Analysis of Approaches to Short Term Passenger Volume Prediction in Public Transport

Abstract

Public Transport systems form an integral part in development of city. The development of the city can be correlated to the proportion of its population adopting public transport as its primary mode of transport. For organizations, which provide public transport services in a city, it will be beneficial to have real-time intelligent scheduling and dispatching system. To have a functional intelligent scheduling system, it is necessary to build a passenger flow prediction system, which predicts the flow of passengers based on historical data and environmental conditions. This paper presents various approaches for transit passenger volume prediction, merits and demerits of each.