Evaluation of driver demand for in-vehicle information: An integrated method combining clustering and multivariate ordered probit model.

INTRODUCTION: The proper execution of driving tasks requires information support. While new technologies have increased the convenience of information access, they have also increased the risk of driver distraction and information overload. Meeting drivers' demands and providing them with adequate information are crucial to driving safety. METHODS: Based on a sample of 1,060 questionnaires, research on driving information demands is conducted from the perspective of drivers. A principal component analysis and the entropy method are integrated to quantify the driving information demands and preferences of drivers. The K-means classification algorithm is selected to classify the different types of driving information demands, including dynamic traffic information demands (DTIDs), static traffic information demands (STIDs), automotive driving status information demands (ATIDs), and total driving information demands (TDIDs). Fisher's least significant difference (LSD) is used to compare the differences in the numbers of self-reported crashes among different driving information demand levels. A multivariate ordered probit model is established to explore the potential factors that influence the different types of driving information demand levels. RESULTS: The DTID is the driver's most in-demand information type, and accordingly, gender, driving experience, average driving mileage, driving skills, and driving style significantly affect the driving information demand levels. Moreover, the number of self-reported crashes decreased as the DTID, ATID, and TDID levels decreased. CONCLUSION: Driving information demands are affected by a variety of factors. This study also provides evidence that drivers who have higher driving information demands are more likely to drive more carefully and safely than their counterparts who do not exhibit high driving information demands. PRACTICAL IMPLICATIONS: The results are indicative of the driver-oriented design of in-vehicle information systems and the development of dynamic information services as a way to avoid negative impacts on driving.

On the forces of driver distraction: Explainable predictions for the visual demand of in-vehicle touchscreen interactions.

With modern infotainment systems, drivers are increasingly tempted to engage in secondary tasks while driving. Since distracted driving is already one of the main causes of fatal accidents, in-vehicle touchscreens must be as little distracting as possible. To ensure that these systems are safe to use, they undergo elaborate and expensive empirical testing, requiring fully functional prototypes. Thus, early-stage methods informing designers about the implication their design may have on driver distraction are of great value. This paper presents a machine learning method that, based on anticipated usage scenarios, predicts the visual demand of in-vehicle touchscreen interactions and provides local and global explanations of the factors influencing drivers' visual attention allocation. The approach is based on large-scale natural driving data continuously collected from production line vehicles and employs the SHapley Additive exPlanation (SHAP) method to provide explanations leveraging informed design decisions. Our approach is more accurate than related work and identifies interactions during which long glances occur with 68% accuracy and predicts the total glance duration with a mean error of 2.4s. Our explanations replicate the results of various recent studies and provide fast and easily accessible insights into the effect of UI elements, driving automation, and vehicle speed on driver distraction. The system can not only help designers to evaluate current designs but also help them to better anticipate and understand the implications their design decisions might have on future designs.

Input modality matters: A comparison of touch, speech, and gesture based in-vehicle interaction.

Innovative input devices are being available for in-vehicle information systems (IVISs). While they have the potential to provide enjoyable driving by enabling drivers to perform non-driving related tasks (NDRTs) in more natural ways, the associated distracting effects should be paid with more attention. The purpose of this exploratory study was to compare the effects of three novel input modalities, i.e., touchscreen-based interaction (TBI), speech-based interaction (SBI), and gesture-based interaction (GBI), on driving performance and driver visual behaviors. Moreover, we examined if the influence of different modalities would be moderated by the difficulty level of NDRTs. A total of 36 participants were invited to a simulated driving experiment where they were randomly assigned to one of the four groups (TBI, GBI, SBI or baseline) and completed three driving trials. The results showed that TBI led to the worse driving performance, as indicated by the significantly prolonged reaction time, reduced minimum time-to-collision, and increased variations in both longitudinal and lateral vehicle control. The deteriorated driving performance could be attributed, at least partially, to the intense visual demand induced by looking towards the touchscreen, as indicated by more and longer off-the-road glances. The adverse impacts of GBI were relatively smaller, but it still posed great crash risk by leading to a shorter minimum time-to-collision and less stable vehicle control compared to the baseline. SBI, although not completely equivalent to the baseline group, showed the minimum influence on driving and visual performance. Only very few interaction effects were found, suggesting that the effects of modality were quite robust across different NDRTs. It was concluded that SBI and GBI provided safer alternatives to in-vehicle interaction than TBI.

Chinese handwriting while driving: Effects of handwritten box size on in-vehicle information systems usability and driver distraction.

OBJECTIVE: Handwritten box size (HBS) is an essential Chinese handwriting interface element when interacting with touchscreen-based in-vehicle information systems (IVISs) since it is compactly bound up with driver distraction besides usability issues. Miscellaneous HBSs are commercially available on IVISs, yet the details of how the drivers interact with them in an in-vehicle display situation remain sparsely examined. Therefore, this study set out to investigate the effects of HBS on IVISs usability (task completion time, number of errors, number of protruding strokes, and NASA-TLX, a subjective workload assessment tool) and driver distraction (mean speed, lane position variation, total glance time, number of glances, mean glance time, and number of glances exceeding 1.6 s). Ultimately, the appropriate HBS on IVISs is determined. METHODS: A simulated driving experiment involving thirty drivers was launched. The primary task was lane-keeping with speed ranging from 40 to 60 km/h, and the secondary task was entering a 5-character text by Chinese handwriting input under five different HBS conditions: 25 × 25 mm, 30 × 30 mm, 35 × 35 mm, 40 × 40 mm, and 45 × 45 mm. A battery of one-way repeated measure analyses of variance (r-ANOVA) was used to examine which HBS can maximize IVISs usability and minimize driver distraction with the smallest HBS. RESULTS: Generally, the issues of IVISs usability and driver distraction improved progressively as the HBS increased to a specific size (40 × 40 mm in this study), at which they got to the asymptotes. Specifically, HBS below 40 × 40 mm was associated with longer text input time, more errors and protruding strokes, extended eyes-off-road time, excessive off-road glances, and deteriorative lateral driving performance. Nevertheless, there were no significant differences in mean glance time and longitudinal driving performance. No improvement measures were observed for HBS above 40 × 40 mm, except for a higher perceived workload. CONCLUSIONS: Overall, the appropriate HBS of in-vehicle Chinese handwriting was found to be 40 × 40 mm. Considering that the in-vehicle human-machine interface (HMI) has limited display space and increasing visual complexity, these findings may help develop evidence-based design guidelines for driver-friendly IVISs and prevent distracted-related traffic injuries.

Evaluation of the optimal quantity of in-vehicle information icons using a fuzzy synthetic evaluation model in a driving simulator.

In-Vehicle Information (IVI) features such as navigation assistance play an important role in the travel of drivers around the world. Frequent use of IVI, however, can easily increase the cognitive load of drivers. The interface design, especially the quantity of icons presented to the driver such as those for navigation, music, and phone calls, has not been fully researched. To determine the optimal number of icons, a systematic evaluation of the IVI Human Machine Interface (HMI) was examined using single-factor and multivariate analytical methods in a driving simulator. When one-way ANOVA was performed, the results showed that the 3-icon design scored best in subjective driver assessment, and the 4-icon design was best in the steering wheel angle. However, when a new method of analyzing the data that enabled a simultaneous accounting of changes observed in the dependent measures, 3 icons had the highest score (that is, revealed the overall best performance). This method is referred to as the fuzzy synthetic evaluation model (FSE). It represents the first use of it in an assessment of the HMI design of IVI. The findings also suggest that FSE will be applicable to various other HMI design problems.

Effects of Gesture-Based Interaction on Driving Behavior: A Driving Simulator Study Using the Projection-Based Vehicle-in-the-Loop.

OBJECTIVE: We observe the driving performance effects of gesture-based interaction (GBI) versus touch-based interaction (TBI) for in-vehicle information systems (IVISs). BACKGROUND: As a contributing factor to a number of traffic accidents, driver distraction is a significant problem for traffic safety. More specifically, visual distraction has a strong negative impact on driving performance and risk perception. Thus, the implementation of new interaction systems that use midair gestures to encourage glance-free interactions could reduce visual distraction among drivers. METHODS: In this experiment, participants drove a projection-based Vehicle-in-the-Loop. The projection-based technology combines a visual simulation with kinesthetic, vestibular, and auditory feedback from a car on a test track. While driving, participants used GBI or TBI to perform IVIS tasks. To investigate driving behavior related to critical driving situations and car-following maneuvers, vehicle data based upon longitudinal and lateral driving were collected. RESULTS: Participants reacted faster to critical driving situations when using GBI compared to TBI. For drivers using TBI, steering performance decreased and time headway to a preceding vehicle was higher. CONCLUSION: Gestures provide a safe alternative to in-vehicle interactions. Moreover, GBI has fewer effects on driver distraction than TBI. APPLICATION: Potential applications of this research include all in-vehicle interaction systems used by drivers.

Feasibility of automated in-vehicle technologies on volunteers' driving performance.

BACKGROUND: Automated in-vehicle technologies, specifically in-vehicle information systems (IVIS) and advanced driver assistance systems (ADAS), are increasingly common in today's cars. Previous studies illustrate benefits of using IVIS and ADAS to improve safety, convenience, and comfort in healthy older drivers. However, research is sparse on the feasibility of such technologies for medically at-risk drivers, such as those with Parkinson's disease (PD). OBJECTIVE: This study enrolled healthy volunteer drivers to examine the feasibility of the procedures and measures for evaluating the effects of IVIS and ADAS on their driving performance. METHODS: During this feasibility study researchers compared drives completed with and without support of IVIS and ADAS, as participants drove a 2019 Toyota Camry XLE. The test vehicle was equipped with IVIS, ADAS, cameras, a telematics system, and sensors. Participants drove the road course supervised by a Driver Rehabilitation Specialist (DRS). RESULTS: Overall study procedures and vehicle equipment were feasible and provided sufficient data collection for measuring the impact of IVIS and ADAS on driving performance. Data observation by the DRS combined with data captured from cameras and telematics, facilitated comparisons to increase data reliability and validity. CONCLUSIONS: Feasibility study findings informed a randomized clinical trial, examining the use of IVIS and ADAS technologies as an intervention to support drivers with Parkinson's disease.

The box task - a method for assessing in-vehicle system demand.

The use of advanced in-vehicle information systems (IVIS) and other complex devices such as smartphones while driving can lead to driver distraction, which, in turn, increases safety-critical event risk. Therefore, using methods for measuring driver distraction caused by IVIS is crucial when developing new in-vehicle systems. In this paper, we present the setup and implementation of the Box Task combined with a Detection Response Task (BT+DRT) as a tool to assess visual-manual and cognitive distraction effects. The BT+DRT represents a low-cost and easy-to-use method which can be easily implemented by researchers in laboratory settings and which was validated in previous research. Moreover, at the end of this paper we describe the experimental procedure, the data analysis and discuss potential modifications of the method.•The setup and implementation of the Box Task combined with a Detection Response Task (BT+DRT) is described.•The method allows for measuring visual-manual and cognitive distraction of drivers.•The BT+DRT is a cost-effective and easy-to-use method that can be implemented in laboratory settings or driving simulators.

Intelligibility of Haptic Signals in Vehicle Information Systems.

OBJECTIVE: The purpose of this study was to verify changes in a driver's emotions through the physical characteristics of haptic signals. This is to improve the performance of drivers by designing haptic signals with emotional semantics. BACKGROUND: Currently, drivers receive a variety of information through intelligent systems installed in their vehicles. Because this is mainly achieved through visual and auditory channels, an excessive amount of information is provided to drivers, which increases the amount of information and cognitive load that they must accept. This, in turn, can reduce driving safety. It is, therefore, necessary to develop a haptic signal, a sensory channel that has not been widely used in in-vehicle information systems. METHODS: The experiment was performed to collect a driver's emotions according to the haptic signal in a driving simulator. Haptic signals were designed by various frequencies and accelerations, and driver emotions were collected through Kansei engineering techniques and analyzed through factor analysis. To verify intelligibility, haptic signals were compared and evaluated based on response time, response rate, and amount of transmitted information. RESULTS: The final determined emotional map consisted of dangerousness and urgency. Based on the emotional map, four emotional semantic haptic signals were designed. It was confirmed that these four signals displayed higher performance than the discriminability haptic signal in terms of response time, response rate, and amount of transmitted information. CONCLUSIONS: Using emotional maps, it is possible to design haptic signals that can be applied to various driving situations. These maps may also assist in securing design guidelines for haptic signals that apply to in-vehicle information systems.

Mitigating Teen Driver Distraction: In-Vehicle Feedback Based on Peer Social Norms.

OBJECTIVE: To investigate the efficacy of in-vehicle feedback based on peer social norms in mitigating teen driver distraction. BACKGROUND: Distraction is a significant problem among teen drivers. Research into the use of in-vehicle technologies to mitigate this issue has been limited. In particular, there is a need to study whether social norms interventions provided through in-vehicle feedback can be effective. Peers are important social referents for teens; thus, normative intervention based on this group is promising. Socially proximal referents have a greater influence on behavior; thus, tailoring peer norm feedback based on gender may provide additional benefits. METHOD: In this study, 57 teens completed a driving simulator experiment while performing a secondary task in three between-subject conditions: (a) postdrive feedback incorporating same-gender peer norms, (b) postdrive feedback incorporating opposite-gender peer norms, and (c) no feedback. Feedback involved information based on descriptive norms (what others do). RESULTS: Teens' self-reported frequency of distraction engagement was positively correlated with their perceptions of their peers' engagement in and approval of distractions. Feedback based on peer norms was effective in reducing distraction engagement and improving driving performance, with no difference between same- and opposite-gender feedback. CONCLUSION/APPLICATION: Feedback based on peer norms can help mitigate driver distraction among teens. Tailoring social norms feedback to teen gender appears to not provide any additional benefits. Longer-term effectiveness in real-world settings should be investigated.

Measuring driver distraction - Evaluation of the box task method as a tool for assessing in-vehicle system demand.

Several tools have been developed over the past twenty years to assess the degree of driver distraction caused by secondary task engagement. A relatively new and promising method in this area is the box task combined with a detection response task (BT + DRT). However, no evaluation regarding the BT's sensitivity currently exists. Thus, the aim of the present study was to evaluate the BT + DRT by comparing its sensitivity to the sensitivity of already established methods. Twenty-nine participants engaged in several artificial and realistic secondary tasks while either performing the BT + DRT, the Lane Change Test (LCT), or driving through a simple course in a simulator. The results showed that the BT parameters (especially the standard deviation of box position and size) were sensitive to differences in demand across the visual-manual secondary tasks. This was comparable to what was found with the LCT. Surprisingly, the BT performance measures were more sensitive than those of the driving simulation task. The BT + DRT also captured cognitive distraction effects with the integration of the DRT. Hence, the BT + DRT could be a cost-effective method to assess in-vehicle system demand. However, further investigations are necessary to better understand the potential of the BT method.

Research and Implementation of Vehicle Target Detection and Information Recognition Technology Based on NI myRIO.

A vehicle target detection and information extraction scheme based on NI (National Instruments) myRIO is designed in this paper. The vehicle information acquisition and processing method based on image recognition is used to design a complete vehicle detection and information extraction system. In the LabVIEW programming environment, the edge detection method is used to realize the vehicle target detection, the pattern matching method is used to realize the vehicle logo recognition, and the Optical Character Recognition (OCR) character recognition algorithm is used to realize the vehicle license plate recognition. The feasibility of the design scheme in this paper is verified through the actual test and analysis. The scheme is intuitive and efficient, with the high recognition accuracy.

Effects of visual complexity of in-vehicle information display: Age-related differences in visual search task in the driving context.

We aimed to investigate the effects of the visual complexity of in-vehicle information display and driver's age in a driving context. A driving simulator study was conducted where participants performed visual search tasks at different visual complexity levels while driving. Two groups were included, 20 younger drivers (mean age = 28.75 years) and 14 older drivers (mean age = 54.87 years). Older drivers were found to be more vulnerable to the effects of increased visual complexity when performing a visual search task. The task completion time of the younger group increased by about 20% (from 7.69 s to 9.30 s), while the older group increased by about 47% (from 8.92 s to 13.14 s). Further, the driving performance of the older group deteriorated, unlike the younger group. The subjective workload score supported the results of the objective performance measures. These differences can be explained by glance behavior. The total off-road glance duration of older drivers was longer than that of younger drivers, but the average off-road glance duration of younger drivers was longer. In other words, older drivers have a more conservative strategy when dealing with increased visual complexity in a driving context so as not to affect their driving. The findings of this study show that the visual complexity level has a significant effect on driving behaviors, especially in older drivers, which provides insights for designing in-vehicle information displays.

Designing in-vehicle signs for connected vehicle features: Does appropriateness guarantee comprehension?

This paper discusses the design and evaluation of connected and cooperative vehicle in-vehicle sign designs displayed on a mobile phone: Emergency Electronic Brake Lights (EEBL), Emergency Vehicle Warning (EVW), Traffic Condition Warning, and Road Works Warning. Appropriateness and comprehension of each design alternative were assessed using quantitative (i.e. Likert scales) and qualitative (i.e. open-ended questions) methods. Forty-four participants took part in the study and were shown twelve dashboard camera videos presenting a total of eleven designs alternatives, displayed with or without a legend. Despite their appropriateness, EEBL and EVW signs displayed with a legend were better comprehended and less ambiguous than those displayed without a legend. Moreover, displaying a legend below the signs to warn drivers of an emergency braking ahead was efficient in low visibility condition and could potentially increase safety in critical situations.

Assessing the visual and cognitive demands of in-vehicle information systems.

BACKGROUND: New automobiles provide a variety of features that allow motorists to perform a plethora of secondary tasks unrelated to the primary task of driving. Despite their ubiquity, surprisingly little is known about how these complex multimodal in-vehicle information systems (IVIS) interactions impact a driver's workload. RESULTS: The current research sought to address three interrelated questions concerning this knowledge gap: (1) Are some task types more impairing than others? (2) Are some modes of interaction more distracting than others? (3) Are IVIS interactions easier to perform in some vehicles than others? Depending on the availability of the IVIS features in each vehicle, our testing involved an assessment of up to four task types (audio entertainment, calling and dialing, text messaging, and navigation) and up to three modes of interaction (e.g., center stack, auditory vocal, and the center console). The data collected from each participant provided a measure of cognitive demand, a measure of visual/manual demand, a subjective workload measure, and a measure of the time it took to complete the different tasks. The research provides empirical evidence that the workload experienced by drivers systematically varied as a function of the different tasks, modes of interaction, and vehicles that we evaluated. CONCLUSIONS: This objective assessment suggests that many of these IVIS features are too distracting to be enabled while the vehicle is in motion. Greater consideration should be given to what interactions should be available to the driver when the vehicle is in motion rather than to what IVIS features and functions could be available to motorists.

Toward best practice in Human Machine Interface design for older drivers: A review of current design guidelines.

Older adults are the fastest growing segment of the driving population. While there is a strong emphasis for older people to maintain their mobility, the safety of older drivers is a serious community concern. Frailty and declines in a range of age-related sensory, cognitive, and physical impairments can place older drivers at an increased risk of crash-related injuries and death. A number of studies have indicated that in-vehicle technologies such as Advanced Driver Assistance Systems (ADAS) and In-Vehicle Information Systems (IVIS) may provide assistance to older drivers. However, these technologies will only benefit older drivers if their design is congruent with the complex needs and diverse abilities of this driving cohort. The design of ADAS and IVIS is largely informed by automotive Human Machine Interface (HMI) guidelines. However, it is unclear to what extent the declining sensory, cognitive and physical capabilities of older drivers are addressed in the current guidelines. This paper provides a review of key current design guidelines for IVIS and ADAS with respect to the extent they address age-related changes in functional capacities. The review revealed that most of the HMI guidelines do not address design issues related to older driver impairments. In fact, in many guidelines driver age and sensory cognitive and physical impairments are not mentioned at all and where reference is made, it is typically very broad. Prescriptive advice on how to actually design a system so that it addresses the needs and limitations of older drivers is not provided. In order for older drivers to reap the full benefits that in-vehicle technology can afford, it is critical that further work establish how older driver limitations and capabilities can be supported by the system design process, including their inclusion into HMI design guidelines.

Driver's adaptive glance behavior to in-vehicle information systems.

The purpose of this study was to examine the adaptive behavior of drivers as they engage with in-vehicle devices over time and in varying driving situations. Behavioral adaptation has been shown to occur among drivers after prolonged use of in-vehicle devices, but few studies have examined drivers' risk levels across different driving demands. A multi-day simulator study was conducted with 28 young drivers (under 30 years old) as they engaged in different text entry and reading tasks while driving in two different traffic conditions. Cluster analysis was used to categorize drivers based on their risk levels and random coefficient models were used to assess changes in drivers' eye glance behavior. Glance duration significantly increased over time while drivers were performing text entry tasks but not for text reading tasks. High-risk drivers had longer maximum eyes-off-road when performing long text entry tasks compared to low-risk drivers, and this difference increased over time. The traffic condition also had a significant impact on drivers' glance behavior. This study suggests that drivers may exhibit negative behavioral adaptation as they become more comfortable with using in-vehicle technologies over time. Results of this paper may provide guidance for the design of in-vehicle devices that adapt based on the context of the situation. It also demonstrates that random coefficient models can be used to obtain better estimations of driver behavior when there are large individual differences.

Assessment of naturalistic use patterns of advanced infotainment systems.

OBJECTIVE: The objective was to examine naturalistic usage of infotainment systems to assess use characteristics and patterns. BACKGROUND: Infotainment systems continue to evolve in terms of their capabilities and information availability, raising concerns about their distraction potential. Assessing potential distraction requires understanding how challenging different tasks are and how frequently they occur during driving. METHOD: High-end infotainment system use was observed across 17 participants over a period of approximately 4 weeks each. One of two different infotainment systems was provided to participants. Audio, video, and driving performance data were collected and observed by trained reductionists. The two infotainment systems integrated iPod™, satellite radio, CD/DVD/MP3 playback, AM/FM, and, in one case, navigation functionalities. Systems differed in their vehicle integration and advanced infotainment features offered. RESULTS: The median participant interacted with the infotainment systems once every 4 hr (90th percentile: 6.1 interactions/hr). More than 50% of these interactions involved adjusting the volume. Although there were a few lengthy interactions, the median duration was 2.2 s (90th percentile: 24.6 s), which required measurable visual involvement when compared to a matched baseline. The median total eyes-off-road time across interactions was 1 s (90th percentile: 11.4 s) and differed significantly across type of system interaction. Longer interactions tended to occur when the vehicle was stationary. CONCLUSION: Drivers habitually interact with infotainment systems while driving; this includes advanced functions. Some self-regulation was observed. APPLICATION: These data provide a comparison basis for use in examining driver interactions with future infotainment systems.

How does a lower predictability of lane changes affect performance in the Lane Change Task?

The Lane Change Task (LCT) is an established method to assess driver distraction caused by secondary tasks. In the LCT ISO standard, "course following and maneuvering" and "event detection" are mentioned as central task properties. Especially event detection seems to be a reasonable feature, as research suggests that distraction has profound effects on drivers' reactions to sudden, unexpected events. However, closer inspection of the LCT reveals that the events to be detected (lane change signs) and the required response are highly predictable. To investigate how the LCT's distraction assessment of secondary tasks might change if lane change events and responses were less predictable, we implemented three different versions of the LCT - an "original" one, a second one with lowered predictability of event position, and a third one with lowered predictability of event position and response. We tested each of these implementations with the same set of visual and cognitive secondary tasks of varying demand. The results showed that a decrease in predictability resulted in overall degraded performance in the LCT when using the basic lane change model for analysis. However, all secondary task conditions suffered equally. No differential effects were found. We conclude that although an ISO conforming implementation of the LCT might not be excessively valid regarding its depiction of safety relevant events, the results obtained are nevertheless comparable to what would be found in settings of higher validity.

The effect of touch-key size on the usability of In-Vehicle Information Systems and driving safety during simulated driving.

Investigating the effect of touch-key size on usability of In-Vehicle Information Systems (IVISs) is one of the most important research issues since it is closely related to safety issues besides its usability. This study investigated the effects of the touch-key size of IVISs with respect to safety issues (the standard deviation of lane position, the speed variation, the total glance time, the mean glance time, the mean time between glances, and the mean number of glances) and the usability of IVISs (the task completion time, error rate, subjective preference, and NASA-TLX) through a driving simulation. A total of 30 drivers participated in the task of entering 5-digit numbers with various touch-key sizes while performing simulated driving. The size of the touch-key was 7.5 mm, 12.5 mm, 17.5 mm, 22.5 mm and 27.5 mm, and the speed of driving was set to 0 km/h (stationary state), 50 km/h and 100 km/h. As a result, both the driving safety and the usability of the IVISs increased as the touch-key size increased up to a certain size (17.5 mm in this study), at which they reached asymptotes. We performed Fitts' law analysis of our data, and this revealed that the data from the dual task experiment did not follow Fitts' law.