The modeling of effective parameters on public bus passengers’ boarding time prediction

Abstract

Passengers’ boarding times at bus stops have a great importance to calculate dwell and travel time for scheduling process in public transport operations. However, there are not so much observed boarding times data in the actual bus transport systems, and it may cause some prediction problems in scheduling process of public transport operations. For this reason, accurate estimation of the boarding times will ensure correct calculation of dwell and total travel time for bus transport systems. Based on this idea, this study aims to model boarding times of each passengers by evaluating different parameters using two different (statistical and optimization analysis) methods. For this purpose, a comprehensive data collection process was conducted in total seven different cities of Turkey based upon their population. Two new models were developed for boarding time estimation by evaluating various parameters using a multiple Ordinary Least Square (OLS) regression and Artificial Bee Colony (ABC) algorithm as statistical and optimization methods, respectively. Study results showed that modeling of boarding times by considering various parameters is an effective strategy to improve the performance of bus transport systems by using developed two models.