Estimating Destination of Bus Trips Considering Trip Type Characteristics
Recently, local governments have been using transportation card data to monitor the use of public transport and improve the service. However, local governments that are applying a single-fare scheme are experiencing difficulties in using data for accurate identification of real travel patterns or po...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-11-01
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| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/11/21/10415 |
| _version_ | 1797411042783920128 |
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| author | Soongbong Lee Jongwoo Lee Bumjoon Bae Daisik Nam Seunghoon Cheon |
| author_facet | Soongbong Lee Jongwoo Lee Bumjoon Bae Daisik Nam Seunghoon Cheon |
| author_sort | Soongbong Lee |
| collection | DOAJ |
| description | Recently, local governments have been using transportation card data to monitor the use of public transport and improve the service. However, local governments that are applying a single-fare scheme are experiencing difficulties in using data for accurate identification of real travel patterns or policy decision support due to missing information on alighting stops of users. This policy limits its functionality of utilizing data such as accurate identification of real travel patterns, policy decision support, etc. In order to overcome these limitations, various methods for estimating alighting stops have been developed. This study classifies trips with missing alighting stop information into trip four types and then applies appropriate alighting stop estimation methodology for each trip type in stages. The proposed method is evaluated by utilizing transportation card data of the Seoul metropolitan area and checking the accuracy for each standard of allowable error for sensitivity analysis. The analysis shows that the stage-by-stage estimation methodology based on the trip type proposed in this study can estimate users’ destinations more accurately than the methodologies of previous studies. Furthermore, based on the construction of nearly 100% valid tag data, this study differs from prior studies. |
| first_indexed | 2024-03-09T04:39:15Z |
| format | Article |
| id | doaj.art-a36b09c8568d409d87326073d0b9faa8 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-09T04:39:15Z |
| publishDate | 2021-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-a36b09c8568d409d87326073d0b9faa82023-12-03T13:23:35ZengMDPI AGApplied Sciences2076-34172021-11-0111211041510.3390/app112110415Estimating Destination of Bus Trips Considering Trip Type CharacteristicsSoongbong Lee0Jongwoo Lee1Bumjoon Bae2Daisik Nam3Seunghoon Cheon4Big Data Platform and Data Economy, The Korea Transport Institute, 370 Sicheong-daero, Sejong 30147, KoreaBig Data Platform and Data Economy, The Korea Transport Institute, 370 Sicheong-daero, Sejong 30147, KoreaCenter for Privately-Financed Highway Studies, The Korea Transport Institute, 370 Sicheong-daero, Sejong 30147, KoreaGraduate School of Logistics, Inha University, Incheon 22212, KoreaBig Data Platform and Data Economy, The Korea Transport Institute, 370 Sicheong-daero, Sejong 30147, KoreaRecently, local governments have been using transportation card data to monitor the use of public transport and improve the service. However, local governments that are applying a single-fare scheme are experiencing difficulties in using data for accurate identification of real travel patterns or policy decision support due to missing information on alighting stops of users. This policy limits its functionality of utilizing data such as accurate identification of real travel patterns, policy decision support, etc. In order to overcome these limitations, various methods for estimating alighting stops have been developed. This study classifies trips with missing alighting stop information into trip four types and then applies appropriate alighting stop estimation methodology for each trip type in stages. The proposed method is evaluated by utilizing transportation card data of the Seoul metropolitan area and checking the accuracy for each standard of allowable error for sensitivity analysis. The analysis shows that the stage-by-stage estimation methodology based on the trip type proposed in this study can estimate users’ destinations more accurately than the methodologies of previous studies. Furthermore, based on the construction of nearly 100% valid tag data, this study differs from prior studies.https://www.mdpi.com/2076-3417/11/21/10415public transit transaction dataestimation of destinationcategorization of trip typestrip chaintravel patternhistorical travel data |
| spellingShingle | Soongbong Lee Jongwoo Lee Bumjoon Bae Daisik Nam Seunghoon Cheon Estimating Destination of Bus Trips Considering Trip Type Characteristics Applied Sciences public transit transaction data estimation of destination categorization of trip types trip chain travel pattern historical travel data |
| title | Estimating Destination of Bus Trips Considering Trip Type Characteristics |
| title_full | Estimating Destination of Bus Trips Considering Trip Type Characteristics |
| title_fullStr | Estimating Destination of Bus Trips Considering Trip Type Characteristics |
| title_full_unstemmed | Estimating Destination of Bus Trips Considering Trip Type Characteristics |
| title_short | Estimating Destination of Bus Trips Considering Trip Type Characteristics |
| title_sort | estimating destination of bus trips considering trip type characteristics |
| topic | public transit transaction data estimation of destination categorization of trip types trip chain travel pattern historical travel data |
| url | https://www.mdpi.com/2076-3417/11/21/10415 |
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