مقاله انگلیسی رایگان در مورد پیش‌بینی زمان توقف اتوبوس بر اساس KNN – الزویر ۲۰۱۶

Abstract

The objective of this research is to develop a dynamic model to predict bus dwell time at downstream stops. The research also intends to test the proposed model using real-world data. This model is based on k-Nearest Neighbour (KNN) algorithm using history and current data collected by GPS (Global Positon System) fixed on buses. In the research, the data of buses of No.B1 line of Changzhou in China is used. In the test with real-world data, the proposed bus dwell time prediction model performed effectively both on accuracy and calculating speed.

Introduction

In order to promote competitiveness with other modes of travel such as the passenger car, bus transit agencies need to improve the quality of service to attract more people. Providing the information about bus arrival time makes public transit more attractive [1]. Bus travel time between two points consists of two parts: bus travel time on segments between every two bus stations, and bus dwell time at bus stations. This article mainly focuses on prediction method of bus dwell time.

Bus dwell time is composed by three parts: bus door opening, passengers up and down, bus door closing [2].Bus dwell time is influenced by many factors. In the TCQSM (Transit Capacity and Quality of Service Manual), factors that affect the dwell time consist of passenger boarding and alighting volumes, fare payment method, in-vehicle circulation, and stop spacing [3]. Prediction models can be set up between dwell time and these influence factors.