activity
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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Showing 2017Show all

5 papers · 1 filter

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…

cs.RO2017

Hazard Analysis and Risk Assessment for an Automated Unmanned Protective Vehicle

Torben Stolte, Gerrit Bagschik, Andreas Reschka +1

For future application of automated vehicles in public traffic, ensuring functional safety is essential. In this context, a hazard analysis and risk assessment is an important inpu…

cs.AI2017

Ontology based Scene Creation for the Development of Automated Vehicles

Gerrit Bagschik, Till Menzel, Markus Maurer

The introduction of automated vehicles without permanent human supervision demands a functional system description, including functional system boundaries and a comprehensive safet…

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…