Personality factors are associated with simulated driving outcomes across the driving lifespan

Riendeau, Julie; Stinchcombe, Arne; Weaver, Bruce; Bédard, Michel

doi:10.1016/j.trf.2018.01.022

Cited by 31 publications

(17 citation statements)

References 35 publications

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“…The latter were recorded drives of human participants, collected before the main study took place, which were then replayed to participants of this study. In order to ensure that distinct differences would arise between the two human-driven controllers, in terms of driving behaviour, recruitment of participants used for the human-driven controllers was based on their sensation seeking scores, since previous studies have shown a positive correlation between speed choice and sensation seeking (Louw et al, 2019) and risk-taking behaviour in manual driving (Ge et al, 2014;Oppenheim et al, 2016;Riendeau et al, 2018;Ulleberg & Rundmo, 2003). These controllers are described further below.…”

Section: Driving Stylesmentioning

confidence: 99%

Drivers’ Evaluation of Different Automated Driving Styles: Is It both Comfortable and Natural?

Peng¹,

Merat²,

Romano³

et al. 2021

Preprint

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Objective: This study investigated users’ subjective evaluation of three highly automated driving styles, in terms of comfort and naturalness, when negotiating a UK road in a high-fidelity, motion-based, driving simulator. Background: Comfort and naturalness are thought to play an important role in contributing to users’ acceptance and trust of automated vehicles (AVs), although not much is understood about the types of driving style which are considered comfortable or natural. Method: A driving simulator study, simulating roads with different road geometries and speed limits, was conducted. Twenty-four participants experienced three highly automated driving styles, two of which were recordings from human drivers, and the other was based on a machine learning (ML) algorithm, termed Defensive, Aggressive, and Turner respectively. Participants evaluated comfort or naturalness of each driving style, for each road segment, and completed a Sensation Seeking (SS) questionnaire, which assessed their risk-taking propensity. Results: Participants regarded human-like driving styles as more comfortable and natural, compared with the less human-like, ML-based, driving controller. However, between the two human-like controllers, only the Defensive style was considered comfortable, especially for the more challenging road environments. Differences in preference for controller by driver trait were also observed, with the Aggressive driving style evaluated as more natural by the high sensation seekers. Conclusion: Participants were able to distinguish between human- and machine-like AV controllers. A range of psychological concepts must be considered for the subjective evaluation of controllers. Application: Knowing how different driver groups evaluate automated vehicle controllers is important to design more acceptable systems in the future.

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Section: Driving Stylesmentioning

confidence: 99%

Drivers’ Evaluation of Different Automated Driving Styles: Is It both Comfortable and Natural?

Peng¹,

Merat²,

Romano³

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…While clear associations between basic personality traits and driving anger have thus been established based on self-reported data, such relations have been tested only sporadically based on actual driving data. A recent study by Riendeau et al (2018), for instance, examined the relationship between basic personality traits and driving performance measured in the driving simulator. Therein, Big Five Extraversion and Neuroticism were negatively associated with safe driving performance (i.e., average speed, number of speed exceedances), lateral control (i.e., road edge and lane excursions), and total collisions.…”

Section: Driving Anger Expression Aggressive Driving and Personalitymentioning

confidence: 99%

Links between observed and self-reported driving anger, observed and self-reported aggressive driving, and personality traits

Ābele

Haustein

Møller

et al. 2020

Accident Analysis & Prevention

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“…Riendeau et al attempted to evaluate the relationship between personality and objective driving results based on simulated driving data. They found that extroversion and neuroticism were significantly correlated with unsafe driving [33]. However, they only considered the connection between speed and personality, and ignored the driver's own responsiveness and other vehicle indicators except for speed.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Driving Behavior Based on Dynamic Changes of Personality States

Wang

Zhang

Wang

et al. 2020

IJERPH

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This study investigated the relationship between personality states and driving behavior from a dynamic perspective. A personality baseline was introduced to reflect the driver’s trait level and can be used as a basic reference for the dynamic change of personality states. Three kinds of simulated scenarios triggered by pedestrian crossing the street were established using a virtual reality driving simulator. Fifty licensed drivers completed the driving experiments and filled in the Neuroticism Extraversion Openness Five-Factor Inventory (NEO-FFI) questionnaire to measure the drivers’ personality baselines. Key indicators were quantified to characterize the five types of personality states by K-means clustering algorithm. The results indicated that the high-risk situation had a greater impact on the drivers, especially for drivers with openness and extroversion. Furthermore, for the drivers of extroverted personality, the fluctuation of personality states in the high-risk scenario was more pronounced. This paper put forward a novel idea for the analysis of driving behavior, and the research results provide a personalized personality database for the selection of different driving modes.

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Personality factors are associated with simulated driving outcomes across the driving lifespan

Cited by 31 publications

References 35 publications

Drivers’ Evaluation of Different Automated Driving Styles: Is It both Comfortable and Natural?

Drivers’ Evaluation of Different Automated Driving Styles: Is It both Comfortable and Natural?

Links between observed and self-reported driving anger, observed and self-reported aggressive driving, and personality traits

Analysis of Driving Behavior Based on Dynamic Changes of Personality States

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