Archive for category Transportation & Safety
Here we report upon results of a validation study conducted on our unique pedestrian simulator.
The simulator validation study confirms the simulator’s ability to correctly simulate the real road environment, and strengthens the reliability as a source for statistical Inference. The goal of this work was to investigate whether the Dome simulator successfully simulates typical pedestrian environment in a manner that will elicit people to act in the same manner as they would in the real world crossing situations. Data analysis shows that the simulator delivers more reliable results concerning speeds rather than distances. Questionnaires analyses show that the simulator’s faith to reality regarding the display, sound effect and perspective is medium.
One more publication within the child pedestrian’s realm of road crossing co-authored by Anat Meir and Yisrael Parmet published in Safety Science, Vol. 80, pages 33-40 (2015)
we explored child-pedestrians’ HP skills employing hazard detection task in virtual settings (our Dome lab). We used the same approach that we have used previously in the driving HP domain to study novice drivers. As pedestrians’ age increased their awareness toward potential hazards increased. 7–9-year-olds reported less instances of FOV obscured by parked vehicles. 7–9-year-olds lingered more in identifying instances of FOV obscured by parked vehicles.
Background. Child-pedestrians are more prone to fail in identifying hazardous situations. Aiming to better understand the development of hazard-perception abilities in dynamic road situations we examined participants’ hazard detection abilities in a virtual environment.
Method. Experienced-adult participants and child-pedestrians observed typical road crossing related scenarios from a pedestrian’s point of view and engaged in a hazard detection task.
Results. Consistent with our hypotheses, less instances of obscured field of view by parked vehicles were reported as hazardous by 7–9-year-olds, who were also prone to linger more in identifying situations depicting field of view partially obscured by parked vehicles compared to all other age groups. Reports of obscured field of view by road curvature as hazardous increased with age.
Conclusions. Understanding child-pedestrians’ shortcomings in evaluating traffic situations contribute to the effort of producing intervention techniques which may increase their attentiveness toward potential hazards and lead toward reduction in their over-involvement in crashes.
Hagai Tapiro, Anat Meir, Yisrael Parmet & Tal Oron-Gilad
Presentation at HFES-EU Annual meeting, Torino 2013
Children are over-represented in road accidents, often due to their limited ability to perform well in road crossing tasks. The present study examined children’s visual search strategies in hazardous road-crossing situations. A sample of 33 young participants (ages 7-13) and 21 adults observed 18 different road-crossing scenarios in a 180° dome shaped mixed reality simulator. Gaze data was collected while participants made the crossing decisions. It was used to characterize their visual scanning strategies. Results showed that age group, limited field of view, and the presence of moving vehicles affect the way pedestrians allocate their attention in the scene. Adults tend to spend relatively more time in further peripheral areas of interest than younger pedestrians do. It was also found that the oldest child age group (11-13) demonstrated more resemblance to the adults in their visual scanning strategy, which can indicate on a learning process that originates from gaining experience and maturation. Characterization of child pedestrian eye movements can be used to determine readiness for independence as pedestrians. The results of this study, emphasize the differences among age groups in terms of visual scanning. This information can contribute to promote awareness and training directions.
Dirichlet regression model and analysis
For each scenario, five areas of interest were defined (as shown in the Figure). The close range central area was defined as the 10 meters of road in each side from the pedestrian’s point of view (AOI 3). Then symmetrically areas to the right of the center and to the left were defined. The medium right/left range (AOIs 2/4) was the part of the road distant at least 10 meter to the right/left of the point of view but less than 100 meters away. The far right/left range (AOIs 1/5) was the part of the road at least 100 meter or more to the right/left of the pedestrian point of view.
- For each participant and scenario, the total Gaze distribution over the five AOI’s sums up to one.
- Therefore Gaze distribution is compositional data i.e., non-negative proportions with unit-sum.
- These types of data arise whenever we classify objects into disjoint categories and record their resulting relative frequencies, or partition a whole measurement into percentage contributions from its various parts.
- Attempts to apply statistical methods for unconstrained data often lead to inappropriate inference.
- Dirichlet regression suggested by Hijazi and Jernigan (2009) is more suitable for such cases.
How to use?
- The Dirichlet regression model was fitted using DirichletReg package, in R Language. Applying a backward elimination procedure found the best fitting model has three significant main effects.
What did we find?
- The dependent variable was the vector of AOIs and the independent variables were Age-group, POV and FOV; all of them were statistically significant (p <0.05). Predicted means for the percentage of time spent in each AOI for each age group based on the Dirichlet regression model are shown in the following figure and reveal differences among age groups. Note how children aged 9-10 spend more time gazing at the central area, note also the differences between mid-left and mid-right.
Exploring the Effects of Driving Experience on Hazard Awareness and Risk Perception – a new publication
This is a “heavy” article co authored by Avinoam Borowsky – it summorizes in one study all the methodologies that we have used in the past to assess hazard perception and risk, and its power is in this overall view.
it portrays the use of three methodologies of assesment for hazard awareness and risk perception in a single study:
- Real-Time Hazard Identification,
- Hazard Classification
- Rating Tasks
Three level of experience/expertise groups were used:
- taxi drivers, who have some unique charaterisitcs
- experienced drivers (more than 7 years of driving experience)
- Young novice drivers (with less than 3 months of driving experience)
Accepted for publication July 2013. Please cite as: Borowsky, A., Oron-Gilad, T., Exploring the Effects of Driving Experience on Hazard Awareness and Risk Perception via Real-Time Hazard Identification, Hazard Classification, and Rating Tasks, Accident Analysis and Prevention (2013), http://dx.doi.org/10.1016/j.aap.2013.07.008
This study investigated the effects of driving experience on hazard awareness and risk perception skills. These topics have previously been investigated separately, yet a novel approach is suggested where hazard awareness and risk perception are examined concurrently. Young, newly qualified drivers, experienced drivers, and a group of commercial drivers, namely, taxi drivers performed three consecutive tasks: (1) observed 10 short movies of real-world driving situations and were asked to press a button each time they identified a hazardous situation; (2) observed one of three possible sub-sets of 8 movies (out of the 10 they have seen earlier) for the second time, and were asked to categorize them into an arbitrary number of clusters according to the similarity in their hazardous situation; and (3) observed the same sub-set for a third time and following each movie were asked to rate its level of hazardousness. The first task is considered a real-time identification task while the other two are performed using hindsight. During it participants’ eye movements were recorded. Results showed that taxi drivers were more sensitive to hidden hazards than the other driver groups and that young-novices were the least sensitive. Young-novice drivers also relied heavily on materialized hazards in their categorization structure. In addition, it emerged that risk perception was derived from two major components: the likelihood of a crash and the severity of its outcome. Yet, the outcome was rarely considered under time pressure (i.e., in real-time hazard identification tasks). Using hindsight, when drivers were provided with the opportunity to rate the movies’ hazardousness more freely (rating task) they considered both components. Otherwise, in the categorization task, they usually chose the severity of the crash outcome as their dominant criterion. Theoretical and practical implications are discussed.
Here is just one example of the manipulation used in the classification task, where we used common still images and one varied exemplar, to asses whether this manipulation changed participants classification.
Our new publication “Towards understanding child-pedestrians’ hazard perception abilities in a mixed reality dynamic environment” co-authored by Anat Meir and Yisrael Parmet is now available on Transportation Research part F.
This is our first published study on child pedestrians where we utilized our Dome projection facility.
Child-pedestrians, especially those in the age range of 5–9-years, are amongst the most vulnerable road users. These youngsters are highly represented in fatal and severe injury road crashes, despite relatively low levels of exposure to traffic. The present research investigated child and adult pedestrians’ perception of hazards utilizing a crossing decision task. Twenty-one adults (20–27 years-old) and twenty-five young-children (eight 7–9-year olds,five 9–10-year-olds and twelve 10–13-year-olds) were requested to observe traffic scene scenarios presented in a mixed reality dynamic environment simulating a typical Israeli city from a pedestrian’s perspective, and to press a response button whenever they assumed it was safe to cross. Results have shown that as pedestrians’ age and experience level increased their attentiveness towards potential hazards increases and their ability to anticipate upcoming events while engaging in a road-crossing task was enhanced. Furthermore, both the 9–10-year-olds and the 10–13-year-olds presented a less decisive performance compared to both the experienced-adult pedestrians and the 7–9-year-olds. Understanding child-pedestrians’ shortcomings in evaluating traffic situations may contribute to the effort of producing intervention techniques which may increase their attentiveness towards potential hazards and pave the way for reducing their over-involvement in road crashes. Implications for training novice road users will be discussed.
Our 3-D environment was specifically designed (B-design) for walking road users, as it provides high level of detail necessary for a walking person (i.e., not the entire urban model is built, the emphasis is on the façade). Using a 180 degrees large dome allows the feeling of immersion.
A sample of a crossing scenario eye tracking pattern of a young pedestrian can be seen in the following video. Note the amount of time that the child spend viewing the cross walk itself rather than the road. My Ph.D student Hagai Tapiro is responsible for the production of this video.