Abstract
Intelligent connected vehicles have attracted great concerns from researchers in intelligent transportation filed for recent years. The safety of a scenario involving multiple intelligent vehicles and infrastructures depends on delicate design of their collaboration. A unified and efficient representation for knowledge sharing and fusion is essential for such collaboration. However, the existing logical representation of spatial knowledge seldom considers integrating the knowledge from distributed agents with different granularities of views and data models. This paper designs a novel spatial logic based on a hierarchical spatial model, and provides a knowledge fusion method based on view and grained conversion between distributed agents. The spatial logic can be used to specify and share the key spatial knowledge in vehicle infrastructure cooperation scenarios. The converted knowledge shared by other agents is beneficial for an intelligent vehicle to improve its cognition and decision-making process. The effectiveness of our approach is illustrated with the case studies in path planning and cooperative cross-traffic turning.
This work was supported by NKRDP (2020AAA0107800) and NSFC (62272165).
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Yao, S., Li, Q. (2023). A Hierarchical Spatial Logic for Knowledge Sharing and Fusion in Intelligent Connected Vehicle Cooperation. In: David, C., Sun, M. (eds) Theoretical Aspects of Software Engineering. TASE 2023. Lecture Notes in Computer Science, vol 13931. Springer, Cham. https://doi.org/10.1007/978-3-031-35257-7_11
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