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...

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Main Authors: Merkebe Getachew Demissie, Santi Phithakkitnukoon, Lina Kattan
Format: Journal
Published: 2018
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http://cmuir.cmu.ac.th/jspui/handle/6653943832/62673
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Institution: Chiang Mai University
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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
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