Page 176 - AI for Good-Innovate for Impact Final Report 2024

AI for Good-Innovate for Impact

Use case – 40: Traffic accidents stop in the virtual world - Use virtual

simulation synthesis data to improve intelligent driving AI algorithm
and reduce the accident rate in traffic scenarios

Country: China

Organization: GEELY

Contact person: Ms. REN Xian, renxian@ geely .com

40�1� Use case summary table

Domain Transportation
The Prob- • The level of autonomous driving at this juncture does not yet align with
lem to be the completion objective of Level 4 unmanned operation, primarily
addressed attributed to the imperative of algorithmic enhancement, and a concomi-
tant deficiency of adequate algorithmic data
• Autonomous driving deployments necessitate an abundance of
real-world data to facilitate training and testing processes, but the
procurement and annotation of this data is inevitably expensive and labor
intensive.
• The acquired data may exhibit biases, and fail to encompass every
conceivable driving scenario.
• Autonomous driving systems are bound by the requirement to withstand
testing under diverse and complex circumstances, such as harsh weather
situations, congested traffic conditions, and ongoing road construction
projects. Nevertheless, these specific conditions may not be consistently
accessible for real-world testing.
• In the dimension of validation and testing, the restrictions of closed test-
ing arenas include a monolithic environmental context, an inability to
replicate varying complexities encountered on real-world roads, a defi-
ciency in affirming performance on actual roadways, and an exorbitantly
high cost associated with utilising testing equipment and spaces.
Key aspects of • Utilizes virtually simulated synthetic data to amplify the perceptual
the solution capabilities of the autonomous driving system, and also to augment the
efficiency of testing and validation processes.
• This avant-garde approach plays a pivotal role in elevating the system's
performance, safety, and adaptability, while concurrently accelerating
the progression of system development and testing. This consequently
results in a substantial reduction in costs and risks.
• AI generated virtual data generation is helpful to realize the purpose of
energy saving and emission reduction, and protect the green earth.

Technology AI-based Network Analysis, Scenario Analysis, energy saving, emission
keywords reduction, Simulated security, Reduce labor costs, protect the green earth,
life saving.
Data availabil- Will be released soon.
ity

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