The paper suggests a methodological approach for assessing the sustainability of the urban transport system. Parameters were selected for assessing the sustainability of the transport system and significant factors affecting sustainability were determined. Parameters of the sustainability of the system when changes in the weather and road conditions affect vehicle operation were estimated on the basis of the simulation modeling. An integral indicator of sustainability was introduced to evaluate the sustainability of the transport flow management subsystem and the methodological approach to its calculation was substantiated. The results from changing the parameters of the traffic flow were demonstrated in the case of a significant amount of precipitation and the constraints put on the movement of vehicles on the road infrastructure unit due to snow-removal operations and road traffic accidents. Also, the parameters of road traffic under the reconstruction of the main street of regulated traffic into a street of uninterrupted traffic were presented.

Transportation process reliability is a competitive advantage in the market of cargo delivery services. Transportation customers are interested in shipping cargoes within agreed timeframes and ensuring their safety. These are the two main parameters of transportation process reliability, compliance with which depends on a number of factors. In particular, changes in the external environment where road transportation companies operate inevitably affect the transportation process stability. The purpose of this study is to develop an approach to road transportation reliability and risk mitigation based on the digital twin concept. The variability of business processes is usually the reason for deviations from the transportation terms agreed with the customer. These deviations can be interpreted as failures in delivering cargoes. A prerequisite for ensuring smooth cargo transportation by a road transportation company is the reduction of deviations in the performance of its business processes. The article proposes methods of computer modeling and creating a digital twin of a company reflecting the reference business processes for transportation. As a result, various deviations from the reference digital model that business processes exhibit when there are changes in the external environment can be promptly identified and corrected.

The article discusses the issues of spatial unevenness of transport demand in the city by various transport modes. It describes the creation of models using an artificial neural network to estimate the travel time and share by private and public transport in a large city that does not have off-street transport. The city transport macromodel in PTV Visum (V.18) was used as a data source, from which data were obtained on 50 basic parameters taken into account in the specialized software during the development of the transport model. In total, 50 factors act as independent variables that do not have linear relationships with each other and with the dependent variable, which significantly complicates the use of other models. These models allow assessing the influence degree of the most important factors. Further, the article shows the uneven spatial distribution of the shares of trips by private and public transport across the areas of a city. Using machine learning methods, the transport areas of Tyumen were clustered into nine classes belonging to the central sector, where the share of public transport is significantly higher than at the city border. The dependence of the trip share by cars and shuttle buses on the average travel time and distance by private and public transport for each class of transport areas has been established. The research results can be used when creating new transport areas in the city macromodel and when adjusting transport planning documents. The methods used for analyzing big data on the operation of the transport complex can be implemented in the digital twin of the city and the Intelligent Transport System.

The article considers the issue of improving the quality of public transport services by implementing the concept of creating an automated traffic management system as an element of an intelligent transport system and using reserves to increase intersection capacity. This concept of improving the quality of transport services is short-term in implementation and requires less financial resources, which is an advantage. The objective of the work is to evaluate traffic parameters for various types of traffic signal regulation. Mathematical models describing the change in delay time and speed of the vehicle in the traffic flow are presented. Results of traffic modelling for various types and parameters of traffic signal sets are provided. The social and economic (average delay time, fuel consumption) and environmental effects obtained from improving organization of traffic by optimizing the work of traffic signal sets are presented. The obtained results confirm the hypothesis on the influence of characteristics of traffic flows and transport system parameters on traffic parameters. Multifactor dependences of average delay time and traffic speed from traffic intensity, distance between regulated intersections and the value of the time shift are constructed.

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To realize the paradigm of the "Sustainable city" it is necessary well in advance to evaluate the ability of the transport system to meet the raising transport demand to decrease the city network load and reduce the influence on the environment. The index of the network element adaptability can exist as such an evaluation. This article contains general results and conclusions of the investigation, had been carried out on the section of the Tyumen city highway to reveal and predict the transport demand to evaluate the adaptability of the highway elements to meet the demand outlook.