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cs.RO2025

From Real-World Traffic Data to Relevant Critical Scenarios

Florian Lüttner, Nicole Neis, Daniel Stadler +5

The reliable operation of autonomous vehicles, automated driving functions, and advanced driver assistance systems across a wide range of relevant scenarios is critical for their d…

cs.RO2024

A Two-Level Stochastic Model for the Lateral Movement of Vehicles Within Their Lane Under Homogeneous Traffic Conditions

Nicole Neis, Juergen Beyerer

The lateral position of vehicles within their lane is a decisive factor for the range of vision of vehicle sensors. This, in turn, is crucial for a vehicle's ability to perceive it…

cs.RO2024

Literature Review on Maneuver-Based Scenario Description for Automated Driving Simulations

Nicole Neis, Juergen Beyerer

The increasing complexity of automated driving functions and their growing operational design domains imply more demanding requirements on their validation. Classical methods such…

cs.RO2024

A Joint Approach Towards Data-Driven Virtual Testing for Automated Driving: The AVEAS Project

Leon Eisemann, Mirjam Fehling-Kaschek, Silke Forkert +18

With growing complexity and responsibility of automated driving functions in road traffic and growing scope of their operational design domains, there is increasing demand for cove…

cs.RO2024

An Approach to Systematic Data Acquisition and Data-Driven Simulation for the Safety Testing of Automated Driving Functions

Leon Eisemann, Mirjam Fehling-Kaschek, Henrik Gommel +13

With growing complexity and criticality of automated driving functions in road traffic and their operational design domains (ODD), there is increasing demand for covering significa…