Navigation equipment of a road surface testing vehicle (car) includes a strapdown inertial navigation system (INS), a global navigations satellite system (GNSS) receiver and an odometer. In this work we analyse a low-cost INS for using in the vehicle navigation equipment. An INS/GNSS/odometer integration algorithm was developed and applied to postprocessing data collected from a typical testing survey. The computed integrated navigation solution was compared with a reference solution provided by a NovAtel navigation system. The reference navigation system consisted of a tactic-grade strapdown INS, an odometer and two high precision GNSS receivers operating in the differential mode. Numerical results presented in the paper show that the low-cost INS/GNSS/odometer integration allows to determine the vehicle position in an urban area with an accuracy of 1 m and the roll and pitch angles with an accuracy of 0.1 degrees that satisfy accuracy requirements.

We study the maximum remaining service time in M(2)∣G2∣∞ fork -join queueing systems where an incoming task forks on arrival for service into two subtasks, each of them being served in one of two infinite-sever subsystems. The following cases for the arrival rate are considered: (1) time-independent, (2) given by a function of time, (3) given by a stochastic process. As examples of service time distributions, we consider exponential, hyperexponential, Pareto, and uniform distributions. In a number of cases we find copula functions and the Blomqvist coefficient. We prove asymptotic independence of maximum remaining service times under high load conditions.

Within the cascade approach to the design of state and perturbation observers, an original method for estimating the derivatives of external perturbations that affect a controlled object is proposed. This method is based on virtual dynamic models compiled by the sequential differentiation of some derivatives of the object’s state variables. Observers are constructed as replicas of virtual models. A cascade design procedure for the observers of the derivatives of external perturbations with piecewise linear corrections is developed. In this procedure, the motions separation method in the virtual space of observation errors is implemented. The observer’s variables and also their corrections serve as estimates of the derivatives of external perturbations. They can be used to design combined feedback control and/or to perform current diagnosis of the control process.

The problems that are being talked about here are related to the scientific field of supply chain management. This article focuses on the preferred control algorithm selection for large-scale railway network logistics for the special case. In this particular case, the dispatch and destination stations belong to the various regional rails. The statistical approach is applied here to the choice of the preferred control algorithm for rail cargo logistics. The peculiarity of our approach is the application of standard score z-test modifications for timing characteristics comparison. The results obtained can be used for logistics process optimization and improvement. These findings may be applicable to large-scale railway networks and transportation networks that combine the different modes of transport.