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An Application-Driven Conceptualization of Corner Cases for Perception in Highly Automated Driving [article]

Florian Heidecker, Jasmin Breitenstein, Kevin Rösch, Jonas Löhdefink, Maarten Bieshaar, Christoph Stiller, Tim Fingscheidt, Bernhard Sick
2021 arXiv   pre-print
In this work, we provide an application-driven view of corner cases in highly automated driving.  ...  Systems and functions that rely on machine learning (ML) are the basis of highly automated driving.  ...  ACKNOWLEDGMENT This work results from the project KI Data Tooling (19A20001O) funded by German Federal Ministry for Economic Affairs and Energy (BMWI) and the DeCoInt 2 -project financed by the German  ... 
arXiv:2103.03678v1 fatcat:mk3tat2sarbidddxgkumwxenlm

Description of Corner Cases in Automated Driving: Goals and Challenges [article]

Daniel Bogdoll, Jasmin Breitenstein, Florian Heidecker, Maarten Bieshaar, Bernhard Sick, Tim Fingscheidt, J. Marius Zöllner
2021 arXiv   pre-print
Since many modules of automated driving systems are based on machine learning (ML), CC are an essential part of the data for their development.  ...  Scaling the distribution of automated vehicles requires handling various unexpected and possibly dangerous situations, termed corner cases (CC).  ...  Acknowledgment This work results from the project KI Data Tooling (19A20001O, 19A20001J, 19A20001M) funded by the German Federal Ministry for Economic Affairs and Energy (BMWI).  ... 
arXiv:2109.09607v3 fatcat:qrcclwval5e4joxao3sntou7yq

Does Redundancy in AI Perception Systems Help to Test for Super-Human Automated Driving Performance? [article]

Hanno Gottschalk, Matthias Rottmann, Maida Saltagic
2021 arXiv   pre-print
As it is known, this strategy is efficient especially for the case of subsystems operating independently, i.e. the occurrence of errors is independent in a statistical sense.  ...  While automated driving is often advertised with better-than-human driving performance, this work reviews that it is nearly impossible to provide direct statistical evidence on the system level that this  ...  An Application-Driven Conceptualization of Corner Cases for Perception in Highly Automated Driving. arXiv, pp. 1–8, March 2021, 2103.03678.  ... 
arXiv:2112.04758v1 fatcat:oimuirtopnb4nfuetjcinnrjwi

A Systematic Literature Review about the impact of Artificial Intelligence on Autonomous Vehicle Safety [article]

A. M. Nascimento, L. F. Vismari, C. B. S. T. Molina, P.S. Cugnasca, J.B. Camargo Jr., J.R. de Almeida Jr., R. Inam, E. Fersman, M. V. Marquezini, A. Y. Hata
2019 arXiv   pre-print
Based on an initial sample of 4870 retrieved papers, 59 studies were selected as the result of the selection criteria detailed in the paper.  ...  However, while some researchers in this field believe AI is the core element to enhance safety, others believe AI imposes new challenges to assure the safety of these new AI-based systems and applications  ...  vehicle" OR "automated car" OR "self-driven vehicle" OR "self-driving" OR "driverless")).  ... 
arXiv:1904.02697v1 fatcat:jsruqsy3kvcyvdyfhzo4ojfaqi

PEGASUS METHOD

Jens Mazzega, Daniel Lipinski, Ulrich Eberle, Helmut Schittenhelm, Walther Wachenfeld
2022 Zenodo  
In such situations, there is an enormous demand for research, when it comes to bringing highly-automated vehicles, quickly and safely on the market.  ...  The objective is to develop a procedure for the testing of automated driving functions, in order to facilitate the rapid implementation of automated driving into practice.  ...  assessment of highly automated driving function.  ... 
doi:10.5281/zenodo.6595201 fatcat:dqlkoodh6rcofjdzlss53gbm4u

Enable an Open Software Defined Mobility Ecosystem through VEC-OF [article]

Sanchu Han, Yong He, Yin Ding
2020 arXiv   pre-print
software platform for its production and service model, use efficient and collaborative ways of vehicles, roads, cloud and network to continuously improve core technologies such as autonomous driving,  ...  In this paper we present one new framework, VEC-OF (Vehicle-Edge-Cloud Open Framework), which is a new data and AI centric vehicle software framework enabling a much safer, more efficient, connected and  ...  Vehicle intelligence without edge and cloud intelligence being supported through the architecture • Too many corner cases need to be handled by perception algorithms, and furthermore the path planning  ... 
arXiv:2007.03879v1 fatcat:6qdigvdaznd7db47omnbfdnigi

Effects of Autonomous Driving on the Vehicle Concept [chapter]

Hermann Winner, Walther Wachenfeld
2016 Autonomous Driving  
Assistance systems and partial automation are only concept changing in very few cases for familiar vehicles.  ...  a design for the automation of the higher vehicle guidance levels that are indispensable for automated driving.  ... 
doi:10.1007/978-3-662-48847-8_13 fatcat:bcloonpq3jenbdwfmjwi6hb7pi

Autonomous driving – a top-down-approach

Richard Matthaei, Markus Maurer
2015 at - Automatisierungstechnik  
It is developed in a top-down approach based on the definition of the functional requirements for an autonomous vehicle and explicitly combines perception-based and localization-based approaches.  ...  AbstractThis paper presents a functional system architecture for an "autonomous vehicle" in the sense of a modular building block system.  ...  Acknowledgement: The authors like to thank all active members and alumni of the research project Stadtpilot, who all contributed by their work and countless discussions to this article.  ... 
doi:10.1515/auto-2014-1136 fatcat:qapr2cbf3ffbld5xnkleh5jziy

Effects of Automated Vehicle Models at the Mixed Traffic Situation on a Motorway Scenario

Xuan Fang, Hexuan Li, Tamás Tettamanti, Arno Eichberger, Martin Fellendorf
2022 Energies  
There is consensus in industry and academia that Highly Automated Vehicles (HAV) and Connected Automated Vehicles (CAV) will be launched into the market in the near future due to emerging autonomous driving  ...  A case study of the different penetration rates of HAV and CAV was performed on the M86 motorway.  ...  Informed Consent Statement: Not applicable. Data Availability Statement: Not applicable. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/en15062008 fatcat:p5xesk7jlbhrzpx7sitrdvbi3q

Algorithmic Decision-Making in AVs: Understanding Ethical and Technical Concerns for Smart Cities

Hazel Si Min Lim, Araz Taeihagh
2019 Sustainability  
Technical issues in the AVs' perception, decision-making and control algorithms, limitations of existing AV testing and verification methods, and cybersecurity vulnerabilities can also undermine the performance  ...  Algorithms form the basis of decision-making in AVs, allowing them to perform driving tasks autonomously, efficiently, and more safely than human drivers and offering various economic, social, and environmental  ...  Acknowledgments: Araz Taeihagh is grateful for the support provided by the Lee Kuan Yew School of Public Policy, National University of Singapore through the Start-up Research Grant.  ... 
doi:10.3390/su11205791 fatcat:6lbowurczjdlpbgepytwrvahei

D2.1 Specification of Use Cases

Panagiotis Lytrivis, Vasilis Sourlas, Visintainer Filippo, Amendola Danilo, Test Side Leaders And SCN Leaders
2019 Zenodo  
the needs of various automated driving use cases (safety critical, comfort, etc.) with different requirements, across test sites with different capabilities.  ...  These are: i) alignment with EU policy and relevant forums and initiatives, ii) significant impact on connected automation, iii) the ability to generalise on the results (applicable in other scenarios  ...  the needs of various automated driving use cases (safety critical, comfort, etc.)  ... 
doi:10.5281/zenodo.6372538 fatcat:lpxtlo6m2zealfx2t6bf3bdwdy

A Review on Scene Prediction for Automated Driving

Anne Stockem Stockem Novo, Martin Krüger, Marco Stolpe, Torsten Bertram
2022 Physics  
Towards the aim of mastering level 5, a fully automated vehicle needs to be equipped with sensors for a 360∘ surround perception of the environment.  ...  More effort should be spent in trying to understand varying model performances, identifying if the difference is in the datasets (many simple situations versus many corner cases) or actually an issue of  ...  and corner cases.  ... 
doi:10.3390/physics4010011 fatcat:4rbh64feprdnrflcf4ydyyre4a

Automotive Intelligence Embedded in Electric Connected Autonomous and Shared Vehicles Technology for Sustainable Green Mobility

Ovidiu Vermesan, Reiner John, Patrick Pype, Gerardo Daalderop, Kai Kriegel, Gerhard Mitic, Vincent Lorentz, Roy Bahr, Hans Erik Sand, Steffen Bockrath, Stefan Waldhör
2021 Frontiers in Future Transportation  
The article gives an overview of the advances in AI technologies and applications to realize intelligent functions and optimize vehicle performance, control, and decision-making for future ECAS vehicles  ...  architectures and the role of AI techniques and methods to implement the different autonomous driving and optimization functions for sustainable green mobility.  ...  The ODD poses many challenges since there is a need to define all possible overlapping conditions, use cases, restrictions, and scenarios that an AV might encounter, even the most obscure corner cases.  ... 
doi:10.3389/ffutr.2021.688482 fatcat:3yr2mvmoanadxpk6zcbgbtjiy4

The Correlation between Vehicle Vertical Dynamics and Deep Learning-Based Visual Target State Estimation: A Sensitivity Study

Yannik Weber, Stratis Kanarachos
2019 Sensors  
Undeniably, the role of cameras and Artificial Intelligence-based (AI) vision is vital in the perception of the driving environment and road safety.  ...  For the first time, this paper analyzes and discusses the influence of road anomalies and vehicle suspension on the performance of detecting and tracking driving objects.  ...  Finally, we discovered IPG CarMaker to be a suitable development tool for the application of vision systems in automated driving systems.  ... 
doi:10.3390/s19224870 pmid:31717341 pmcid:PMC6891543 fatcat:kcimwk45n5c37p5ugktbzsxndu

DeepTest: Automated Testing of Deep-Neural-Network-driven Autonomous Cars [article]

Yuchi Tian, Kexin Pei, Suman Jana, Baishakhi Ray
2018 arXiv   pre-print
Most existing testing techniques for DNN-driven vehicles are heavily dependent on the manual collection of test data under different driving conditions which become prohibitively expensive as the number  ...  In this paper, we design, implement and evaluate DeepTest, a systematic testing tool for automatically detecting erroneous behaviors of DNN-driven vehicles that can potentially lead to fatal crashes.  ...  ACKNOWLEDGEMENTS We would like to thank Yoav Hollander and the anonymous reviewers for their helpful feedback.  ... 
arXiv:1708.08559v2 fatcat:jsdj442r35d4hmj6476shvt3oi
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