Assessing Bus way Operation for City Transportation System using Simulation Approach

Abstract

Public bus transportation service has a significant benefit in society's daily life by facilitating a more natural movement way from place to place. To provide a punctual and a shorter travel time service, Stavanger municipality had a plan to change mixed-traffic bus routes into bus rapid transit systems in the Rogaland area. However, complicated zoning plans and cost cuts have made the BRT infrastructure project subject to several changes along the way. Due to these changes and uncertainties regarding possible decisions on a future solution for the remaining infrastructure projects, the mobility provider company becomes unreceptive to their future service. The purpose of this thesis is, therefore, to make an assessment and demonstrate the effect of different parameters on the BRT system's future operation. The effect is measured in terms of bus frequency, travel time, and the number of buses needed for various scenarios in the network. A combination of agent-based, system dynamic, and discrete event simulation model is developed using AnyLogic simulation tool. The route between Stavanger and Sandnes, with an arm to ForusNord has chosen as the model case study. In addition to the reference model, three different scenarios are built. The findings showed that the punctuality was about 70% with 31% bus bunching if the routes operate in a full BRT system. When there is a change in the system and buses have no priority in only two roundabouts, the bus punctuality degraded by 14%, and bus bunching increased by about 11%. In addition, the result showed a rise of approximately 18% and 20% in travel time for buses operating in route2 and route3 if only the first 2.18Km of the route is operated in mixed traffic. Furthermore, the findings indicated an improvement in punctuality and bus bunching with an increase in bus rate.

This thesis provides an insight into the possible effect of the changes made on parts of the BRT system in terms of the relationship between bus frequency, travel time, and bus rate. Thus, it can be used to support decision-making on planning and optimization of the bus transportation system's future operation.