Application of Multivariate State Estimation Technique for Early Detection of Potential Threats while Driving a Truck

Existing telematic monitoring systems for the state of functioning parameters and characteristics of cars and other mobile equipment make it possible to obtain a large amount of digital data on the state of objects of observation in real time. At the same time, it is possible to evaluate the features and current characteristics of their control parameters by the driver or operator. The paper proposes a fundamental possibility of obtaining predictive information about the features of changes in the characteristics of driving a vehicle by a driver based on the analysis of information received from telematic control of transport information, a block diagram of an information-mathematical system and the principles of mathematical processing of incoming information are proposed. The paper presents some results of the analysis of the time series of the selected vehicle monitoring parameters, which allow applying the Multivariate State Estimation Technique (MSET) method to their assessment in order to obtain the possibility of early detection of a potential emergency situation in driving a car (falling asleep, driver fatigue, stressful situations, inappropriate behavior). The results of the study can become prerequisites for a larger-scale application of MSET methods in monitoring the operation of mobile equipment and assessing the characteristics of its control.