Despite the efforts of scientists and practitioners, pedestrian safety remains one of the world's most acute problems. According to research by scientists and road safety experts, people (both drivers and pedestrians) often create road hazards. Therefore, it is essential to reduce the impact of human error. To this end, increasingly intelligent vehicles and road infrastructure are being created, along with passive safety measures for pedestrians. Furthermore, intelligent systems are being developed to alert pedestrians, monitor their attention, and analyze pedestrian flows, all of which can warn drivers of dangerous behavior and the risk of accidents. Experience shows that only comprehensive solutions can address strategic challenges, including road safety improvement. We propose an upgrade to the pedestrian push-button traffic light, making it “smarter” through dynamic traffic light phase control based on real-time road conditions. This is enabled by a pedestrian classification system we developed, which categorizes individuals based on characteristics such as age, behavior patterns, and mitigating factors. We believe that a smart traffic light system tailored to pedestrian flow patterns will enhance pedestrian safety and optimize traffic flow parameters.

This article investigates methods for optimizing traffic light control parameters with the aim of improving urban traffic efficiency. Modern approaches to ensuring the sustainability of urban transport systems are discussed. The study concludes that simulation modeling serves as a leading methodology for analyzing transportation systems and identifying optimal solutions to diverse challenges, which ultimately enhances traffic flow characteristics and increases the resilience of the transport network. An optimized simulation model of a major city intersection has been developed, an optimization experiment carried out, and optimal values for traffic light signal phases have been determined.

The article addresses issues concerning the improvement of urban transport infrastructure with the aim of enhancing its efficiency and environmental sustainability. It highlights that simulation modeling techniques have considerable potential and are currently widely employed to address challenges associated with traffic flow and road infrastructure modeling. A simulation model of a section of a large city's road network has been developed. The experiment conducted using this model revealed opportunities for reconstruction aimed at increasing capacity and reducing automobile exhaust gas emissions

Transport logistics in modern conditions includes more and more intelligent elements that improve both physical objects and optimize processes, using technologies of communication means, the Internet of things, and data analysis,. One of the processes that is implemented in the logistics chain is the loading and unloading process. The implementation of this process is especially relevant when delivering goods to shopping centers located in cities. To optimize loading and unloading processes, simulation models are used that allow not only to reduce the waiting time of trucks in the queue for unloading, but also to increase the efficiency of the entire process, as well as reduce the impact on the environment, which is extremely important in cities, and especially megacities. The article provides a practical example of using such a model, an optimization experiment was conducted and the achieved efficiency is shown.

The strategy of spatial development of the country for the period up to 2024, based on the infrastructure of a specific type of transport, provides for the connection of the territories of settlements with modern communications; phased reconstruction and modernization; personnel, technical and technological support for interaction and digital transformation of the Russian transport complex. The development of the Russian Arctic is a priority area, since it has a significant natural resource, socio-economic and transport potential, which must be maximized, taking into account all the features of this region. It is important to develop the northern territories in such a way that the transport infrastructure of the Arctic meets the requirements in the field of comfort and safety of the human environment. This can be achieved through the use of vehicles of increased environmental friendliness and energy efficiency. In the study we analyse the possibility of converting shift buses used to deliver personnel involved in the development of fields in the Arctic zone to gas motor fuel using simulation models.

One of the most significant factors in environmental degradation is the increase in motorization. Currently, road transport is the largest source of environmental pollution in urban areas. The article analyzes the environmental impact of chemical (emissions) and physical (noise) factors from road transport. It is found that these factors have a strong relationship. Considering that continuous simultaneous monitoring of air quality and noise level requires significant investments, using the ratios obtained in the article based on linear regression, you can get quite reliable data on the degree of environmental impact of one of the factors (for example, volume emissions) by monitoring another factor (for example, noise).

The digitalization and intellectualization of all processes, accompanying the transition to the fourth industrial revolution, opens up new possibilities in managing large systems. Any enterprise activity and any economy sector is associated with goods and people movement. In the increasing mobility conditions, the issues of improving the transport system reliability are of particular importance. We propose to solve these issues at all stages of the technical systems life cycle, in particular trucks, by creating a common information space that allows, on the actual information basis and the use of new analysis methods, to increase the efficiency and reliability of the transport system as a whole.