Comfort and Safety in Conditional Automated Driving in Dependence on Personal Driving Behavior
IEEE Open Journal of Intelligent Transportation Systems, 2023 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.
Laurin Vasile +4 more
doaj +2 more sources
How Do Drivers Perceive Risks During Automated Driving Scenarios? An fNIRS Neuroimaging Study. [PDF]
Hum Factors, 2023 Objective Using brain haemodynamic responses to measure perceived risk from traffic complexity during automated driving. Background Although well-established during manual driving, the effects of driver risk perception during automated driving remain ...
Perello-March J +4 more
europepmc +2 more sources
Impact of Partially Automated Driving Functions on Forensic Accident Reconstruction: A Simulator Study on Driver Reaction Behavior in the Event of a Malfunctioning System Behavior [PDF]
Sensors, 2023 Partially automated driving functions (SAE Level 2) can control a vehicle’s longitudinal and lateral movements. However, taking over the driving task involves automation risks that the driver must manage.
Daniel Paula +7 more
doaj +2 more sources
A Credibility Assessment Approach for Scenario-Based Virtual Testing of Automated Driving Functions
IEEE Open Journal of Intelligent Transportation Systems, 2022 An immense test space is pushing the development and testing of automated driving functions from real to virtual environments. The virtual world is provided by interconnected simulation models representing sensors, vehicle dynamics, and both static and ...
Christoph Stadler +4 more
doaj +2 more sources
A Dataset on Takeover during Distracted L2 Automated Driving [PDF]
Scientific DataAutomated driving systems enable drivers to perform various non-driving tasks, which has led to concerns regarding driver distraction during automated driving.
Jiwoo Hwang +5 more
doaj +2 more sources
Survey on Unsupervised Domain Adaptation for Semantic Segmentation for Visual Perception in Automated Driving [PDF]
IEEE Access, 2023 Deep neural networks (DNNs) have proven their capabilities in the past years and play a significant role in environment perception for the challenging application of automated driving. They are employed for tasks such as detection, semantic segmentation,
Manuel Schwonberg +6 more
semanticscholar +1 more source
A Survey on Automated Driving System Testing: Landscapes and Trends [PDF]
ACM Transactions on Software Engineering and Methodology, 2022 Automated Driving Systems (ADS) have made great achievements in recent years thanks to the efforts from both academia and industry. A typical ADS is composed of multiple modules, including sensing, perception, planning, and control, which brings together
Shuncheng Tang +10 more
semanticscholar +1 more source
e & i Elektrotechnik und Informationstechnik, 2018 Peer ...
Daniel Watzenig, Wolfgang Bösch
openaire +4 more sources
Learning and Aggregating Lane Graphs for Urban Automated Driving [PDF]
Computer Vision and Pattern Recognition, 2023 Lane graph estimation is an essential and highly challenging task in automated driving and HD map learning. Existing methods using either onboard or aerial imagery struggle with complex lane topologies, out-oj-distribution scenar-ios, or significant ...
M. Buchner +4 more
semanticscholar +1 more source
Optimization of On-Demand Shared Autonomous Vehicle Deployments Utilizing Reinforcement Learning
Sensors, 2022 Ride-hailed shared autonomous vehicles (SAV) have emerged recently as an economically feasible way of introducing autonomous driving technologies while serving the mobility needs of under-served communities.
Karina Meneses-Cime +2 more
doaj +1 more source