A novel markov model-based traffic density estimation Technique for intelligent transportation system
An intelligent transportation system (ITS) aims to improve traffic efficiency by integrating innovative sensing, control, and communications technologies. The industrial Internet of things (IIoT) and Industrial Revolution 4.0 recently merged to design the industrial Internet of things–intelligent tr...
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| Format: | Article |
| Language: | English English |
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Molecular Diversity Preservation International (MDPI)
2023
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| Online Access: | https://eprints.ums.edu.my/id/eprint/36084/1/ABSTRACT.pdf https://eprints.ums.edu.my/id/eprint/36084/2/FULL%20TEXT.pdf |
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| author | Hira Beenish Tariq Javid Muhammad Fahad Adnan Ahmed Siddiqui Ghufran Ahmed Hassan Jamil Syed |
| author_facet | Hira Beenish Tariq Javid Muhammad Fahad Adnan Ahmed Siddiqui Ghufran Ahmed Hassan Jamil Syed |
| author_sort | Hira Beenish |
| collection | UMS |
| description | An intelligent transportation system (ITS) aims to improve traffic efficiency by integrating innovative sensing, control, and communications technologies. The industrial Internet of things (IIoT) and Industrial Revolution 4.0 recently merged to design the industrial Internet of things–intelligent transportation system (IIoT-ITS). IIoT sensing technologies play a significant role in acquiring raw data. The application continuously performs the complex task of managing traffic flows effectively based on several parameters, including the number of vehicles in the system, their location, and time. Traffic density estimation (TDE) is another important derived parameter desirable to keep track of the dynamic state of traffic volume. The expanding number of vehicles based on wireless connectivity provides new potential to predict traffic density more accurately and in real time as previously used methodologies. We explore the topic of assessing traffic density by using only a few simple metrics, such as the number of surrounding vehicles and disseminating beacons to roadside units and vice versa. This research paper investigates TDE techniques and presents a novel Markov model-based TDE technique for ITS. Finally, an OMNET++-based approach with an implementation of a significant modification of a traffic model combined with mathematical modeling of the Markov model is presented. It is intended for the study of real-world traffic traces, the identification of model parameters, and the development of simulated traffic. |
| first_indexed | 2024-03-06T03:24:19Z |
| format | Article |
| id | ums.eprints-36084 |
| institution | Universiti Malaysia Sabah |
| language | English English |
| last_indexed | 2024-03-06T03:24:19Z |
| publishDate | 2023 |
| publisher | Molecular Diversity Preservation International (MDPI) |
| record_format | dspace |
| spelling | ums.eprints-360842023-07-20T01:39:26Z https://eprints.ums.edu.my/id/eprint/36084/ A novel markov model-based traffic density estimation Technique for intelligent transportation system Hira Beenish Tariq Javid Muhammad Fahad Adnan Ahmed Siddiqui Ghufran Ahmed Hassan Jamil Syed TK1-9971 Electrical engineering. Electronics. Nuclear engineering TK5101-6720 Telecommunication Including telegraphy, telephone, radio, radar, television An intelligent transportation system (ITS) aims to improve traffic efficiency by integrating innovative sensing, control, and communications technologies. The industrial Internet of things (IIoT) and Industrial Revolution 4.0 recently merged to design the industrial Internet of things–intelligent transportation system (IIoT-ITS). IIoT sensing technologies play a significant role in acquiring raw data. The application continuously performs the complex task of managing traffic flows effectively based on several parameters, including the number of vehicles in the system, their location, and time. Traffic density estimation (TDE) is another important derived parameter desirable to keep track of the dynamic state of traffic volume. The expanding number of vehicles based on wireless connectivity provides new potential to predict traffic density more accurately and in real time as previously used methodologies. We explore the topic of assessing traffic density by using only a few simple metrics, such as the number of surrounding vehicles and disseminating beacons to roadside units and vice versa. This research paper investigates TDE techniques and presents a novel Markov model-based TDE technique for ITS. Finally, an OMNET++-based approach with an implementation of a significant modification of a traffic model combined with mathematical modeling of the Markov model is presented. It is intended for the study of real-world traffic traces, the identification of model parameters, and the development of simulated traffic. Molecular Diversity Preservation International (MDPI) 2023 Article NonPeerReviewed text en https://eprints.ums.edu.my/id/eprint/36084/1/ABSTRACT.pdf text en https://eprints.ums.edu.my/id/eprint/36084/2/FULL%20TEXT.pdf Hira Beenish and Tariq Javid and Muhammad Fahad and Adnan Ahmed Siddiqui and Ghufran Ahmed and Hassan Jamil Syed (2023) A novel markov model-based traffic density estimation Technique for intelligent transportation system. Sensors, 23. pp. 1-24. https://doi.org/10.3390/s23020768 |
| spellingShingle | TK1-9971 Electrical engineering. Electronics. Nuclear engineering TK5101-6720 Telecommunication Including telegraphy, telephone, radio, radar, television Hira Beenish Tariq Javid Muhammad Fahad Adnan Ahmed Siddiqui Ghufran Ahmed Hassan Jamil Syed A novel markov model-based traffic density estimation Technique for intelligent transportation system |
| title | A novel markov model-based traffic density estimation Technique for intelligent transportation system |
| title_full | A novel markov model-based traffic density estimation Technique for intelligent transportation system |
| title_fullStr | A novel markov model-based traffic density estimation Technique for intelligent transportation system |
| title_full_unstemmed | A novel markov model-based traffic density estimation Technique for intelligent transportation system |
| title_short | A novel markov model-based traffic density estimation Technique for intelligent transportation system |
| title_sort | novel markov model based traffic density estimation technique for intelligent transportation system |
| topic | TK1-9971 Electrical engineering. Electronics. Nuclear engineering TK5101-6720 Telecommunication Including telegraphy, telephone, radio, radar, television |
| url | https://eprints.ums.edu.my/id/eprint/36084/1/ABSTRACT.pdf https://eprints.ums.edu.my/id/eprint/36084/2/FULL%20TEXT.pdf |
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