Archive for category Transportation & Safety

Pedestrians’ road crossing decisions and body parts’ movements

A new publication in TR part F by Semyon Kalantarov, Raziel Riemer, and Tal Oron-Gilad.

Highlights:

  • Road-crossing simulator synched with a 3D motion capturing system was built
  • Time pressure and longer wait times cause riskier crossing decisions
  • Pedestrians adjusted posture, crossing speed and timing of crossing to the risk taken
  • Body parts’ movement prior to the crossing can be divided into four increments

In this study we examined pedestrians’ crossing decision, body parts’ movement and full body movement, just before and during road crossing in a simulated setup. To accomplish this, a novel experimental setup for analyzing pedestrians’ crossing behavior and motion was developed where the simulated display was synchronized with a 3D motion capturing system. Twenty participants, divided into control and an experimental time pressure group, observed sixteen short (less than 30 seconds) and long road (70 seconds or more) crossing scenarios with varying crossing opportunities. Based on the crossing opportunities they were asked to cross a 3.6 m wide one-lane one way urban road. It was found that the crossing initiation process consists of four incremental movements of body parts: the head and the shoulder first; the hip, wrist and elbow second; the knee as a separate joint, and finally the ankle. Results showed that pedestrians’ decision to cross and body parts movement are influenced by time pressure and wait time for a safe crossing opportunity. Specifically, pedestrians prepare their body parts earlier, initiate their crossing earlier, and adjust their speed to compensate for the risk taken in less safe or non-safe crossing opportunities. Within the control group, women tended to be more risk avoiding than men, however those differences disappeared in the time pressure group. Most importantly, the findings provide initial evidence that this novel simulation configuration can be used to gain precise knowledge of pedestrians’ decision-making and movement processes.

What did we learn about pedestrians crossing movement?
Pedestrians change their strategy as a function of internal and external reasons:

  • Take higher risk when crossing opportunities are sparse or when they are under time pressure
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Initiate crossing, Kalantarov, Riemer, and Oron-Gilad for TRF

  • Prepare their movement in advance by adjusting body position
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body parts movement, Kalantarov, Riemer, and Oron-Gilad for TRF

  • Change the timing of crossing as a function of perceived risk
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timing of crossing, Kalantarov, Riemer, and Oron-Gilad for TRF

  • Adjust their crossing speed to the perceived risk
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walking speed, Kalantarov, Riemer, and Oron-Gilad for TRF

Kalantarov, S. , Riemer, R., Oron-Gilad, T. (in press). Pedestrians’ road crossing decisions and body parts’ movements. Transportation Research Part F: Psychology and Behaviour.

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Child Pedestrians’ perceived risk of the crossing place

We are excited to present our studies in the 10th University Transportation Centers Spotlight Conference on Pedestrian and Bicycle Safety to be held December 1-2 ,2016 in the Keck Center, Washington DC.

Here is a link to a short description of the BGU pedestrian laboratory.pedestrian-lab-brochure and to a short brief about the work we are presenting (Child Pedestrians’ perceived risk of the crossing place).

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How Full Vehicle Automation affects Driving, Under the Influence of Alcohol and Without It

Yisrael Parmet, Lee Shoham and Tal Oron-Gilad

Presentation at the ICTTP 2016.

link to presentation: How full vehicle automation affects…
DESCRIPTION: The purpose of this study was to examine the effects of full vehicle automation on performance and behavior, specifically the transition from a fully automated mode to manual driving, under the influence of alcohol and without it. Previous studies have revealed a deterioration in driving performance while transitioning from an automated mode to manual driving and further suggested that automated driving may result in a degraded situation awareness. It was therefore hypothesized that the performance of secondary driving related tasks would deteriorate during the automated phase, while performance of secondary non-driving related tasks would improve, in comparison to manual driving. It was further hypothesized that the transition from automated to manual driving would damage driving performance and that alcohol, while affecting performance of all driving conditions, would affect the manual phase following the automated phase to a greater extent. Method. A fixed base driving simulator was used. The design contained a first manual phase, an automated phase and another manual phase, under the influence of BAC 0.05% alcohol and without it. The study involved 16 participants. Two type of secondary tasks were introduced to the participants, driving and non-driving related tasks and the precision (% of success) and response time (RT) were measured. Driving quality indices such as speed and lane position were measures along the drive as well. Results. In the nondriving related secondary task we found significant differences in the response time only, the response time under the placebo condition were on average 15% higher than the response time under the alcohol condition. In the driving related secondary task we found significant difference in both measures, the participants on average were 5% more accurate and 13% faster while they drove manually. The results of the driving quality indices indicate a deterioration in precision of driving related secondary tasks, and a decrease in driving velocity after an automated phase, the latter being moderated by alcohol, which causes an increase in driving velocity. Conclusion. As hypothesized the performance of secondary driving related tasks deteriorated during the automated phase but contrary to our hypothesis, the automation had no influence on the performance of the non-driving secondary task. Opposing to our hypothesis, we found no evidence that alcohol deteriorates the drivers’ performance in the two types of secondary tasks. The last results might be due to the low level of alcohol that was used in the experiment. As expected we found that driving quality decreases after automated phase and while performing secondary tasks.

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Can traffic violations be traced to gender-role, sensation seeking, demographics and driving exposure?

A new publication co-authored by Ilit Oppenheim, Yisrael Parmet and David Shinar published in Transportation Research Part F.

http://dx.doi.org/10.1016/j.trf.2016.06.027

ABSTRACT
Background: Traffic safety is often expressed as the ‘inverse of accidents’. However, it is
more than the mere absence of accidents. Past studies often looked for associations
between accidents and self-reports like the Driver Behaviour Questionnaire
(DBQ; Reason, Manstead, Stradling, Baxter, & Campbell, 1990). The focus in this study
changed from counting accidents to quantifying unsafe acts as violations. The objective
was to show that drivers’ specific violations can be traced to personal characteristics such
as sensation seeking (SSS-V; Zuckerman, 1994), gender role (BSRI; Bem sex role inventory,
Bem, 1974), demographics, and driving exposure.
Method: A web-based questionnaire was distributed, integrating several known questionnaires.
Five hundred and twenty-seven questionnaires were completed and analyzed.
Results: Sensation seeking, gender role, experience, and age predicted respondents’ score
on the DBQ, as well as the interaction of sensation seeking with gender and gender role.
Gender role was a more valid predictor of driver behavior than gender.
Conclusions: The effect of gender role on drivers’ self-reported violation tendency is the
most interesting and the most intriguing finding of this survey and indicates the need to
further examine gender role affects in driving.

 

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Cell phone conversations and child pedestrian’s crossing behavior; a simulator study

This is our most recent publication, accepted for publication in Safety Science.

Please cite this article in press as: Tapiro, H., et al. Cell phone conversations and child pedestrian’s crossing behavior; a simulator study. Safety Sci. (2016), http://dx.doi.org/10.1016/j.ssci.2016.05.013

Cell phone conversations and child pedestrian’s crossing behavior; a simulator study

Hagai Tapiro, Yisrael Parmet and Tal Oron-Gilad

Abstract

Child pedestrians are highly represented in fatal and severe road crashes and differ in their crossing behavior from adults. Although many children carry cell phones, the effect that cell phone conversations have on children’s crossing behavior has not been thoroughly examined. A comparison of children and adult pedestrians’ crossing behavior while engaged in cell phone conversations was conducted. In a semi-immersive virtual environment simulating a typical city, 14 adults and 38 children (11 children aged 7-8; 18 aged 9-10 and 9 aged 11-13), experienced road crossing related traffic-scene scenarios. They were requested to press a response button whenever they felt it was safe to cross. Eye movements were tracked. Results have shown that all age groups’ crossing behaviors were affected by cell phone conversations. When busy with more cognitively demanding conversation types, participants were slower to react to a crossing opportunity, chose smaller crossing gaps, and allocated less visual attention to the peripheral regions of the scene. The ability to make better crossing decisions improved with age, but no interaction with cell phone conversation type was found. The most prominent improvement was shown in ‘safety gap’; each age group maintained a longer gap than its predecessor younger age group. In accordance to the current study, it is safe to say that cell phone conversations can hinder child and adult pedestrians’ safety. Thereby, it is important to take those findings in account when aiming to train young pedestrians for road-safety and increase public awareness.

Interested in seeing an interactive visualization app of our data?https://eyemove.shinyapps.io/cell-phone/

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Interactive app to view the eye gaze data. Click on the link and follow the instructions shown above.

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Validation study: Dome Pedestrian Simulator

Abstract

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.

dome-tapiro-and-oron-gilad

 

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Are child-pedestrians able to identify hazardous traffic situations?

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)

Are Child pedestrians able to identify hazardous traffic situations?

Highlights

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.

Abstract

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.

Pedestrians' crossing scenarios

Traffic scenes for pedestrian crossing (only the left part of the scene is shown). Top: no moving elements, Mid: road curvature obscuring FOV, Bottom: Parked vehicles obscuring FOV.

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