This paper presents a modular driver behavioural model developed within the BERTHA project, focusing on the motor control, simulating the interaction of drivers with the steering wheel, throttle, and brake. The core novelty lies in the estimation and control error correction mechanisms for speed and direction control using predictive models of driver intention. Thirty participants were recorded while driving in a CARLA-based simulator. The motor parameters of each driver were identified using an unscented transform approach. Bayesian ANOVA analyses were conducted on the identified parameters to understand the effect of age and gender groups. Results show both robust identification and interpretable group trends, demonstrating the model’s potential for personalized autonomous driving systems.
A Bayesian network framework is proposed for modelling unit-bounded continuous variables using conditional beta-distributed nodes within a fully Bayesian inference setting. The model captures conditional dependencies and propagates uncertainty through the network, with inference performed via Markov Chain Monte Carlo methods implemented in WinBUGS. The framework is applied to an experimental study of emotional and facial responses, focusing on rage intensity and facial gestures. Results show that brow lowering is strongly associated with rage intensity and is more frequent in men, whereas upper lid raising decreases under provocation independently of rage or sex. The model also predicts rage severity from informative facial gestures.
Purpose: The subject of this work is the study of the use of passive exoskeletons in industrial enterprises. The topic of the work is focused on the analysis of the role of passive exoskeletons as a transitional stage to full robotization of production processes. The purpose of the study is to assess the impact of the introduction of passive exoskeletons on labor productivity, worker safety and economic efficiency of enterprises. Methods: The research methodology includes the collection and analysis of technical data from public sources, as well as directly from internal reports of organizations, on productivity and safety at Russian and foreign enterprises where passive exoskeletons are already used. Results: Foreign experience shows that the use of exoskeletons can reduce the risk of musculoskeletal diseases by 45–58%, reduce the cost of disability compensation by 31-53% and increase labor productivity up to 153% for certain tasks. In Russia, the process of introducing exoskeletons is at an early stage, but there are already successful examples of their use at enterprises that have shown a 13% reduction in task completion time. An expert assessment of the effectiveness of the introduction of exoskeletons confirmed their high social and economic significance. Practical significance: The introduction of exoskeletons in industrial enterprises helps to reduce injuries, improve working conditions and increase productivity, which is especially important in the context of personnel shortages. The use of exoskeletons allows to reduce costs for disability compensation and increase the prestige of the company among potential employees. The article offers recommendations for Russian enterprises on the introduction of exoskeletons, which can contribute to the implementation of tasks set within the framework of national projects and increase the competitiveness of the domestic industry. The introduction of exoskeletons can be an important step towards full automation and robotization of processes. The conclusions emphasize that passive exoskeletons are an effective tool for increasing productivity and labor safety.
