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Interpretable Safety Validation for Autonomous Vehicles
v1v2 (latest)

Interpretable Safety Validation for Autonomous Vehicles

14 April 2020
Anthony Corso
Mykel J. Kochenderfer
ArXiv (abs)PDFHTML

Papers citing "Interpretable Safety Validation for Autonomous Vehicles"

12 / 12 papers shown
SanDRA: Safe Large-Language-Model-Based Decision Making for Automated Vehicles Using Reachability Analysis
SanDRA: Safe Large-Language-Model-Based Decision Making for Automated Vehicles Using Reachability Analysis
Yuanfei Lin
Sebastian Illing
Matthias Althoff
257
1
0
08 Oct 2025
Diffusion Models for Safety Validation of Autonomous Driving Systems
Juanran Wang
Marc R. Schlichting
Harrison Delecki
Mykel J. Kochenderfer
167
1
0
10 Jun 2025
Explainable Artificial Intelligence: A Survey of Needs, Techniques, Applications, and Future Direction
Explainable Artificial Intelligence: A Survey of Needs, Techniques, Applications, and Future Direction
Melkamu Mersha
Khang Lam
Joseph Wood
Ali AlShami
Jugal Kalita
XAIAI4TS
887
137
0
30 Aug 2024
Learning Temporal Logic Predicates from Data with Statistical Guarantees
Learning Temporal Logic Predicates from Data with Statistical GuaranteesConference on Learning for Dynamics & Control (L4DC), 2024
Emi Soroka
Rohan Sinha
Sanjay Lall
424
4
0
15 Jun 2024
RADIUM: Predicting and Repairing End-to-End Robot Failures using
  Gradient-Accelerated Sampling
RADIUM: Predicting and Repairing End-to-End Robot Failures using Gradient-Accelerated SamplingIEEE Transactions on robotics (IEEE Trans. Robot.), 2024
Charles Dawson
Anjali Parashar
Chuchu Fan
174
0
0
04 Apr 2024
Explainable AI for Safe and Trustworthy Autonomous Driving: A Systematic
  Review
Explainable AI for Safe and Trustworthy Autonomous Driving: A Systematic Review
Anton Kuznietsov
Bálint Gyevnár
Cheng Wang
Steven Peters
Stefano V. Albrecht
XAI
523
93
0
08 Feb 2024
A Bayesian approach to breaking things: efficiently predicting and
  repairing failure modes via sampling
A Bayesian approach to breaking things: efficiently predicting and repairing failure modes via samplingConference on Robot Learning (CoRL), 2023
Charles Dawson
Chuchu Fan
191
0
0
14 Sep 2023
Self-Improving Safety Performance of Reinforcement Learning Based
  Driving with Black-Box Verification Algorithms
Self-Improving Safety Performance of Reinforcement Learning Based Driving with Black-Box Verification AlgorithmsIEEE International Conference on Robotics and Automation (ICRA), 2022
Resul Dagdanov
Halil Durmus
N. K. Üre
333
6
0
29 Oct 2022
Scenario Parameter Generation Method and Scenario Representativeness
  Metric for Scenario-Based Assessment of Automated Vehicles
Scenario Parameter Generation Method and Scenario Representativeness Metric for Scenario-Based Assessment of Automated Vehicles
Erwin de Gelder
Jasper P Hof
Eric Cator
J. Paardekooper
Olaf Op den Camp
J. Ploeg
B. de Schutter
141
46
0
24 Feb 2022
Explainable Artificial Intelligence for Autonomous Driving: A
  Comprehensive Overview and Field Guide for Future Research Directions
Explainable Artificial Intelligence for Autonomous Driving: A Comprehensive Overview and Field Guide for Future Research DirectionsIEEE Access (IEEE Access), 2021
Shahin Atakishiyev
Mohammad Salameh
Hengshuai Yao
Randy Goebel
727
220
0
21 Dec 2021
The Reasonable Crowd: Towards evidence-based and interpretable models of
  driving behavior
The Reasonable Crowd: Towards evidence-based and interpretable models of driving behaviorIEEE/RJS International Conference on Intelligent RObots and Systems (IROS), 2021
Bassam Helou
Aditya Dusi
Anne-Sophie Collin
N. Mehdipour
Zhiliang Chen
Cristhian G. Lizarazo
C. Belta
Tichakorn Wongpiromsarn
R. D. Tebbens
Oscar Beijbom
255
28
0
28 Jul 2021
A Survey of Algorithms for Black-Box Safety Validation of Cyber-Physical
  Systems
A Survey of Algorithms for Black-Box Safety Validation of Cyber-Physical SystemsJournal of Artificial Intelligence Research (JAIR), 2020
Anthony Corso
Robert J. Moss
Mark Koren
Ritchie Lee
Mykel J. Kochenderfer
381
202
0
06 May 2020
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