Mind the Gap! A Study on the Transferability of Virtual vs
Physical-world Testing of Autonomous Driving Systems

Mind the Gap! A Study on the Transferability of Virtual vs Physical-world Testing of Autonomous Driving Systems

21 December 2021

Paolo Tonella

Papers citing "Mind the Gap! A Study on the Transferability of Virtual vs Physical-world Testing of Autonomous Driving Systems"

13 / 13 papers shown

Title
On the Need for a Statistical Foundation in Scenario-Based Testing of Autonomous Vehicles Xingyu Zhao Robab Aghazadeh-Chakherlou Chih-Hong Cheng Peter Popov L. Strigini 24 0 0 04 May 2025
Behavioral Cloning Models Reality Check for Autonomous Driving M. Yildirim Barkin Dagda Vinal Asodia Saber Fallah OffRL 19 1 0 11 Sep 2024
Predicting Safety Misbehaviours in Autonomous Driving Systems using Uncertainty Quantification Ruben Grewal Paolo Tonella Andrea Stocco 40 10 0 29 Apr 2024
Realistic pedestrian behaviour in the CARLA simulator using VR and mocap Sergio Martín Serrano David Fernández Llorca Iván García Daza Miguel Ángel Sotelo 19 5 0 08 Sep 2023
Testing of Deep Reinforcement Learning Agents with Surrogate Models Matteo Biagiola Paolo Tonella 23 19 0 22 May 2023
Digital twin in virtual reality for human-vehicle interactions in the context of autonomous driving Sergio Martín Serrano R. Izquierdo Iván García Daza Miguel Ángel Sotelo David Fernández Llorca 30 6 0 20 Mar 2023
Generative AI-empowered Simulation for Autonomous Driving in Vehicular Mixed Reality Metaverses Minrui Xu Dusit Niyato Junlong Chen Hongliang Zhang Jiawen Kang Zehui Xiong Shiwen Mao Zhu Han 25 73 0 16 Feb 2023
AmbieGen: A Search-based Framework for Autonomous Systems Testing D. Humeniuk Foutse Khomh G. Antoniol 22 13 0 01 Jan 2023
TUM autonomous motorsport: An autonomous racing software for the Indy Autonomous Challenge Johannes Betz Tobias Betz F. Fent Maximilian Geisslinger Alexander Heilmeier ... Florian Sauerbeck Tim Stahl Rainer Trauth Frederik Werner A. Wischnewski 23 60 0 31 May 2022
Ergo, SMIRK is Safe: A Safety Case for a Machine Learning Component in a Pedestrian Automatic Emergency Brake System Markus Borg Jens Henriksson Kasper Socha Olof Lennartsson Elias Sonnsjo Lonegren T. Bui Piotr Tomaszewski S. Sathyamoorthy Sebastian Brink M. H. Moghadam 22 23 0 16 Apr 2022
SilGAN: Generating driving maneuvers for scenario-based software-in-the-loop testing Dhasarathy Parthasarathy Anton Johansson 11 10 0 05 Jul 2021
Deep Reinforcement Learning for Autonomous Driving: A Survey B. R. Kiran Ibrahim Sobh V. Talpaert Patrick Mannion A. A. Sallab S. Yogamani P. Pérez 146 1,628 0 02 Feb 2020
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 247 9,134 0 06 Jun 2015