This paper presents a safe reinforcement learning system for automated driving that benefits from multimodal future trajectory predictions.We propose a safety system that consists of two safety components: a rule-based and a PRINTED multimodal learning-based safety system.The rule-based module is based on common driving rules.On the other hand, the
There Wide Fireplace Insert is increasing interest in the application of machine learning (ML) technologies to safety-critical cyber-physical systems, with the promise of increased levels of autonomy due to their potential for solving complex perception and planning tasks.However, demonstrating the safety of ML is seen as one of the most challengin
This paper aims to identify potential explanatory variables of the entrepreneurial orientation and innovation capacity (EO-IC) of family enterprises (FEs) through a comparative study of family businesses in Spain and Latin America.The innovation literature reports a paradigm shift whereby the dynamic boost provided by corporate governance and produ