances of each task under the single-task condition were not changed after applying any settings of tDCS. However, anodal tDCS over the left DLPFC significantly improved the word task performance immediately after tDCS under the dual-task condition. Our findings suggested that the effect of anodal tDCS over the left DLPFC varies on the task performance under the dual-task condition was changed depending on the dual-task content.
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This research examined the effects of hands-free cell phone conversations on simulated driving. The authors found that these conversations impaired driver's reactions to vehicles braking in front of them. The authors assessed whether this impairment could be attributed to a withdrawal of attention from the visual scene, yielding a form of inattention blindness. Cell phone conversations impaired explicit recognition memory for roadside billboards. Eye-tracking data indicated that this was due to reduced attention to foveal information. This interpretation was bolstered by data showing that cell phone conversations impaired implicit perceptual memory for items presented at fixation. The data suggest that the impairment of driving performance produced by cell phone conversations is mediated, at least in part, by reduced attention to visual inputs.
Article
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To explore the effect of drivers' use of mobile (cell) phones on road safety. A case-crossover study. Perth, Western Australia. 456 drivers aged > or = 17 years who owned or used mobile phones and had been involved in road crashes necessitating hospital attendance between April 2002 and July 2004. Driver's use of mobile phone at estimated time of crash and on trips at the same time of day in the week before the crash. Interviews with drivers in hospital and phone company's records of phone use. Driver's use of a mobile phone up to 10 minutes before a crash was associated with a fourfold increased likelihood of crashing (odds ratio 4.1, 95% confidence interval 2.2 to 7.7, P < 0.001). Risk was raised irrespective of whether or not a hands-free device was used (hands-free: 3.8, 1.8 to 8.0, P < 0.001; hand held: 4.9, 1.6 to 15.5, P = 0.003). Increased risk was similar in men and women and in drivers aged > or = 30 and < 30 years. A third (n = 21) of calls before crashes and on trips during the previous week were reportedly on hand held phones. When drivers use a mobile phone there is an increased likelihood of a crash resulting in injury. Using a hands-free phone is not any safer.
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The objective of this research was to determine the relative impairment associated with conversing on a cellular telephone while driving. Epidemiological evidence suggests that the relative risk of being in a traffic accident while using a cell phone is similar to the hazard associated with driving with a blood alcohol level at the legal limit. The purpose of this research was to provide a direct comparison of the driving performance of a cell phone driver and a drunk driver in a controlled laboratory setting. We used a high-fidelity driving simulator to compare the performance of cell phone drivers with drivers who were intoxicated from ethanol (i.e., blood alcohol concentration at 0.08% weight/volume). When drivers were conversing on either a handheld or hands-free cell phone, their braking reactions were delayed and they were involved in more traffic accidents than when they were not conversing on a cell phone. By contrast, when drivers were intoxicated from ethanol they exhibited a more aggressive driving style, following closer to the vehicle immediately in front of them and applying more force while braking. When driving conditions and time on task were controlled for, the impairments associated with using a cell phone while driving can be as profound as those associated with driving while drunk. This research may help to provide guidance for regulation addressing driver distraction caused by cell phone conversations.
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The amplitude of the P300 component of the Event-Related Potential (ERP) has proven useful in identifying the resource requirements of complex perceptual-motor tasks. In dual-task conditions, increases in primary task difficulty result in decreases in the amplitude of P300s elicited by secondary tasks. Furthermore, P300s elicited by discrete primary task events increase in amplitude with increases in the difficulty of the primary task. The reciprocity in P300 amplitudes has been used to infer the processing tradeoffs that occur during dual-task performance. The present study was designed to investigate further the P300 amplitude reciprocity effect under conditions in which primary and secondary task ERPs could be concurrently recorded within the same experimental situation. Forty subjects participated in the study. Measures of P300 amplitude and performance were obtained within the context of a pursuit step tracking task (the primary task) performed alone and with a concurrent auditory discrimination task (the secondary task). Primary task difficulty was manipulated by varying both the number of dimensions to be tracked (from one to two), and the control dynamics of the system (velocity or acceleration). ERPs were obtained from both secondary task tones and primary task step changes. Average root-mean-square (RMS) error estimates were also obtained for each tracking condition. Increased primary task difficulty, reflected in increased RMS error scores, was associated with decreased secondary task P300 amplitudes and increased primary task P300 amplitudes. The increases in primary task P300 amplitudes were complementary to the decrements obtained for the secondary task, supporting the hypothesis of reciprocity between primary and secondary task P300 amplitudes across different manipulations of primary task difficulty.
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Previous research has indicated that components of the event-related potential (ERP) may be used to quantify the resource requirements of complex cognitive tasks. The present study was designed to explore the degree to which these results could be generalized to complex, real-world tasks. The study also examined the relations among performance-based, subjective, and psychophysiological measures of operator workload. Seven male volunteers, enrolled in an instrument flight rule (IFR) aviation course at the University of Illinois, participated in the study. The student pilots flew a series of IFR flight missions in a single-engine, fixed-based simulator. In dual-task conditions subjects were also required to discriminate between two tones differing in frequency and to make an occasional overt response. ERPs time-locked to the tones, subjective effort ratings, and overt performance measures were collected during two separate 45-min flights differing in difficulty. The difficult flight was associated with high subjective effort ratings, as well as increased deviations from the command altitude, heading, and glideslope. The P300 component of the ERP discriminated among levels of task difficulty, decreasing in amplitude with increased task demands. Within-flight demands were examined by dividing each flight into four segments: takeoff, straight and level flight, holding patterns, and landings. The amplitude of the P300 was negatively correlated with deviations from command headings across the flight segments. In sum, the findings provide preliminary evidence for the assertion that ERP components can be employed as metrics of resource allocation in complex, real-world environments.
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In previous research Karis, Fabiani, and Donchin (1984) found a relationship between the amplitude of the P300s elicited by words and subsequent recall performance. Words later recalled elicited larger P300s than words later not recalled. However, this relationship was dependent on the mnemonic strategies used by the subjects. There was a strong relationship between P300 amplitude and recall when rote rehearsal strategies were used, but when subjects used elaborative strategies the relationship between P300 amplitude and recall was not evident. In the present experiment we employed an incidental memory paradigm to reduce the use of rehearsal strategies. An “oddball’ task consisting of a series of names was presented, and subjects were required to count either the male or the female names. Event-related brain potentials were recorded to the presentation of each name. Following the oddball task, subjects were asked, unexpectedly, to recall as many names as possible. The names that were recalled had elicited, on their initial presentation, larger P300s than names not recalled. Thus, these results confirm our hypothesis: when elaborative rehearsal strategies are not used, the relationship between P300 and memory emerges more consistently. Our data provide support for a “context updating’ hypothesis of the functional significance of the P300.
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The resources allocated to a primary and secondary task are reciprocal. Subjects performed a tracking task in which the discrete displacements of the tracking cursor could be used to elicit event-related brain potentials. As the resource demands of the tracking task were increased, potentials elicited by the task-defined events increased in amplitude, whereas those elicited by secondary task auditory stimuli decreased.
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This research examined the processing demands imposed upon experienced pilots by two different communication formats, digital and verbal, in a high fidelity simulation of an advanced multi-function helicopter. The mental workload imposed by the type and magnitude of communications was assessed by a battery of subjective, performance, secondary, and physiological measures. The performance data indicated that the pilots had difficulty adhering to the Nap of the Earth altitude criterion with high communication demands, particularly with the digital communication system. This was presumably due to the requirement to spend more time scanning the multi-function displays with the digital than with the verbal communication system. On the other hand, the pilots were less prone to task shedding when they used the digital communication system possibly due to the provision of a permanent list of queries that was unavailable with the verbal system. Measures of heart rate variability and blink rate were larger with the verbal than with the digital system, presumably reflecting increased respiratory demands in the verbal condition as well as increased visual processing demands with the digital format. Finally, the probe evoked P300 component decreased in amplitude as a function of increases in the magnitude of communications. The results are discussed in terms of the structural and capacity demands of the communications systems that were proposed for the advanced multi-function helicopter.
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Because of a belief that the use of cellular telephones while driving may cause collisions, several countries have restricted their use in motor vehicles, and others are considering such regulations. We used an epidemiologic method, the case-crossover design, to study whether using a cellular telephone while driving increases the risk of a motor vehicle collision. We studied 699 drivers who had cellular telephones and who were involved in motor vehicle collisions resulting in substantial property damage but no personal injury. Each person's cellular-telephone calls on the day of the collision and during the previous week were analyzed through the use of detailed billing records. A total of 26,798 cellular-telephone calls were made during the 14-month study period. The risk of a collision when using a cellular telephone was four times higher than the risk when a cellular telephone was not being used (relative risk, 4.3; 95 percent confidence interval, 3.0 to 6.5). The relative risk was similar for drivers who differed in personal characteristics such as age and driving experience; calls close to the time of the collision were particularly hazardous (relative risk, 4.8 for calls placed within 5 minutes of the accident, as compared with 1.3 for calls placed more than 15 minutes before the accident; P<0.001); and units that allowed the hands to be free (relative risk, 5.9) offered no safety advantage over hand-held units (relative risk, 3.9; P not significant). Thirty-nine percent of the drivers called emergency services after the collision, suggesting that having a cellular telephone may have had advantages in the aftermath of an event. The use of cellular telephones in motor vehicles is associated with a quadrupling of the risk of a collision during the brief time interval involving a call. Decisions about regulation of such telephones, however, need to take into account the benefits of the technology and the role of individual responsibility.
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Distinctive words elicit the P300 component of the event-related brain potential, and are also likely to be recalled. Previous studies have shown that the larger the P300 elicited by distinctive words, the more likely it is that those words will be recalled. The present study addressed whether this relationship is affected by the manner in which distinctiveness is induced. Distinctiveness was manipulated either by varying the size of the characters in which a word was displayed, or by surrounding the word with a frame at close or far distance. All distinctiveness attributes resulted in improved recall performance. The words whose size was distinctive elicited a large P300, and P300 amplitude was larger for subsequently recalled words. The frame attributes elicited a small P300, and the amplitude of these P300s was not correlated with subsequent recall performance. Instead, a frontal slow wave was correlated with subsequent recall performance in the far frame group. It is concluded that the relationship between P300 amplitude and subsequent recall depends on the type of distinctiveness attribute, and should therefore not be ascribed to a generalized effect of distinctiveness on memory encoding processes.
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Dual-task studies assessed the effects of cellular-phone conversations on performance of a simulated driving task. Performance was not disrupted by listening to radio broadcasts or listening to a book on tape. Nor was it disrupted by a continuous shadowing task using a handheld phone, ruling out, in this case, dual-task interpretations associated with holding the phone, listening, or speaking, However significant interference was observed in a word-generation variant of the shadowing task, and this deficit increased with the difficulty of driving. Moreover unconstrained conversations using either a handheld or a hands-free cell phone resulted in a twofold increase in the failure to detect simulated traffic signals and slower reactions to those signals that were detected. We suggest that cellular-phone use disrupts performance by diverting attention to an engaging cognitive context other than the one immediately associated with driving.
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Participants attempted to perform two tasks concurrently during simulated driving. In the choice task, they responded either manually or vocally to the number of times a visual or auditory stimulus occurred; in the braking task, they depressed a brake pedal in response to the lead car's brake lights. The time delay between the onset of the tasks' stimuli, or stimulus onset asynchrony (SOA), was varied. The tasks were differentially affected by the manipulations. Brake reaction times increased as SOA was reduced, showing the psychological refractory period effect, whereas the choice task showed large effects of the stimulus and response modalities but only a small effect of SOA. These results demonstrate that a well-practiced "simple" task such as vehicle braking is subject to dual-task slowing and extend the generality of the central-bottleneck model.