Description of Corner Cases in Automated Driving: Goals and Challenges [PDF]
2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW), 2021 Scaling the distribution of automated vehicles requires handling various unexpected and possibly dangerous situations, termed corner cases (CC). Since many modules of automated driving systems are based on machine learning (ML), CC are an essential part ...
Daniel Bogdoll +6 more
semanticscholar +1 more source
Virtual Testing of Automated Driving Systems. A Survey on Validation Methods
IEEE Access, 2022 This paper surveys the state-of-the-art contributions supporting the validation of virtual testing toolchains for Automated Driving System (ADS) verification.
R. Donà, B. Ciuffo
semanticscholar +1 more source
An Application-Driven Conceptualization of Corner Cases for Perception in Highly Automated Driving [PDF]
2021 IEEE Intelligent Vehicles Symposium (IV), 2021 Systems and functions that rely on machine learning (ML) are the basis of highly automated driving. An essential task of such ML models is to reliably detect and interpret unusual, new, and potentially dangerous situations.
Florian Heidecker +7 more
semanticscholar +1 more source
The Impact of Situational Complexity and Familiarity on Takeover Quality in Uncritical Highly Automated Driving Scenarios [PDF]
, 2020 In the development of highly automated driving systems (L3 and 4), much research has been done on the subject of driver takeover. Strong focus has been placed on the takeover quality.
Russwinkel, Nele +2 more
core +1 more source
Physiological Measures of Risk Perception in Highly Automated Driving
IEEE transactions on intelligent transportation systems (Print), 2022 Highly automated driving will likely result in drivers being out-of-the-loop during specific scenarios and engaging in a wide range of non-driving related tasks.
Jaume R. Perello-March +4 more
semanticscholar +1 more source
Exploring how drivers perceive spatial earcons in automated vehicles [PDF]
, 2017 Automated vehicles seek to relieve the human driver from primary driving tasks, but this substantially diminishes the connection between driver and vehicle compared to manual operation.
Baillie, Lynne +2 more
core +1 more source
What Is the Best Way to Optimally Parameterize the MPC Cost Function for Vehicle Guidance?
Mathematics, 2023 Model predictive control (MPC) is a promising approach to the lateral and longitudinal control of autonomous vehicles. However, the parameterization of the MPC with respect to high-level requirements such as passenger comfort, as well as lateral and ...
David Stenger +4 more
doaj +1 more source
Information, 2021 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.
Johannes Ossig +2 more
doaj +1 more source
Human-centered challenges and contributions for the implementation of automated driving [PDF]
, 2011 Automated driving is expected to increase safety and efficiency of road transport. With regard to the implementation of automated driving, we observed that those aspects which need to be further developed especially relate to human capabilities. Based on
B. Arem +5 more
core +2 more sources
Multi-Sensor Fusion in Automated Driving: A Survey
IEEE Access, 2020 With the significant development of practicability in deep learning and the ultra-high-speed information transmission rate of 5G communication technology will overcome the barrier of data transmission on the Internet of Vehicles, automated driving is ...
Zhangjing Wang, Yu Wu, Qingqing Niu
semanticscholar +1 more source