The analysis of drivers’ hazard detecting ability using Empathizing–Systemizing model

Danno, Mikio; Taniguchi, Shunji

doi:10.1016/j.trf.2015.07.003

Cited by 3 publications

(4 citation statements)

References 16 publications

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“…On the contrary, the larger D score drivers could be unsafe drivers since the larger D score drivers have less visual attention capability and are able to respond slower to hazards than the lower D score drivers. This does not contradict the results of the web survey findings[1].However, it should be noted that the relationship between the D scores and a driver's visual attention ability was revealed in the hasty driving condition but not in the normal driving condition. Furthermore, it should be noted as well that the relationship was not found in the high risk of near-miss crash traffic situations.…”

supporting

confidence: 61%

“…However, it should be noted that the "x" marks indicate the locations of the corresponding each Empathizing and Systemizing score of seven participants (from A to G) discussed in this paper. Those positions are well-balanced and almost equally distributed along the range of two dimensional coordinate of both Empathizing and Systemizing scores obtained from the Web survey data (N = 811)[1] shown inFigure 6.…”

mentioning

confidence: 92%

“…The hazard perception of a driver determines the ability to detect a potential collision. Danno & Taniguchi (2015) showed that near-miss incident experience was basically reduced by the Empathy Quotient and was disturbed by the Systemizing Quotient when the Empathy Quotient was low [1], based on Wakabayashi et al [4]. They also showed that a D score (difference between Systemizing Quotient standard score and Empathy Quotient standard score), which is used to classify the term "E-S types" into five cognitive types using a two-dimensional coordinate (Empathy Quotient and Systemizing Quotient), relates to dangerous experience.…”

Section: Introductionmentioning

confidence: 99%

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Pilot Test for the Relationship between Drivers’ Hazard Perception Ability and Cognitive Traits of Empathizing-Systemizing

Danno¹

2019

JBBS

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The previous research (Danno & Taniguchi, 2015) showed that near-miss incident experience was basically reduced by the Empathy Quotient (EQ) and was disturbed by the Systemizing Quotient (SQ) when the Empathy Quotient was low, based on the Empathizing and Systemizing (E-S) model using a web survey [1]. It means that drivers whose EQ was low and SQ was high had more near-miss incident experience. It suggested that drivers who have a stronger Empathizing function may have stronger hazard perception ability although the Systemizing function may weaken hazard perception ability when Empathizing is weak. And, then, it was revealed that the D score (standard SQ (T) score minus standard EQ (T) score) had a significant effect on the near-miss incident experience. Those results implied that a D score, which is used to classify "E-S types", should have a relationship with near-miss incident experience, i.e., hazard perception ability. The EQ and SQ scores were supposed to relate to the cognitive ability to estimate other road users' mental situations and predict their behavior or to recognize stable laws in traffic situations. The aim of this research was to investigate the relationship between a driver's visual attention ability (gaze movement) and hazard (near-miss incident) perception ability of different EQ and SQ scores. Drivers' Real-time Useful Field of View (rUFOV) [2] was measured under normal and hasty driving conditions in a driving simulator which had six scenarios of traffic situation. The result from seven participants who had different EQ and SQ scores showed that a driver's visual attention ability (gaze movement) corresponds to their scores. This pilot test research revealed a possibility that the individual difference in cognitive trait with E-S model could be a promising tool to understand the mechanism of hazard perception since a D score is used to classify "E-S types". How to cite this paper: Danno, M. (2019) Pilot Test for the Relationship between Drivers' Hazard Perception Ability and Cognitive Traits of Empathizing-Systemizing.

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confidence: 61%

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confidence: 92%

Section: Introductionmentioning

confidence: 99%

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Pilot Test for the Relationship between Drivers’ Hazard Perception Ability and Cognitive Traits of Empathizing-Systemizing

Danno¹

2019

JBBS

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“…In addition, many studies show that age, driving skill, and education affect drivers' hazard perception. In some recent studies, psychological tests were carried out to show the effect of drivers' psychological condition on hazard perception [7,8,9]. nighttime driving) also makes drivers estimate vehicle speed and distance using head or rear lights of vehicles [13].…”

Section: Introductionmentioning

confidence: 99%

Hazard Detection Prediction Model for Rural Roads Based on Hazard and Environment Properties

Asadamraji

Saffarzadeh

Borujerdian

et al. 2018

PROMET

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A driver’s reaction time encountering hazards on roads involves different sections, and each section must occur at the right time to prevent a crash. An appropriate reaction starts with hazard detection. A hazard can be detected on time if it is completely visible to the driver. It is assumed in this paper that hazard properties such as size and color, the contrast between the environment and a hazard, whether the hazard is moving or fixed, and the presence of a warning are effective in improving driver hazard detection. A driving simulator and different scenarios on a two-lane rural road are used for assessing novice and experienced drivers’ hazard detection, and a Sugeno fuzzy model is used to analyze the data. The results show that the hazard detection ability of novice and experienced drivers decreases by 35% and 64%, respectively, during nighttime compared to daytime. Also, moving hazards increase hazard detection ability by 9% and 180% for experienced and novice drivers, respectively, compared to fixed hazards. Moreover, increasing size, contrast, and color difference affect hazard detection under nonlinear functions. The results could be helpful in safety improvement solution prioritization and in preventing vehicle-pedestrian, vehicle-animal, and vehicle-object crashes, especially for novice drivers.

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Identifying novice drivers in need of hazard perception ability improvement for takeover performance in Level 3 automated driving

Weng,

Chai,

Yin

et al. 2024

Accident Analysis & Prevention

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The analysis of drivers’ hazard detecting ability using Empathizing–Systemizing model

Cited by 3 publications

References 16 publications

Pilot Test for the Relationship between Drivers’ Hazard Perception Ability and Cognitive Traits of Empathizing-Systemizing

Pilot Test for the Relationship between Drivers’ Hazard Perception Ability and Cognitive Traits of Empathizing-Systemizing

Hazard Detection Prediction Model for Rural Roads Based on Hazard and Environment Properties

Identifying novice drivers in need of hazard perception ability improvement for takeover performance in Level 3 automated driving

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