Effects of environmental, vehicle and human factors on comfort in partially automated driving: A scenario-based study

Delmas, Maxime; Camps, Valérie; Lemercier, Céline

doi:10.1016/j.trf.2022.03.012

Cited by 18 publications

(13 citation statements)

References 23 publications

(42 reference statements)

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“…These results are in line with previous studies that showed that in most situations, personalized automated driving-styles are preferred [1,5,6], more accepted [6,7], and are perceived as more trustful [6,8], comfortable [6,8] and safe [6]. They also are in line with previous research, that showed that participants felt more comfortable in unfavorable driving conditions when the speed of the AC was lower than the speed limit [10]. Exploratory analyses revealed that the negative influence of adverse weather conditions and high levels of traffic congestion on both types of speed was stronger for highway than for secondary roads and downtown, and that it was stronger for secondary roads than for downtown.…”

Section: Plos Onesupporting

confidence: 92%

“…It relies on written scenarios, where participants are asked to evaluate combinations of variables, rather than individual ones. This methodology has already been used in various research areas [ 23 ], including automated driving [ 10 , 24 ].…”

Section: Methodsmentioning

confidence: 99%

“…In the present study, an original modification was made to this second phase. Rather than asking participants to indicate their responses on a single item, which is usually done (e.g., [ 10 , 24 ]), they were asked to indicate their responses on two. First, they were asked: “ If you were Charlie , how fast would you prefer the partially autonomous vehicle to drive in this situation ?”.…”

Section: Methodsmentioning

confidence: 99%

“…Another study has also shown that while young participants preferred a familiar automated driving-style, older participants preferred an unfamiliar one, tending to be faster than their age-affected manual driving-style [ 1 ]. Other studies have also shown that the appreciation of automated driving-style could vary according to driving situations such as driving in intersections [ 9 ], in adverse weather conditions [ 10 ], or in heavy traffic [ 10 ]. These variations might be explained by driver-related variables, such as trust in automated driving systems.…”

Section: Introductionmentioning

confidence: 99%

“…These variations might be explained by driver-related variables, such as trust in automated driving systems. It has for instance been shown that the participants with the highest level of trust in ACs had their comfort less affected by adverse driving conditions than participants with the lowest level of trust in AC [ 10 ]. Calibration of trust in an automated system must be appropriate for the interaction to be safe and effective, since over-trust and mistrust can lead to both the misuse and disuse of the automated system [ 11 , 12 ].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Should my automated car drive as I do? Investigating speed preferences of drivengers in various driving conditions

Delmas

Camps²,

Lemercier³

2023

PLoS ONE

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Studies investigating the question of how automated cars (ACs) should drive converge to show that a personalized automated driving-style, i.e., mimicking the driving-style of the human behind the wheel, has a positive influence on various aspects of his experience (e.g., comfort). However, few studies have investigated the fact that these benefits might vary with respect to driver-related variables, such as trust in ACs, and contextual variables of the driving activity, such as weather conditions. Additionally, the context of intermediate levels of automation, such as SAE level 3, remains largely unexplored. The objective of this study was to investigate these points. In a scenario-based experimental protocol, participants were exposed to written scenarios in which a character is driven by a SAE level 3 AC in different combinations of conditions (i.e., types of roads, weather conditions and traffic congestion levels). For each condition, participants were asked to indicate how fast they would prefer their AC to drive and how fast they would manually drive in the same situation. Through analyses of variance and equivalence tests, results showed a tendency for participants to overall prefer a slightly lower AC speed than their own. However, a linear regression analysis showed that while participants with the lowest levels of trust preferred an AC speed lower than theirs, those with the highest levels preferred an AC speed nearly identical to theirs. Overall, the results of this study suggest that it would be more beneficial to implement a personalization approach for the design of automated driving-styles rather than a one for all approach.

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