A Kind of Urban Road Travel Time Forecasting Model with Loop Detectors
Urban road travel time is an important parameter to reflect the traffic flow state. Besides, it is one of the important parameters for the traffic management department to formulate guidance measures, provide traffic information service, and improve the efficiency of the detectors group. Therefore,...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2016-02-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1155/2016/9043835 |
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| _version_ | 1832547904354516992 |
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| author | Guangyu Zhu Li Wang Peng Zhang Kang Song |
| author_facet | Guangyu Zhu Li Wang Peng Zhang Kang Song |
| author_sort | Guangyu Zhu |
| collection | DOAJ |
| description | Urban road travel time is an important parameter to reflect the traffic flow state. Besides, it is one of the important parameters for the traffic management department to formulate guidance measures, provide traffic information service, and improve the efficiency of the detectors group. Therefore, it is crucial to improve the forecast accuracy of travel time in traffic management practice. Based on the analysis of the change-point and the ARIMA model, this paper constructs a model for the massive data collected by loop detectors to forecast travel time parameters. Firstly, the preprocessing algorithm for the data of loop detectors is given, and the calculating model of the travel time is studied. Secondly, a change-point detection algorithm is designed to classify the sequence of large number of travel time data items into several patterns. Then, this paper establishes a forecast model to forecast travel time in different patterns using the improved ARIMA model. At last, the model is verified by simulation and the verification results of several groups of examples show that the model has high accuracy and practicality. |
| format | Article |
| id | doaj-art-2a0ddc26c85b434a98c6cf1fff36b859 |
| institution | Kabale University |
| issn | 1550-1477 |
| language | English |
| publishDate | 2016-02-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-2a0ddc26c85b434a98c6cf1fff36b8592025-02-03T06:42:54ZengWileyInternational Journal of Distributed Sensor Networks1550-14772016-02-011210.1155/2016/90438359043835A Kind of Urban Road Travel Time Forecasting Model with Loop DetectorsGuangyu Zhu0Li Wang1Peng Zhang2Kang Song3 Key Laboratory of System Control and Information Processing, Ministry of Education, Shanghai 200240, China Center of Cooperative Innovation for Beijing Metropolitan Transportation, Beijing 100044, China Beijing Municipality Key Laboratory of Urban Traffic Operation Simulation and Decision Support, Beijing Transportation Research Center, Beijing 100073, China Center of Cooperative Innovation for Beijing Metropolitan Transportation, Beijing 100044, ChinaUrban road travel time is an important parameter to reflect the traffic flow state. Besides, it is one of the important parameters for the traffic management department to formulate guidance measures, provide traffic information service, and improve the efficiency of the detectors group. Therefore, it is crucial to improve the forecast accuracy of travel time in traffic management practice. Based on the analysis of the change-point and the ARIMA model, this paper constructs a model for the massive data collected by loop detectors to forecast travel time parameters. Firstly, the preprocessing algorithm for the data of loop detectors is given, and the calculating model of the travel time is studied. Secondly, a change-point detection algorithm is designed to classify the sequence of large number of travel time data items into several patterns. Then, this paper establishes a forecast model to forecast travel time in different patterns using the improved ARIMA model. At last, the model is verified by simulation and the verification results of several groups of examples show that the model has high accuracy and practicality.https://doi.org/10.1155/2016/9043835 |
| spellingShingle | Guangyu Zhu Li Wang Peng Zhang Kang Song A Kind of Urban Road Travel Time Forecasting Model with Loop Detectors International Journal of Distributed Sensor Networks |
| title | A Kind of Urban Road Travel Time Forecasting Model with Loop Detectors |
| title_full | A Kind of Urban Road Travel Time Forecasting Model with Loop Detectors |
| title_fullStr | A Kind of Urban Road Travel Time Forecasting Model with Loop Detectors |
| title_full_unstemmed | A Kind of Urban Road Travel Time Forecasting Model with Loop Detectors |
| title_short | A Kind of Urban Road Travel Time Forecasting Model with Loop Detectors |
| title_sort | kind of urban road travel time forecasting model with loop detectors |
| url | https://doi.org/10.1155/2016/9043835 |
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