Conception of an Automatic Scenario Generator for Seamless Testing of Intelligent Autonomous Functions

The Introduction of new digital technologies is driving social and economic change, especially in the mobile sector, made possible by autonomous driving technologies in cyber-physical systems (CPS). Extensive testing over billions of kilometers is required to realize autonomous driving systems. In this paper, an automatic scenario generator is designed that helps in scenario-based testing of autonomous driving functions in cyber-physical environments. It employs a closed-loop generation approach that encompasses scenario setup, generation, evaluation, and optimization. Based on its conceptualization realizes the automatic generation and simulation of static scenario building, filtering, fusion of elevation data and experimental reference scenarios.

Authors

Institutions

Publication Details

Published
2024-10-16
DOI
https://doi.org/10.1109/isse63315.2024.10741133
Citations
1
Primary Topic
AI-based Problem Solving and Planning
Type
article
Field-Weighted Citation Impact
0.35

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Conception of an Automatic Scenario Generator for Seamless Testing of Intelligent Autonomous Functions

Taihao Li, Xiaobo Liu-Henke, Sven Jacobitz, Marian Göllner et al.
1 citations
AI-based Problem Solving and Planning
0.35
article

Conception of an Automatic Scenario Generator for Seamless Testing of Intelligent Autonomous Functions

Taihao Li, Xiaobo Liu-Henke, Sven Jacobitz, Marian Göllner, Björn Carstens
article en
1 citations

Abstract

The Introduction of new digital technologies is driving social and economic change, especially in the mobile sector, made possible by autonomous driving technologies in cyber-physical systems (CPS). Extensive testing over billions of kilometers is required to realize autonomous driving systems. In this paper, an automatic scenario generator is designed that helps in scenario-based testing of autonomous driving functions in cyber-physical environments. It employs a closed-loop generation approach that encompasses scenario setup, generation, evaluation, and optimization. Based on its conceptualization realizes the automatic generation and simulation of static scenario building, filtering, fusion of elevation data and experimental reference scenarios.

Ostfalia University of Applied Sciences (DE)
Volkswagen Foundation
Climate action
Openalex Percentile: Top 32%
AI-based Problem Solving and Planning
0.35
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Conception of an Automatic Scenario Generator for Seamless Testing of Intelligent Autonomous Functions — Taihao Li, Xiaobo Liu-Henke, et al. · (2024) | TGRS Research Map | TGRS