Automated vehicle control requirements processing using machine learning models

A system for automated vehicle control requirements processing, the system comprising:

• memory configured to store multiple data artifacts associated with vehicle control system requirements, at least one machine learning model, and computer-executable instructions, wherein the multiple data artifacts include at least two different modalities;
• and
• at least one processor configured to execute the computer-executable instructions to:
• preprocess the multiple data artifacts including reducing redundancy among the multiple data artifacts and resolving conflicts between the multiple data artifacts;
• determine, for each of the multiple data artifacts, a modality of the data artifact;
• create an embedding for each of the multiple data artifacts according to the modality of the data artifact;
• generate, as an output of the at least one machine learning model, at least one of a message sequence chart, a finite state machine and a Gherkin use case, according to the embeddings of the multiple data artifacts;
• build a unified requirements model according to the at least one of the message sequence chart, the finite state machine and the Gherkin use case, wherein the unified requirements model defines control requirements for at least one vehicle control feature;
• and
• display the unified requirements model on a user interface of a display device.