I Care Who and Where You Are – Influence of Type, Position and Quantity of Oncoming Vehicles on Perceived Safety During Automated Driving on Rural Roads

Roßner, Patrick; Bullinger, Angelika C.

doi:10.1007/978-3-030-50537-0_6

Cited by 7 publications

(3 citation statements)

References 11 publications

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“…And yet these factors have an effect on comfort during manual driving (e.g., Beggiato et al, 2020;Faria et al, 2018), and could also have an effect on comfort during automated driving. As argued by Rossner and Bullinger (2020), factors that influence perceived safety in manual driving are also factors that influence perceived safety during highly automated driving.…”

Section: Introductionmentioning

confidence: 99%

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

Delmas¹,

Camps²,

Lemercier³

2022

Transportation Research Part F: Traffic Psychology and Behaviou

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Section: Introductionmentioning

confidence: 99%

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

Delmas¹,

Camps²,

Lemercier³

2022

Transportation Research Part F: Traffic Psychology and Behaviou

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“…To investigate risk perception, this study proposes coupling this physiological measurement with a real-time subjective assessment by using an analogue device that can be operated using one hand. A similar method was used by Rossner and Bullinger ( 2019 , 2020a , b ). In their study, the participants were asked to assess their levels of comfort while they were on board a simulated autonomous vehicle.…”

Section: Introductionmentioning

confidence: 99%

Risk Assessment by a Passenger of an Autonomous Vehicle Among Pedestrians: Relationship Between Subjective and Physiological Measures

Petit

Charron

Mars

2021

Front. Neuroergonomics

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Autonomous navigation becomes complex when it is performed in an environment that lacks road signs and includes a variety of users, including vulnerable pedestrians. This article deals with the perception of collision risk from the viewpoint of a passenger sitting in the driver's seat who has delegated the total control of their vehicle to an autonomous system. The proposed study is based on an experiment that used a fixed-base driving simulator. The study was conducted using a group of 20 volunteer participants. Scenarios were developed to simulate avoidance manoeuvres that involved pedestrians walking at 4.5 kph and an autonomous vehicle that was otherwise driving in a straight line at 30 kph. The main objective was to compare two systems of risk perception: These included subjective risk assessments obtained with an analogue handset provided to the participants and electrodermal activity (EDA) that was measured using skin conductance sensors. The relationship between these two types of measures, which possibly relates to the two systems of risk perception, is not unequivocally described in the literature. This experiment addresses this relationship by manipulating two factors: The time-to-collision (TTC) at the initiation of a pedestrian avoidance manoeuvre and the lateral offset left between a vehicle and a pedestrian. These manipulations of vehicle dynamics made it possible to simulate different safety margins regarding pedestrians during avoidance manoeuvres. The conditional dependencies between the two systems and the manipulated factors were studied using hybrid Bayesian networks. This relationship was inferred by selecting the best Bayesian network structure based on the Bayesian information criterion. The results demonstrate that the reduction of safety margins increases risk perception according to both types of indicators. However, the increase in subjective risk is more pronounced than the physiological response. While the indicators cannot be considered redundant, data modeling suggests that the two risk perception systems are not independent.

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“…However, the number of studies investigating preferences for automated driving behavior is not yet sufficient to understand how users want to be driven in an automated vehicle (AV), especially with regard to their personal driving behavior. In addition, multiple scenarios and maneuvers have been investigated in urban and rural environments [5]- [7], [11]- [14], whereas lane change maneuvers have been the primary focus on motorways [8], [10], [15]- [17]. Although steady-state car-following and decelerating to a lead vehicle are both driving situations with a high frequency [18] and considered as highly comfort relevant [3], [19], they have been rarely examined so far.…”

Section: Introductionmentioning

confidence: 99%

Comfort and Safety in Conditional Automated Driving in Dependence on Personal Driving Behavior

Vasile,

Dinkha,

Seitz

et al. 2023

IEEE Open J. Intell. Transp. Syst.

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When changing from active driving to conditional automated driving (CAD), the question arises whether users still prefer their own driving behavior while being a passenger. The aim of this paper is to analyze driving behavior preferences in CAD based on the perception of comfort and safety, taking the personal driving behavior into account. Furthermore, it is investigated if users are able to manually demonstrate their desired driving behavior for CAD. Data on the personal, desired and experienced automated driving behavior of 42 participants from a real-world study was used to investigate both research questions for car-following (CF) and decelerating to a lead vehicle (DL) situations. In a first step, the personal and desired driving behavior is compared with the automated driving behavior based on selected parameters. Subsequently, the relationship between behavior differences and the assessed situation comfort and safety is analyzed. The results show a dependency between differences of personal and automated driving behavior and subjective ratings for comfort and safety. Furthermore, results suggest that participants prefer a driving behavior similar to or more defensive than their own for CAD. Our findings also show that participants were able to demonstrate their desired comfort driving behavior in CF and DL situations.

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I Care Who and Where You Are – Influence of Type, Position and Quantity of Oncoming Vehicles on Perceived Safety During Automated Driving on Rural Roads

Cited by 7 publications

References 11 publications

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

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

Risk Assessment by a Passenger of an Autonomous Vehicle Among Pedestrians: Relationship Between Subjective and Physiological Measures

Comfort and Safety in Conditional Automated Driving in Dependence on Personal Driving Behavior

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