Оценка интенсивности транспортных потоков с использованием геоинформационных систем

Abstract

The main discussion is about methods for assessing the intensity of traffic flows using geoinformation technologies. The intensity of traffic flows is one of the key indicators that determine the emission from transport in urban areas. In Russia, the growth in the volume and share of motor transport in pollution is increasing under the influence of an increase in the number of cars. This is most obvious examples of it are regions of the Central Federal District, but in the regional centers, under the influence of the improvement in the structure of the vehicle park, the growth of pollution is much slower, and in Moscow it has practically stabilized. At the local level, the determining factor of road traffic pollution is the change in the building density and the transport-planning structure. The collection and calculation of indicators that give an idea of the spatial differentiation of emissions from road transport is a very time-consuming stage of the study. The most common method of obtaining information on the transport and environmental situation in the city is directly field data collection. However, this method is quite time consuming for research. In conditions when the transport infrastructure is developing rapidly, the speed of field observations does not allow promptly updating information on changes in the traffic load of the road network and, as a result, assessing the current ecological situation in the territory. As an alternative to the traditional collection of information, modern sources of geoinformation data can be used. The services, originally developed to provide operational monitoring of the traffic situation and the construction of optimal routes, can also serve as a source of data for models for assessing the intensity of traffic load in environmental studies. The proposed technique has been tested at the level of districts and administrative districts of Moscow. The results obtained are compared with control field observations. The relatively low measurement error when using data from information systems is compensated by the possibility of more efficiently obtaining information about the traffic load on the sections of the road network.