most citedSystematic Analysis of the Sensor Coverage of Automated Vehicles Using Phenomenological Sensor Models

21 citations · 21 across the 5 of their papers we have counts for

collaborators

5 papers

cs.RO202021 cited

Systematic Analysis of the Sensor Coverage of Automated Vehicles Using Phenomenological Sensor Models

Thomas Ponn, Fabian Müller, Frank Diermeyer

The objective of this paper is to propose a systematic analysis of the sensor coverage of automated vehicles. Due to an unlimited number of possible traffic situations, a selection…

cs.RO2020

Identification of Challenging Highway-Scenarios for the Safety Validation of Automated Vehicles Based on Real Driving Data

Thomas Ponn, Matthias Breitfuß, Xiao Yu +1

For a successful market launch of automated vehicles (AVs), proof of their safety is essential. Due to the open parameter space, an infinite number of traffic situations can occur,…

cs.RO2020

Automatic Generation of Road Geometries to Create Challenging Scenarios for Automated Vehicles Based on the Sensor Setup

Thomas Ponn, Thomas Lanz, Frank Diermeyer

For the offline safety assessment of automated vehicles, the most challenging and critical scenarios must be identified efficiently. Therefore, we present a new approach to define…

cs.RO2020

Steer with Me: A Predictive, Potential Field-Based Control Approach for Semi-Autonomous, Teleoperated Road Vehicles

Andreas Schimpe, Frank Diermeyer

Autonomous driving is among the most promising of upcoming traffic safety technologies. Prototypes of autonomous vehicles are already being tested on public streets today. However,…

eess.SY2020

Online Verification Concept for Autonomous Vehicles -- Illustrative Study for a Trajectory Planning Module

Tim Stahl, Matthis Eicher, Johannes Betz +1

Regulatory approval and safety guarantees for autonomous vehicles facing frequent functional updates and complex software stacks, including artificial intelligence, are a challengi…