نفيسه دوستي فرد

Over the past few decades, transportation planners and policymakers have investigated passenger route choice and the factors that affect it, leading to the creation of dozens of public transportation assignment models. The main issue after identifying the parameters affecting the route choice of passengers is the lack of computational efficiency in the existing assignment models. This issue has reduced the effectiveness of the proposed models in previous studies. The purpose of this study is to investigate and improve the mathematical model of passenger route choice in previous studies, increase computational efficiency and reduce data processing time. This work was done by multi-core data processing method, using programming techniques, as well as modifying the mathematical models presented in previous studies, by examining a dynamic transit assignment model based on schedule-based shortest path algorithm and trip elimination sub-algorithm to obtain a more accurate representation of how public transportation users choose and the influencing parameters in their choice. As a final step, a comparison of the introduced model with a non-dynamic model based on the link-based shortest path algorithm has been made to eva‎luate the effect of the capacity constraint and algorithm dynamics on calculation time, and the accuracy of the output data, as well as the effect of the multi-core process in the calculation time. Based on the output data, the schedule-based shortest path algorithm’s total calculation time improved by about 20% by adding the multi-core process to the data processing procedure. In addition, despite leading to 116.4 minutes or about 13.7% more computational time than the link-based algorithm, the dynamic schedule-based algorithm seems to be more efficient in a high-demand network due to its more detailed network investigation and the capacity consideration, and the link-based algorithm is more suitable for a low-demand public transportation network. Also, the average travel time of passengers in the link-based algorithm is about 9 minutes or 22.3 percent less, and their average travel cost is about 18.2 minutes or 27.6 percent less than the average travel time of passengers in the schedule-based algorithm with capacity constraint. Keywords: Public transportation network, Assignment models, Capacity constraint, Shortest path algorithm

شبكه حمل‌ونقل همگاني , مدل تخصيص سفر , محدوديت ظرفيت

Public transportation network , Assignment models , Capacity constraint

Nafiseh Doostifard

Dr. Shahriar Afandizadeh Zargari