Affective Use Cases for Empathic Vehicles in Highly Automated Driving: Results of an Expert Workshop

2020 ◽  
pp. 89-100 ◽  
Author(s):  
Michael Oehl ◽  
Klas Ihme ◽  
Anna-Antonia Pape ◽  
Mathias Vukelić ◽  
Michael Braun
Keyword(s):  
Use Cases ◽  
Automated Driving ◽  
Expert Workshop ◽  
Highly Automated Driving

Automated driving on public roads: Experiences in real traffic

2015 ◽  
Vol 57 (4) ◽  
Author(s):  
Oliver Pink ◽  
Jan Becker ◽  
Sören Kammel
Keyword(s):  
System Design ◽  
Use Cases ◽  
Automated Driving ◽  
Robust Implementation ◽  
Technical Realization ◽  
Driving Task ◽  
High Level ◽  
The Impact ◽  
Highly Automated Driving ◽  
Country Specific

AbstractAutomated driving on public roads is affected by many foreseeable and unforeseeable driving situations. Depending on the driving task, the environmental and road conditions, and the behavior of other drivers, different actions have to be taken. This paper provides a high-level overview of the development of highly automated driving systems and illustrates challenging situations and use cases. We outlined the impact of these use cases on system design, key technologies, and their technical realization for a highly automated driving system. Furthermore, the paper demonstrates how certain aspects of the system design as well as their implementation are country specific and how continuous testing is required for robust implementation of the functionalities.

scholarly journals Dynamic scan paths investigations under manual and highly automated driving

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jordan Navarro ◽  
Otto Lappi ◽  
François Osiurak ◽  
Emma Hernout ◽  
Catherine Gabaude ◽  
...  
Keyword(s):  
Relative Frequency ◽  
Human Locomotion ◽  
Visual Scanning ◽  
Automated Driving ◽  
The Gaze ◽  
Visual Inputs ◽  
Gaze Patterns ◽  
Gaze Behaviour ◽  
Scan Paths ◽  
Highly Automated Driving

AbstractActive visual scanning of the scene is a key task-element in all forms of human locomotion. In the field of driving, steering (lateral control) and speed adjustments (longitudinal control) models are largely based on drivers’ visual inputs. Despite knowledge gained on gaze behaviour behind the wheel, our understanding of the sequential aspects of the gaze strategies that actively sample that input remains restricted. Here, we apply scan path analysis to investigate sequences of visual scanning in manual and highly automated simulated driving. Five stereotypical visual sequences were identified under manual driving: forward polling (i.e. far road explorations), guidance, backwards polling (i.e. near road explorations), scenery and speed monitoring scan paths. Previously undocumented backwards polling scan paths were the most frequent. Under highly automated driving backwards polling scan paths relative frequency decreased, guidance scan paths relative frequency increased, and automation supervision specific scan paths appeared. The results shed new light on the gaze patterns engaged while driving. Methodological and empirical questions for future studies are discussed.

scholarly journals Highly Automated Driving, Secondary Task Performance, and Driver State

2012 ◽  
Vol 54 (5) ◽  
pp. 762-771 ◽  
Author(s):  
Natasha Merat ◽  
A. Hamish Jamson ◽  
Frank C. H. Lai ◽  
Oliver Carsten
Keyword(s):  
Task Performance ◽  
Secondary Task ◽  
Automated Driving ◽  
Highly Automated Driving

MEC-enabled 5G Use Cases: A Survey on Security Vulnerabilities and Countermeasures

2022 ◽  
Vol 54 (9) ◽  
pp. 1-37
Author(s):  
Pasika Ranaweera ◽  
Anca Jurcut ◽  
Madhusanka Liyanage
Keyword(s):  
Edge Computing ◽  
Use Cases ◽  
Automated Driving ◽  
Security Vulnerabilities ◽  
Internet Technologies ◽  
Computing Platform ◽  
Service Guarantees ◽  
Fifth Generation ◽  
Machine Type Communication ◽  
Multi Access

The future of mobile and internet technologies are manifesting advancements beyond the existing scope of science. The concepts of automated driving, augmented-reality, and machine-type-communication are quite sophisticated and require an elevation of the current mobile infrastructure for launching. The fifth-generation (5G) mobile technology serves as the solution, though it lacks a proximate networking infrastructure to satisfy the service guarantees. Multi-access Edge Computing (MEC) envisages such an edge computing platform. In this survey, we are revealing security vulnerabilities of key 5G-based use cases deployed in the MEC context. Probable security flows of each case are specified, while countermeasures are proposed for mitigating them.

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