اثرات عملکرد راننده از حواس پرتی همزمان بصری و شناختی و رفتار سازگاری

Abstract Driver distraction has become a major concern for transportation safety due to increasing use of infotainment systems in vehicles. To reduce safety risks, it is crucial to understand how fundamental aspects of distracting activities affect driver behavior at different levels of vehicle control. This study used a simulator-based experiment to assess the effects of visual, cognitive and simultaneous distraction on operational (braking, accelerating) and tactical (maneuvering) control of vehicles. Twenty drivers participated in the study and drove in lead-car following or passing scenarios under four distraction conditions: without distraction, with visual distraction, with cognitive distraction, and with simultaneous distraction. Results revealed higher perceived workload for passing than following. Simultaneous distraction was most demanding and also resulted in the greatest steering errors among distraction conditions during both driving tasks. During passing, drivers also appeared to slow down their responses to secondary distraction tasks as workload increased. Visual distraction was associated with more off-road glances (to an in-vehicle device) and resulted in high workload. Longer headway times were also observed under visual distraction, suggesting driver adaptation to the workload. Similarly, cognitive distraction also increased driver workload but this demand did not translate into steering errors as high as for visual distraction. In general, findings indicate that tactical control of a vehicle demands more workload than operational control. Visual and cognitive distractions both increase driver workload, but they influence vehicle control and gaze behavior in different ways.

. Introduction The soaring popularity of in-vehicle infotainment systems (e.g., navigation systems, mp3 players, smart phones, etc.) has raised concern for driver distractions and roadway safety. A study that examined the behavior of 100 drivers in a naturalistic environment showed that 78% of crashes (n = 100) and 65% of near-crashes (n = 100) involved some form of driver inattention, among which distraction by in-vehicle infotainment systems accounted for approximately 25% of all events ( Klauer et al., 2006). Roadway safety risks due to inattention have been found to be especially high for young drivers because of their inexperience and high adoption of new technology ( Lee, 2007 and Stutts et al., 2001). To mitigate such risks it is important to understand how distracting activities affect driver behavior. Driving tasks require a driver to monitor and comprehend the roadway in real time and to make timely decisions to maneuver a vehicle safely (Ma & Kaber, 2005). Driving involves three levels of skill or control including operational, tactical and strategic (Michon, 1985). Operational control refers to driver reactions to roadway situations with limited conscious control, such as reactive steering or braking due to sudden changes in lead vehicle behavior. This level of control relies on sensorimotor skills of drivers and occurs in the millisecond time frame. Tactical control requires drivers to maneuver a vehicle in response to roadway conditions, including negotiation of traffic, intersections, etc. For example, drivers may reduce speed or overtake a slow vehicle based on immediate roadway demands, such as following traffic. This type of control occurs in time frame of several seconds. Strategic control refers to route planning, including goal selection and identification of route criteria, and operates on the time scale of minutes to hours (enroute or offline, respectively). Among these three levels, operational and tactical controls are required by real-time traffic negotiation. Failures in these two types of control can lead to crashes. Young drivers are especially vulnerable to poor performance at these two levels of control because they may be inexperienced in vehicle control skills; they may not be able to correctly identify/anticipate hazards; and they may poorly judge their own abilities in driving (Lee, 2007). These vulnerabilities may also be exaggerated under distraction situations. Driver distraction is defined as a diversion of attention away from activities critical to safe driving for performance of a secondary competing activity (Lee, Regan, & Young, 2009). Multiple resource theory (MRT) suggests that secondary tasks that compete for the same resources required by driving could degrade driver performance (Wickens, 2002). Two essential resources for driving are visual attention to perceive the roadway situation and central processing resources to comprehend and project situations and make decisions. Secondary tasks demanding these two types of resources (e.g., cell phone use, navigation aid use) pose visual and cognitive distractions to driving. Visual distraction attracts visual attention from the roadway; cognitive distraction competes with driving tasks for central processing resources. These two types of distraction can affect driver behavior and undermine driving performance. Visual distractions can cause drivers to look away from the roadway (e.g., to reprogram a navigation aid) and has been found to lead to large and frequent lane deviations, uneven steering control, and slow responses to lead vehicle braking (Dingus et al., 1989 and Zhang et al., 2006). Compared to visual distraction, cognitive distraction has a less overt effect. Cognitive distractions can also cause drivers to fail to perceive critical cues in the roadway environment but, more importantly, fail to project the intent of other drivers (Malaterre, 1990). Recarte and Nunes (2000) found cognitive distraction to cause drivers to concentrate their gaze in the center of the driving scene. This diminished their ability to detect targets across the entire driving scene and to effectively plan vehicle control behaviors. Similarly, Strayer, Drews, and Johnston (2003) found cognitive distraction to impair the comprehension of information related to objects that drivers look at. From a performance perspective, cognitive distraction has also been found to delay driver responses to hazards and cause uneven steering control (Horrey & Wickens, 2006). However, the effects of distraction are not passively imposed on drivers. Drivers usually chose to engage themselves in a secondary task and adapt their behavior accordingly. During visual distraction, drivers intermittently sample roadway situations before finishing a secondary task. Senders et al. (1967) modeled this behavior sampling based on data from an in vivo experiment in which drivers wore a helmet to obstruct their peripheral vision. They observed that when drivers looked away from the road with focal vision, uncertainty about the roadway situation increased. When uncertainty reached a certain threshold, drivers looked back to the road with focal vision. Wierwille (1993) found the threshold level of uncertainty to occur with an off-road glance duration at 1.8 s on straight-road segments and 1.2 s on curves. He used an instrumented vehicle on public roads with a moving map navigation display as the off-road distraction. Cognitive distraction has also been found influential in driving behavior. Under cognitive distraction drivers tend to increase headway distance to a lead vehicle in a car-following scenario, which requires mainly operational control (instantaneous braking and accelerating) (Strayer and Drews, 2004 and Strayer et al., 2003). However, this behavior may be simply an automatic process or a consequence of lack of attention when drivers perform operational tasks. Such adaptation, increasing headway, may not compensate for the full range of demands in a highly dynamic situation either. Horrey and Simons (2007) found that unlike the car-following scenario, drivers did not increase their safety margin (i.e., headway distance to other vehicles) under high cognitive workload, when overtaking a vehicle. Overtaking requires the negotiation of traffic (i.e., tactical vehicle control) and imposes higher demands than car-following. These findings suggest that cognitive distraction may diminish driver capacity to adapt behavior in specific driving tasks, especially when workload is high and the task is time-constrained. The majority of prior research on driving distraction focuses on either specific secondary tasks (e.g., cell phone conversation, text messaging, etc.) or one type of distraction (Alm and Nilsson, 1995, Blanco et al., 2006, Dingus et al., 1989, Horrey and Simons, 2007 and Lee et al., 2001). However, to understand the effects of a large variety of secondary tasks, which can impose both visual and cognitive driver distraction simultaneously, it is necessary to identify independent and combined effects of these two types of distraction in highly realistic and varied driving scenarios. One study that compared the effects of visual, cognitive and combined distraction found that visual distraction dominates the effects of combined distraction (Liang & Lee, 2010). However, the characteristics of the visual and cognitive distraction tasks used in this study were confounded in terms of the response modality required of drivers (both required manual responses). Therefore, attentional resource competition with the primary driving task was not unique among the distraction tasks. Beyond this, only a simple car-following scenario was used in a lower fidelity driving simulation, and visual and cognitive distractions were presented in a sequential manner and not simultaneously. Consequently, Liang and Lee (2010) did not assess the interaction effect of the two types of distraction. Another study by Engström, Johansson, and Östlund (2005) also addressed the effects of visual and cognitive distractions in driving. However, this was similarly limited in terms of the required control modes and did not investigate the interaction between the two sources of distraction. In addition, the cognitive task in the Engström et al. study (audio-verbal) required verbal coding (different sounds) rather than spatial coding (orientation) as a form of competition for central processing recourses with driving tasks that primarily rely on spatial processing. Therefore, the study might have underestimated the influence of cognitive distraction. There remains a question as to whether combined visual and cognitive distraction in driving is essentially the “sum” of the two types of distraction or if implications for performance are different than the sum of the parts. There is also a need to investigate the effects of visual and cognitive distractions to driving unique task definitions from an attentional resource perspective. Therefore, the goal of the current study was to examine the interaction between uniquely defined visual and cognitive distractions on driver behavior, including performance and visual behavior, under both simple car-following (operational control) and dynamic overtaking (tactical control) driving scenarios using a simulator-based experiment. (Hypotheses on the specific experimental conditions are presented in the Methods.)

Conclusions The findings of this study demonstrate that driver visual and cognitive distractions have independent and combined effects on driver performance, visual behavior and workload. These effects also appear to vary depending upon the level of driving control, including operational and tactical. While visual distraction appears to increase driver workload through more complex gaze behavior, cognitive distraction also leads to increased workload by dividing driver concentration among the roadway and secondary task(s). Drivers appear to compensate for visual distraction by increasing their headway time. However, such adaptation may fail to occur when the task demands are considerably high, as in tactical control, and especially with simultaneous distraction. In general, tactical control behaviors in driving appear to be more demanding in terms of cognitive and motor control resources than operational behaviors. Therefore, tactical behavior is more sensitive to driver distraction and less conducive to adaptation. Furthermore, when engaged in tactical control and posed with simultaneous distraction conditions, drivers perceive higher workload and accordingly set their priority on the primary driving task, which results in slower responses to secondary tasks. This study used young drivers (16–21 years old), who have been found to be more vulnerable to the influence of distraction because of their inexperience and interest in the use of new technologies while driving. Research has noted that young drivers represent the highest crash risk population among all drivers (Stutts et al., 2001). The results of this study provide insight for high-risk drivers, but at the same time may be somewhat exaggerated relative to the adult experienced driver population. Consequently, this particular sample may limit the generalization of the study results. A broader sample population should be investigated in future research. In addition, because no actual threats are posed by driving in a simulated environment, drivers may engage in more liberal performance in such an environment, compared to driving in the real world. Beyond this, the abstract secondary tasks used in this study were neither related to primary driving goals nor to the daily life goals of the participants. Therefore, drivers may not be accustomed to or motivated to fully engage in such tasks as they do for cell phone and GPS devices. These limitations of the study need to be taken into account in application of the results and future applied research investigations should explore driver use of actual on-line and in-vehicle navigation systems for driver cognitive and visual distraction affects on performance under the various levels of driving control, including operational, tactical and strategic.