A Meta-Modeling Approach for Autonomous Driving Scenario Based on STTD
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National Natural Science Foundation of China (61972153); National Key R&D Program of China (2018YFE 0101000); Key Projects of the Ministry of Science and Technology (2020AAA0107800)

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    Abstract:

    In the current autonomous driving scenario modeling and simulation field, autonomous driving modeling driven by Spatio-Temporal Trajectory Data (STTD) is a key problem, which is significant to improve the safety of the system. In recent years, great progress has been achieved in the modeling and application of STTD, and the application of this data in specific fields has attracted wide attention. However, because STTD has diversity and complexity as well as massive, heterogeneous, dynamic characteristics, the research in the safety-critical field modeling still faces challenges, including unified metadata of spatio-temporal trajectories, meta-modeling methods based on STTD, data processing based on the data analysis of spatio-temporal trajectories, and data quality evaluation. In view of the modeling requirements in the field of autonomous driving, a meta-modeling approach is proposed to construct spatio-temporal trajectory metadata based on Meta Object Facility (MOF) meta-modeling system. According to the characteristics of spatio-temporal trajectory data and autonomous driving domain knowledge, a meta-model of spatio-temporal trajectory data is constructed. Then, we study the modeling approach of autonomous driving safety-critical scenarios based on the spatio-temporal trajectory data meta-modeling technology system, use the modeling language ADSML for automatic instantiation of safety-critical scenarios, and construct a library of safety-critical scenarios, aiming to provide a feasible approach for the modeling of such safety-critical scenarios. Combined with the scenarios of lane changing and overtaking, the effectiveness of the meta-modeling method for autonomous driving safety scenarios driven by spatio-temporal trajectory data is demonstrated, which lays a solid foundation for the construction, simulation, and analysis of the model.

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Menghan Zhang, Dehui Du, Mingzhuo Zhang, Lei Zhang, Yao Wang, Wentao Zhou. A Meta-Modeling Approach for Autonomous Driving Scenario Based on STTD. International Journal of Software and Informatics, 2021,11(3):315~333

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  • Received:
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  • Online: September 26,2021
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