arXiv subjects

Marcus Nolte

Publications and source records attributed to Marcus Nolte.

25 records · Page 2Linked to original sources

arXiv2018

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

Level 3+ automated driving implies highest safety demands for the entire vehicle automation functionality. For the part of trajectory tracking, functional redundancies among all available actuators provide an opportunity to reduce safety requirements for single actuators. Yet, the exploitation of functional redundancies must be well argued if employed in a safety concept as physical limits can be reached. In this paper, we want to examine from a trajectory tracking perspective whether such a concept can be used. For this, we present a model predictive fault-tolerant trajectory tracking approach for over-actuated vehicles featuring wheel individual all-wheel drive, brakes, and steering. Applying this approach exemplarily demonstrates for a selected reference trajectory that degradations such as missing or undesired wheel torques as well as reduced steering dynamics can be compensated. Degradations at the physical actuator limits lead to significant deviations from the reference trajectory while small constant steering angles are partially critical.

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arXiv2018

Assessment of Deep Convolutional Neural Networks for Road Surface Classification

When parameterizing vehicle control algorithms for stability or trajectory control, the road-tire friction coefficient is an essential model parameter when it comes to control performance. One major impact on the friction coefficient is the condition of the road surface. A camera-based, forward-looking classification of the road-surface helps enabling an early parametrization of vehicle control algorithms. In this paper, we train and compare two different Deep Convolutional Neural Network models, regarding their application for road friction estimation and describe the challenges for training the classifier in terms of available training data and the construction of suitable datasets.

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arXiv2018

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

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 different approaches having been published in the recent years. When considering the market introduction of SAE Level 3+ vehicles, the topic of motion planning will most likely be subject to even more detailed discussions between safety and user acceptance. This paper shall discuss parameters of the motion planning problem and requirements to an environment model. The focus is put on the representation of different types of uncertainty at the example of sensor occlusion, arguing the importance of a well-defined interface between decision making and trajectory generation.

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arXiv2018

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

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. Thus, holistic systems engineering becomes a severe challenge. Emergent properties like system safety are not solely arguable in singular viewpoints such as structural representations of software or electrical wiring (e.g. fault tolerant). This states the need to get several viewpoints on a system and describe correspondences between these views in order to enable traceability of emergent system properties. Today, the most abstract view found in architecture frameworks is a logical description of system functions which structures the system in terms of information flow and functional components. In this article we extend established system viewpoints towards a capability-based assessment of an automated vehicle and conduct an exemplary safety analysis to derive behavioral safety requirements. These requirements can afterwards be attributed to different viewpoints in an architecture frameworks and thus be integrated into a development process for automated vehicles.

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arXiv2017

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

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 complicated urban scenarios in great detail. Yet, what is often missing are general-purpose path- or trajectory planners which are not designed for a specific purpose. In this paper we look at path- and trajectory planning from an architectural point of view and show how model predictive frameworks can contribute to generalized path- and trajectory generation approaches for generating safe trajectories even in cases of system failures.

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arXiv2017

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

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 sufficient to account for the huge variety of scenarios which will be encountered by (fully) automated vehicles, approaches for designing safe systems must be extended in order to allow for an ISO~26262 compliant development process. During operation of vehicles implementing SAE Levels 3+ safe behavior must always be guaranteed, as the human driver is not or not immediately available as a fall-back. Thus, the vehicle must be aware of its current performance and remaining abilities at all times. In this paper we combine insights from two research projects for showing how a skill- and ability-based approach can provide a basis for the development phase and operation of self-aware automated road vehicles.

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arXiv2017

Towards a Functional System Architecture for Automated Vehicles

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 particular vehicle project. Yet, it has been inspired and cross-checked with a real world automated driving implementation in the Stadtpilot project at the Technische Universität Braunschweig. The architecture entails aspects like environment and self perception, planning and control, localization, map provision, Vehicle-To-X-communication, and interaction with human operators.

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