Taxi cab service optimization using spatio-temporal implementation to hot-spot analysis with taxi trajectories: A case study in Seoul, Korea

Sung Bum Yun, Sang Hyun Yoon, Sungha Ju, Won Seob Oh, Jong Won Ma, Joon Heo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Currently there are demands for maximization of taxi services and also for saving fuel usage within massive cities. Spatial big data extracted from taxi service records and GPS can be used to suggest optimal routing options to achieve these goals. The taxi cab ride data contains 7,000 unique taxies being serviced in Seoul, South Korea. In this study one week worth of data with the size of 3.13GB were used. Also road network data provided by Ministry of Land, Infrastructure and Transport (MOLIT), which contains 19,229 nodes and 22,192 links, and census map provided by Statistics Korea were used as base-map. Lastly floating population data of Seoul city area, gathered with mobile phones, has been used as an index of demand for taxi service. By using taxi cab ride data, which contains trajectory with time and 2D coordinates, and information about whether passenger is on the taxi or not, hot spots were analyzed for 1) taxies without passengers whom are available to pick-up passengers, 2) places where people are experiencing difficulty hailing a taxi due to high demand for taxi. Combination of these two types of hot spots can provide new insight for both public and commercial sectors to maximize the efficiency of taxi service and to reduce idle fuel usage. Afterwards the floating population data is used to provide indices for taxi usage in Seoul area, providing further insights. Utilizing the time stamp records on the taxi GPS data, hourly based hot spots for both 'demand' and 'supply' for taxi cab ride can be derived, and this outcome can be practically used to guide taxi drivers to high demanding places and avoid high supplying places.

Original languageEnglish
Title of host publicationProceedings of the 5th ACM SIGSPATIAL International Workshop on Mobile Geographic Information Systems, MobiGIS 2016
EditorsChi-Yin Chow, Reza Nourjou, Shashi Shekhar, Maria Luisa Damiani
PublisherAssociation for Computing Machinery, Inc
Pages12-18
Number of pages7
ISBN (Electronic)9781450345828
DOIs
Publication statusPublished - 2016 Oct 31
Event5th ACM SIGSPATIAL International Workshop on Mobile Geographic Information Systems, MobiGIS 2016 - Burlingame, United States
Duration: 2016 Oct 31 → …

Publication series

NameProceedings of the 5th ACM SIGSPATIAL International Workshop on Mobile Geographic Information Systems, MobiGIS 2016

Other

Other5th ACM SIGSPATIAL International Workshop on Mobile Geographic Information Systems, MobiGIS 2016
CountryUnited States
CityBurlingame
Period16/10/31 → …

Fingerprint

taxis
Korea
Global positioning system
trajectory
Trajectories
Mobile phones
Statistics
floating
demand
analysis
services
road network
South Korea
ministry
GPS
census
driver
statistics
infrastructure
supply

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Computer Networks and Communications
  • Geography, Planning and Development

Cite this

Yun, S. B., Yoon, S. H., Ju, S., Oh, W. S., Ma, J. W., & Heo, J. (2016). Taxi cab service optimization using spatio-temporal implementation to hot-spot analysis with taxi trajectories: A case study in Seoul, Korea. In C-Y. Chow, R. Nourjou, S. Shekhar, & M. L. Damiani (Eds.), Proceedings of the 5th ACM SIGSPATIAL International Workshop on Mobile Geographic Information Systems, MobiGIS 2016 (pp. 12-18). (Proceedings of the 5th ACM SIGSPATIAL International Workshop on Mobile Geographic Information Systems, MobiGIS 2016). Association for Computing Machinery, Inc. https://doi.org/10.1145/3004725.3004732
Yun, Sung Bum ; Yoon, Sang Hyun ; Ju, Sungha ; Oh, Won Seob ; Ma, Jong Won ; Heo, Joon. / Taxi cab service optimization using spatio-temporal implementation to hot-spot analysis with taxi trajectories : A case study in Seoul, Korea. Proceedings of the 5th ACM SIGSPATIAL International Workshop on Mobile Geographic Information Systems, MobiGIS 2016. editor / Chi-Yin Chow ; Reza Nourjou ; Shashi Shekhar ; Maria Luisa Damiani. Association for Computing Machinery, Inc, 2016. pp. 12-18 (Proceedings of the 5th ACM SIGSPATIAL International Workshop on Mobile Geographic Information Systems, MobiGIS 2016).
@inproceedings{404a4a30ee3943efb99cdc41e3a0b263,
title = "Taxi cab service optimization using spatio-temporal implementation to hot-spot analysis with taxi trajectories: A case study in Seoul, Korea",
abstract = "Currently there are demands for maximization of taxi services and also for saving fuel usage within massive cities. Spatial big data extracted from taxi service records and GPS can be used to suggest optimal routing options to achieve these goals. The taxi cab ride data contains 7,000 unique taxies being serviced in Seoul, South Korea. In this study one week worth of data with the size of 3.13GB were used. Also road network data provided by Ministry of Land, Infrastructure and Transport (MOLIT), which contains 19,229 nodes and 22,192 links, and census map provided by Statistics Korea were used as base-map. Lastly floating population data of Seoul city area, gathered with mobile phones, has been used as an index of demand for taxi service. By using taxi cab ride data, which contains trajectory with time and 2D coordinates, and information about whether passenger is on the taxi or not, hot spots were analyzed for 1) taxies without passengers whom are available to pick-up passengers, 2) places where people are experiencing difficulty hailing a taxi due to high demand for taxi. Combination of these two types of hot spots can provide new insight for both public and commercial sectors to maximize the efficiency of taxi service and to reduce idle fuel usage. Afterwards the floating population data is used to provide indices for taxi usage in Seoul area, providing further insights. Utilizing the time stamp records on the taxi GPS data, hourly based hot spots for both 'demand' and 'supply' for taxi cab ride can be derived, and this outcome can be practically used to guide taxi drivers to high demanding places and avoid high supplying places.",
author = "Yun, {Sung Bum} and Yoon, {Sang Hyun} and Sungha Ju and Oh, {Won Seob} and Ma, {Jong Won} and Joon Heo",
year = "2016",
month = "10",
day = "31",
doi = "10.1145/3004725.3004732",
language = "English",
series = "Proceedings of the 5th ACM SIGSPATIAL International Workshop on Mobile Geographic Information Systems, MobiGIS 2016",
publisher = "Association for Computing Machinery, Inc",
pages = "12--18",
editor = "Chi-Yin Chow and Reza Nourjou and Shashi Shekhar and Damiani, {Maria Luisa}",
booktitle = "Proceedings of the 5th ACM SIGSPATIAL International Workshop on Mobile Geographic Information Systems, MobiGIS 2016",

}

Yun, SB, Yoon, SH, Ju, S, Oh, WS, Ma, JW & Heo, J 2016, Taxi cab service optimization using spatio-temporal implementation to hot-spot analysis with taxi trajectories: A case study in Seoul, Korea. in C-Y Chow, R Nourjou, S Shekhar & ML Damiani (eds), Proceedings of the 5th ACM SIGSPATIAL International Workshop on Mobile Geographic Information Systems, MobiGIS 2016. Proceedings of the 5th ACM SIGSPATIAL International Workshop on Mobile Geographic Information Systems, MobiGIS 2016, Association for Computing Machinery, Inc, pp. 12-18, 5th ACM SIGSPATIAL International Workshop on Mobile Geographic Information Systems, MobiGIS 2016, Burlingame, United States, 16/10/31. https://doi.org/10.1145/3004725.3004732

Taxi cab service optimization using spatio-temporal implementation to hot-spot analysis with taxi trajectories : A case study in Seoul, Korea. / Yun, Sung Bum; Yoon, Sang Hyun; Ju, Sungha; Oh, Won Seob; Ma, Jong Won; Heo, Joon.

Proceedings of the 5th ACM SIGSPATIAL International Workshop on Mobile Geographic Information Systems, MobiGIS 2016. ed. / Chi-Yin Chow; Reza Nourjou; Shashi Shekhar; Maria Luisa Damiani. Association for Computing Machinery, Inc, 2016. p. 12-18 (Proceedings of the 5th ACM SIGSPATIAL International Workshop on Mobile Geographic Information Systems, MobiGIS 2016).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Taxi cab service optimization using spatio-temporal implementation to hot-spot analysis with taxi trajectories

T2 - A case study in Seoul, Korea

AU - Yun, Sung Bum

AU - Yoon, Sang Hyun

AU - Ju, Sungha

AU - Oh, Won Seob

AU - Ma, Jong Won

AU - Heo, Joon

PY - 2016/10/31

Y1 - 2016/10/31

N2 - Currently there are demands for maximization of taxi services and also for saving fuel usage within massive cities. Spatial big data extracted from taxi service records and GPS can be used to suggest optimal routing options to achieve these goals. The taxi cab ride data contains 7,000 unique taxies being serviced in Seoul, South Korea. In this study one week worth of data with the size of 3.13GB were used. Also road network data provided by Ministry of Land, Infrastructure and Transport (MOLIT), which contains 19,229 nodes and 22,192 links, and census map provided by Statistics Korea were used as base-map. Lastly floating population data of Seoul city area, gathered with mobile phones, has been used as an index of demand for taxi service. By using taxi cab ride data, which contains trajectory with time and 2D coordinates, and information about whether passenger is on the taxi or not, hot spots were analyzed for 1) taxies without passengers whom are available to pick-up passengers, 2) places where people are experiencing difficulty hailing a taxi due to high demand for taxi. Combination of these two types of hot spots can provide new insight for both public and commercial sectors to maximize the efficiency of taxi service and to reduce idle fuel usage. Afterwards the floating population data is used to provide indices for taxi usage in Seoul area, providing further insights. Utilizing the time stamp records on the taxi GPS data, hourly based hot spots for both 'demand' and 'supply' for taxi cab ride can be derived, and this outcome can be practically used to guide taxi drivers to high demanding places and avoid high supplying places.

AB - Currently there are demands for maximization of taxi services and also for saving fuel usage within massive cities. Spatial big data extracted from taxi service records and GPS can be used to suggest optimal routing options to achieve these goals. The taxi cab ride data contains 7,000 unique taxies being serviced in Seoul, South Korea. In this study one week worth of data with the size of 3.13GB were used. Also road network data provided by Ministry of Land, Infrastructure and Transport (MOLIT), which contains 19,229 nodes and 22,192 links, and census map provided by Statistics Korea were used as base-map. Lastly floating population data of Seoul city area, gathered with mobile phones, has been used as an index of demand for taxi service. By using taxi cab ride data, which contains trajectory with time and 2D coordinates, and information about whether passenger is on the taxi or not, hot spots were analyzed for 1) taxies without passengers whom are available to pick-up passengers, 2) places where people are experiencing difficulty hailing a taxi due to high demand for taxi. Combination of these two types of hot spots can provide new insight for both public and commercial sectors to maximize the efficiency of taxi service and to reduce idle fuel usage. Afterwards the floating population data is used to provide indices for taxi usage in Seoul area, providing further insights. Utilizing the time stamp records on the taxi GPS data, hourly based hot spots for both 'demand' and 'supply' for taxi cab ride can be derived, and this outcome can be practically used to guide taxi drivers to high demanding places and avoid high supplying places.

UR - http://www.scopus.com/inward/record.url?scp=85016428912&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85016428912&partnerID=8YFLogxK

U2 - 10.1145/3004725.3004732

DO - 10.1145/3004725.3004732

M3 - Conference contribution

AN - SCOPUS:85016428912

T3 - Proceedings of the 5th ACM SIGSPATIAL International Workshop on Mobile Geographic Information Systems, MobiGIS 2016

SP - 12

EP - 18

BT - Proceedings of the 5th ACM SIGSPATIAL International Workshop on Mobile Geographic Information Systems, MobiGIS 2016

A2 - Chow, Chi-Yin

A2 - Nourjou, Reza

A2 - Shekhar, Shashi

A2 - Damiani, Maria Luisa

PB - Association for Computing Machinery, Inc

ER -

Yun SB, Yoon SH, Ju S, Oh WS, Ma JW, Heo J. Taxi cab service optimization using spatio-temporal implementation to hot-spot analysis with taxi trajectories: A case study in Seoul, Korea. In Chow C-Y, Nourjou R, Shekhar S, Damiani ML, editors, Proceedings of the 5th ACM SIGSPATIAL International Workshop on Mobile Geographic Information Systems, MobiGIS 2016. Association for Computing Machinery, Inc. 2016. p. 12-18. (Proceedings of the 5th ACM SIGSPATIAL International Workshop on Mobile Geographic Information Systems, MobiGIS 2016). https://doi.org/10.1145/3004725.3004732