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 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.

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.

Comparison of Energy-Saving Driving Style Strategies

2016 ◽  
Author(s):  
Yigit Fidansoy ◽  
Sohejl Wanjani ◽  
Sebastian Schmidt
Keyword(s):  
Energy Consumption ◽  
Energy Saving ◽  
Fossil Fuels ◽  
Design Thinking ◽  
Energy Savings ◽  
Driving Style ◽  
Advisory Systems ◽  
Train Dynamics ◽  
Input Variables ◽  
And Training

Due to the increasing scarcity of fossil fuels and the climate change, the importance of energy efficiency is increasing. This importance is major especially in areas where the energy consumption is high. Rail transport depicts such an area. The highest proportion of energy consumed in the railway is the so called traction energy. This energy is required for the train run. In the timetable, allowances leave a margin for the driving style of train run. By the selective use of strategies that change the driving style, it is possible to exploit these allowances and reduce the traction energy consumption. The first objective of this study deals with the development of algorithms for energy-saving driving style. First, the necessary input variables of the algorithms based on the literature research and the formulas of train dynamics were determined. Then the algorithms were developed to create different energy-saving driving styles, resulting choose the best result which should be shown as a driving recommendation. The developed algorithms were used in an application example in order to calculate the potential of energy-savings. The example should represent the influence of the input variables for a comparison of different situations. At last the acceptance of the determined driving strategies in practice was investigated. By implementing the design thinking method it was identified that driver advisory systems and training programs are necessary to facilitate energy-saving driving in practice.

Privacy-Preserving k-means Clustering: an Application to Driving Style Recognition

2019 ◽  
pp. 685-696
Author(s):  
Othmane El Omri ◽  
Aymen Boudguiga ◽  
Malika Izabachene ◽  
Witold Klaudel
Keyword(s):  
Privacy Preserving ◽  
Driving Style

scholarly journals Factors Influencing and Contributing to Perceived Safety of Passengers during Driverless Shuttle Rides

2021 ◽  
Vol 1 (3) ◽  
pp. 657-671
Author(s):  
Claudia Luger-Bazinger ◽  
Cornelia Zankl ◽  
Karin Klieber ◽  
Veronika Hornung-Prähauser ◽  
Karl Rehrl
Keyword(s):  
Autonomous Driving ◽  
Future Research ◽  
Natural Setting ◽  
Mixed Traffic ◽  
Control Room ◽  
Driving Style ◽  
Perceived Safety ◽  
Factors Influencing ◽  
Traffic Environment ◽  
Set Up

This study investigates the perceived safety of passengers while being on board of a driverless shuttle without a steward present. The aim of the study is to draw conclusions on factors that influence and contribute to perceived safety of passengers in driverless shuttles. For this, four different test rides were conducted, representing aspects that might challenge passengers’ perceived safety once driverless shuttles become part of public transport: passengers had to ride the shuttle on their own (without a steward present), had to interact with another passenger, and had to react to two different unexpected technical difficulties. Passengers were then asked what had influenced their perceived safety and what would contribute to it. Results show that perceived safety of passengers was high across all different test rides. The most important factors influencing the perceived safety of passengers were the shuttle’s driving style and passengers’ trust in the technology. The driving style was increasingly less important as the passengers gained experience with the driverless shuttle. Readily available contact with someone in a control room would significantly contribute to an increase in perceived safety while riding a driverless shuttle. For researchers, as well as technicians in the field of autonomous driving, our findings could inform the design and set-up of driverless shuttles in order to increase perceived safety; for example, how to signal passengers that there is always the possibility of contact to someone in a control room. Reacting to these concerns and challenges will further help to foster acceptance of AVs in society. Future research should explore our findings in an even more natural setting, e.g., a controlled mixed traffic environment.

Sign in / Sign up

Export Citation Format

Share Document