Trip Distribution Modeling Using Mobile Phone Data: Emphasis on Intra-Zonal Trips
IEEE The development of a trip distribution model requires a massive data collection task, such as expensive travel surveys to identify trip makers' origin and destination zones. Intra-zonal trips are usually ignored in the development of trip distribution models because of the difficulty assoc...
Saved in:
Main Authors: | , , |
---|---|
Format: | Journal |
Published: |
2018
|
Subjects: | |
Online Access: | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85055028513&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/62673 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Chiang Mai University |
id |
th-cmuir.6653943832-62673 |
---|---|
record_format |
dspace |
spelling |
th-cmuir.6653943832-626732018-11-29T07:43:11Z Trip Distribution Modeling Using Mobile Phone Data: Emphasis on Intra-Zonal Trips Merkebe Getachew Demissie Santi Phithakkitnukoon Lina Kattan Computer Science Engineering IEEE The development of a trip distribution model requires a massive data collection task, such as expensive travel surveys to identify trip makers' origin and destination zones. Intra-zonal trips are usually ignored in the development of trip distribution models because of the difficulty associated with measuring travel costs. However, ignoring intra-zonal trips leads to incomplete model estimation especially when the zone size is large, and thus, the number of intra-zonal trips is substantial. This is especially important, with the growing interest around the world on creating more walkable and bikeable cities where a high share of those trips is intra-zonal. In this paper, we use mobile phone data to derive country-wide mobility trends. A set of doubly constrained trip distribution models that integrates intra-zonal trips was estimated for 123-district-level traffic analysis zones. We present two approaches to estimate the intra-zonal travel costs measured in terms of trip distance. Our analysis reveals that the average intra-zonal trip distances obtained from the two approaches provide different levels of sensitivity to the distance-decay effect. Our result also shows that model estimation in the absence of intra-zonal trips produces biased estimates. 2018-11-29T07:39:32Z 2018-11-29T07:39:32Z 2018-01-01 Journal 15249050 2-s2.0-85055028513 10.1109/TITS.2018.2868468 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85055028513&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/62673 |
institution |
Chiang Mai University |
building |
Chiang Mai University Library |
country |
Thailand |
collection |
CMU Intellectual Repository |
topic |
Computer Science Engineering |
spellingShingle |
Computer Science Engineering Merkebe Getachew Demissie Santi Phithakkitnukoon Lina Kattan Trip Distribution Modeling Using Mobile Phone Data: Emphasis on Intra-Zonal Trips |
description |
IEEE The development of a trip distribution model requires a massive data collection task, such as expensive travel surveys to identify trip makers' origin and destination zones. Intra-zonal trips are usually ignored in the development of trip distribution models because of the difficulty associated with measuring travel costs. However, ignoring intra-zonal trips leads to incomplete model estimation especially when the zone size is large, and thus, the number of intra-zonal trips is substantial. This is especially important, with the growing interest around the world on creating more walkable and bikeable cities where a high share of those trips is intra-zonal. In this paper, we use mobile phone data to derive country-wide mobility trends. A set of doubly constrained trip distribution models that integrates intra-zonal trips was estimated for 123-district-level traffic analysis zones. We present two approaches to estimate the intra-zonal travel costs measured in terms of trip distance. Our analysis reveals that the average intra-zonal trip distances obtained from the two approaches provide different levels of sensitivity to the distance-decay effect. Our result also shows that model estimation in the absence of intra-zonal trips produces biased estimates. |
format |
Journal |
author |
Merkebe Getachew Demissie Santi Phithakkitnukoon Lina Kattan |
author_facet |
Merkebe Getachew Demissie Santi Phithakkitnukoon Lina Kattan |
author_sort |
Merkebe Getachew Demissie |
title |
Trip Distribution Modeling Using Mobile Phone Data: Emphasis on Intra-Zonal Trips |
title_short |
Trip Distribution Modeling Using Mobile Phone Data: Emphasis on Intra-Zonal Trips |
title_full |
Trip Distribution Modeling Using Mobile Phone Data: Emphasis on Intra-Zonal Trips |
title_fullStr |
Trip Distribution Modeling Using Mobile Phone Data: Emphasis on Intra-Zonal Trips |
title_full_unstemmed |
Trip Distribution Modeling Using Mobile Phone Data: Emphasis on Intra-Zonal Trips |
title_sort |
trip distribution modeling using mobile phone data: emphasis on intra-zonal trips |
publishDate |
2018 |
url |
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85055028513&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/62673 |
_version_ |
1681425850905395200 |