Digital Twin Test Method for Autonomous Vehicles Based on PanoSim Beihang University

Format:

Book

Conference/Event

Author/Creator:

Jianyu, Duan, author.

Contributor:

Deng, Weiwen

Ding, Juan

Wang, Ying

Conference Name:

SAE 2023 Intelligent and Connected Vehicles Symposium (2023-09-22 : Nanchang, China)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2023

Summary:

This paper proposes an intelligent car testing and evaluation method based on digital twins, which is crucial for ensuring the proper functioning of autonomous driving systems. This method utilizes digital twin testing technology to effectively map and integrate real vehicles in real-world testing scenarios with virtual test environments. By enriching the testing and validation environment for smart cars, this approach improves testing efficiency and reduces costs. This study connects real test vehicles with simulation software testing toolchains to build a digital twin autonomous driving testing platform. This platform facilitates the validation, testing, and evaluation of functional algorithms, and case study is conducted through testing and validation of an emergency collision avoidance system. By rapidly applying digital twin testing and evaluation techniques for intelligent cars, this approach accelerates the development and deployment of autonomous vehicles

Notes:

Vendor supplied data

Publisher Number:

2023-01-7056

Access Restriction:

Restricted for use by site license