Specification-based autonomous driving system testing
Autonomous vehicle (AV) systems must be comprehensively tested and evaluated before they can be deployed. High-fidelity simulators such as CARLA or LGSVL allow this to be done safely in very realistic and highly customizable environments. Existing testing approaches, however, fail to test simulated...
Saved in:
Main Authors: | ZHOU, Yuan, SUN, Yang, TANG, Yun, CHEN, Yuqi, SUN, Jun, POSKITT, Christopher M., LIU, Yang, YANG, Zijiang |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2023
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/sis_research/7772 https://ink.library.smu.edu.sg/context/sis_research/article/8775/viewcontent/avunit_tse23.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
Similar Items
-
ACAV: A framework for automatic causality analysis in autonomous vehicle accident recordings
by: SUN, Huijia, et al.
Published: (2024) -
LawBreaker: An approach for specifying traffic laws and fuzzing autonomous vehicles
by: SUN, Yang, et al.
Published: (2022) -
BehAVExplor: Behavior diversity guided testing for autonomous driving systems
by: CHENG, Mingfei, et al.
Published: (2023) -
sFuzz2.0: Storage-access pattern guided smart contract fuzzing
by: WANG, Haoyu, et al.
Published: (2024) -
ObjSim: Efficient testing of cyber-physical systems
by: SUN, Jun, et al.
Published: (2020)