Sora for Intelligent Vehicles: A Step From Constraint-Based Simulation to Artificiofactual Experiments Through Dynamic Visualization

Xumeng Wang, Xiao Xue, Ran Yan, Xingxia Wang, Yining Di, Wei Chen, Fei Yue Wang*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Scenario simulation plays an integral role in the development, application, and management of intelligent vehicles. However, planning agents and customizing scenarios for complex systems are laborious, making it challenging to implement high-performance simulations. The striking progress made by Sora, a large-scale text-to-video model, suggests a research opportunity for high-performance simulation through dynamic visualizations. This paper reports the prospective effects of Sora on the scenario simulation of intelligent vehicles. Specifically, we review the achievements of Sora, picture the perspectives of artificiofactual experiments on intelligent vehicles based on the performance of Sora-type techniques, and discuss how far are we now.

Original languageEnglish
Pages (from-to)4249-4253
Number of pages5
JournalIEEE Transactions on Intelligent Vehicles
Volume9
Issue number3
DOIs
Publication statusPublished - Mar 1 2024
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

ASJC Scopus Subject Areas

  • Automotive Engineering
  • Control and Optimization
  • Artificial Intelligence

Keywords

  • artificiofactual experiments
  • dynamic visualization
  • Intelligent vehicles
  • Sora

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