Big Data for Traffic Estimation and Prediction: A Survey of Data and Tools
Big data have been used widely in many areas, including the transportation industry. Using various data sources, traffic states can be well estimated and further predicted to improve the overall operation efficiency. Combined with this trend, this study presents an up-to-date survey of open data and...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-02-01
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| Series: | Applied System Innovation |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2571-5577/5/1/23 |
| _version_ | 1797482846666883072 |
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| author | Weiwei Jiang Jiayun Luo |
| author_facet | Weiwei Jiang Jiayun Luo |
| author_sort | Weiwei Jiang |
| collection | DOAJ |
| description | Big data have been used widely in many areas, including the transportation industry. Using various data sources, traffic states can be well estimated and further predicted to improve the overall operation efficiency. Combined with this trend, this study presents an up-to-date survey of open data and big data tools used for traffic estimation and prediction. Different data types are categorized, and off-the-shelf tools are introduced. To further promote the use of big data for traffic estimation and prediction tasks, challenges and future directions are given for future studies. |
| first_indexed | 2024-03-09T22:39:19Z |
| format | Article |
| id | doaj.art-0e03ad1e89cb4fc5a261635fbfc6d755 |
| institution | Directory Open Access Journal |
| issn | 2571-5577 |
| language | English |
| last_indexed | 2024-03-09T22:39:19Z |
| publishDate | 2022-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied System Innovation |
| spelling | doaj.art-0e03ad1e89cb4fc5a261635fbfc6d7552023-11-23T18:42:55ZengMDPI AGApplied System Innovation2571-55772022-02-01512310.3390/asi5010023Big Data for Traffic Estimation and Prediction: A Survey of Data and ToolsWeiwei Jiang0Jiayun Luo1Department of Electronic Engineering, Tsinghua University, Beijing 100084, ChinaSchool of Computer Science and Engineering, Nanyang Technological University, Singapore 639798, SingaporeBig data have been used widely in many areas, including the transportation industry. Using various data sources, traffic states can be well estimated and further predicted to improve the overall operation efficiency. Combined with this trend, this study presents an up-to-date survey of open data and big data tools used for traffic estimation and prediction. Different data types are categorized, and off-the-shelf tools are introduced. To further promote the use of big data for traffic estimation and prediction tasks, challenges and future directions are given for future studies.https://www.mdpi.com/2571-5577/5/1/23big datacall detail recordscensus dataGPS trajectory datalocation-based service dataopen data |
| spellingShingle | Weiwei Jiang Jiayun Luo Big Data for Traffic Estimation and Prediction: A Survey of Data and Tools Applied System Innovation big data call detail records census data GPS trajectory data location-based service data open data |
| title | Big Data for Traffic Estimation and Prediction: A Survey of Data and Tools |
| title_full | Big Data for Traffic Estimation and Prediction: A Survey of Data and Tools |
| title_fullStr | Big Data for Traffic Estimation and Prediction: A Survey of Data and Tools |
| title_full_unstemmed | Big Data for Traffic Estimation and Prediction: A Survey of Data and Tools |
| title_short | Big Data for Traffic Estimation and Prediction: A Survey of Data and Tools |
| title_sort | big data for traffic estimation and prediction a survey of data and tools |
| topic | big data call detail records census data GPS trajectory data location-based service data open data |
| url | https://www.mdpi.com/2571-5577/5/1/23 |
| work_keys_str_mv | AT weiweijiang bigdatafortrafficestimationandpredictionasurveyofdataandtools AT jiayunluo bigdatafortrafficestimationandpredictionasurveyofdataandtools |