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1707.04792
Cited By
From the Lab to the Street: Solving the Challenge of Accelerating Automated Vehicle Testing
15 July 2017
Ding Zhao
H. Peng
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Papers citing
"From the Lab to the Street: Solving the Challenge of Accelerating Automated Vehicle Testing"
7 / 7 papers shown
EDGAR: An Autonomous Driving Research Platform -- From Feature Development to Real-World Application
Phillip Karle
Tobias Betz
Marcin Bosk
F. Fent
Nils Gehrke
...
K. Bengler
Georg Carle
Frank Diermeyer
Jorg Ott
Markus Lienkamp
264
44
0
27 Sep 2023
Continuous Risk Measures for Driving Support
Julian Eggert
Tim Puphal
107
5
0
14 Mar 2023
Exiting the Simulation: The Road to Robust and Resilient Autonomous Vehicles at Scale
Richard Chakra
180
2
0
19 Oct 2022
Certifiable Deep Importance Sampling for Rare-Event Simulation of Black-Box Systems
Mansur Arief
Yuanlu Bai
Wenhao Ding
Shengyi He
Zhiyuan Huang
Henry Lam
Ding Zhao
205
15
0
03 Nov 2021
Pass-Fail Criteria for Scenario-Based Testing of Automated Driving Systems
R. Myers
Z. Saigol
70
7
0
19 May 2020
Unsupervised and Supervised Learning with the Random Forest Algorithm for Traffic Scenario Clustering and Classification
Friedrich Kruber
Jonas Wurst
Eduardo Sánchez Morales
S. Chakraborty
M. Botsch
110
36
0
05 Apr 2020
An Unsupervised Random Forest Clustering Technique for Automatic Traffic Scenario Categorization
International Conference on Intelligent Transportation Systems (ITSC), 2018
Friedrich Kruber
Jonas Wurst
M. Botsch
206
59
0
05 Apr 2020
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