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Using Mobile Telephones: Cognitive Workload and Attention Resource Allocation
Abstract
Driver distraction is recognized as being one of the central causes of road traffic incidents and mobile telephones are tangible devices (among many other electronic devices) that can distract the driver through changes in workload. Forty participants completed a motorway route characterized by a low level of road complexity in the form of vehicle handling and information processing. A peripheral detection task (PDT) was employed to gauge mental workload. We compared effects of conversation type (simple versus complex) and telephone mode (hands-free versus handheld) to baseline conditions. The participants' reaction times increased significantly when conversing but no benefit of hands-free units over handheld units on rural roads/motorways were found. Thus, in regard to mobile telephones, the content of the conversation was far more important for driving and driver distraction than the type of telephone when driving on a motorway or similar type of road. The more difficult and complex the conversation, the greater the possible negative effect on driver distraction.
... Looking at the particular target from the windscreen, rearview mirrors, and windows when driving is related to the primary driving task, which results in visual distraction and lane departure [13,14]. The reaction time of drivers is postponed while conversing through a mobile phone on a motorway [15], which shows an agreement with the result obtained in a field test [16]. Reading text in a real driving scenario leads to the vehicle departing the road, and these risky experiments were carried out in a track environment [17]. ...
... The electroencephalography power and the response time of secondary tasks both change noticeably under different stimulus [28]. Moreover, a driver's reaction time to the primary tasks, e.g., braking, turning on lights, and traffic light response, is increased as well due to the distracting behaviors [12,15,16,[29][30][31]. ...
... Furthermore, driving simulators are not the best apparatus for measuring driving behaviors [33], especially for Electrocardiography (ECG) signals. Real driving experiments have been conducted on motorways [13][14][15], controlled fields, and track environment [16,17], but distracted driving tests in real conditions under complex urban scenarios are relatively few [18,19]. In addition, the majority of research concerned the differences in driving performance caused by distracting tasks, while driving workload that could be quantitatively analyzed by heart rate variability (HRV) was seldom involved. ...
Distractors faced by drivers grow continuously, and concentration on driving becomes increasingly difficult, which has detrimental influences on road traffic safety. The present study aims to investigate changes in driving workload and driving performance caused by distracting tasks. The recruited subjects were requested to drive along a city route in a real vehicle and perform three secondary tasks sequentially. Electrocardiography and driving performance were measured. Heart rate variability (HRV) was adopted to quantitatively analyze the driving workload. Findings show that: (i) increments are noticed in the root mean square differences of successive heartbeat intervals (RMSSD), the standard deviation of normal-to-normal peak (SDNN), the heart rate growth rate (HRGR), and the ratio of low-frequency to high-frequency powers (LF/HF) compared to undistracted driving; (ii) the hands-free phone conversation task has the most negative impacts on driving workload; (iii) vehicle speed reduces due to secondary tasks while changes in longitudinal acceleration exhibit inconsistency; (iv) the experienced drivers markedly decelerate during hands-free phone conversation, and HRGR shows significant differences in both driving experience and gender under distracted driving conditions; (v) correlations exist between HRV and driving performance, and LF/HF correlates positively with SDNN/RMSSD in the hands-free phone conversation and chatting conditions while driving.
... Although in-vehicle systems such as adaptive cruise control systems and navigation are designed to advance safety and convenience (4,5), working with in-vehicle systems occasionally diverts a driver's attention from the main driving tasks (6)(7)(8). For example, talking on the phone while driving is considered a distracting behavior, even with hands-free systems (9,10). The subject of the conversation was found to be potentially more distracting than ''how'' the phone conversation is conducted (10). ...
... For example, talking on the phone while driving is considered a distracting behavior, even with hands-free systems (9,10). The subject of the conversation was found to be potentially more distracting than ''how'' the phone conversation is conducted (10). The driver's attention diverts from the driving task to the conversation, which diminishes driving performance. ...
... Distracted driving may also reduce the efficiency of the traffic network by increasing the headway between vehicles unreasonably (33). Studies about distracted driving showed that talking on a handheld cellphone while driving harms drivers' capability to sustain their speed and location on the road (34-37); texting while driving increases reaction times to brake, the variability of lane changing with no change in speed (10,38), and the frequency of deviations in a lane with the position from the centerline (39). Reading texts while driving is the most distracting activity for young drivers (40). ...
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.
... Using a hands-free system while driving, although it might seem safer than holding a phone, still poses some risk. [12][13][14][15]. There are limited evidences that holding a phone in hand may function as a reminder to drivers of the potential impact of the device on road safety and lead to more cautious driving [14]. ...
... [12][13][14][15]. There are limited evidences that holding a phone in hand may function as a reminder to drivers of the potential impact of the device on road safety and lead to more cautious driving [14]. The hands-free system mitigates the risks associated with handling a phone (such as searching for and holding the device), but it introduces new risks. ...
The study aimed to evaluate the effect of two different types of music and cognitive task on students’ reaction time and additionally to compare results of two groups: drivers and non-drivers. Reaction tests associated with driving-related skills were conducted on 52 students aged 18–25, 33 of them were drivers and 19 were no-drivers. Tests included three parameters: choice reaction time, the number of correct reactions and the number of no reactions and were conducted in four conditions: in silence (control test), with energetic music, with relaxing music and with cognitive task (answering questions). It turned out that results of all three parameters were better in silence and with music than while doing cognitive task. There were no differences between the two examined groups.
... Though all of the reports mentioned distraction or inattention as either the main cause for the crashes or as a road safety problem in general, 45.5% specified what is meant by inattention or what the supposed source for the distraction, is and what role it played in the reported crash. Other articles (54.5%) used distraction and inattention in vague statements without further explanation (e.g., "all it took was a moment of inattention", "a moment of distraction was costly"). ...
... The media coverage analysis shows that crash causation reports mentioned phone calls most frequently. Phone calls are also frequently studied by simulated and naturalistic driving studies [43][44][45][46], although these studies face validity limitations [11] because the simulation of a real phone call environment is controversial due to the related emotional state and the unique individual conditions that create different levels of engagement within the conversation. ...
Road users' inattention is one of the leading factors that contribute to crashes. It has been thoroughly researched from many perspectives, but there is limited information about the factors that influence risk perception and road users' attitudes. These factors are formed by personal and mediated experience, but education and public awareness play important roles. In this context, media seems to significantly influence risk perception and it may result in behavioural changes. This study aimed to review the coverage of driver inattention in the Czech media to analyse how it covers different types of inattention. Both quantitative and qualitative content analyses were conducted, and the sources of inattention mentioned in media reports were coded. We found the following: distraction is the most often reported inattention subtype; the media often communicates illegal behaviour, such as mobile phone handling; the preventive and educational potential of media coverage seems to not be fully utilized; and media reports are often focused on specific crashes, consequences, and immediate causes. Other risky aspects or inattention contributory factors tend to be neglected.
... In a safety-critical event, a fast and appropriate driver response is often crucial to avoid a crash. However, there is a great concern that cognitive load causes increased response times, resulting in an increased risk of crashes in critical situations (Merat & Jamson, 2008;Patten et al., 2004;Strayer & Fisher, 2016). The concern stems from the large number of experiments that have shown increased response times to different stimuli, such as artificial detection tasks (Bruyas & Dumont, 2013;Conti et al., 2012;Engström, Larsson, et al., 2013;Mantzke & Keinath, 2015) and braking lead vehicles (Alm & Nilsson, 1995;Engström et al., 2010;Salvucci & Beltowska, 2008), when drivers were performing cognitive tasks. ...
... Although the task is practiced before trials, it is not practiced to the extent that full automaticity can be expected (ISO, 2016;. In line with the hypothesis' prediction, numerous studies have shown increased response times to the DRT stimulus during cognitive task execution compared to a baseline (no task) condition (Bruyas & Dumont, 2013;Conti et al., 2012;Engstrӧm, Larsson et al., 2013;Mantzke & Keinath, 2015;Merat & Jamson, 2008;Patten et al., 2004). ...
... Consequently, the issue of operator load is an ongoing subject of research (Biernacki & Zieliński, 2010;Luximon & Goonetilleke, 2011;Rubio et al., 2004). Despite many problems with definition (Cain, 2007;Martins, 2016), workload in its simplest form is defined as the ratio of the resources required to perform a task by the operator to the number of cognitive resources available (Martins, 2016;Patten et al., 2004;Rubio et al., 2004). The right number of cognitive resources is needed to complete the task (Martins, 2016). ...
... The right number of cognitive resources is needed to complete the task (Martins, 2016). These resources, however, are limited and can be fully used (Patten et al., 2004). The concept of load is considered to be multidimensional (Cain, 2007). ...
The widely held thesis is that the profession of pilot is one of the most difficult jobs to do. The task of the article was to analyse whether and how the difficulty of the performed task affects the pilot’s workload during the flight. The research was carried out using a flight simulator. During the simulator tests, the cognitive load measurements represented by the change in pilot pulse and concentration were used. A finger pulse oximeter was used for the first purpose. The second device was Mindwave Mobile which allows to measure level of pilot’s concentration and relaxation. The NASA-TLX questionnaire is used as a subjective method of operator’s workload assessment. The examined person assesses the level of his/her load, using six dimensions: mental demand, physical demand, temporal demand, performance, effort, and frustration level. Five research hypotheses were put forward and verified by the Friedman test. It has been shown that the level of difficulty of individual stages of the study is appropriately differentiated by pulse, concentration, relaxation, and subjective assessment of the respondents’ workload. It has been proved that pulse measurement, concentration, and relaxation levels, as well as subjective assessment of load levels, can be successfully used to assess the psychophysical condition of the operator.
... However, handsfree phone conversations slowed them down only in rural 90 and urban complex scenarios. This finding was in line with the results of Burns et al. (2002) [96] and Patten et al. (2004) [97] studies, who observed that driving speed reduced more when conversing with a handheld phone. One possible explanation is that drivers start underestimating the risk involved with a phone conversation when using a hands-free phone and thus do not adjust as much by reducing speed as they do when using a handheld phone. ...
... However, handsfree phone conversations slowed them down only in rural 90 and urban complex scenarios. This finding was in line with the results of Burns et al. (2002) [96] and Patten et al. (2004) [97] studies, who observed that driving speed reduced more when conversing with a handheld phone. One possible explanation is that drivers start underestimating the risk involved with a phone conversation when using a hands-free phone and thus do not adjust as much by reducing speed as they do when using a handheld phone. ...
The number of traffic accidents because of distracted driving is increasing rapidly worldwide. Hence, the main objective of the present study is to review the effects of different distracting factors on driving performance indicators. Distracting factors considered in this study are roadside advertisements (billboards), mobile use, in-built vehicle systems, and sleepiness; and driving performance indicators are lane deviation, reaction time, and speed variation. Studies from existing literature reveal that all the distracting factors distract drivers from forwarding roadways in many ways. The location and content displayed on the billboard and the use of mobile phones increase reaction time. However, the former decreases the driver’s ability to control the vehicle, and the latter increases the speed variation and reduces lane-keeping capacity. Lateral vehicle control and reaction time are compromised when drivers engage in searching for songs or videos on music players. When sleepiness occurs, drivers exhibit a higher standard deviation of speed and a decreased headway distance. Nevertheless, most of the studies in this area are carried out in developed countries like the USA and European countries. Therefore, a detailed study and further research in developing countries like India, where activities like installing billboards and mobile phone use are increasing day by day due to the rapid urbanization of major cities in the country, are quite essential. Doi: 10.28991/CEJ-2022-08-02-014 Full Text: PDF
... Devoting greater effort plays a central role in keeping the amount of available resources above the amount of required resources, since it can increase the amount of available resources based on an increase in the arousal level (Kahneman, 1973). Second, drivers may reduce their driving speed if allowed (often referred to as compensatory speed reduction; Antin et al., 1990;de Waard et al., 1995de Waard et al., , 2004Engström et al., 2005;Godley et al., 2004;Lewis-Evans & Charlton, 2006;Patten et al., 2004). A reduction in driving speed is highly effective for keeping the amount of available resources above the amount of required resources, since it can help to reduce the processing that needs to be performed per unit time and generally decrease the amount of resources required to be allocated to visual, cognitive, and action processing. ...
... Importantly, this speed reduction was more prominent in the fast conditions where visual, cognitive, and action processing were likely to compete for available attentional resources: 22.8 km/h in the fast-narrow and 27.0 km/h in the fast-wide conditions (i.e., speed reduction of about 4 km/h) and 14.8 km/h in the slow-narrow and 15.9 km/h in the slow-wide condition (speed reduction of about 1 km/h). These results support the view that the speed reduction in the narrow compared to wide conditions would reflect a compensatory speed reduction to keep the amount of available resources above the amount of required resources (Antin et al., 1990;de Waard et al., 1995de Waard et al., , 2004Engström et al., 2005;Godley et al., 2004;Lewis-Evans & Charlton, 2006;Patten et al., 2004). ...
Driving a vehicle is comprised of multiple tasks (e.g., monitoring the environment around the vehicle, planning the trajectory, and controlling the vehicle), and requires the allocation of capacity-limited attentional resources to visual, cognitive, and action processing; otherwise, the quality of task performance will deteriorate, increasing the risk of near-accidents or crashes. The present study proposes that variations in the total amount as well as the individual amounts of attentional resources allocated to visual, cognitive, and action processing depending on the driving situations could be objectively estimated by the combined use of three physiological measures: (1) the duration of eye blinks during driving, (2) the size of eye-fixation-related potentials (EFRPs), i.e., event-related potentials (ERPs) that are time-locked to the offset of saccadic eye-movements during driving, and (3) the size of auditory-evoked potentials (AEPs), i.e., ERPs time-locked to the onset of task-unrelated auditory stimuli discretely presented during driving. We implemented these measures when participants (N = 16) drove a vehicle on a slalom course under four driving conditions defined by a combination of two levels of speed requirement (fast and slow) and two levels of path width (narrow and wide). The findings suggested that, (1) when driving at fast compared to slow speeds, the total amount of resources allocated to overall processing increased, which consisted of an increase in the amount of resources allocated to cognitive (and possibly action) processing and a decrease in the amount of resources allocated to visual processing, and (2) when driving on narrow compared to wide paths, the total amount of resources allocated to overall processing remained almost the same (due to complementary speed reduction), which consisted of an increase in the amount of resources allocated to visual processing, a decrease in the amount of resources allocated to cognitive processing, and almost the same amount of resources allocated to action processing. The driver’s resource management strategies indicated by these results as well as the utility and limitations of the proposed method are discussed.
... Several studies have shown that the incidence and severity of road crashes increase in construction work zones (Khattak et al., 2002;Li & Bai, 2008;Theofilatos et al., 2017;Wang et al., 2024), with a notable increase in rear-end collisions (Meng & Weng, 2011;Zheng et al., 2010). When motorways are not congested, the driving task is relatively simple, and the driver's mental workload is usually low (Patten et al., 2004;Tejero & Ch� oliz, 2002). In contrast, when approaching work zones, drivers must make complex decisions to adjust speed and lane position, often resulting in potential conflicts between vehicle paths (La Shahin et al., 2023, Shakouri et al., 2014. ...
... In cognitive psychology, people's attentional resources are limited, and when drivers are distracted, their cognitive resources are divided among multiple tasks. This means that the cognitive resources available for performing the main driving tasks are reduced, thereby affecting the quality of execution of these tasks [53]. Therefore, understanding the cognitive mechanisms behind distracted driving and exploring drivers' cognitive decision-making processes while distracted is crucial for reducing the dangers of distraction. ...
Distracted driving significantly affects the efficiency and safety of traffic flow. Modeling distracted driving behavior in microscopic traffic flow simulation is essential for understanding its critical impacts on traffic flow. However, due to the influence of various external factors and the considerable uncertainties in behavior characteristics, modeling distracted driving behavior remains a challenge. This study proposed a model which incorporates distraction features into the microscopic traffic flow model to simulate distracted driving behavior. Specifically, the study first examines the characteristics of distracted driving, including the intervals and durations of distraction events, as well as the patterns and environments of distraction. It then introduces distraction parameters into the Intelligent Driver Model (IDM), including reaction time delays and perception deviations in both speed difference and following distance. These parameters are quantified by probabilistic distributions to reflect the uncertainty and individual differences in driving behavior. The model is calibrated and validated using 772 distracted following events from the Shanghai Naturalistic Driving Study (SH-NDS) data. Three patterns of distraction (excessive, moderate, mild) are distinguished and modeled separately. The results show that the model's accuracy surpasses that of the IDM under various road types and traffic volumes, with an average improvement in model accuracy of about 11.30% on expressways with high traffic volume, 4.54% on expressways with low traffic volume, and 4.46% on surface roads. Meanwhile, the model can effectively simulate the variations in reaction times and perceptual deviations in both speed and following distance for different distraction modes at the individual level, maintaining consistency with reality. Finally, the study simulates distracted driving behavior under different road environments and traffic volumes to explore the impact of distracted driving on traffic flow. The simulation results indicate that an increase in the proportion of distraction reduces the efficiency and safety of traffic flow, which is consistent with real-world observations. Since the model considers human distraction factors, it can generate more dangerous driving scenarios in simulations, which holds significant importance for safety-related research. The findings from this study are expected to be helpful for understanding distracted driving behavior and mitigate its negative influence on the efficiency and safety of traffic flow.
... Among voice alarms, slow voice alarm performance is optimal [10]. Auditory icon alarms are superior to earcon alarms in intuitiveness, learnability, and memorability [8] [11]. For simultaneous audible alarms, it is easier to distinguish them using audible icons [12]. ...
... Given the fact that we have limited attentional resources (Kahneman 1973) any substantial increase in the cognitive workload associated with the performance of a concurrent task (in this context, listening to FMRC) would reduce the available attentional resources that otherwise could have been allocated to driving. In the context of driving, a number of studies have shown that the more demanding the secondary task is the more compromised is the driving performance (e.g., Jäncke et al. 1994;Briem and Hedman 1995;Patten et al. 2004;Horberry et al. 2006). During DSM condition, the participants listened to music that they were already familiar with. ...
... Given the fact that we have limited attentional resources (Kahneman 1973) any substantial increase in the cognitive workload associated with the performance of a concurrent task (in this context, listening to FMRC) would reduce the available attentional resources that otherwise could have been allocated to driving. In the context of driving, a number of studies have shown that the more demanding the secondary task is the more compromised is the driving performance (e.g., Jäncke et al. 1994;Briem and Hedman 1995;Patten et al. 2004;Horberry et al. 2006). During DSM condition, the participants listened to music that they were already familiar with. ...
Objectives:
Driving is a dynamic activity that takes place in a constantly changing environment, carrying safety implications not only for the driver but also for other road users. Despite the potentially life-threatening consequences of incorrect driving behavior, drivers often engage in activities unrelated to driving. This study aims to investigate the frequency and types of errors committed by drivers when they are distracted compared to when they are not distracted.
Methods:
A total of 64 young male participants volunteered for the study, completing four driving trials in a driving simulator. The trials consisted of different distraction conditions: listening to researcher-selected music, driver-selected music, FM radio conversation, and driving without any auditory distractions. The simulated driving scenario resembled a semi-urban environment, with a track length of 12 km.
Results:
The findings of the study indicate that drivers are more prone to making errors when engaged in FM radio conversations compared to listening to music. Additionally, errors related to speeding were found to be more prevalent across all experimental conditions.
Conclusions:
These results emphasize the significance of reducing distractions while driving to improve road safety. The findings add to our understanding of the particular distractions that carry higher risks and underscore the necessity for focused interventions to reduce driver errors, especially related to FM radio conversations. Future research can delve into additional factors that contribute to driving errors and develop effective strategies to promote safer driving practices.
... In accordance with these three properties, a workload assessment method is expected to capture the multi-dimensional property of the cognitive load and to account for driver age differences. Among several techniques to assess the level of the driver's workload, subjective methods are the most frequently used in practice [66]: they make use of driver's reports concerning subjective judgments of the effort and expenditure that was experienced during the task [67]. The most popular subjective method is the National Aeronautic and Space Administration Task Load indeX (NASA-TLX) [68], which was originally designed for aviation pilots. ...
In recent years, advancements in Intelligent and Connected Vehicles (ICVs) have led to a significant increase in the amount of information to the driver through Human–Machine Interfaces (HMIs). To prevent driver cognitive overload, the development of Adaptive HMIs (A-HMIs) has emerged. Indeed, A-HMIs regulate information flows by dynamically adapting the presentation to suit the contextual driving conditions. This paper presents a novel methodology, based on multi-objective optimization, that offers a more generalized design approach for adaptive strategies in A-HMIs. The proposed methodology is specifically tailored for designing an A-HMI that, by continuously monitoring the Driver–Vehicle–Environment (DVE) system, schedules actions requested by applications and selects appropriate presentation modalities to suit the current state of the DVE. The problem to derive these adaptive strategies is formulated as an optimization task where the objective is to find a set of rules to manage information flow between vehicle and driver that minimizes both the driver’s workload and the queuing of actions. To achieve these goals, the methodology evaluates through two indexes how applications’ requests impact the driver’s cognitive load and the waiting queue for actions. The optimization procedure has been solved offline to define adaptive strategies for scheduling five application requests, i.e., forward collision warning, system interaction, turn indicators, infotainment volume increase, and phone calls. A theoretical analysis has demonstrated the effectiveness of the proposed framework in optimizing the prioritization strategy for actions requested by applications. By adopting this approach, the design of rules for the scheduling process of the A-HMI architecture is significantly streamlined while gaining adaptive capabilities to prevent driver cognitive overload.
... Similarly, participants averaged significantly more questions asked on the TQT in the cellphone call, as opposed to the texting condition. This finding is also consistent with previous hand-held vs. hand-free driving comparisons (Saifuzzaman et al. 2015;Patten et al. 2004;Caird et al. 2008). This result may be attributed to an increase in mental workload due to the primary task demand. ...
The present study examined the impact of individual differences, attention, and memory deficits on distracted driving. Drivers with ADHD are more susceptible to distraction which results in more frequent collisions, violations, and license suspensions. Consequently, the present investigation had thirty-six participants complete preliminary questionnaires, memory tasks, workload indices, and four, 4-minute simulated driving scenarios to evaluate such impact. It was hypothesized ADHD diagnosis, type of cellular distraction, and traffic density would each differentially and substantively impact driving performance. Results indicated traffic density and distraction type significantly affected the objective driving facets measured, as well as subjective and secondary task performance. ADHD diagnosis directly impacted secondary task performance. Results further showed significant interactions between distraction type and traffic density on both brake pressure and steering wheel angle negatively impacting lateral and horizontal vehicle control. Altogether, these findings provide substantial empirical evidence for the deleterious effect of cellphone use on driving performance.
... Although providing a secondary task has been shown to be useful to reduce workers' boredom, few researchers have determined whether such a secondary task results in worse or better performance. For example, although talking on one's cell phone while driving has been repeatedly shown to lead to distracted driving in high mental workload settings [21], another study found that drivers who performed various taskunrelated activities and experienced larger variance (e.g., looking for deer on the side of the road, which both reduced boredom and increased alertness) made fewer errors during a monotonous laboratory task [22]. Other research also considers possible positive benefits, such as when driving during long stretches of highway, particularly at night. ...
Boredom is a common workplace problem. Previous research has suggested that repetitive and monotonous work tasks may lead to boredom. However, these tasks have been reduced due to increased workplace automation. Thus, the current cause of boredom may be due to low mental work-load. This research developed a general boredom model and compared the effects of feedback type (performance and ranking) and intervention method (game and quiz) on boredom and task performance. Results revealed that the secondary task interventions can reduce boredom and feedback could shorten the response time. Gender also had a significant influence on response time. Notably, results revealed a 4% probability of task failure during the experiment, indicating other interventions are also required. This research indicates that interventions to reduce boredom caused by low mental workload should be designed differently from tasks that have been designed to combat the boredom caused by repetitive and monotonous work.
... Harbluk, Noy, Trbovich & Eizenman, 2007) and laboratory studies (e.g. Patten, Kircher, Östlund & Nilsson, 2004). Prior to the Olson et al. and Hickman et al. results, the complementary epidemiological and laboratory approaches provided a coherent account of the effect of mobile phone conversations on driving risk. ...
This paper investigates the odds ratios for mobile phone use when driving for a sample of vehicles from fleets in the USA, UK, and New Zealand, employing a similar protocol to that used by Hickman, Hanowski & Bocanegra (2010). The event data was collected from vehicles of various types, ranging from commercial to private vehicles. Vehicles used the SmartDrive in-vehicle camera and telematics systems to record video, audio, location and speed information in response to kinematic triggers. Data was reviewed at SmartDrive by trained observers and coded for the safety criticality of the event (safety critical event (SCE) vs. baseline epoch (BE)) and the associated factors observed over the time-course of the event. The SmartDrive dataset comprised a total of 103,264 epochs recorded from the start of April 2012 until mid-October 2013 and was evaluated by SmartDrive expert reviewers. Of this total number of epochs, 14,097 were classified as SCEs and 89,167 as BEs. SmartDrive provided data on the incidence of events and associated factors to TRL for further analysis, particularly for tasks relating to mobile phone use. Similar to the findings of Hickman, Hanowski & Bocanegra (2010), handsfree mobile phone use was associated with a significant odds ratio of less than one for the occurrence of a SCE. In contrast to the findings of Hickman et al. (2010), results from this investigation revealed that both handheld mobile phone use and manual interaction with the mobile phone (texting/dialling) were also associated with a significant odds ratio of less than one. These results are used to discuss the advantages and disadvantages of the use of naturalistic driving data, the method of classification employed by trained observers, and the use of odds ratios as an approach for investigating the effects of engagement in secondary tasks while driving has on driver behaviour and driving performance.
... Previous research [4], [5], [6], [7], [8] has repeatedly shown that awareness and perception of human CWL can improve the performance of a human-machine interaction system as such awareness allows identifying and alleviating task errors that result from situations of task over-load or under-load. Monitoring the CWL of human operators in a human-robot team, for instance, enables the workload and autonomy levels of the robots to be adjusted as needed to help human operators efficiently and productively maintain their working state [9]. ...
This paper presents MOCAS, a multimodal dataset dedicated for human cognitive workload (CWL) assessment. In contrast to existing datasets based on virtual game stimuli, the data in MOCAS was collected from realistic closed-circuit television (CCTV) monitoring tasks, increasing its applicability for real-world scenarios. To build MOCAS, two off-the-shelf wearable sensors and one webcam were utilized to collect physiological signals and behavioral features from 21 human subjects. After each task, participants reported their CWL by completing the NASA-Task Load Index (NASA-TLX) and Instantaneous Self-Assessment (ISA). Personal background (e.g., personality and prior experience) was surveyed using demographic and Big Five Factor personality questionnaires, and two domains of subjective emotion information (i.e., arousal and valence) were obtained from the Self-Assessment Manikin, which could serve as potential indicators for improving CWL recognition performance. Technical validation was conducted to demonstrate that target CWL levels were elicited during simultaneous CCTV monitoring tasks; its results support the high quality of the collected multimodal signals.
... The method used most frequently to assess cognitive distraction is the ISO standardized (ISO 17488, 2016) detection response task (DRT; Conti et al., 2012). Several studies have found increased reaction times and increased miss rates with the DRT during cognitive distraction (Patten et al., 2004;Rakauskas et al., 2004). The DRT is advantageous in that it is able to discriminate between different levels of cognitive workload (Goodsell & Cunningham, 2019). ...
Speech is considered a promising modality for human-machine interaction while driving, especially in reducing visual and manual distraction. However, speech-based user interfaces themselves have shown to increase cognitive distraction. There remains a lack of standardized and unambiguous methods for measuring the impact of speech-based assistants on cognitive distraction while driving. This work aims to investigate whether the combination of the box task and the detection response task (DRT) is a suitable method for assessing the cognitive distraction caused by speech-based assistants. For this purpose, participants (N = 39) engaged in artificial (n-back tasks) and natural speech-based secondary tasks (interaction with Android's Google Assistant and Apple's Siri) differing in predefined levels of cognitive workload while performing the box task and the DRT. The results showed that DRT performance differed between the 0-back and 1-back task but not between the different cognitive workload levels of the speech-based assistants. No clear effects emerged for the box task parameters. Thus, the combination of the box task and DRT is well-suited for measuring cognitive distraction caused by artificial secondary tasks but not by natural interactions with speech-based assistants.
... However, a study evidenced that using both hand-held and hands-free devices increases risks of crashes and obviates driving performance (Young et al. 2007). Besides, several incidents substantiate that demanding cell-phone conversations might upsurge driving impairment (McKnight and McKnight 1993;Cain and Burris 1999;Strayer and Johnson 2001;Harbluk et al. 2002;Nunes and Recarte 2002;Patten et al. 2004;Atchley and Dressel 2004). ...
Pedestrians cross at uncontrolled intersections and mid-blocks through gap acceptance. The absence of traffic enforcement and sufficient safety measures increases the chances of severe road crashes. These days, mobile phone use on roads has become customary for everyone. Often, it causes inattentiveness of pedestrians and increases the risk of collisions, particularly when they cross a road at intersections and mid-block. For years researchers took some initiatives to understand the impact of mobile phone usage on drivers’ cognitive, physical or visual distractions. There have been limited studies that attempted to investigate these effects on pedestrians who prefer to use mobile phones while walking. Hence, it appears highly relevant to diagnose proper research aiming at assessing the impacts of (a) mobile phone usage, (b) panic-stricken behaviour and (c) the tendency to cross at mid-block road sections devoid of any zebra markings among part of pedestrians that may lead to road crashes and even fatalities. The paper attempts to provide a comprehensive review of past literature on traffic characteristics, human factors and road environment and its association with pedestrian safety and identify research gaps where intervention is needed. Further, it illustrates the need to evaluate the chances of a driver or a pedestrian to act as the offender and initiate systematic investigations.
... Extensive research has shown that multitasking while driving has a negative impact on driving performance: it increases reaction times (Gershon et al., 2009;Atchley and Chan, 2011;He et al., 2014;Nijboer et al., 2016;Jokinen et al., 2020;Kim et al., 2020). One common multitasking while driving is definitely the use of mobile phones (e.g., handheld or hands-free texting) with consequent negative effects on an individual's performance (Salvucci and Macuga, 2002;Strayer et al., 2003;Patten et al., 2004;Horrey and Wickens, 2006;Hosking et al., 2006;Drews et al., 2008;Cooper et al., 2011;Yager et al., 2012;Hill et al., 2021;Keffane, 2021;Sullman et al., 2021;Truelove et al., 2021;Vollrath et al., 2021). Several studies have investigated brain activity during careless driving (Schweizer et al., 2013;Karthaus et al., 2018). ...
Background
Extensive research showed that multitasking negatively affects driving performance. Multitasking activities can range from talking and texting to listening to music; particularly among young drivers, multitasking behavior is caused mainly from mobile phone use while driving which is one of the main causes of road accidents.
Objective
The main purpose of this study was to investigate whether some variables (e.g., Sensation-Seeking, preferences of Multitasking) could affect mobile phone use while driving in young drivers and whether any gender differences were present among the examined variables.
Setting and participants
The sample consists of 424 Italian students (56% males) with an age range of 18–21 years. A self-report questionnaire was specifically developed to assess variables such as: Attitude toward Multitasking, Perceived Self-efficacy in Multitasking, Accident Risk Perception, General Multitasking Habits, and Sensation Seeking.
Results
Through SEM modeling, we found the attitude to multitasking while driving to be largely explained by the considered variables. Using multigroup analysis (MGSEM), the model we developed appears to be suitable for explaining the behaviors of both male and female young drivers. Furthermore, data comparison showed that females were more likely to risk perception toward multitasking, and risk perception when using a mobile phone while driving, while males obtained higher mean scores in Sensation Seeking, Perceived Self-Efficacy in Multitasking, and in Multitasking caused by mobile phone use while driving.
Conclusion
Our research showed how some variables may influence the inclination of some subjects to engage in multitasking while driving. Furthermore, we discussed the importance of considering these variables in the implementation of effective road safety education projects on driving multitasking.
... To solve this problem, Gremlin observes past interactions and builds an attention demand prediction model by observing and quantifying attention demanded by low-level I/O components such as pressing a button, reading text, and listening to audio. This prediction model is derived from past studies [123,115,100,98,99,87] it learns more about each interaction so that it can make better predictions for future interactions. ...
We live in a world where mobile computing systems are increasingly integrated with our day-to-day activities. People use mobile applications virtually everywhere they go, executing them on mobile devices such as smartphones, tablets, and smart watches. People commonly interact with mobile applications while performing other primary tasks such as walking and driving (e.g., using turn-by-turn directions while driving a car). Unfortunately, as an application becomes more mobile, it can experience resource scarcity (e.g., poor wireless connectivity) that is atypical in a traditional desktop environment. When critical resources become scarce, the usability of the mobile application deteriorates significantly. In this dissertation, I create system support that enables users to interact smoothly with mobile applications when wireless network connectivity is poor and when the user’s attention is limited. First, I show that speculative execution can mitigate user-perceived delays in application responsiveness caused by high-latency wireless network connectivity. I focus on cloud-based gaming, because the smooth usability of such application is highly dependent on low latency. User studies have shown that players are sensitive to as little as 60 ms of additional latency and are aggravated at latencies in excess of 100ms. For cloud-based gaming, which relies on powerful servers to generate high-graphics quality gaming content, a slow network frustrates the user, who must wait a long time to see input actions reflected in the game. I show that by predicting the user’s future gaming inputs and by performing visual misprediction compensation at the client, cloud-based gaming can maintain good usability even with 120 ms of network latency. Next, I show that the usability of mobile applications in an attention-limited environment (i.e., driving a vehicle) can be improved by automatically checking whether interfaces meet best-practice guidelines and by adding attention-aware scheduling of application interactions. When a user is driving, any application that demands too much attention is an unsafe distraction. I first develop a model checker that systematically explores all reachable screens for an application and determines whether the application conforms to best-practice vehicular UI guidelines. I find that even well- known vehicular applications (e.g., Google Maps and TomTom) can often demand too much of the driver’s attention. Next, I consider the case where applications run in the background and initiate interactions with the driver. I show that by quantifying the driver’s available attention and the attention demand of an interaction, real-time scheduling can be used to prevent attention overload in varying driving conditions.
This study investigated the effect of different types of distractions related to use of a hands-free phone on driving performance. The study used three types of verbal distractors: casual conversation, simple arithmetic number guessing, and number adding, in the phone conversation. 12 adults were instructed to follow a lead vehicle on a closed-course highway in a fixed-based driving simulator. The results showed that use of a hands-free cellular phone involving verbal and cognitive distractions impaired driving performance and skill. Types of distraction produced significantly different effects on several dependent variables: the driving speed, headway (distance between the lead car and the manipulated car), brake reaction time, and number of collisions with the lead car. In general, the higher the cognitive load involved in the dialogue, the worse the driving performance.
Objectives:
This study aims to investigate the impact of mobile phone use (specifically, conversation), considering various use modes, on driving behavior at night. Mobile phone use is a source of driver distraction and has been associated with increased accident risk. Driving at night also entails higher accident risk and severity compared to daytime driving. Several studies have investigated the impact of mobile phone use on driving behavior; however, only a few have explored the differences between the different use modes. Most present studies involved daytime driving, although mobile phone use at night is equally if not more prevalent.
Method:
A driving simulator experiment was designed in which 55 participants drove under nighttime simulator conditions, in different road environments (urban and rural) and under different types of distraction: no distraction, handheld, wired earphone, and speaker mode. The drives were performed during late afternoon and evening hours to resemble nighttime conditions both in the simulator and in the actual environment. Participants also completed a questionnaire for collection of different types of data.
Results:
Results highlight the effect of mobile phone use on driving behavior, through specific indicators. Mobile phone use resulted in reduced 85th percentile driving speed and 85th percentile acceleration and increased reaction time and lateral deviation. However, safer stopping distance was observed in rural roads. Parameters relative to mobile phone use familiarity and exposure were found to mitigate mobile phone use effects.
Conclusions:
Mobile phones affect driving behavior at night in a similar manner to that noted in several different studies considering daytime driving. The hands-free regulation should be revisited, because driver distraction also occurred under this particular use mode. Further research is required considering mobile phone use familiarity and exposure and effects of mobile phone use, because the latter is reduced with an increase in the former. Stopping distance, an understudied but more immediate surrogate measure of road safety, was increased with mobile phone use, mainly as a result of the risk compensation behavior that drivers adopt, indicating that more research is required in this field.
Bu çalışmanın temel amacı, genç ve deneyimsiz sürücülerde sürüş becerilerine odaklanarak sürüş sırasında cep telefonu kullanımının belirleyicilerini anlamaktır. Spesifik olarak, sürüş sırasında telefon kullanımını algısal motor becerilerin pozitif, güvenlik becerilerinin ise negatif bir şekilde yordayacağı hipotezini test etmek için Türkiye’deki bir devlet üniversitesinde lisans düzeyinde öğrenim gören 218 (125 erkek, 86 kadın, 7 cinsiyetini belirtmeyen; Ortyaş = 21.4, SSyaş = 1.28) araç sürücüsüne ulaşılmıştır. Katılımcılar, sürüş becerilerine (algısal motor beceriler ve güvenlik becerileri), araç kullanırken telefon kullanmaya ilişkin soruları ve demografik bilgi formunu (cinsiyet, araç kullanım sıklığı, son 3 yılda yapılan kaza sayısı) cevaplandırmışlardır. Yapılan bağımsız örneklemler t-testi erkeklerin sürüş sırasında daha çok cep telefonu kullandığını ve daha yüksek algısal motor becerilere sahip olduklarını ortaya koymaktadır. Yapılan hiyerarşik regresyon analizinin sonuçları ise seyir halindeyken telefon kullanımını algısal motor becerilerin pozitif yönde, güvenlik becerilerinin ise negatif yönde yordadığını göstermektedir. Bulgularımız sürücülerin gerçek sürüş becerileri hakkında daha kesin bir anlayış geliştirmek ve aşırı güven veya yanlış yerleştirilmiş güvenlik duygusunu azaltmak için ilgili otoriteler tarafından daha fazla çalışma yapılması gerekliliğini vurgulamaktadır. Özellikle, Türkiye'deki trafik eğitim programlarının çoğunlukla genel sürüş becerilerinin geliştirilmesine odaklandığı ve trafik kuralları hakkında bilgi içerdiği göz önünde bulundurulduğunda, güvenli sürüş eğitim programlarının sürücü eğitimi programlarına eklenmesinin gerekliliği ortaya çıkmaktadır.
The main aim of this study was to understand the predictors of mobile phone use while driving, focusing on driving skills in young and novice drivers. Specifically, in order to test the hypothesis that perceptual motor skills would positively, and safety skills would negatively predict mobile phone use while driving 218 (125 males, 86 females, 7 did not specify; Mage = 21.4, SDage = 1.28) undergraduate car drivers from a state university in Türkiye were recruited. Participants answered questions on driving skills (i.e., perceptual motor skills and safety skills), cell phone use while driving, and a demographic information form (gender, frequency of driving, number of accidents in the last 3 years). The independent samples t-test revealed that males used mobile phones more while driving and had higher perceptual motor skills. The results of the hierarchical regression analysis showed that perceptual motor skills positively and safety skills negatively predicted mobile phone use while driving. Our findings highlight the need for further work by relevant authorities to develop a more precise understanding of drivers' actual driving skills and to reduce overconfidence or misplaced sense of security. In particular, given that traffic education programs in Türkiye mostly focus on the development of general driving skills and include information about traffic rules, there is a need to include safe driving education programs in driver training programs.
This paper presents
MOCAS
, a multimodal dataset dedicated for human cognitive workload (CWL) assessment. In contrast to existing datasets based on virtual game stimuli, the data in MOCAS was collected from realistic closed-circuit television (CCTV) monitoring tasks, increasing its applicability for real-world scenarios. To build
MOCAS
, two off-the-shelf wearable sensors and one webcam were utilized to collect physiological signals and behavioral features from 21 human subjects. After each task, participants reported their CWL by completing the NASA-Task Load Index (NASA-TLX) and Instantaneous Self-Assessment (ISA). Personal background (e.g., personality and prior experience) was surveyed using demographic and Big Five Factor personality questionnaires, and two domains of subjective emotion information (i.e., arousal and valence) were obtained from the Self-Assessment Manikin (SAM), which could serve as potential indicators for improving CWL recognition performance. Technical validation was conducted to demonstrate that target CWL levels were elicited during simultaneous CCTV monitoring tasks; its results support the high quality of the collected multimodal signals.
In this study, we sought to compare the mental workload of eating/drinking and phone use while driving. This was done by using Micro Saint Sharp to model a simulated driving task that included stop lights combined with either eating and drinking or a phone call. We hypothesized that the mental workload for phone use and eating/drinking would be the same, as literature suggests that eating while driving can be equally dangerous. Results show that eating and drinking were associated with a lower mental workload than phone use, and both eating and drinking are associated with significantly higher workload than baseline. This research has the potential to inform future legislation regarding driver safety.
Purpose
One of the most important challenges confronting enterprise managers is that of controlling employees' social cyberloafing. The use of enterprise social media entails opportunities for cyberloafing. However, previous research on how enterprise social media use affects cyberloafing is rather limited. Using the job demands-resources (JD-R) model, this paper proposes a research model to investigate the relationship between enterprise social media usage and employees' social cyberloafing behavior.
Design/methodology/approach
Structural equation modeling was performed to test the research model and hypotheses. Surveys were conducted in an online platform in China, generating 510 employees' data for analysis.
Findings
First, both public social media and private social media used for work-related and social-related purposes have a positive effect on employees' job engagement. Further, job engagement has a negative effect on employees' social cyberloafing. Second, the use of public social media for work-related and social-related purposes has no effect on employees' emotional exhaustion. However, work-related private social media usage has a negative effect on employees' emotional exhaustion, and social-related private social media usage has a positive effect on employees' emotional exhaustion. Further, employees' emotional exhaustion has a positive effect on employees' social cyberloafing. Third, there are significant differences in the effects of enterprise social media on employees' social cyberloafing between male and female employees.
Originality/value
First, this paper contributes to the social cyberloafing literature by establishing a relationship between enterprise social media usage and social cyberloafing in relation to the dual influence mechanism. Second, it contributes to the JD-R model by clarifying how the use of enterprise social media with different motivations affects social cyberloafing through a mediation mechanism, namely, an enabling mechanism and a burden mechanism. Third, this paper also contributes to the social cyberloafing literature by revealing the boundary condition, namely gender, between enterprise social media use and employees' social cyberloafing.
The book examines the current state of mHealth and Human-Centered Design (HCD) initiatives toward health, care, and well-being. The present surge in interest in improving people's quality of life is creating new prospects for the development of innovative design solutions aimed at enhancing living conditions. The combination of emerging user needs and opportunities provided by recent innovative mHealth technologies enables research institutions, stakeholders, and academia to design new solutions to promote well-being, health, and care, thereby improving the quality of life of people of all ages. The book analyzes and discusses the most innovative services, products, and systems in the healthcare field. This strategy is in line with the concept of ambient assisted living or enhanced living environment, which focuses on the comfort and health of specific categories of users.
This book covers several topics highlighting the importance of involving end-users in the design of innovative solutions in digital health care, and design considerations of mobile healthcare applications.
Furthermore, the covered topics are described in their current applications in relevant fields focusing on the design of smart solutions, such as biomonitoring systems, activity recognition tools, smart living environments, physical autonomy, and virtual assistance.
This editorial project is addressed to academics, designers, engineers, and practitioners in health care who want to promote cooperation between academia, stakeholders, and research institutions.
Research has shown the detrimental effects of using mobile phones whilst driving, which are more prominent and concerning for young drivers, who are often less experienced and riskier. As such, this study investigates young drivers’ response times when they encounter a safety–critical event on a suburban road whilst using a mobile phone. To collect high-quality trajectory data, the CARRS-Q advanced driving simulator was used. Thirty-two licenced young drivers were exposed to the sudden braking of the lead vehicle in their lane in three driving conditions: baseline (no phone conversation), handheld, and hands-free. Unlike extant studies, this paper proposes a hybrid modelling framework for the response times of distracted drivers. This framework combines a decision tree model and a correlated grouped random parameters duration model with heterogeneity-in-means. While the decision tree model identifies a priori relationship among main effects, the random parameter model captures unobserved heterogeneity and correlation between random parameters. The modelling results reveal that mobile phone distraction impairs response time behaviour for the majority of drivers. However, some drivers tend to respond earlier whilst being distracted, suggesting that the perceived risk of mobile use might have led to an early response, indicating their risk compensation behaviour. Female drivers tend to respond earlier compared to male drivers, indicating their safer and risk-averse behaviour. Overall, mobile phone distraction appears to deteriorate response time behaviour and poses a significant safety concern to drivers and the overall traffic stream unless mitigated.
In recent years, the continuous development of in-vehicle information systems (IVIS) has greatly enriched the driving experience, while also occupying the driver’s cognitive resources to varying degrees, causing driving distraction. Therefore, studying the influence of the AR-HUD (Augmented Reality Head-up Display, AR-HUD) system on driving behaviour is of great significance for the in-vehicle information system to manage the complexity of information and enhance driving safety. This experiment applied five typical risky driving scenarios under two lighting conditions (daytime and night), as stimulus materials. The effects of eye movement behaviour and risk reaction time indicators during driving were comprehensively analysed. The experiment results showed that the AR-HUD system can significantly improve the subjects' attention to risky AOIs (Area of Interest, AOI) in night driving situations, as well as reduce the difficulty of processing information in risky driving scenarios, thus reducing cognitive load; In terms of reaction time, the AR-HUD system can significantly reduce the driver's perception time for risky driving scenarios, thus responding to risky situations more quickly. The experiment conclusions verified the role of AR-HUD technology in improving driving safety and driving behaviour, and provide a new direction for the future development of in-vehicle information systems.
While the rapid evolution of social media has generated several positive outcomes, there is a growing concern of negative effects due to its excessive usage. The excessive use of social media, often termed as Problematic social media use has been generalised as an addiction-like behaviour that is very common with more established features of drug addictions. In this paper, the relationship between social media use, sleep difficulties and depressive symptoms is evaluated using a survey sample of 205 youth participants, recruited from various areas in Cape Town. The participants completed questionnaires that included a social media addiction scale (SMAS-SF), Insomnia Severity Index (ISI) and Center of Epidemiological Studies Depression Scale (CES-D). The results suggest a high prevalence of social media use among the participants. Furthermore, the findings displayed a positive relationship between social media use and sleep difficulties, while a positive effect of social media use on depressive symptoms was also confirmed among the sample. The findings highlight the potential threats to the health of youth from the excessive use of social media and digital devices. Further studies are required to establish a deeper understanding of this phenomenon.
The logistic activity most visible to the general population is the presence of trucks transporting goods across the nation's highways. Transportation also represents the largest portion of total logistics costs and a large percentage of the problems. At times, these problems arise in the form of accidents, even tragedies, as trucks collide with automobiles. Car-truck accidents, though expensive, are an unfortunate cost of doing business and motorists' behaviors are out of the control of the transportation manager. Recently, the federal government and private industry have attempted to educate motorists concerning dangerous spots around trucks. Programs such as the Share the Road campaign, though mildly successful at directing behaviors of motorists near trucks, do not address motorists' perceptions of trucks—which may determine how they behave around the larger vehicles. This article is one of the first that directly examines motorists' perceptions of trucks on the highway and the effect these perceptions have on support for stricter safety regulation of the trucking industry. Based on a national random sample of U.S. motorists, these results suggest that the general U.S. driving population's perception of trucks is predominately negative, and these perceptions are significant predictors of support for stricter truck speed regulation.
Distracted driving refers to multisensory integration and attention shifts between attentional driving and different interferences from different modalities, including visual and auditory stimuli. Here, we compared the behavioral performance with interacting multisensory distractors during attentional driving. Then, the independent component analysis (ICA) and event-related spectral perturbation (ERSP) were applied to investigate the neural oscillation changes. The behavioral results showed that the response times (RTs) increased when distractors appeared in response to attentional driving. Moreover, the RTs were longer when the distractor interference was presented in the auditory modality compared with the visual modality. Eye movement intervals showed shorter tracking saccades under distractor interference. These results may indicate that attentional driving performance was impaired under the exposure to multisensory distractor interference. The ERSPs under visual and auditory distraction exposure showed decreased beta power in the frontal area, increased theta and delta power in the central area, and decreased alpha power in the parietal area. During this process, distracted driving under cross-modal sensory interference required more neural oscillation involvement. Moreover, the visual modality showed increased gamma power in the frontal, central, parietal and occipital areas, while the auditory modality showed decreased gamma power in the frontal area, indicating that auditory interference could intervene in top-down attentional processing.
This research introduces requirements for subjective instruments that assess the cognitive workload of in-vehicle information systems (IVIS) while driving. The suitability of 11 existing subjective instruments is evaluated, but none of the instruments matches all of the proposed requirements for this specific scenario. Therefore, a new subjective one-item measure is presented. The one-item measure is based on the mental dimension of the NASA Task Load Index (NASA-TLX) questionnaire. It combines the discussed requirements for IVIS research, e.g., time-efficiency and descriptiveness for non-expert participants. A series of three studies with 107 participants overall was conducted to verify the suitability of the measure. The results show that the instrument discriminates effectively and is valid between different levels of cognitive workload. The results are stable across different experimental setups and samples, and the instrument shows high sensitivity even in non-critical cognitive load levels.
Background
Dual-task interference is a concern when users attempt to use head mounted displays (HMD) while performing seated manual control tasks. Auditory warnings of information displayed on the HMD may or may not assist users while multi-tasking.
Objective
In this study, we investigated the dual-task interference of words, to be remembered later, presented on a HMD and motor control in a manual tracking task. The word presentations were warned or not warned with auditory signals and the impact of audio warnings were examined.
Methods
Participants were required to perform five tasks: (1) a compensatory tracking task performed alone, (2) a word memory task performed alone, (3) a tracking and word memory task, (4) a word memory task with words preceded by audial signals, and (5) a tracking and word memory task with words preceded by audial signals. In addition, in the dual-tasks, half of the word presentations were paired with directions changes in the tracking task to test for immediate perceptual interference.
Results
There were significant dual task costs for both mean tracking error and later word recall. Additionally, participants took significantly longer to respond to motion changes paired with word presentations than motion changes not paired with word presentations. However, the impact of auditory warnings on tracking performance was nuanced.
Conclusion
Even with an in field of view transparent HMD momentary and sustained cognitive dual-task interference remains. Reaction times are affected most in the worst case scenario, when task critical events occur at the same time as a text message.
Application
The use of HMDs in time critical manual control tasks (such as operating machinery) should be limited. The use of audial warnings to alert operators to information displayed on an HMD requires further research; it may disrupt appropriate or natural task ordering.
Aomation has become prevalent in the everyday lives of humans. However, despite significant technological advancements, human supervision and intervention are still necessary in almost all sectors of automation, ranging from manufacturing and transportation to disaster management and health care [1]. Therefore, it is expected that the future will be built around human?agent collectives [2] that will require efficient and successful interaction and coordination between humans and machines. It is well established that, to achieve this coordination, human trust in automation plays a central role [3]-[5]. For example, the benefits of automation are lost when humans override it due to a fundamental lack of trust [3], [5], and accidents may occur due to human mistrust in such systems [6]. Therefore, trust should be appropriately calibrated to avoid the disuse or misuse of automation [4].
Cette thèse vise à étudier les facteurs de dégradation dans la prise de décision des pilotes d’avion dans des situations dynamiques, en vue de définir les principes d’une assistance à la prise de décision dans les futurs cockpits d’avion. L’analyse des processus de prise de décision dans le domaine aéronautique a permis de centrer la problématique sur la question du contrôle cognitif. Nous avons considéré le Modèle de Contrôle Contextuel (Hollnagel, 1993), qui présente quatre modes de contrôle cognitif - stratégique, tactique, opportuniste et brouillé, du plus au moins proactif - et nous avons exploré les liens entre ces modes, la contrainte de la situation, et l’astreinte des opérateurs. Cela a abouti à l’hypothèse que l’on pouvait déterminer le mode de contrôle cognitif instancié à partir de la connaissance de la contrainte et de la mesure de l’astreinte, via des mesures physiologiques (rythme cardiaque) ou neurophysiologiques (oxygénation du cortex préfrontal). À l’aide d’une Analyse Cognitive du Travail réalisée sur l’activité de pilotage, nous avons construit et mené deux expérimentations afin d’explorer les liens évoqués ci-dessus : l’une en laboratoire avec des étudiants confrontés au logiciel MATB-II, l’autre en simulateur de vol avec des pilotes experts confrontés à des scénarios réalistes. Les résultats expérimentaux ont confirmé les liens entre les modes de contrôle et la contrainte, montrant une adoption préférentielle du mode tactique lorsque la contrainte est faible. Nous avons également observé un lien entre modes de contrôle et astreinte. En effet, le taux d’oxygénation sanguine du cortex préfrontal est plus bas pour le mode tactique que pour les autres modes. Enfin, ces deux expérimentations ont montré que le mode tactique est le plus efficient, puisqu’il est associé au plus faible niveau d’astreinte et à des performances correctes. Les apports de cette étude sont discutés au regard des perspectives concernant le développement d’assistances adaptatives.
As vehicles become increasingly automated, drivers may allocate more of their attention to various non-driving tasks or experience suboptimal workload levels while monitoring the environment and/or automation. However, until fully automated vehicles are available in the market, drivers are still expected to allocate some level of attention to the driving environment and take over the driving task if necessary. Attentive user interfaces (AUIs) are interfaces that adapt based on the operator’s state and task/environmental demands to manage and direct the operator’s attention. In this chapter, we examine how AUIs can be used to modulate drivers’ attention in automated vehicles. We begin by discussing the frameworks that have been used to define AUIs, followed by the relationship between workload, arousal, and attention. We then review the research on AUIs in the driving context and discuss opportunities for further research.
Automated driving is transforming the driving experience in the 21st-century vehicle. As a result, interacting with in-vehicle information systems, infotainment, in-car productivity or social interactions and real-life experiences with other passengers in the car, are slowly emerging as primary activities. UX researchers focus more and more on the users not only by developing products and services for them and enhancing their experiences but also actively involving them in co-designing for their own experience. Our research with designers inside the automotive industry suggests that the industry is exceptionally traditional regarding the methods and tools used to design and evaluate interactive experiences in comparison to other domains. In this chapter, we will report on the limitations of the industry in comparison to academia. Besides, we will report on the needs of the automotive UX practitioners and discuss the state of the art methods and tools that are most valued in the automotive industry.
Background: Reaction time is the ability to respond quickly to a stimulus. Athletes can improve reaction times by training to make the right choices (choice reaction).Simple reaction time is very important in activities such as 100 meter sprint on the track or in the pool. There are various methods to measure reaction time but most of these methods require expensive machines or computer software. Other common method to measure reaction time is the meter stick test or the Ruler Drop Test. Objective: To prove intrarater reliability of measuring reaction time with audio visual reaction time machine and ruler drop test. Methods: Design: Analytical study. Subject: Total 92 female subjects were taken for the study. Informed consent was obtained. Reaction time measured with audio visual machine and Ruler Drop Test. Reaction time was noted. After a gap of one day both the test were done again. Reaction time was measured. Same procedure was repeated twice and data was noted. Result: Interclass correlation method (ICC) was used to prove intrarater reliability of the tests to measure reaction time. Intrarater reliabilities for audio visual reaction time machine (ICC=0.889) were higher than for ruler drop test (ICC=.743). Conclusion: These results show that both these tests are highly reliable for measuring reaction time and ruler drop test can also be used in cases where audio visual reaction time machine is not present.
La conducción distraída es uno de los factores humanos más importantes en la seguridad del transporte y, por ende, es un riesgo que se está convirtiendo en una creciente preocupación para la seguridad vial. La investigación establece que el uso del teléfono celular puede ser la fuente de distracción más importante para los conductores dentro del vehículo, dado que su uso añade demandas cognitivas, físicas o visuales al conductor hacia una tarea secundaria que desvía la atención de las actividades críticas para una conducción segura y, por tanto, puede afectar negativamente el comportamiento y desempeño del conductor. El objetivo de la presente investigación fue estudiar los efectos de las distracciones debido al uso del teléfono celular en las respuestas del conductor durante la tarea de conducción y su vínculo con la ocurrencia de accidentes de tránsito. Los resultados sugieren que el uso del teléfono celular, independientemente de las tareas y modalidad utilizada tienen un efecto negativo en el comportamiento y desempeño de los conductores y, por tanto, los usuarios que usan el teléfono celular mientras conducen corren un mayor riesgo de estar involucrado en un accidente de tránsito, principalmente los conductores mayores y los jóvenes, siendo estos últimos los que están sujetos a una mayor exposición y altos riesgos ante esta distracción.
Este estudio busca estudiar el uso de aceite reciclado de cocina (WCO, por sus siglas en inglés) para mejorar el desempeño en fatiga y deformación permanente del asfalto modificado con polímeros comerciales. Se seleccionaron y caracterizaron los materiales a utilizar con este fin. La metodología consistió en realizar pruebas previas para determinar el comportamiento del asfalto con el WCO. Luego, se modificó el asfalto a distintas dosificaciones de WCO y de polímero comercial (SBS o RET). Por último, se acondicionaron las muestras, se midió el grado de desempeño (PG) y se evaluó su resistencia a la deformación y a la fatiga mediante ensayos avanzados de reología. Se encontró que el aceite disminuye el grado superior e inferior del PG. Además, se evidenció que la presencia del WCO afectó la interacción del asfalto con el SBS. No obstante, con la incorporación del RET al asfalto con aceite, el límite superior de PG aumentó 2 grados sin afectar las temperaturas intermedia y baja. El análisis estadístico determinó que el polímero utilizado en cada muestra (SBS o RET) fue el factor que generó diferencias más significativas en la resistencia a deformación permanente y fatiga. La dosificación de cada polímero influenció mayormente en la recuperación elástica. Además, se determinó que la diferencia en la cantidad de WCO utilizado en las muestras del diseño experimental no generó cambios significativos en las variables medidas. Por último, se determinaron los rangos de dosificación de polímero y WCO necesarios para alcanzar los PG requeridos en Costa Rica. Generalmente, las guías de diseño de asfalto utilizadas en el país se establecen para suplir distintos requerimientos a los presentes en las carreteras nacionales. Por lo que este estudio permite sentar las bases de una metodología que oriente en el proceso de modificación de asfaltos y brinde mayor detalle de cómo garantizar un buen desempeño de los asfaltos nacionales.
The possibilities for measuring workload or driver distraction by means of the Peripheral Detection Task during driving with in-vehicle equipment were investigated in a driving simulator experiment. The results show that the Peripheral Detection Task is a very sensitive method of measuring peaks in workload, induced by either a critical scenario or messages provided by a driver support system. The more demanding the task, the more cues will be missed and the longer the response times to the Peripheral Detection Task. Also, the experiment showed that the hypothesis that PDT measures the width of the functional field of view (perceptual tunnelling) is not supported. The results favour the 'cognitive tunnelling' hypothesis. This is consistent with the hypothesis that the PDT measures the (cognitive) selectivity of attention.
Driver distraction can arise from sources internal as well as external to the driver. In this paper we describe a study (in progress) designed to examine the influence of internal distraction, created by cognitive tasks, on drivers' visual behavior and vehicle control. Sixteen drivers will drive a city route while carrying out tasks of varying cognitive complexity. The tasks and their responses will be communicated via a handsfree cell phone so that drivers will not have to look away from the road or manually operate the phone. Driver performance will be examined under conditions of close vehicle following and more open driving conditions. Visual scanning patterns will be recorded using eyetracking equipment, measures of vehicle control will be obtained using the MicroDAS system, and drivers' subjective evaluation of workload and safety will be assessed through questionnaires. Based on previous research, it is expected that increased cognitive load will result in a reduced area of visual inspection. In addition, detailed analyses will be made of the fixation distributions as a function of cognitive task. The results of this study will contribute to the understanding of driver internal distraction that may be associated with voice interactive technologies.
Driving a vehicle may seem to be a fairly simple task. After some initial training many people are able to handle a car safely. Nevertheless, accidents do occur and the majority of these accidents can be attributed to human failure. At present there are factors that may even lead to increased human failure in traffic. Firstly, owing in part to increased welfare, the number of vehicles on the road is increasing. Increased road intensity leads to higher demands on the human information processing system and an increased likelihood of vehicles colliding. Secondly, people continue to drive well into old age. Elderly people suffer from specific problems in terms of divided attention performance, a task that is more and more required in traffic. One of the causes of these increased demands is the introduction of new technology into the vehicle. It began with a car radio, was followed by car-phones and route guidance systems, and will soon be followed by collision avoidance systems, intelligent cruise controls and so on. All these systems require drivers’ attention to be divided between the system and the primary task of longitudinal and lateral vehicle control. Thirdly, drivers in a diminished state endanger safety on the road. Longer journeys are planned and night time driving increases for economic purposes and/or to avoid congestions. Driver fatigue is currently an important factor in accident causation. But not only lengthy driving affects driver state, a diminished driver state can also be the result of the use of alcohol or (medicinal) sedative drugs. The above-mentioned examples have in common that in all cases driver workload is affected. An increase in traffic density increases the complexity of the driving task. Additional systems in the vehicle add to task complexity. A reduced driver state affects the ability to deal with these demands. How to assess this, i.e. how to assess driver mental workload is the main theme of this thesis. In chapter 1, the theoretical aspects of mental workload are introduced. The difference between task demand, i.e. the external demand, the goals that have to be reached, and (work)load, i.e. the individual reaction to these demands, receive attention in this chapter. Mental workload is defined as a relative concept; it is the ratio of demand to allocated resources. Task difficulty is explicitly separated from task complexity. Task complexity would have been an objective property of the task that is related to demand on computational processes, were it not dependent upon individual goal setting. Task difficulty is very much dependent upon the context and the individual. Applied strategies may affect resource allocation or task complexity and thus difficulty and mental workload.
The results of a multi-year research program to identify the factors associated with variations in subjective workload within and between different types of tasks are reviewed. Subjective evaluations of 10 workload-related factors were obtained from 16 different experiments. The experimental tasks included simple cognitive and manual control tasks, complex laboratory and supervisory control tasks, and aircraft simulation. Task-, behavior-, and subject-related correlates of subjective workload experiences varied as a function of difficulty manipulations within experiments, different sources of workload between experiments, and individual differences in workload definition. A multi-dimensional rating scale is proposed in which information about the magnitude and sources of six workload-related factors are combined to derive a sensitive and reliable estimate of workload.
Obra sobre los factores humanos en la ingeniería, cuya organización responde a la forma como los humanos procesamos la información: 1. Introducción a la psicología de la ingeniería y al desempeño humano. 2. Detección de signos, teoría de la información y juicio absoluto. 3. Atención en percepción y despliegue del espacio. 4. Despliegues espaciales. 5. Navegación e interacción en ambientes reales y virtuales. 6. Lenguaje y comunicación. 7. Memoria y capacitación. 8. Toma de decisiones. 9. Selección de la acción. 10. Control manual. 11. Atención, tiempo compartido y carga laboral. 12. Estrés y error humano y 13. Sistemas complejos, control de procesos y automatización.
Recent research is reviewed and its implications discussed. "On-the-Spot" accident investigations have confirmed that errors of perception by the driver are a major contributory factor to accidents. However, the available evidence suggests that few of these are attributable to reduced or defective vision, since at best only a weak relationship has been found between a driver's level of vision (or visual performance) and his accident rate. A number of reasons for this general finding are considered, including driver compensation. For all drivers, the rapid fall in visual acuity with angular distance from the centre of vision presents particular problems, giving special significance to eye-movement patterns and the problems of visual search. Numerous physical and psychophysical restrictions on visibility could lead to the "looked, but failed to see" type of accident, but their relative importance requires evaluation. There is now much evidence that the driver is quite often operating beyond his visual or perceptual capabilities in a number of key driving situations, including overtaking, joining or crossing a high-speed road, and a number of nighttime situations. It is concluded that "expectancy", based on experience in both the long and the short term, has a profound influence on driver perception and assessment of risk. For all drivers, serious errors of judgment from time to time would seem inevitable. In general, these do not lead to accidents because of, among other things, the safety margins added by the driver and adjustments made by other road users. Thus, despite his limitations and fallibilities, the average driver is involved in surprisingly few serious incidents, particularly in view of the rapid rate of decisionmaking that is required. However, the present accident rate should not be accepted as inevitable and various countermeasures are discussed.
In this study, 150 subjects observed a 25-minute video driving sequence containing 45 highway traffic situations to which they were expected to respond by manipulation of simulated vehicle controls. Each situation occurred under five conditions of distraction: placing a cellular phone call, carrying on a causal cellular phone conversation, carrying on an intense cellular phone conversation, tuning a radio, and no distraction. All of the distractions led to significant increases in the proportion of situations to which subjects failed to respond. However, significant age differences of nonresponse appeared. Among subjects over age 50, nonresponses increased by about one-third under all of the telephone distractions. The response rate of younger subjects increased by a lesser degree except under intense conversation. Results were not influenced by gender or prior experience with cellular phones. The authors conclude that older drivers might reduce their accident risk during attention-demanding traffic conditions by avoiding use of cellular phones and that other drivers might do so by refraining from calls involving intense conversation.
The effects of a mobile telephone task on young and elderly drivers' choice reaction time, headway, lateral position, and workload were studied when the subjects were driving in a car-following situation, in the VTI driving simulator. It was found that a mobile telephone task had a negative effect upon the drivers' choice reaction time, and that the effect was more pronounced for the elderly drivers. Furthermore, the subjects did not compensate for their increased reaction time by increasing their headway during the phone task. The subjects' mental workload, as measured by the NASA-TLX, increased as a function of the mobile telephone task. No effect on the subjects' lateral position could be detected. Taken together, these results indicate that the accident risk can increase when a driver is using the mobile telephone in a car following situation. The reasons for the increased risk, and possible ways to eliminate it, are also discussed.
Behavioral evidence suggests that the processing of parafoveal stimuli decreases as the perceptual demands of a task at fixation increase. However, it remains unclear whether or not this effect of perceptual load occurs during initial sensory-level processing at early stages of visuocortical analysis. Using event-related potential measures, we found that increasing the perceptual load of foveal targets led to a significant decrease in the sensory-evoked response to parafoveal stimuli. Moreover, these effects were observed using two different operational definitions of perceptual load. This result indicates that perceptual load affects the flow of information during the initial stages of visuocortical processing.
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