Showing papers by "J.C.F. de Winter published in 2012"

Factor recovery by principal axis factoring and maximum likelihood factor analysis as a function of factor pattern and sample size

Abstract: Principal axis factoring (PAF) and maximum likelihood factor analysis (MLFA) are two of the most popular estimation methods in exploratory factor analysis. It is known that PAF is better able to recover weak factors and that the maximum likelihood estimator is asymptotically efficient. However, there is almost no evidence regarding which method should be preferred for different types of factor patterns and sample sizes. Simulations were conducted to investigate factor recovery by PAF and MLFA for distortions of ideal simple structure and sample sizes between 25 and 5000. Results showed that PAF is preferred for population solutions with few indicators per factor and for overextraction. MLFA outperformed PAF in cases of unequal loadings within factors and for underextraction. It was further shown that PAF and MLFA do not always converge with increasing sample size. The simulation findings were confirmed by an empirical study as well as by a classic plasmode, Thurstone's box problem. The present results are...

Advantages and Disadvantages of Driving Simulators: A Discussion

Abstract: For half a century at least, each new generation of computer chip, appearing every two years or so, has provided twice as many transistors per unit cost (as predicted by Moore’s law [1]). Extrapolating the accelerating pace of technological potential, logic dictates that computational devices will be tiny and powerful by the early 2020s, giving rise to virtual-reality applications such as displays built into our eyeglasses [2]. By the 2030s, going to a website could mean entering a totally realistic and compelling virtual environment facilitated by miniature computers that interact with brain cells, and people will probably spend most of their time in virtual reality [3]. Although these prospects may sound farfetched, we can already see that virtual-reality-based applications are increasingly used in such common tasks as driving. We use driving simulators for assessment, rehabilitation, learner driver training, race-car driver training, research into safety, and for at-home entertainment and in amusement halls.

Automated Driving: Human-Factors Issues and Design Solutions:

Abstract: The goal of this paper is to outline human-factors issues associated with automated driving, with a focus on car following. First, we review the challenges of having automated driving systems from a human-factors perspective. Next, we identify human-machine interaction needs for automated vehicles and propose some available solutions. Finally, we propose design requirements for Cooperative Adaptive Cruise Control. Language: en

Why do drivers maintain short headways in fog? A driving-simulator study evaluating feeling of risk and lateral control during automated and manual car following

Abstract: Drivers in fog tend to maintain short headways, but the reasons behind this phenomenon are not well understood. This study evaluated the effect of headway on lateral control and feeling of risk in both foggy and clear conditions. Twenty-seven participants completed four sessions in a driving simulator: clear automated (CA), clear manual (CM), fog automated (FA) and fog manual (FM). In CM and FM, the drivers used the steering wheel, throttle and brake pedals. In CA and FA, a controller regulated the distance to the lead car, and the driver only had to steer. Drivers indicated how much risk they felt on a touchscreen. Consistent with our hypothesis, feeling of risk and steering activity were elevated when the lead car was not visible. These results might explain why drivers adopt short headways in fog. Practitioner Summary: Fog poses a serious road safety hazard. Our driving-simulator study provides the first experimental evidence to explain the role of risk-feeling and lateral control in headway reduction. These results are valuable for devising effective driver assistance and support systems.

The effect of tire grip on learning driving skill and driving style: A driving simulator study

Abstract: There is a need for training methods that improve the driving skill and driving style of novice drivers. Previous research in motor learning has shown that degrading the task conditions during practice can enhance long-term retention performance. Inspired by these findings, this study investigated the effects of the tire-road friction coefficient on learning a self-paced lane-keeping task in a driving simulator. A sample of 63 young and inexperienced drivers were divided into three groups, low grip (LG), normal grip (NG) and high grip (HG), who practiced driving with a friction coefficient of 0.45, 0.90, and 1.80, respectively. All groups drove six 8 min sessions on a road with curves in a rural environment: four practice sessions, an immediate retention session, and a delayed retention session on the next day. The two retention sessions were driven with normal-grip tires. The results show that LG drove with lower speed than NG during practice and retention. Transferring from the last practice session to the immediate retention session, LG's workload decreased, as measured with a secondary task, whereas HG's workload increased. During the immediate retention session, LG had less road departures than HG, but HG drove closer to the lane center in curves than the other two groups. HG reported elevated confidence during practice, but not in retention. In conclusion, this simulator-based study showed that practicing with low-grip tires resulted in lower driving speeds during retention tests, an effect which persisted overnight. These results have potential implications for the way drivers are trained.

Modelling driver behaviour: a rationale for multivariate statistics

Abstract: This article provides a discussion of driver behaviour models. Based on a literature survey and using experimental driving simulator data, three types of driver behaviour models are evaluated: motivational models, adaptive control models and trait models. It is shown that motivational models are comprehensive but lack specificity. Many adaptive control models yield precise results but tend to be overly specific and psychologically implausible. Trait models have not been successful in the past and have been criticised for providing post hoc explanations and for the absence of a multifactorial structural approach. We demonstrate that if the right multivariate statistical techniques are used, trait models are suitable for the parsimonious modelling of predictive-valid driver characteristics, thereby taking an intermediate position on a dimension ranging from specific to unspecific models.

The effects of control-display gain on performance of race car drivers in an isometric braking task

Abstract: To minimise lap times during car racing, it is important to build up brake forces rapidly and maintain precise control. We examined the effect of the amplification factor (gain) between brake pedal force and a visually represented output value on a driver's ability to track a target value. The test setup was a formula racing car cockpit fitted with an isometric brake pedal. Thirteen racing drivers performed tracking tasks with four control-display gains and two target functions: a step function (35 trials per gain) and a multisine function (15 trials per gain). The control-display gain had only minor effects on root mean-squared error between output value and target value, but it had large effects on build-up speed, overshoot, within-participants variability, and self-reported physical load. The results confirm the hypothesis that choosing an optimum gain involves balancing stability against physical effort.

Can We Discriminate Safe and Unsafe Visual Scanning in Multitask Driving Conditions

Abstract: Traffic accidents are a major public health concern with 1.2 million fatalities occurring every year and with millions more individuals getting injured [1]. More than 90% of the accidents are, at least partially, caused by the driver [2]. Figure 1 shows the overrepresentation of younger and older drivers among these crashes. The overrepresentation of younger drivers [1] can be explained by an increased willingness to take risk, poor anticipation of hazards, and insufficiently learned lateral and longitudinal vehicle control [3]. Figure 1 also shows the overrepresentation of elderly drivers which is caused by decline of cognitive and physical abilities [4] such as visual impairment (e.g., glaucoma).

Relationship Between Distal and Proximal Neoplasia

Abstract: Authors Reply:--- In a recent meta-analysis, we found that all types of distal lesions are predictive of proximal neoplasia (PN) and that on average 60 % of PN are isolated, that is, not accompanied by distal lesions.1 A commentary by Dr. Filik concluded that if all types of distal lesions are predictive of PN, colonoscopy should be performed instead of flexible sigmoidoscopy (FS). We thank Dr. Filik for his comment. In this reply we highlight why FS should not be abandoned in favor of colonoscopy. Deciding which colon inspection method is most suitable for screening depends on many parameters, including discomfort, complication rates, logistics, and costs.2 FS is performed without sedation, leading to more pain than colonoscopy. Colonoscopy has a complication rate that, although low, is 10 times higher than that of FS. Colonoscopy is further accompanied by a loss of three working days for preparing for, undergoing, and recovering from the procedure, compared to half a day in FS. Colonoscopy has the theoretical advantage over FS that it allows inspection of the proximal colon. Recent population-based studies have reported that, compared to no screening, colonoscopy led to significant reductions of cancer incidence in the distal colon and associated mortality, but its efficacy in the proximal colon was similar to that of FS.3 It remains unclear whether these studies failed to show a protective effect of colonoscopy against proximal colon cancer incidence because of poor design or practical limitations (e.g., by including cases in which colonoscopy was performed by non-gastroenterologists), inherent visualization problems of colonoscopy (e.g., miss of flat and pale proximal adenomas), or inherent properties of the proximal colon (e.g., the aggressive nature of proximal tumors). Randomized controlled trials of screening colonoscopy are underway, but their results will not be available before 2021. In an effort to improve the predictive value of FS, Imperiale et al.4 introduced a clinical index including distal findings, gender, and age. The index was applied to a cohort of asymptomatic individuals 50 years or older undergoing screening colonoscopy for the first time and detected 92 % of individuals with advanced proximal neoplasia. Using the index could reduce the number of screening colonoscopies by 40 % as compared to sending everyone to colonoscopy. In our meta-analysis, health characteristics were an important moderator of the association between distal and proximal lesions, with proximal advanced neoplasia being better predicted in asymptomatic populations, young populations, and populations with a low prevalence for proximal advanced neoplasia. Combining the FS outcome with demographics, health characteristics, genetic predisposition, and environmental risks can improve the prediction of PN and strengthen the role of FS as a screening modality. Technological advances in imaging and visualization as well as emerging techniques such as virtual colonoscopy will also contribute to future lesion detection.