Comparison of Clustered-based MNL and Duration Models in Departure Time Choice Modelling
One of the important decisions for travellers about each trip is the time that they depart from their point of origin. The aggregation of the departure times of all travellers forms the pattern of a temporal distribution of trips in a day and also peak periods of a day. In this paper, we applied the...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek
2021-01-01
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| Series: | Tehnički Vjesnik |
| Subjects: | |
| Online Access: | https://hrcak.srce.hr/file/365710 |
| _version_ | 1797207039770886144 |
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| author | Shahriar Afandizadeh Zargari* Farshid Safari |
| author_facet | Shahriar Afandizadeh Zargari* Farshid Safari |
| author_sort | Shahriar Afandizadeh Zargari* |
| collection | DOAJ |
| description | One of the important decisions for travellers about each trip is the time that they depart from their point of origin. The aggregation of the departure times of all travellers forms the pattern of a temporal distribution of trips in a day and also peak periods of a day. In this paper, we applied the multinomial logit (MNL) on a choice set which was derived from cluster analysis, and we also made use of the duration models to estimate departure time for home-based work trips. For the duration models, the Kaplan-Meier and Cox proportional methods are used and then, the results are compared to cluster-based MNL model. This study is conducted in Mashhad city which has a population of about 2.7 million people. The results show the traveller's job and traveller's selected mode have a significant effect on his departure time choice. Comparison of the predictability power of these two modelling approaches indicates that the cluster-based MNL model in this case study is the preferable model. |
| first_indexed | 2024-04-24T09:16:35Z |
| format | Article |
| id | doaj.art-fa760366ab40459ab646ccd1f22c7bbf |
| institution | Directory Open Access Journal |
| issn | 1330-3651 1848-6339 |
| language | English |
| last_indexed | 2024-04-24T09:16:35Z |
| publishDate | 2021-01-01 |
| publisher | Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek |
| record_format | Article |
| series | Tehnički Vjesnik |
| spelling | doaj.art-fa760366ab40459ab646ccd1f22c7bbf2024-04-15T16:48:36ZengFaculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in OsijekTehnički Vjesnik1330-36511848-63392021-01-0128127027510.17559/TV-20180115064630Comparison of Clustered-based MNL and Duration Models in Departure Time Choice ModellingShahriar Afandizadeh Zargari*0Farshid Safari1Department of Transportation Engineering and Planning, School of Civil Engineering, Iran University of Science & Technology, P.O. Box 16765-163, Narmak, Tehran, IranDepartment of Transportation Engineering and Planning, School of Civil Engineering, Iran University of Science & Technology, P.O. Box 16765-163, Narmak, Tehran, IranOne of the important decisions for travellers about each trip is the time that they depart from their point of origin. The aggregation of the departure times of all travellers forms the pattern of a temporal distribution of trips in a day and also peak periods of a day. In this paper, we applied the multinomial logit (MNL) on a choice set which was derived from cluster analysis, and we also made use of the duration models to estimate departure time for home-based work trips. For the duration models, the Kaplan-Meier and Cox proportional methods are used and then, the results are compared to cluster-based MNL model. This study is conducted in Mashhad city which has a population of about 2.7 million people. The results show the traveller's job and traveller's selected mode have a significant effect on his departure time choice. Comparison of the predictability power of these two modelling approaches indicates that the cluster-based MNL model in this case study is the preferable model.https://hrcak.srce.hr/file/365710clustered-based MNLcox proportional methodDeparture Time Choice (DTC)duration modelsK-mean clustering |
| spellingShingle | Shahriar Afandizadeh Zargari* Farshid Safari Comparison of Clustered-based MNL and Duration Models in Departure Time Choice Modelling Tehnički Vjesnik clustered-based MNL cox proportional method Departure Time Choice (DTC) duration models K-mean clustering |
| title | Comparison of Clustered-based MNL and Duration Models in Departure Time Choice Modelling |
| title_full | Comparison of Clustered-based MNL and Duration Models in Departure Time Choice Modelling |
| title_fullStr | Comparison of Clustered-based MNL and Duration Models in Departure Time Choice Modelling |
| title_full_unstemmed | Comparison of Clustered-based MNL and Duration Models in Departure Time Choice Modelling |
| title_short | Comparison of Clustered-based MNL and Duration Models in Departure Time Choice Modelling |
| title_sort | comparison of clustered based mnl and duration models in departure time choice modelling |
| topic | clustered-based MNL cox proportional method Departure Time Choice (DTC) duration models K-mean clustering |
| url | https://hrcak.srce.hr/file/365710 |
| work_keys_str_mv | AT shahriarafandizadehzargari comparisonofclusteredbasedmnlanddurationmodelsindeparturetimechoicemodelling AT farshidsafari comparisonofclusteredbasedmnlanddurationmodelsindeparturetimechoicemodelling |