Professor Heikki Summala
heikki.summala [at] helsinki.fi
Traffic Research Unit
Traffic Psychology Chair
Institute of Behavioural Sciences
P.O. Box 9
Siltavuorenpenger 1 A
FI-00014 University of Helsinki
Traffic Research Unit
The Traffic Resarch Unit of the University of Helsinki was founded in 1971.
The Unit’s mission is to conduct high quality basic research in behavioural science, to provide research-based higher education, and to produce and disseminate research results conducive to the well-being of people on the move.
The object of our research is human behaviour in a natural hazardous activity, and the cognitive and neural mechanisms behind it.
The reseach methods used include quantitative measurements in the field with instrumented cars, laboratory experiments and simulations, psychological tests, accident analysis, and computational modeling of road-user behaviour and traffic cognition.
We study human behaviour across the entire life span, and at all levels of skill and learning, from novice to expert.
The research has applications in driver education, driver assessment and licensing, road and traffic design, vehicle design, legislation, and in the prevention of road fatalities.
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Recent articles from Traffic Research Unit
Lehtonen, E., Lappi, O. Kotkanen, H., & Summala, H. (2012) Look-ahead fixations in curve driving. Ergonomics, doi:10.1080/00140139.2012.739205
Two functionally distinct types of fixation, guiding fixations and look-ahead fixations, have been identified in naturalistic tasks based on their temporal relationship to the task execution. In car driving, steering through a curve is guided by fixations toward a region located 1–2 s in the future, but drivers also make fixations further along the road. We recorded drivers' eye movements while they drove an instrumented vehicle on curved rural roads and developed a method to quantify lead time and distance of look-ahead fixations. We also investigated the effect of cognitive load on look-ahead fixations. The look-ahead fixations appear to have a pattern which is connected to the sequential structure of a curve. This suggests that they have a role both in advance planning of the driving line and in the anticipation of oncoming vehicles. Cognitive load led to a shorter look-ahead lead time and distance.
Lehtonen, E., Lappi, O. & Summala, H. (2012). Anticipatory eye movements when approaching a curve on a rural road depend on working memory load. Transportation Research Part F 15(3), doi:10.1016/j.trf.2011.08.007
Where do drivers look when approaching curves on a winding road? Existing models on visual processes in curve driving have focused on path-controlling behavior. Another aspect in curve driving is the visual anticipation of potential oncoming vehicles, obstacles and road alignment. We define the occlusion point of a curve as the nearest point where the view of the road is blocked by some obstacle (e.g. vegetation). Monitoring the occlusion point is relevant for safe driving because potential oncoming vehicles or obstacles on the road will come into view on the occlusion point.
In the current on-road study, 10 participants drove an instrumented car at their own pace on a low standard rural road while their eye-movements were recorded. We investigated anticipatory glances towards the occlusion point while approaching open sight curves and how anticipatory glances are affected by a cognitive secondary task without explicit visuo-spatial or motor components.
The results demonstrate that drivers indeed look at the occlusion point while approaching open curves on rural roads, and that working memory load leads to a significant decrease in visual anticipation. Previously, it has been shown that cognitive secondary tasks lead to reduction of looking at the speedometer and mirrors and of safety critical visual scanning at street crossings. We show that the effect is also present in the anticipation of road curvature and hazards on rural roads.
Mattsson, M. (2012). Investigating the factorial invariance of the 28-item DBQ across genders and age groups: An Exploratory Structural Equation Modeling Study. Accid. Anal. Prev., doi:10.1016/j.aap.2012.02.009
The Driver Behaviour Questionnaire (DBQ) is perhaps the most widely used questionnaire instrument in traffic psychology with 174 studies published by late 2010. The instrument was developed based on a plausible cognitive ergonomic theory (the Generic Error Modeling System, GEMS), but the factor structure obtained in the original study (Reason et al., 1990) did not mirror the theory's conceptual structure. This led to abandoning GEMS and adopting the obtained factor structure as a starting point for further DBQ research. This article argues that (1) certain choices in the original study, concerning statistical methodology and the wording of individual question items, may have contributed to the ways the obtained factor structure deviated from the underlying theory and (2) the analysis methods often used in DBQ studies, principal components (PC) analysis and maximum likelihood (ML) factor analysis, are not optimal choices for the non-normally distributed categorical data that is obtained using the instrument. This is because ML produces biased results when used with this type of data, while PC is by definition unable to uncover latent factors as it summarizes all variation in the measured variables. (3) Even though DBQ factor scores have been routinely compared in subgroups of men and women and respondents of different ages, DBQ's factorial invariance in these groups has not been rigorously tested. These concerns are addressed in this article by framing the results of certain previous DBQ studies as a structural equation model (SEM) and an Exploratory Structural Equation Model (ESEM) and testing measurement model fit in subgroups of respondents. The SEM analyses indicate that the model does not fit data from the whole sample of respondents as it stands, while the ESEM analyses show that a modification of the model does. However, the ESEM analyses indicate the DBQ measures different underlying latent variables in the different subgroups. Based on the analyses and a review of recent advances in attention and memory research, an update to the theory underlying the DBQ is suggested.