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20172023
most citedAssessment of Deep Convolutional Neural Networks for Road Surface Classification

121 citations · 419 across the 24 of their papers we have counts for

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14 papers · 1 filter

eess.SY2023★ 1 cited

On Assumptions with Respect to Occlusions in Urban Environments for Automated Vehicle Speed Decisions

Robert Graubohm, Nayel Fabian Salem, Marcus Nolte +1

Automated driving systems are subject to various kinds of uncertainty during design, development, and operation. These kinds of uncertainty lead to an inherent risk of the technolo…

eess.SY2023★ 11 cited

Risk Management Core -- Towards an Explicit Representation of Risk in Automated Driving

Nayel Fabian Salem, Thomas Kirschbaum, Marcus Nolte +4

While current automotive safety standards provide implicit guidance on how unreasonable risk can be avoided, manufacturers are required to specify risk acceptance criteria for Auto…

eess.SY2023

ODD-Centric Contextual Sensitivity Analysis Applied To A Non-Linear Vehicle Dynamics Model

Richard Schubert, Marcus Nolte, Arnaud de La Fortelle +1

Advanced driving functions, for assistance or full automation, require strong guarantees to be deployed. This means that such functions may not be available all the time, like now…

eess.SY2021★ 48 cited

A Taxonomy to Unify Fault Tolerance Regimes for Automotive Systems: Defining Fail-Operational, Fail-Degraded, and Fail-Safe

Torben Stolte, Stefan Ackermann, Robert Graubohm +4

This paper presents a taxonomy that allows defining the fault tolerance regimes fail-operational, fail-degraded, and fail-safe in the context of automotive systems. Fault tolerance…

eess.SY2020

Supporting Safe Decision Making Through Holistic System-Level Representations & Monitoring -- A Summary and Taxonomy of Self-Representation Concepts for Automated Vehicles

Marcus Nolte, Inga Jatzkowski, Susanne Ernst +1

The market introduction of automated vehicles has motivated intense research efforts into the safety of automated vehicle systems. Unlike driver assistance systems, SAE Level 3+ sy…

eess.SY2020

Sensitivity Analysis for Vehicle Dynamics Models -- An Approach to Model Quality Assessment for Automated Vehicles

Marcus Nolte, Richard Schubert, Cordula Reisch +1

Model-based approaches have become increasingly popular in the domain of automated driving. This includes runtime algorithms, such as Model Predictive Control, as well as formal an…

eess.SY2020★ 10 cited

Towards Efficient Hazard Identification in the Concept Phase of Driverless Vehicle Development

Robert Graubohm, Torben Stolte, Gerrit Bagschik +1

The complex functional structure of driverless vehicles induces a multitude of potential malfunctions. Established approaches for a systematic hazard identification generate indivi…

eess.SY2018★ 4 cited

Investigating Functional Redundancies in the Context of Vehicle Automation - A Trajectory Tracking Perspective

Torben Stolte, Tianyu Liao, Matthias Nee +2

Level 3+ automated driving implies highest safety demands for the entire vehicle automation functionality. For the part of trajectory tracking, functional redundancies among all av…

eess.SY2018

Identification of Potential Hazardous Events for an Unmanned Protective Vehicle

Gerrit Bagschik, Andreas Reschka, Torben Stolte +1

The project Automated Unmanned Protective Vehicle for Highway Hard Shoulder Road Works (aFAS) aims to develop an unmanned protective vehicle to reduce the risk of injuries due to c…

eess.SY2018

A System's Perspective Towards an Architecture Framework for Safe Automated Vehicles

Gerrit Bagschik, Marcus Nolte, Susanne Ernst +1

With an increasing degree of automation, automated vehicle systems become more complex in terms of functional components as well as interconnected hardware and software components.…

eess.SY2018★ 16 cited

Representing the Unknown - Impact of Uncertainty on the Interaction between Decision Making and Trajectory Generation

Marcus Nolte, Susanne Ernst, Jan Richelmann +1

Even though motion planning for automated vehicles has been extensively discussed for more than two decades, it is still a highly active field of research with a variety of differe…

eess.SY2017★ 56 cited

Model Predictive Control Based Trajectory Generation for Autonomous Vehicles - An Architectural Approach

Marcus Nolte, Marcel Rose, Torben Stolte +1

Research in the field of automated driving has created promising results in the last years. Some research groups have shown perception systems which are able to capture even compli…

eess.SY2017★ 24 cited

Towards a Skill- And Ability-Based Development Process for Self-Aware Automated Road Vehicles

Marcus Nolte, Gerrit Bagschik, Inga Jatzkowski +3

The development of fully automated vehicles imposes new challenges in the development process and during the operation of such vehicles. As traditional design methods are not suffi…

eess.SY2017★ 69 cited

Towards a Functional System Architecture for Automated Vehicles

Simon Ulbrich, Andreas Reschka, Jens Rieken +5

This paper presents a functional system architecture for an automated vehicle. It provides an overall, generic structure that is independent of a specific implementation of a parti…