Factors affecting perceived safety and enjoyment based on driver experience

A positive driving experience, especially for older drivers, increases the attention to the emotional dimensions of driving, such as the driver’s perceived safety. Therefore, this study empirically presents factors affecting driver experience and compares them between older and younger drivers. Consequently, we conducted a face-to-face survey on elderly and young drivers and analyzed the data of 246 drivers using structural equation modeling. The analysis presented measurements and structural model evaluations. Considering the analysis, it was found that driving-related information and car-exterior context affect the perceived safety and enjoyment of a driver’s experience. Additionally, car-exterior context exerts a greater influence on the perceived safety and enjoyment of the elderly drivers’ group than the young drivers’ group. The results of this study will empirically contribute to the satisfaction of driver experience and perceived safety improvement in the future. It also provides a basis for the development of driving interfaces to improve the quality of the driving experience of the elderly.     

Estimating Age-Based Developmental Trajectories Using Latent Change Score Models Based on Measurement Occasion

Abstract

Accelerated longitudinal designs (ALDs) are designs in which participants from different cohorts provide repeated measures covering a fraction of the time range of the study. ALDs allow researchers to study developmental processes spanning long periods within a relatively shorter time framework. The common trajectory is studied by aggregating the information provided by the different cohorts. Latent change score (LCS) models provide a powerful analytical framework to analyze data from ALDs. With developmental data, LCS models can be specified using measurement occasion as the time metric. This provides a number of benefits, but has an important limitation: It makes it not possible to characterize the longitudinal changes as a function of a developmental process such as age or biological maturation. To overcome this limitation, we propose an extension of an occasion-based LCS model that includes age differences at the first measurement occasion. We conducted a Monte Carlo study and compared the results of including different transformations of the age variable. Our results indicate that some of the proposed transformations resulted in accurate expectations for the studied process across all the ages in the study, and excellent model fit. We discuss these results and provide the R code for our analysis.     

Spanning seven orders of magnitude: a challenge for cognitive modeling

Much of cognitive psychology focuses on effects measured in tens of milliseconds while significant educational outcomes take tens of hours to achieve. The task of bridging this gap is analyzed in terms of Newell's (1990) bands of cognition—the Biological, Cognitive, Rational, and Social Bands. The 10 millisecond effects reside in his Biological Band while the significant learning outcomes reside in his Social Band. The paper assesses three theses: The Decomposition Thesis claims that learning occurring at the Social Band can be reduced to learning occurring at lower bands. The Relevance Thesis claims that instructional outcomes at the Social Band can be improved by paying attention to cognition at the lower bands. The Modeling Thesis claims that cognitive modeling provides a basis for bridging between events on the small scale and desired outcomes on the large scale. The unit‐task level, at the boundary of the Cognitive and Rational Bands, is useful for assessing these theses. There is good evidence for all three theses in efforts that bridge from the unit‐task level to educational applications. While there is evidence for the Decomposition Thesis all the way down to the 10 millisecond level, more work needs to be done to establish the Relevance Thesis and particularly the Modeling Thesis at the lower levels.     

Modeling duration of overtaking in two lane highways

The paper attempts to reveal which factors may influence the duration of overtaking in two lane highways. Questions such as what is the duration of young male and female drivers’ overtaking activities and, given that a driver conducts an overtaking maneuver, how long will it take, are addressed using classical survival analysis. Data are collected using a driving simulator. Different models are developed for describing the total overtaking duration, as well as the duration of the acceleration and back-to-lane phases. Results show that the duration of each of the phases of overtaking considered, as well as the total overtaking duration may be best described by a Log–logistic distribution. Analyses point out that, apart from the acceleration phase, the gender is a critical factor to the duration modeling. Other influential factors are the speed difference from the lead vehicle, the speed of opposing traffic, the spacing from the lead and opposing traffic, as well as whether the driver is engaged in multiple overtakes. Finally, the modeling implications to driving assistance systems are discussed.