Graph Modeling in Computer Assisted Automotive Development

TL;DR

This paper presents a structured graph model for vehicle development data, especially crash safety, enabling improved search, filtering, and prediction during the R&D process by integrating diverse data sources and safety protocols.

Contribution

It introduces a novel semantics for crash CAE data within a knowledge graph, enhancing data integration and analysis in vehicle safety development.

Findings

Provides a comprehensive schema for crash safety data integration.

Enables advanced search and prediction for vehicle safety data.

Connects CAE data with safety assessment protocols.

Abstract

We consider graph modeling for a knowledge graph for vehicle development, with a focus on crash safety. An organized schema that incorporates information from various structured and unstructured data sources is provided, which includes relevant concepts within the domain. In particular, we propose semantics for crash computer aided engineering (CAE) data, which enables searchability, filtering, recommendation, and prediction for crash CAE data during the development process. This graph modeling considers the CAE data in the context of the R\&D development process and vehicle safety. Consequently, we connect CAE data to the protocols that are used to assess vehicle safety performances. The R\&D process includes CAD engineering and safety attributes, with a focus on multidisciplinary problem-solving. We describe previous efforts in graph modeling in comparison to our proposal, discuss its strengths and limitations, and identify areas for future work.