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...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-01-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/23/2/768 |
| _version_ | 1797437297503764480 |
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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 | DOAJ |
| 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 | 2024-03-09T11:16:50Z |
| format | Article |
| id | doaj.art-5b412aa8288240528d63cbb3a967db80 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T11:16:50Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-5b412aa8288240528d63cbb3a967db802023-12-01T00:27:16ZengMDPI AGSensors1424-82202023-01-0123276810.3390/s23020768A Novel Markov Model-Based Traffic Density Estimation Technique for Intelligent Transportation SystemHira Beenish0Tariq Javid1Muhammad Fahad2Adnan Ahmed Siddiqui3Ghufran Ahmed4Hassan Jamil Syed5Faculty of Engineering Sciences & Technology, Hamdard University, Karachi 74600, PakistanFaculty of Engineering Sciences & Technology, Hamdard University, Karachi 74600, PakistanCollege of Computing and Information Science, Karachi Institute of Economics and Technology, Karachi 75190, PakistanFaculty of Engineering Sciences & Technology, Hamdard University, Karachi 74600, PakistanSchool of Computing, National University of Computer and Engineering Science (FAST-NUCES), Karachi 75030, PakistanFaculty of Computing & Informatics, Universiti Malaysia Sabah, Jalan UMS, Kota Kinabalu 88400, Sabah, MalaysiaAn 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.https://www.mdpi.com/1424-8220/23/2/768industrial Internet of thingsfourth industrial revolutionintelligent transportation systemtraffic density estimationtraffic efficiencyMarkov model |
| spellingShingle | 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 Sensors industrial Internet of things fourth industrial revolution intelligent transportation system traffic density estimation traffic efficiency Markov model |
| 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 | industrial Internet of things fourth industrial revolution intelligent transportation system traffic density estimation traffic efficiency Markov model |
| url | https://www.mdpi.com/1424-8220/23/2/768 |
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