Retraction Notice: Sora for Scenarios Engineering of Intelligent Vehicles: Vx0026;V, Cx0026;C, and Beyonds

The advent of Scenarios Engineering (SE) paves the way to a new era of intelligent vehicles (IVs), driven by Artificial Intelligence (AI)-enabled strategies. It aims at shaping the IVs to be a form that is more relevant to the underlying scenario, thereby accomplishing validation, verification (V&V), and calibration, certification (C&C) of each vehicle. However, such improved capabilities relies on the accumulation and analysis of an unprecedented volume of scenarios. Recently, Sora and other video generation models have opened up new horizons for Imaginative Intelligence. As an extension of TIV-DHW (Distributed/Decentralized Hybrid Workshop) on SE, this letter discusses the potential of Sora to change the scenario generation process by reducing physical shooting, increasing extreme scenario generation, thereby enabling more comprehensive training and testing of IVs. This letter also analyzes the limitations of Sora in accurately model physics and understand cause and effect, which may affect its effectiveness in SE applications. Last, through a comprehensive outlook, this letter aims to provide a potential direction for the development of Sora-like AI technology, thereby promoting the safety, efficiency, reliability, and sustainability of IVs.

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Publication Details

Journal
IEEE Transactions on Intelligent Vehicles
Published
2024-11-20
DOI
https://doi.org/10.1109/tiv.2024.3502594
Citations
1
Primary Topic
Simulation Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.49
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Retraction Notice: Sora for Scenarios Engineering of Intelligent Vehicles: Vx0026;V, Cx0026;C, and Beyonds

Yonglin Tian, Qinghua Ni, Xuan Li, Yutong Wang et al.
1 citations
IEEE Transactions on Intelligent Vehicles
Simulation Techniques and Applications
0.49
article

Retraction Notice: Sora for Scenarios Engineering of Intelligent Vehicles: Vx0026;V, Cx0026;C, and Beyonds

Yonglin Tian, Qinghua Ni, Xuan Li, Yutong Wang, Lingxi Li, Lili Fan, Fei‐Yue Wang, Qinghai Miao
article en
1 citations

Abstract

The advent of Scenarios Engineering (SE) paves the way to a new era of intelligent vehicles (IVs), driven by Artificial Intelligence (AI)-enabled strategies. It aims at shaping the IVs to be a form that is more relevant to the underlying scenario, thereby accomplishing validation, verification (V&V), and calibration, certification (C&C) of each vehicle. However, such improved capabilities relies on the accumulation and analysis of an unprecedented volume of scenarios. Recently, Sora and other video generation models have opened up new horizons for Imaginative Intelligence. As an extension of TIV-DHW (Distributed/Decentralized Hybrid Workshop) on SE, this letter discusses the potential of Sora to change the scenario generation process by reducing physical shooting, increasing extreme scenario generation, thereby enabling more comprehensive training and testing of IVs. This letter also analyzes the limitations of Sora in accurately model physics and understand cause and effect, which may affect its effectiveness in SE applications. Last, through a comprehensive outlook, this letter aims to provide a potential direction for the development of Sora-like AI technology, thereby promoting the safety, efficiency, reliability, and sustainability of IVs.

IEEE Transactions on Intelligent Vehicles
Macau University of Science and Technology (MO), Beijing Institute of Technology (CN), Chinese Academy of Sciences (CN), Beijing Academy of Artificial Intelligence (CN), Institute of Automation (CN), Peng Cheng Laboratory (CN), University of Chinese Academy of Sciences (CN), Indiana University – Purdue University Indianapolis (US)
Openalex Percentile: Top 29%
Simulation Techniques and Applications
0.49
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