Nowadays, the concept of digital economy along with market competition requires constant modification of current business models and logistic services. Since branded service companies directly interact with customers, the efficiency of the vehicle maintenance strongly influences on the company's level of service. Digital Twins helps to track data of failures throughout the whole transportation and to predict failures of each particular vehicle and plan the full capacity. By the example of the KAMAZ company we analyze the efficiency of such technology for the final customer. The comparison of the predicted number of failures, obtained from Digital Twin, shows a high level of flexibility that could be achieved with such a system, showing a potential towards leasing market.

In recent years, there has been a significant increase in urban public transport. This has led to overabundant route networks; deteriorated conditions for moving route transport within cities; conflict situations at stop points occurring between vehicles of duplicating routes. Conflict situations occurring between vehicles of different routes at stop points when loading and unloading passengers prove the problem of optimizing urban route networks to be insufficiently investigated, with traffic, demand and infrastructure limitations being considered. Conflict situations at stop points are found to be dependent on route configurations and network parameters, with the number of conflict situations being inversely dependent on the number of combined intervals for route transportation through stop points and their throughout capacity. There has been developed an imitation model for moving vehicles of adjacent routes, with a model for optimizing urban route network parameters being presented. It reduces conflicts in number due redistributed vehicles of various types for routes, with the population's demand for transportation being absolutely satisfied. Models and methods can be used by transportation companies, city administrations to develop and improve urban route public transport networks.