In-vehicle Information Systems Research Articles

Auditory signs to support traffic awareness

In-vehicle information systems (IVIS) may contribute to increased levels of cognitive workload, which in turn can lead to a more dangerous driving behaviour. An experiment was conducted to examine the use of auditory signs to support drivers' traffic situation awareness. Eighteen experienced truck drivers identified traffic situations based on information conveyed by brief sounds. Aspects of learning, cognitive demand and pleasantness were monitored and rated by the drivers. Differences in cognitive effort was estimated using a dual-task set-up, in which drivers responded to auditory signs while simultaneously performing a simulated driving task. As expected, arbitrary sounds required significantly longer learning times compared to sounds that have a natural meaning in the driving context. The arbitrary sounds also resulted in a significant degradation in response performance, even after the drivers got a chance to learn the sounds. Finally, the results indicate that the use of arbitrary sounds can negatively impact driver satisfaction. These results have implications for a broad range of developing intelligent transport systems designed to assist drivers in absence of fundamental visual information or in visually demanding traffic situations.

Measuring visual distraction in driving: the potential of head movement analysis

Owing to several reasons (e.g. changing light conditions) the measurement of eye movement behaviour is often unstable and data loss can occur. It is investigated whether head movement recording could be an alternative to eye movement analysis for measuring distraction through visual secondary tasks in driving. During a 1-h drive in the driving simulator, 16 participants conducted a self-paced menu system task that was designed according to design principles for commercial in-vehicle information systems. Influence of visual distraction was analysed and compared for parameters of eye and head movement. Parameters like percent road centre for head and eye movement and proportion of head movement were calculated. The results show that head movement analysis can differentiate nearly as well between distracted and attentive driving as parameters based on eye movement recording in this task context. It is concluded that head movement analysis seems to be a promising alternative for assessing drivers’ distraction under certain circumstances.

Useful Field of View of Aging Drivers as a Product Design Tool for In-Vehicle Visual Aids

Technology has provided drivers with in-vehicle information systems (INVIS) that can make driving more pleasurable but at the same time more complex in sharing visual attention. The purpose of this study was to evaluate the use of the useful field of view (UFOV) as a tool for developing driver visual attention and visual processing aids by automobile and INVIS designers. We expressed UFOV as a function of saccadic amplitude between fixation points and durations and evaluated it across different driving scenarios and age groups. Our results suggest that UFOV radius depends on driving scenario, time of event, and age, with two-factor and three-factor interactions among these variables. Based on these results suggestions are made that will aid designers in developing better in-vehicle information systems – scenario information that may otherwise be missed by older drivers.

Comparison of manual vs. speech-based interaction with in-vehicle information systems

This study examined whether speech-based interfaces for different in-vehicle-information-systems (IVIS) reduce the distraction caused by these systems. For three frequently used systems (audio, telephone with name selection, navigation system with address entry and point of interest selection) speech, manual control and driving without IVIS (baseline) were compared. The Lane Change Task was used to assess driving performance. Additionally, gaze behavior and a subjective measure of distraction were analyzed. Speech interfaces improved driving performance, gaze behavior and subjective distraction for all systems with the exception of point-of-interest entry. However, these improvements were overall not strong enough to reach the baseline performance level. Only in easy segments of the driving task the performance level was comparable to baseline. Thus, speech-based IVIS have to be further developed to keep the cognitive complexity at an adequate level which does not disturb driving. However, looking at the benefits, speech control is a must for the car of the future.

Driver distraction based lane-keeping assistance

Abstract Driver assistance systems could be much more effective, if they were adaptive to the driver’s state. Following the idea of a lane-keeping assistance system, which is adaptive to the use of in-vehicle information systems (IVIS), two field experiments were conducted. The first experiment concerned the influence of typical IVIS tasks on lane-keeping. Most IVIS tasks increased the lateral deviations, but in the majority of cases the drivers were still able to stay in their lane. The second experiment concerned two questions: (1) how much lateral support would be needed and (2) how drivers accept this kind of support. The results show that all lateral support algorithms increased the lane-keeping performance with the algorithms providing a higher amount of assistance proving the most useful. All assistance systems were rated as helpful and were considered to increase driver safety, both by the drivers who did not have problems in lane-keeping without assistance. In light of these results an adaptation of a lateral support system to the IVIS-use seems to be useful and worthwhile.

Skill Acquisition While Operating In-Vehicle Information Systems: Interface Design Determines the Level of Safety-Relevant Distractions

This study tested whether the ease of learning to use human-machine interfaces of in-vehicle information systems (IVIS) can be assessed at standstill. Assessing the attentional demand of IVIS should include an evaluation of ease of learning, because the use of IVIS at low skill levels may create safety-relevant distractions. Skill acquisition in operating IVIS was quantified by fitting the power law of practice to training data sets collected in a driving study and at standstill. Participants practiced manual destination entry with two route guidance systems differing in cognitive demand. In Experiment 1, a sample of middle-aged participants was trained while steering routes of varying driving demands. In Experiment 2, another sample of middle-aged participants was trained at standstill. In Experiment 1, display glance times were less affected by driving demands than by total task times and decreased at slightly higher speed-up rates (0.02 higher on average) than task times collected at standstill in Experiment 2. The system interface that minimized cognitive demand was operated more quickly and was easier to learn. Its system delays increased static task times, which still predicted 58% of variance in display glance times compared with even 76% for the second system. The ease of learning to use an IVIS interface and the decrease in attentional demand with training can be assessed at standstill. Fitting the power law of practice to static task times yields parameters that predict display glance times while driving, which makes it possible to compare interfaces with regard to ease of learning.

Practical issues in the application of occlusion to measure visual demands imposed on drivers by in-vehicle tasks

Occlusion is a practical technique to measure the visual demand imposed by in-vehicle tasks and to assess whether a task can be resumed having been interrupted. This study describes a number of important factors and variables that need to be controlled to ensure reliability of results. Training of participants on in-vehicle tasks is found to help consistency and five training sessions are required for complex tasks. No significant differences in training with and without occlusion goggles are reported. The required sample size is dependent on the variability of the task; for those investigated an appropriate sample size is found to be 14. For in-vehicle systems that exhibit a delay in response to the user, consistency is improved when these delays are excluded from timing measurements. In terms of calculating the occlusion parameter R, the within-participant basis is most consistent by taking the ratio of the respective median total shutter open time and total task times across trial repetitions completed by one participant on each task under evaluation and, for the purposes of identifying interface designs that exhibit poor resumability, the 85th percentile value is identified as most suitable. Findings from the study are discussed in terms of future application of the occlusion technique to assess in-vehicle information systems (IVIS).

On-line Method for Evaluating Driver Distraction of Memory-decision Workload Based on Dynamics of Vestibulo-ocular Reflex

Recently, development of in-vehicle information systems provides much information to driver. Despite the usefulness of such systems, it is concerned that information processing demand to the drivers leads to distractions that exert a negative effect on the appropriate driving behavior with handle, quick detection of obstacles and reaction on brake pedal. However, the on-line method to evaluate the influence of distractions while driving has not yet been proposed. Therefore, the purpose of this study is to propose the method to quantitatively evaluate the influence of driver distractions caused by information processing demand in real time. For this purpose, we focus on VOR (vestibulo-ocular reflex) which is involuntary eye movement to compensate against disturbance on the head position for gaze stabilization. First, our method is to identify the eye movement model for a particular subject from measured data without another information processing demand. This model represents the subject's dynamics of VOR. After that, the eye movement is measured when the subject get distracted by paying attention to information processing demand, and it is compared with the identified model output in real time. This model-based method makes it possible to quantitatively evaluate the influence of distraction on VOR. This study experimentally has confirmed that the proposed on-line method is effective to evaluate the influence of driver distractions.

On the reliability of the occlusion technique as a tool for the assessment of the HMI of in-vehicle information and communication systems

In recent years considerable efforts have been spent on the development of the occlusion technique as a procedure for the assessment of the human–machine interface of in-vehicle information and communication systems (IVIS) designed to be used by the driver while driving. The importance and significance of the findings resulting from the application of this procedure depends essentially on its reliability. Because there is a lack of evidence as to whether this basic criterion of measurement is met with this procedure, and because questionable reliability can lead to doubts about their validity, our project strove to clarify this issue. This paper reports on a statistical reanalysis of data obtained from previous experiments. To summarise, the characteristic values found for internal consistency were almost all in the range of .90 for the occlusion technique, which can be considered satisfactory.

A Dynamic Programming Algorithm for Scheduling In-Vehicle Messages

In-vehicle information systems (IVISs) can enhance or compromise driving safety. Such systems present an array of messages that range from collision warnings and navigation instructions to tire pressure and e-mail alerts. If these messages are not properly managed, the IVIS might fail to provide the driver with critical information, which could undermine safety. In addition, if the IVIS simultaneously presents multiple messages, the driver may fail to attend to the most critical information. To date, only simple algorithms that use priority-based filters have been developed to address this problem. This paper presents a dynamic programming model that goes beyond the immediate relevance and urgency parameters of the current Society of Automotive Engineers (SAE) message scheduling algorithm. The resulting algorithm considers the variation of message value over time, which extends the planning horizon and creates a more valuable stream of messages than that based only on the instantaneous message priority. This method has the potential to improve road safety because the most relevant information is displayed to drivers across time and not just the highest priority at any given instant. Applying this algorithm to message sets shows that scheduling that considers the time-based message value, in addition to priority, results in substantially different and potentially better message sequences compared with those based only on message priority. This method can be extended to manage driver workload by adjusting message timing relative to demanding driving maneuvers.

A Roadside ITS Data Bus Prototype for Intelligent Highways

Intelligent transport systems (ITSs) usually include three principal elements: vehicle, driver, and road (or, more generally, the environment). The use of ITS data bus (IDB) has been proposed to build sharable standard interfaces for in-vehicle information systems. Despite broadband communication technologies, such as dedicated short-range communication (DSRC), which have been developed to provide high-quality roadside-vehicle communication services for intelligent highways, the existing IDB model has not paid enough attention to the demands of information exchanges between the roadside and onboard units. In this paper, a new model of the roadside IDB (RIDB) is proposed to improve the existing IDB architecture. The physical layer, data-link layer, and application layer of the new model are also discussed. A prototype system of the RIDB, which is based on the wireless 802.11b protocol, has been developed in a test site. The experimental results demonstrated that the RIDB is feasible to provide high-quality roadside-vehicle and roadside-roadside communication services. Other potential applications of the IDB, such as probe cars and intersection collision prevention, are also discussed. The RIDB proposed in this paper is potentially useful for the construction of an intelligent transport infrastructure.

Effects of cognitive load presence and duration on driver eye movements and event detection performance

This study examined the effects of cognitive load on driving performance for interactions with an in-vehicle information system (IVIS) that varied in duration from 1 to 4 min. Twelve participants drove in a simulator while intermittently performing the IVIS task. There were three IVIS conditions: interacting with the IVIS, non-IVIS periods between IVIS interactions, and baseline driving without the IVIS task. Contrary to our hypothesis, driver response to lead vehicle braking was surprisingly uniform across IVIS conditions. IVIS interaction did undermine driver ability to detect the bicyclist along the side of the road, and some of these performance decrements persisted after the IVIS interaction had ended. Reaction time for bicyclist detection increased from the first to the subsequent minutes of the interaction. Eye movements were influenced by the IVIS conditions but not by task duration. Both ANOVA and factor analyses revealed that some of the changes in eye movements were concurrent with IVIS interaction while others persisted after the driver completed the IVIS interaction. Overall, the findings suggest that two mechanisms might account for the distraction-related performance decrements in this study: competition for processing resources and interference due to activation of competing goals.

A Comparison of Tactile, Visual, and Auditory Warnings for Rear-End Collision Prevention in Simulated Driving

This study examined the effectiveness of rear-end collision warnings presented in different sensory modalities as a function of warning timing in a driving simulator. The proliferation of in-vehicle information and entertainment systems threatens driver attention and may increase the risk of rear-end collisions. Collision warning systems have been shown to improve inattentive and/or distracted driver response time (RT) in rear-end collision situations. However, most previous rear-end collision warning research has not directly compared auditory, visual, and tactile warnings. Sixteen participants in a fixed-base driving simulator experienced four warning conditions: no warning, visual, auditory, and tactile. The warnings activated when the time-to-collision (TTC) reached a critical threshold of 3.0 or 5.0 s. Driver RT was captured from a warning below critical threshold to brake initiation. Drivers with a tactile warning had the shortest mean RT. Drivers with a tactile warning had significantly shorter RT than drivers without a warning and had a significant advantage over drivers with visual warnings. Tactile warnings show promise as effective rear-end collision warnings. The results of this study can be applied to the future design and evaluation of automotive warnings designed to reduce rear-end collisions.

Predicting the distraction of car drivers by cognitive modelling

When reviewing the literature on accident research it becomes obvious that the distraction of car drivers has increased intensively during the last years and that it is a serious reason for many car crashes: drivers are not only faced with a more complex traffic environment, but at the same time the availability of in-vehicle information systems has increased, too. For sure, a major aim must be to gain a better understanding of the underlying distracters and to provide tools for designing both the traffic environment and the in-vehicle interfaces less demanding.

The Effect of Stimulus Modality on Signal Detection: Implications for Assessing the Safety of In-Vehicle Technology

This study examined the effect of two in-vehicle information systems (IVIS) on signal detection in the visual, auditory, and tactile modalities; established whether the detrimental effects of an IVIS on driving could be quantified by these detection tasks; and examined the effect of stimulus modality on signal detection. The peripheral detection task has been used widely for assessing the effects of an IVIS on driving. However, performance on this task relies on drivers' ability to see a series of LEDs, which can be problematic in field tests (e.g., on sunny days). Participants responded to one of three detection tasks during a simulated driving experiment. The effect of IVIS interaction on these detection tasks was also measured. Reduced performance in the detection tasks was assumed to indicate a decline in drivers' ability to handle sudden events in the driving task. Response time to all detection tasks increased by around 200 ms when drivers performed the IVIS tasks, as compared with baseline driving. Analyses of variance and comparison of effect sizes showed the effects of these two IVISs to be the same across the three detection tasks. These detection tasks are useful for quantifying the safety of an IVIS during driving. The absence of a difference in signal detection by modality suggests that performance on these tasks relies on general attentional resources and is not modality specific. The signal detection tasks employed here should be further investigated for their suitability in assessing the safety of in-vehicle systems.

Assessing the visual demand from in-vehicle information systems by means of the occlusion technique: the effects of participant age

Occlusion is a measurement technique for assessing the visual demand and interruptability of in-vehicle information system (IVIS) tasks using a means for intermittent viewing of the IVIS displays/controls. Testing the visual demand of IVIS tasks using occlusion is gaining international support, largely due to it being a relatively simple method to use. Although an ISO occlusion standard has been published, some important issues remain; these include developing a robust and fully detailed measurement protocol. The age of participants is an important individual difference potentially affecting the validity and reliability of results from occlusion. To develop an effective protocol, the age ranges of participants need to be specified; otherwise experimenters undertaking measurements with varying age samples for the same systems/tasks may come to different conclusions. To assess the impact of age on occlusion task performance, 60 participants in various age ranges were tested on four different IVIS tasks. The results showed age-related differences; in particular, the older participants showed a greater spread of measurements. Excluding the issues of representative samples, the results imply that purely to obtain minimal inter-subject variability an occlusion measurement should use younger/middle-aged participants only.

Pattern Adaptive and Finger Image-guided Keypad Interface for In-vehicle Information Systems

Abstract In this paper we propose a pattern adaptive keypad interface for in-vehicle information system. The keypad interface recommends the estimated input sequence to fit the user’s preference based on individual model of operation pattern. Pattern (shape) of button switches corresponding to the estimated input sequence is actively reformed. Button switches are displayed tactilely and visually. Finger image is shown on the monitor in real-time in order to guide input operation on the tactile input device. To confirm the effect of the keypad interface, experiments are performed comparing with a touch screen on which pattern (shape) of buttons switch is unchanged.

Mitigating driver distraction with retrospective and concurrent feedback

Objectives An experiment was conducted to assess the effects of retrospective and combined retrospective and concurrent feedback on driver performance and engagement in distracting activities. Background A previous study conducted by the authors showed that concurrent (or real time) feedback can help drivers better modulate their distracting activities. However, research also shows that concurrent feedback can pose additional distractions due to the limited time and resources available during driving. Retrospective feedback, which is presented at the end of a trip (i.e., post-drive), can include additional information on safety critical situations during a trip and help the driver learn safe driving habits. Method A driving simulator study was conducted with 48 participants and 3 conditions: retrospective feedback, combined feedback (both retrospective and concurrent), and no feedback (baseline case). Results The feedback conditions (retrospective and combined) resulted in faster response to lead vehicle braking events as depicted by shorter accelerator release times. Moreover, combined feedback also resulted in longer glances to the road. Conclusions The results suggest that both feedback types have potential to improve immediate driving performance and driver engagement in distractions. Application Combined feedback holds the most promise for mitigating the effects of distraction from in-vehicle information systems.

In-vehicle information systems to improve traffic safety in road tunnels

Abstract Introduction In-vehicle information systems can improve safety, improve driver’s situational awareness and reduce anxiety, but they may also increase mental workload and distraction. This issue is particularly important in road tunnels because they create extremely dangerous driving conditions. Goals To evaluate the effect of in-vehicle displays on driving safety in road tunnels, this paper address two questions: (1) can we still add information to in-vehicle displays without compromising safety? and (2) if information can still be added, how much information should added? Method We simulated tunnel driving and evaluated the effects of driving performance with innovative in-vehicle displays in terms of safety and satisfaction. We compared a highly informative display and a minimal information display with driving without a display as a control. Results Using the displays, drivers improved their speed control but had some difficulty in maintaining lane stability, apparently due to some distraction imposed by the displays. Yet, neither of them increased the mental workload relative to driving without a display. The drivers found the in-vehicle displays useful and responded well to the presented information. The drivers preferred the more informative display to the minimalist display, although it slightly increased distraction from road. Conclusions In light of the potential benefits of in-vehicle displays, the level of distraction was relatively minor and should not compromise driving safety. Apparently, the highly informative display provided drivers with more information that reduced anxiety and boredom, which are common psychological experiences during tunnel driving. Thus, safety-related information displays can be added to improve safety even when some of their benefits are offset by increased distraction.

Real-Time Detection of Driver Cognitive Distraction Using Support Vector Machines

As use of in-vehicle information systems (IVISs) such as cell phones, navigation systems, and satellite radios has increased, driver distraction has become an important and growing safety concern. A promising way to overcome this problem is to detect driver distraction and adapt in-vehicle systems accordingly to mitigate such distractions. To realize this strategy, this paper applied support vector machines (SVMs), which is a data mining method, to develop a real-time approach for detecting cognitive distraction using drivers' eye movements and driving performance data. Data were collected in a simulator experiment in which ten participants interacted with an IVIS while driving. The data were used to train and test both SVM and logistic regression models, and three different model characteristics were investigated: how distraction was defined, which data were input to the model, and how the input data were summarized. The results show that the SVM models were able to detect driver distraction with an average accuracy of 81.1%, outperforming more traditional logistic regression models. The best performing model (96.1% accuracy) resulted when distraction was defined using experimental conditions (i.e., IVIS drive or baseline drive), the input data were comprised of eye movement and driving measures, and these data were summarized over a 40-s window with 95% overlap of windows. These results demonstrate that eye movements and simple measures of driving performance can be used to detect driver distraction in real time. Potential applications of this paper include the design of adaptive in-vehicle systems and the evaluation of driver distraction