Comparative Analysis of Anpr and TIRTL Systems Using Artificial Neural Networks for Traffic Speed Management
Transportation networks are struggling with increased traffic due to mixed flows and the unregulated growth of private vehicles. Over-speeding and congestion are critical issues for urban planners. Effective speed management and enforcement are essential to mitigate excessive speed, which is a major...
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| Format: | Article |
| Language: | English |
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Sciendo
2025-03-01
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| Series: | Slovak Journal of Civil Engineering |
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| Online Access: | https://doi.org/10.2478/sjce-2025-0004 |
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| author | Kumar Boddu Sudhir Kumar Pala Gireesh Kumar Kontham Pavan |
| author_facet | Kumar Boddu Sudhir Kumar Pala Gireesh Kumar Kontham Pavan |
| author_sort | Kumar Boddu Sudhir |
| collection | DOAJ |
| description | Transportation networks are struggling with increased traffic due to mixed flows and the unregulated growth of private vehicles. Over-speeding and congestion are critical issues for urban planners. Effective speed management and enforcement are essential to mitigate excessive speed, which is a major cause of traffic accidents. This study aims to develop efficient traffic speed management measures by evaluating the performance of Automatic Number Plate Recognition (ANPR) and The Infra-Red Traffic Logger (TIRTL) in data collection and the detection of excessive speeding. The results show ANPR detected only 51% of the vehicle classes, while TIRTL detected 96% of them. A maximum speed reduction of 20 km/h was observed in the vehicles, with an average reduction of 8 km/h. The ANN model developed can help urban planners devise new speed management techniques by accurately estimating their effectiveness in an urban setting. |
| format | Article |
| id | doaj-art-e1bc472bbe4b40fa841ed34771730e0b |
| institution | OA Journals |
| issn | 1338-3973 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Sciendo |
| record_format | Article |
| series | Slovak Journal of Civil Engineering |
| spelling | doaj-art-e1bc472bbe4b40fa841ed34771730e0b2025-08-20T02:08:12ZengSciendoSlovak Journal of Civil Engineering1338-39732025-03-01331344310.2478/sjce-2025-0004Comparative Analysis of Anpr and TIRTL Systems Using Artificial Neural Networks for Traffic Speed ManagementKumar Boddu Sudhir0Kumar Pala Gireesh1Kumar Kontham Pavan21Assistant Professor, Department of Civil Engineering, Shri Vishnu Engineering College for Women, Bhimavaram, India2Professor, Department of Civil Engineering, Shri Vishnu Engineering College for Women, Bhimavaram, India3Assistant Executive Engineer, Irrigation and CAD Department, Kamareddy, Telangana, IndiaTransportation networks are struggling with increased traffic due to mixed flows and the unregulated growth of private vehicles. Over-speeding and congestion are critical issues for urban planners. Effective speed management and enforcement are essential to mitigate excessive speed, which is a major cause of traffic accidents. This study aims to develop efficient traffic speed management measures by evaluating the performance of Automatic Number Plate Recognition (ANPR) and The Infra-Red Traffic Logger (TIRTL) in data collection and the detection of excessive speeding. The results show ANPR detected only 51% of the vehicle classes, while TIRTL detected 96% of them. A maximum speed reduction of 20 km/h was observed in the vehicles, with an average reduction of 8 km/h. The ANN model developed can help urban planners devise new speed management techniques by accurately estimating their effectiveness in an urban setting.https://doi.org/10.2478/sjce-2025-0004artificial neural networkautomatic number plate recognitionintelligent transport flowinfra-red traffic loggertraffic speed management |
| spellingShingle | Kumar Boddu Sudhir Kumar Pala Gireesh Kumar Kontham Pavan Comparative Analysis of Anpr and TIRTL Systems Using Artificial Neural Networks for Traffic Speed Management Slovak Journal of Civil Engineering artificial neural network automatic number plate recognition intelligent transport flow infra-red traffic logger traffic speed management |
| title | Comparative Analysis of Anpr and TIRTL Systems Using Artificial Neural Networks for Traffic Speed Management |
| title_full | Comparative Analysis of Anpr and TIRTL Systems Using Artificial Neural Networks for Traffic Speed Management |
| title_fullStr | Comparative Analysis of Anpr and TIRTL Systems Using Artificial Neural Networks for Traffic Speed Management |
| title_full_unstemmed | Comparative Analysis of Anpr and TIRTL Systems Using Artificial Neural Networks for Traffic Speed Management |
| title_short | Comparative Analysis of Anpr and TIRTL Systems Using Artificial Neural Networks for Traffic Speed Management |
| title_sort | comparative analysis of anpr and tirtl systems using artificial neural networks for traffic speed management |
| topic | artificial neural network automatic number plate recognition intelligent transport flow infra-red traffic logger traffic speed management |
| url | https://doi.org/10.2478/sjce-2025-0004 |
| work_keys_str_mv | AT kumarboddusudhir comparativeanalysisofanprandtirtlsystemsusingartificialneuralnetworksfortrafficspeedmanagement AT kumarpalagireesh comparativeanalysisofanprandtirtlsystemsusingartificialneuralnetworksfortrafficspeedmanagement AT kumarkonthampavan comparativeanalysisofanprandtirtlsystemsusingartificialneuralnetworksfortrafficspeedmanagement |