Multi-Feature Fusion: A Driver-Car Matching Model Based on Curve Comparison
With the development of the mobile Internet, novel things are constantly emerging, and among them, online car-hailing is one of the representatives. However, the rapid development of online car-hailing also brings about normative problems and safety loophole, the most prominent of which is the incon...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2019-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8740866/ |
| _version_ | 1798002036900364288 |
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| author | Xianwei Meng Hao Fu Guiquan Liu Lei Zhang Yang Yu Weiyi Hu Enhong Cheng |
| author_facet | Xianwei Meng Hao Fu Guiquan Liu Lei Zhang Yang Yu Weiyi Hu Enhong Cheng |
| author_sort | Xianwei Meng |
| collection | DOAJ |
| description | With the development of the mobile Internet, novel things are constantly emerging, and among them, online car-hailing is one of the representatives. However, the rapid development of online car-hailing also brings about normative problems and safety loophole, the most prominent of which is the inconsistency between operating cars and registered drivers. Some existing algorithms based on curve similarity measurements, such as Hausdorff distance and discrete Fréchet distance, can be used to solve this problem. However, they only consider one of the characteristics of the two curves, such as the distance or the area between two curves, which does not achieve good results on this problem. On this ground, we propose a model based on curve comparison, named multi-feature fusion (MFF), which extracts the features of length, distance, and area from the GPS positioning track of car and the application mobile phone of the driver, to testify whether the car is being operated by the registered driver and thus solving the problem of mismatch between the driver and the car during the operation. Among them, the MFF model designs different algorithms for different features and fuses different features by an ensemble learning method. The experimental results prove that the model can effectively detect the mismatch between drivers and cars. |
| first_indexed | 2024-04-11T11:45:49Z |
| format | Article |
| id | doaj.art-be47284770794b69ae2ced78b7b194d7 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-11T11:45:49Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-be47284770794b69ae2ced78b7b194d72022-12-22T04:25:35ZengIEEEIEEE Access2169-35362019-01-017835268353510.1109/ACCESS.2019.29237958740866Multi-Feature Fusion: A Driver-Car Matching Model Based on Curve ComparisonXianwei Meng0Hao Fu1https://orcid.org/0000-0002-1791-3311Guiquan Liu2Lei Zhang3https://orcid.org/0000-0002-6447-2053Yang Yu4Weiyi Hu5Enhong Cheng6Anhui Province Key Laboratory of Big Data Analysis and Application, School of Computer Science and Technology, University of Science and Technology of China, Hefei, ChinaAnhui Province Key Laboratory of Big Data Analysis and Application, School of Computer Science and Technology, University of Science and Technology of China, Hefei, ChinaAnhui Province Key Laboratory of Big Data Analysis and Application, School of Computer Science and Technology, University of Science and Technology of China, Hefei, ChinaSchool of Computer Science and Technology, Institute of Bio-inspired Intelligence and Mining Knowledge, Anhui University, Hefei, ChinaAnhui Province Key Laboratory of Big Data Analysis and Application, School of Computer Science and Technology, University of Science and Technology of China, Hefei, ChinaDepartment of Applied Mathematics, Sichuan University, Chengdu, ChinaAnhui Province Key Laboratory of Big Data Analysis and Application, School of Computer Science and Technology, University of Science and Technology of China, Hefei, ChinaWith the development of the mobile Internet, novel things are constantly emerging, and among them, online car-hailing is one of the representatives. However, the rapid development of online car-hailing also brings about normative problems and safety loophole, the most prominent of which is the inconsistency between operating cars and registered drivers. Some existing algorithms based on curve similarity measurements, such as Hausdorff distance and discrete Fréchet distance, can be used to solve this problem. However, they only consider one of the characteristics of the two curves, such as the distance or the area between two curves, which does not achieve good results on this problem. On this ground, we propose a model based on curve comparison, named multi-feature fusion (MFF), which extracts the features of length, distance, and area from the GPS positioning track of car and the application mobile phone of the driver, to testify whether the car is being operated by the registered driver and thus solving the problem of mismatch between the driver and the car during the operation. Among them, the MFF model designs different algorithms for different features and fuses different features by an ensemble learning method. The experimental results prove that the model can effectively detect the mismatch between drivers and cars.https://ieeexplore.ieee.org/document/8740866/Curve similarity measurementdriver-car matchingGPS positioning trajectory similarity |
| spellingShingle | Xianwei Meng Hao Fu Guiquan Liu Lei Zhang Yang Yu Weiyi Hu Enhong Cheng Multi-Feature Fusion: A Driver-Car Matching Model Based on Curve Comparison IEEE Access Curve similarity measurement driver-car matching GPS positioning trajectory similarity |
| title | Multi-Feature Fusion: A Driver-Car Matching Model Based on Curve Comparison |
| title_full | Multi-Feature Fusion: A Driver-Car Matching Model Based on Curve Comparison |
| title_fullStr | Multi-Feature Fusion: A Driver-Car Matching Model Based on Curve Comparison |
| title_full_unstemmed | Multi-Feature Fusion: A Driver-Car Matching Model Based on Curve Comparison |
| title_short | Multi-Feature Fusion: A Driver-Car Matching Model Based on Curve Comparison |
| title_sort | multi feature fusion a driver car matching model based on curve comparison |
| topic | Curve similarity measurement driver-car matching GPS positioning trajectory similarity |
| url | https://ieeexplore.ieee.org/document/8740866/ |
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