TY - JOUR
T1 - Sora for Senarios Engineering of Intelligent Vehicles
T2 - V&V, C&C, and Beyonds
AU - Li, Xuan
AU - Miao, Qinghai
AU - Li, Lingxi
AU - Ni, Qinghua
AU - Fan, Lili
AU - Wang, Yutong
AU - Tian, Yonglin
AU - Wang, Fei Yue
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2024/2/1
Y1 - 2024/2/1
N2 - 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.
AB - 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.
KW - artificial intelligence
KW - intelligent vehicles
KW - scenarios engineering
KW - Sora
KW - text-to-video model
UR - https://www.scopus.com/pages/publications/85189144264
U2 - 10.1109/TIV.2024.3379989
DO - 10.1109/TIV.2024.3379989
M3 - Article
AN - SCOPUS:85189144264
SN - 2379-8858
VL - 9
SP - 3117
EP - 3122
JO - IEEE Transactions on Intelligent Vehicles
JF - IEEE Transactions on Intelligent Vehicles
IS - 2
ER -