Density-based clustering methodology for estimating fuel consumption of intracity bus by using DTG data

Oh Hoon Kwon, Yongjin Park, Shin Hyoung Park

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This study suggests the methodology of estimating the standard bus fuel consumption based on large scale data. The purpose of the estimation is to encourage private transport companies to decrease the fuel costs of their intracity buses. To calculate the standard fuel consumption, we used the digital tachograph data of all intracity buses, and applied the density-based clustering analysis method to systematically eliminate many outliers which might be caused by system errors. With the suggested methodology, we calculated the accurate driving distance of each bus route, analyzed it with the bus fueling data, and estimated the monthly standard fuel consumption of each bus route. Through this study, it is expected to significantly improve the accuracy of the standard fuel consumption of intracity buses by removing the errors in the data.

Original languageEnglish
Title of host publicationAdvanced Multimedia and Ubiquitous Engineering - MUE/FutureTech 2018
EditorsJames J. Park, Kim-Kwang Raymond Choo, Gangman Yi, Vincenzo Loia
PublisherSpringer Verlag
Pages879-885
Number of pages7
ISBN (Print)9789811313271
DOIs
StatePublished - 2019
Event13th International Conference on Future Information Technology, FutureTech 2018 - Salerno, Italy
Duration: 23 Apr 201825 Apr 2018

Publication series

NameLecture Notes in Electrical Engineering
Volume518
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

Conference13th International Conference on Future Information Technology, FutureTech 2018
Country/TerritoryItaly
CitySalerno
Period23/04/1825/04/18

Keywords

  • Density-based clustering analysis
  • Digital tachograph data
  • Fuel consumption
  • Intracity bus
  • Outlier detection

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