METHODOLOGY FOR FORMING A TRANSPORT DEMAND MODEL FOR PASSENGER MOBILITY IN SUBURBAN TRANSPORT BASED ON TRIP DISTANCE DISTRIBUTION PATTERNS

Abstract

The purpose of the study is to formalize a methodology for constructing passenger origin–destination matrices in suburban transport within the framework of the interval concept of public transport demand modeling, taking into account statistical patterns in trip distance distribution. Scientific novelty lies in the development of an approach to forming passenger origin–destination matrices that involves the use of probabilistic intervals of travel distance, calculation of the share of passengers within each interval, and the formation of a system of constraints for allocating correspondences between transport zones based on the empirical distribution of trip distances. Research results include the development of an algorithm for generating passenger origin–destination matrices that satisfy constraints on transport zone capacities and reproduce the actual distribution of travel distances. The algorithm is implemented in the MS Excel software environment using a random number generator and procedures for verifying the compliance of generated correspondence matrices with empirical frequencies of trip distance distribution. The proposed methodology ensures a reduction in the set of possible matrix states to those consistent with real spatial and temporal characteristics of transport demand. Conclusions indicate that the proposed approach improves the validity of forming passenger origin–destination matrices in suburban transport, ensures more accurate reproduction of actual mobility patterns of the population, and provides a reliable basis for forecasting transport demand and evaluating development scenarios for areas adjacent to urban territories.