Abstract
The development of public transport in cities is an effective way to reduce “congestion” in the road network and, as a result, increase the speed of passenger transportation. Improving the qua¬lity of urban bus services helps attract more passengers. Bus intervals are calculated once for each route line individually, based on the average congestion of passengers at the stops. In turn, the sudden accumulation of a large number of passengers at bus stops causes that not all passengers can move in a timely manner, which causes concern for passengers. This is one of the factors that redu¬ces the quality of passenger transport services. The aim of the study is to develop a model for predicting the congestion of passengers at bus stops to optimize traffic management of urban public transport. Materials and methods. This article presents a neural network model for predicting passenger congestion at bus stops. It takes into account the spatio-temporal characteristics of bus traffic. Results. The developed model for predicting passenger congestion at bus stops was tested on real data from bus route 3 (Dushanbe, Tajikistan). The model made it possible to predict passenger traffic (the number of passengers at bus stops) with an accuracy of 72% to 74.5% of the actual number of passengers at bus stops. Conclusion. The proposed method, in contrast to other methods, allows you to automatically adapt the forecasting model to the changing conditions of the route line. This method is universal and can be used for other route lines (bus stops). It does not require much time to reconfigure.
Highlights
In connection with an increase in the level of motorization and an increase in the mobility of the population against the background of insufficient development of the road network of cities, the problem of optimizing passenger traffic is very acute, aimed at reducing the time or money associated with the formation of an unforeseen accumulation of passengers at stopping stations at different periods of time. , which often becomes a causal decrease in the speed of movement
Its distinctive feature is that it takes into account the spatial and temporal characteristics of passenger transport
It was tested on real data from bus route 3 (Dushanbe, Tajikistan)
Summary
Urban passenger transport plays a significant role in the economy of any country, region or city, since it is the route transport that is the main way of moving passengers, where there is a high demand for passenger traffic.Passenger traffic is the movement of passengers ordered by the transport network, quantitatively expressed in the volume of passengers transported by any type of public (ground, underground, air, etc.)or individual transport per unit of time (hour, day, month or year).In connection with an increase in the level of motorization and an increase in the mobility of the population against the background of insufficient development of the road network of cities, the problem of optimizing passenger traffic is very acute, aimed at reducing the time or money associated with the formation of an unforeseen accumulation of passengers at stopping stations at different periods of time. , which often becomes a causal decrease in the speed of movement. Urban passenger transport plays a significant role in the economy of any country, region or city, since it is the route transport that is the main way of moving passengers, where there is a high demand for passenger traffic. A sharp decrease in traffic speeds, hours of traffic jams, obstruction of pedestrian traffic, environmental pollution, and traffic noise, an increase in the number of road accidents are the main negative consequences of motorization. Urban passenger traffic is studied on the basis of passenger traffic, which, as a rule, is highly irregular in seasons, days of the week, hours of the day and directions.
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