scholarly journals Identifikation von Fahrertypen im Kontext des automatisierten Fahrens

2021 ◽  
Author(s):  
Jan Schlüter ◽  
Marco Hellmann ◽  
Johannes Weyer
Keyword(s):  
Driving Style ◽  
Driving Skill

ZusammenfassungIm Straßenverkehr existieren unterschiedliche Konzepte zur Identifikation von Fahrertypen, die sich hinsichtlich Fahrverhalten und Einstellung zum Fahren unterscheiden. Im Rahmen der Automatisierung von Fahraufgaben gilt es zu überprüfen, wie diese Konzepte an die Herausforderungen veränderter Mensch-Maschine-Interaktion angepasst werden müssen und ob sich neuartige Fahrertypen identifizieren lassen. Auf Basis bestehender Typisierungen aus der Verkehrspsychologie sowie Erkenntnissen der Automationsforschung werden dazu die Konzepte des „Driving Style“ und „Driving Skill“ weiterentwickelt, um Fahrertypen im Kontext des automatisierten Fahrens zu identifizieren. In einer großzahligen Online-Umfrage wurden drei Fahrertypen identifiziert, die sich insbesondere hinsichtlich ihrer Einstellung zum automatisierten Fahren unterscheiden. In einer experimentellen Studie im Fahrsimulator kann anschließend gezeigt werden, dass diese Fahrertypen die Automation im Fahrzeug jeweils anders erleben und daher differenzierte Ansprüche an diese richten. Insgesamt deuten die Studienergebnisse darauf hin, dass die Akzeptanz des automatisierten Fahrens durch nutzergerechte Technik gefördert werden könnte. Die Ergebnisse dienen dazu, die jeweiligen Fahrertypen, ihre Einstellungen und ihre Nutzungspräferenzen im Kontext des automatisierten Fahrens besser zu verstehen und erste Ansatzpunkte für deren Berücksichtigung in der adaptiven Technikentwicklung zu identifizieren.

scholarly journals Acceptance of Highly Automated Vehicles: Weak or Absent Relationships with Desire for Control, Illusion of Control, and Driving Styles

2020 ◽  
Author(s):  
Michael Nees ◽  
Karli Herwig ◽  
Lindsey Quigley
Keyword(s):  
Illusion Of Control ◽  
Automated Vehicles ◽  
Control Scale ◽  
Driving Style ◽  
Automated Vehicle ◽  
Self Rating ◽  
Driving Skill ◽  
Demographic Questionnaire ◽  
Acceptance Scale ◽  
Automation Technology

Participants (including an online sample and college undergraduates) completed a highly automated vehicle acceptance scale as well as: (1) the Multi-dimensional Driving Style Inventory (MDSI); (2) the Desirability of Control Scale; (3) an illusion of control scale; (4) an accident concern self-rating, (5) a speed questionnaire; (6) an accidents, violations and close-calls questionnaire; (7) a driving skill self-rating; and (8) a demographic questionnaire. Exploratory analyses showed that relationships between acceptance factors and other variables generally were weak or absent, although self-rated familiarity with automation technology and education may predict acceptance. Practical and theoretical implications are discussed.

Driving Style Influence on Vehicles Performances

2018 ◽  
Vol 1 (1) ◽  
pp. 39-42
Author(s):  
Laszlo Barothi ◽  
◽  
Daniel Sava ◽  
Cătălin-Dumitru Darie ◽  
Leonard-Iulian Cucu ◽  
...  
Keyword(s):  
Driving Style

scholarly journals Concept of an Ontology for Automated Vehicle Behavior in the Context of Human-Centered Research on Automated Driving Styles

Information ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 21
Author(s):  
Johannes Ossig ◽  
Stephanie Cramer ◽  
Klaus Bengler
Keyword(s):  
Driving Behavior ◽  
Automation System ◽  
Automated Driving ◽  
Driving Style ◽  
Driving Experience ◽  
Automated Vehicle ◽  
Future Design ◽  
Vehicle System ◽  
The Future ◽  
Conceptual Distinction

In the human-centered research on automated driving, it is common practice to describe the vehicle behavior by means of terms and definitions related to non-automated driving. However, some of these definitions are not suitable for this purpose. This paper presents an ontology for automated vehicle behavior which takes into account a large number of existing definitions and previous studies. This ontology is characterized by an applicability for various levels of automated driving and a clear conceptual distinction between characteristics of vehicle occupants, the automation system, and the conventional characteristics of a vehicle. In this context, the terms ‘driveability’, ‘driving behavior’, ‘driving experience’, and especially ‘driving style’, which are commonly associated with non-automated driving, play an important role. In order to clarify the relationships between these terms, the ontology is integrated into a driver-vehicle system. Finally, the ontology developed here is used to derive recommendations for the future design of automated driving styles and in general for further human-centered research on automated driving.

scholarly journals The Pilot Study of the Hazard Perception Test for Evaluation of the Driver’s Skill Using Virtual Reality

Electronics ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 1114
Author(s):  
Tatsunori Sawada ◽  
Hiroki Uda ◽  
Akira Suzuki ◽  
Kounosuke Tomori ◽  
Kanta Ohno ◽  
...  
Keyword(s):  
Limited Range ◽  
Chi Square ◽  
Hazard Perception ◽  
Novice Drivers ◽  
Head Mounted Display ◽  
Road Users ◽  
Driving Skill ◽  
Significant Difference ◽  
Chi Square Test ◽  
Gender Groups

Background: Although various technologies are used to evaluate driving skill, there are some limitations such as the limited range of the monitor and the possible risk of causing cybersickness. The purpose of this study is to investigate differences in the hazard perception and cybersickness experienced between novice and experienced drivers measured in a VR hazard perception test with a head-mounted display (HMD). Methods: The novice (n = 32) and the experienced drivers (n = 36) participated in the hazard perception test through the VR of an HMD. Results: The total number of identified hazards was 1071 in the novice drivers and 1376 in the experienced drivers. Two of the hazards appeared to be only identifiable through the HMD. A chi-square test revealed that experienced drivers were more likely to identify the hazards than the novice drivers (p < 0.05). The novice drivers appeared to identify “hazard prediction of the current behavior of other road users” more than other hazard types, unlike the experienced group. The Simulator Sickness Questionnaire scores indicated no significant difference in the different age or gender groups (p > 0.05). Conclusion: Our results suggest that the VR hazard perception test may be useful for evaluating patients’ driving skills.

scholarly journals The Influence of Operating Strategies regarding an Energy Optimized Driving Style for Electrically Driven Railway Vehicles

Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 583
Author(s):  
Lukas Pröhl ◽  
Harald Aschemann ◽  
Roberto Palacin
Keyword(s):  
Load Distribution ◽  
Optimization Approach ◽  
Total Energy Consumption ◽  
Driving Style ◽  
Optimal Velocity ◽  
Railway Vehicles ◽  
Operating Modes ◽  
Detailed Simulation ◽  
Operating Strategies ◽  
Optimal Driving

The aim of this paper is the optimization of velocity trajectories for electrical railway vehicles with the focus on total energy consumption. On the basis of four fundamental operating modes—acceleration, cruising, coasting, and braking—energy-optimal trajectories are determined by optimizing the sequence of the operating modes as well as the corresponding switching points. The optimization approach is carried out in two consecutive steps. The first step ensures compliance with the given timetable, regarding both time and position constraints. In the second step, the influence of different operating strategies, such as load distribution and the switch-off of traction components during low loads, are analyzed to investigate the characteristics of the energy-optimal velocity trajectory. A detailed simulation model has been developed to carry out the analysis, including an assessment of its capabilities and advantages. The results suggest that the application of load-distribution techniques, either by a switch-off of parallel traction units or by a load-distribution between active units, can affect the energy-optimal driving style.

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