Modeling demand for passenger transfers in the bounds of public transport network

Abstract

The passenger transfers optimization is one of the main directions to enhance the quality of public transport services. Modelling a demand for services of transfer nodes is quite a complex issue due to the stochastic nature of the transport process and the random nature of demand for trips of urban residents. However, this procedure is an essential stage for any problem related to optimization in transfer nodes, such as timetables scheduling for public transport lines, designing the public transport network or estimating the parameters of a given transfer node. The proposed model is based on the developed approach to perform the routing assignment stage in the classical four-stage urban planning procedure. Demand for trips is generated for each stop of a public transport system on the grounds of the stochastic variable of the time interval between passengers arrival to the respective stop. After defining of the destination stop, the route for the passenger’s trip is determined with the use of Dijkstra’s algorithm within the frame of a public transport network which is presented as a graph model with stops for vertices and route segments for edges. Transfer nodes are defined in the model as such graph vertices which are common for at least two lines of the public transport system. The author presents a class library implemented with the use of the Python programming language. On the basis of this library, the model for simulations of demand for transfers within the given public transport system was developed. The proposed approach to the demand modeling and the developed software were used for simulations of demand for transfers within the bounds of the public transport system of Bochnia (Poland). The brief results of these simulations are presented in the paper.

Fuzzy-Logic Approach to Estimate the Passengers' Preference when Choosing a Bus Line within the Public Transport System

“…The results of the assessment of the travelers' preference are used for modelling the demand for transport services [10][11], but also for optimization of transport processes [12][13], as well as for designing and simulation of the transport system [14][15][16].…”