Archive for category driving skills

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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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:

  1. Real-Time Hazard Identification,
  2. Hazard Classification
  3. 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

Abstract

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.

Representative photos of the seven common movies for Sets 1-3, as they appear in Borowsky and Oron-Gilad (2013)

Representative photos of the seven common movies for Sets 1-3, as they appear in Borowsky and Oron-Gilad (2013)

Representative photos of the varied exemplar for Sets 1-3, as they appear in Borowsky and Oron-Gilad (2013)

Representative photos of the varied exemplar for Sets 1-3, as they appear in Borowsky and Oron-Gilad (2013)

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Traffic Safety: Current Issues and Emerging Directions – conference program now available

Conference program is now available.

If you plan to attend don’t forget to register at the conference website  http://davidshinar.eventbrite.com/ no later than September 30, 2012.

click here to download the Traffic Safety conference program

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Inexperienced drivers training program – Trailer

Driving is a demanding task combining complex motor and cognitive skills. A typical driving task may include maneuvering among other vehicles, paying attention to various road users (e.g., drivers and pedestrians), and discerning static and dynamic road signs and obstacles). The total amount and rate of information presented to the driver is  more than a human brain can handle at a given time. Thus, the road presents a vast array of accessible information, but drivers notice and attend only to a small fraction of it.

Recent evidence suggests that among all driving skills, only hazard awareness – the ability of drivers to read the road and identify hazardous situations –correlates with traffic crashes (e.g., Horswill and McKenna, 2004). Furthermore, McKenna et al. (2006) have shown that improving hazard awareness skills (via training to identify hazardous situations) resulted in a decrease in risk taking attitudes for novice drivers. These findings and others (e.g., Pradhan et al., 2009; Borowsky et al., 2010; Pollatsek et al., 2006; Deery, 1999) acknowledge that young-novice drivers might be less aware of potential hazards and risks embedded in a situation, and thus are more susceptible to taking risks while driving because of this lack of awareness.

References

Borowsky, A., Shinar, D., & Oron-Gilad, T. (2010). Age and skill differences in driving related hazard perception, Accident Analysis and Prevention, vol. 42, pp. 1240-1249.

Deery, H.A. (1999). Hazard and risk perception among young novice drivers. Journal of Safety Research, 30(4), 225-236.

Horswill, M. S., & McKenna, F. P. (2004). Drivers’ hazard perception ability: Situation awareness on the road. In S. Banbury and S. Tremblay (Eds.), A cognitive approach to situation awareness: Theory and application (pp. 155-175). Aldershot, United Kingdom: Ashgate.

McKenna, F. P., Horswill, M. S., & Alexander, J. L. (2006). Does anticipation training affect drivers’ risk taking? Journal of Experimental Psychology, 12, 1-10.

Pollatsek, A., Narayanaan, V., Pradhan, A., & Fisher, D. L. (2006). Using eye movements to evaluate a PC-based risk awareness and perception training program on a driving simulator. Human Factors, 48, 447–464.

 Pradhan, A. K., Pollatsek, A., Knodler, M., & Fisher, D. L. (2009). Can younger drivers be trained to scan for information that will reduce their risk in roadway traffic scenarios that are hard to identify as hazardous? Ergonomics, 52, 657-673.

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Act and Anticipate Hazard Perception Training – AAHPT

AAHPT is a research effort aimed toward developing innovative training strategies for Hazard perception among young-inexperienced drivers.

  • AAHPT is still in its development stages. Nevertheless several experimental phases have already been completed
  • Initial findings concerning AAHPT training methodologies are available, those are constantly embedded into future development directions.

AAHPT principles

  • Intended for novice drivers who have already obtained the basic skills of driving (i.e., vehicle handling and maneuvering)
  • Enriching driving experience in a short period of time (i.e., in a condensed way)
  • Exposure to diverse real life driving situations (see below, residential, sparsely populated urban and inter-city areas)

residentialSparesely populated urban areaintercity

  • Training- Actual hazards vs. Testing- Potential hazards (i.e., less salient situations)
  • Data driven events-not are defined a priori (i.e., there is no one single master solution)
  • Goal standard of experienced drivers (performance of young-inexperienced is compared to a pool of data obtained
  • Variety of HP measurements

AAHPT variations

  • Active – Participants observe 63 HP video-based traffic scenes and are asked to press a response button each time they detect a hazardous situation.

Participants first observe a movie press a button each time they perceive a hazardous situation. Once, completed a text box appears and they have to specify the reason for their presses.

active 1active 2

  • Instructional – The ‘Instructional’ group underwent a theoretical tutorial, where written material concerning HP was followed by video-based examples. Participants were not asked to actively respond to situations, but rather to become familiar with concepts and examples.

Here are two sample slides taken from the Instructional-based training. The first leads to a discussion on different traffic environments and the second shows a specific example of pedestrians in an urban area including tips and information. This snapshot was taken from one of the 63 videos of traffic scenes used in the AAHPT training.

InstructionalInstructional1

  • Hybrid – The ‘Hybrid’ participants observed a concise theoretical component first (similar to the ‘Instructional’ mode) followed by a shortened active component (similar to the ‘Active’ mode). This mode enables the young-inexperienced drivers to receive both theoretical information as well as to act and respond.

HPT (Hazard Perception Test)

  • Observe 58  HP movies and  press a response button each time they detect a hazard similar way as in the Active training but different movies with less salient hazards (see following images left-training, the hazard (e.g., vehicle) is apparent whereas right-testing the hazard is not apparent ,i.e., potential danger).

training1testing 1

To read more:

Borowsky, A., Oron-Gilad, T., Meir A. and Parmet Y. Human Factors and Ergonomics Society’s 54th Annual Meeting. California, September 27-October 1, 2010.

Meir, Borowsky, Oron-Gilad, Parmet and Shinar. Act and Anticipate Hazard Perception Training for Young-Inexperienced Drivers, The 3rd International Conference on Applied Human Factors and Ergonomics (AHFE), July 17-20, 2010. see book chapter online http://www.crcnetbase.com/doi/abs/10.1201/EBK1439835074-c15

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