How to cite this paper
Rajabi, M., Habibpour, M., Bakhtiari, S., Rad, F & Aghakhani, S. (2023). The development of BPR models in smart cities using loop detectors and license plate recognition technologies: A case study.Journal of Future Sustainability, 3(2), 75-84.
Refrences
Aghakhani, S., Mohammadi, B., & Rajabi, M. S. (2022). A New Hybrid Multi-Objective Scheduling Model for Hierar-chical Hub and Flexible Flow Shop Problems. arXiv preprint arXiv:2205.06465.
Aghakhani, S., & Rajabi, M.S. (2022). A New Hybrid Multi-Objective Scheduling Model for Hierarchical Hub and Flex-ible Flow Shop Problems. available at: http://arxiv.org/abs/2205.06465 (accessed 3 September 2022).
Babiceanu, S., & Lahiri, S. (2022). Methodology for Predicting MAP-21 Interstate Travel Time Reliability Measure Target in Virginia. Transportation Research Record, 03611981221083290.
Beigi, P., Rajabi, M. S., & Aghakhani, S. (2022). An Overview of Drone Energy Consumption Factors and Models. arXiv preprint arXiv:2206.10775.
Berry, D. S. (1952). Evaluation of Techniques for Determining Over-All Travel Time. In Highway Research Board Pro-ceedings, 31.
Berry, D. S., & Green, F. H. (1950). Techniques for measuring over-all speeds in urban areas. In Highway Research Board Proceedings, 29.
Dowling, R.G., & Skabardonis, A. (2008). Urban Arterial Speed–Flow Equations for Travel Demand Models. Transpor-tation Research Board Conference Proceedings, 2.
Pourzahedi, H., & Ashtiani, H. (1995), Study of Link Travel Time Functions in Mashhad, Institute for Transportation Studies and Research, Tehran.
Hansen, S. (2020). Does the COVID-19 Outbreak Constitute a Force Majeure Event? A Pandemic Impact on Construc-tion Contracts. Journal of the Civil Engineering Forum, Universitas Gadjah Mada, 6(1), 201.
Holt, R.B., Smith, B.L., & Park, B. (2003). An Investigation of Travel Time Estimation Based on Point Sensors, Smart Travel Lab.
Hummer, J.E., Robertson, H.D., & Nelson, D.C. (1994). Manual of Transportation Engineering Studies. Institute of Transportation Engineering, by Prentice-Hall, Inc, Englewood Cliffs, New Jersey.
Ishak, S., & Al-Deek, H. (2002). Performance Evaluation of Short-Term Time-Series Traffic Prediction Model. Journal of Transportation Engineering, 128(6), 490–498.
Laroca, R., Severo, E., Zanlorensi, L.A., Oliveira, L.S., Gonçalves, G.R., Schwartz, W.R., & Menotti, D. (2018). A ro-bust real-time automatic license plate recognition based on the YOLO detector. 2018 International Joint Conference on Neural Networks (Ijcnn), IEEE, pp. 1–10.
Lin, H.-E., Zito, R., & Taylor, M. (2005). A review of travel-time prediction in transport and logistics. Proceedings of the Eastern Asia Society for Transportation Studies, Vol. 5, Bangkok, Thailand, pp. 1433–1448.
Lomax, T., Turner, S., Shunk, G., Levinson, H.S., Pratt, R.H., Bay, P.N., & Douglas, G.B. (1997). Quantifying Conges-tion. Volume 2: User’s Guide.
Lotfi, R., Kargar, B., Gharehbaghi, A., Afshar, M., Rajabi, M.S., & Mardani, N. (2022). A data-driven robust optimiza-tion for multi-objective renewable energy location by considering risk. Environment, Development and Sustainabil-ity, available at:https://doi.org/10.1007/s10668-022-02448-7.
Luo, X., Ma, D., Jin, S., Gong, Y., & Wang, D. (2019). Queue length estimation for signalized intersections using li-cense plate recognition data. IEEE Intelligent Transportation Systems Magazine, IEEE, 11(3), 209–220.
Tabibi, M., Moghadasnezhad, F., & Mohseni, M. (2012). Prediction of Travel Time in Road Network Using Neural Networks. The 11th Int. Conference on Traffic and Transportation Engineering, Tehran.
Yang, M., Liu, Y., & You, Z. (2009). The reliability of travel time forecasting. IEEE Transactions on Intelligent Trans-portation Systems, 11(1), 162-171.
Moeinifard, P., Rajabi, M. S., & Bitaraf, M. (2022). Lost Vibration Test Data Recovery Using Convolutional Neural Network: A Case Study. arXiv preprint arXiv:2204.05440.
Mudiyanselage, S.E., Nguyen, P.H.D., Rajabi, M.S., & Akhavian, R. (2021). Automated Workers’ Ergonomic Risk As-sessment in Manual Material Handling Using sEMG Wearable Sensors and Machine Learning. Electronics, 10(20), 2558.
Omer, M.M., Adeeq, N.M., Ezazee, M., Lee, Y.S., Sadra Rajabi, M., & Rahman, R.A. (2022). Constructive and Destruc-tive Leadership Behaviors, Skills, Styles and Traits in BIM-Based Construction Projects. Buildings, 12, Page 2068.
Rajabi, M. S., Beigi, P., & Aghakhani, S. (2022). Drone Delivery Systems and Energy Management: A Review and Fu-ture Trends. arXiv preprint arXiv:2206.10765.
Rajabi, M. S., Radzi, A. R., Rezaeiashtiani, M., Famili, A., Rashidi, M. E., & Rahman, R. A. (2022). Key assessment cri-teria for organizational BIM capabilities: a cross-regional study. Buildings, 12(7), 1013.
Rajabi, M. S., Rezaeiashtiani, M., Radzi, A. R., Famili, A., Rezaeiashtiani, A., & Rahman, R. A. (2022). Underlying Fac-tors and Strategies for Organizational BIM Capabilities: The Case of Iran. Applied System Innovation, 5(6), 109.
Rajabi, M. S., Taghaddos, H., & Zahrai, S. M. (2022). Improving Emergency Training for Earthquakes Through Immer-sive Virtual Environments and Anxiety Tests: A Case Study. Buildings, 12(11), 1850.
United States. Bureau of Public Roads. (1964). Traffic assignment manual for application with a large, high speed com-puter (Vol. 2). US Department of Commerce, Bureau of Public Roads, Office of Planning, Urban Planning Division.
Roess, R. P., Prassas, E. S., & McShane, W. R. (2004). Traffic engineering. Pearson/Prentice Hall.
Saberi, M., & Figliozzi, M. A. (2010). A study of freeway volume-to-capacity ratio based travel time approximations using archived loop detector data. In 90th annual meeting of the transportation research board (pp. 1-23).
Shakerian, M., Rajabi, M. S., Tajik, M., & Taghaddos, H. (2022). Hybrid Simulation-based Resource Planning and Con-structability Analysis of RCC Pavement Projects. arXiv preprint arXiv:2204.05659.
Sun, H., Fu, M., Abdussalam, A., Huang, Z., Sun, S., & Wang, W. (2018, May). License plate detection and recognition based on the YOLO detector and CRNN-12. In International Conference On Signal And Information Processing, Networking And Computers (pp. 66-74). Springer, Singapore.
Tan, H. F., Yang, Y., & Zhang, L. R. (2017). Improved BPR function to counter road impedance through OD matrix es-timation of freight transportation. Journal of Highway and Transportation Research and Denelopment, 11(2), 97-102.
Li, Y., & McDonald, M. (2002, September). Link travel time estimation using single GPS equipped probe vehicle. In Proceedings. The IEEE 5th International Conference on Intelligent Transportation Systems (pp. 932-937). IEEE.
Zhao, L., & Li, Y. (2022). Identifying Origin-Destination Trips from GPS Data–Application in Travel Time Reliability of Dedicated Trucks. Promet-Traffic&Transportation, 34(1), 25-38.
Aghakhani, S., & Rajabi, M.S. (2022). A New Hybrid Multi-Objective Scheduling Model for Hierarchical Hub and Flex-ible Flow Shop Problems. available at: http://arxiv.org/abs/2205.06465 (accessed 3 September 2022).
Babiceanu, S., & Lahiri, S. (2022). Methodology for Predicting MAP-21 Interstate Travel Time Reliability Measure Target in Virginia. Transportation Research Record, 03611981221083290.
Beigi, P., Rajabi, M. S., & Aghakhani, S. (2022). An Overview of Drone Energy Consumption Factors and Models. arXiv preprint arXiv:2206.10775.
Berry, D. S. (1952). Evaluation of Techniques for Determining Over-All Travel Time. In Highway Research Board Pro-ceedings, 31.
Berry, D. S., & Green, F. H. (1950). Techniques for measuring over-all speeds in urban areas. In Highway Research Board Proceedings, 29.
Dowling, R.G., & Skabardonis, A. (2008). Urban Arterial Speed–Flow Equations for Travel Demand Models. Transpor-tation Research Board Conference Proceedings, 2.
Pourzahedi, H., & Ashtiani, H. (1995), Study of Link Travel Time Functions in Mashhad, Institute for Transportation Studies and Research, Tehran.
Hansen, S. (2020). Does the COVID-19 Outbreak Constitute a Force Majeure Event? A Pandemic Impact on Construc-tion Contracts. Journal of the Civil Engineering Forum, Universitas Gadjah Mada, 6(1), 201.
Holt, R.B., Smith, B.L., & Park, B. (2003). An Investigation of Travel Time Estimation Based on Point Sensors, Smart Travel Lab.
Hummer, J.E., Robertson, H.D., & Nelson, D.C. (1994). Manual of Transportation Engineering Studies. Institute of Transportation Engineering, by Prentice-Hall, Inc, Englewood Cliffs, New Jersey.
Ishak, S., & Al-Deek, H. (2002). Performance Evaluation of Short-Term Time-Series Traffic Prediction Model. Journal of Transportation Engineering, 128(6), 490–498.
Laroca, R., Severo, E., Zanlorensi, L.A., Oliveira, L.S., Gonçalves, G.R., Schwartz, W.R., & Menotti, D. (2018). A ro-bust real-time automatic license plate recognition based on the YOLO detector. 2018 International Joint Conference on Neural Networks (Ijcnn), IEEE, pp. 1–10.
Lin, H.-E., Zito, R., & Taylor, M. (2005). A review of travel-time prediction in transport and logistics. Proceedings of the Eastern Asia Society for Transportation Studies, Vol. 5, Bangkok, Thailand, pp. 1433–1448.
Lomax, T., Turner, S., Shunk, G., Levinson, H.S., Pratt, R.H., Bay, P.N., & Douglas, G.B. (1997). Quantifying Conges-tion. Volume 2: User’s Guide.
Lotfi, R., Kargar, B., Gharehbaghi, A., Afshar, M., Rajabi, M.S., & Mardani, N. (2022). A data-driven robust optimiza-tion for multi-objective renewable energy location by considering risk. Environment, Development and Sustainabil-ity, available at:https://doi.org/10.1007/s10668-022-02448-7.
Luo, X., Ma, D., Jin, S., Gong, Y., & Wang, D. (2019). Queue length estimation for signalized intersections using li-cense plate recognition data. IEEE Intelligent Transportation Systems Magazine, IEEE, 11(3), 209–220.
Tabibi, M., Moghadasnezhad, F., & Mohseni, M. (2012). Prediction of Travel Time in Road Network Using Neural Networks. The 11th Int. Conference on Traffic and Transportation Engineering, Tehran.
Yang, M., Liu, Y., & You, Z. (2009). The reliability of travel time forecasting. IEEE Transactions on Intelligent Trans-portation Systems, 11(1), 162-171.
Moeinifard, P., Rajabi, M. S., & Bitaraf, M. (2022). Lost Vibration Test Data Recovery Using Convolutional Neural Network: A Case Study. arXiv preprint arXiv:2204.05440.
Mudiyanselage, S.E., Nguyen, P.H.D., Rajabi, M.S., & Akhavian, R. (2021). Automated Workers’ Ergonomic Risk As-sessment in Manual Material Handling Using sEMG Wearable Sensors and Machine Learning. Electronics, 10(20), 2558.
Omer, M.M., Adeeq, N.M., Ezazee, M., Lee, Y.S., Sadra Rajabi, M., & Rahman, R.A. (2022). Constructive and Destruc-tive Leadership Behaviors, Skills, Styles and Traits in BIM-Based Construction Projects. Buildings, 12, Page 2068.
Rajabi, M. S., Beigi, P., & Aghakhani, S. (2022). Drone Delivery Systems and Energy Management: A Review and Fu-ture Trends. arXiv preprint arXiv:2206.10765.
Rajabi, M. S., Radzi, A. R., Rezaeiashtiani, M., Famili, A., Rashidi, M. E., & Rahman, R. A. (2022). Key assessment cri-teria for organizational BIM capabilities: a cross-regional study. Buildings, 12(7), 1013.
Rajabi, M. S., Rezaeiashtiani, M., Radzi, A. R., Famili, A., Rezaeiashtiani, A., & Rahman, R. A. (2022). Underlying Fac-tors and Strategies for Organizational BIM Capabilities: The Case of Iran. Applied System Innovation, 5(6), 109.
Rajabi, M. S., Taghaddos, H., & Zahrai, S. M. (2022). Improving Emergency Training for Earthquakes Through Immer-sive Virtual Environments and Anxiety Tests: A Case Study. Buildings, 12(11), 1850.
United States. Bureau of Public Roads. (1964). Traffic assignment manual for application with a large, high speed com-puter (Vol. 2). US Department of Commerce, Bureau of Public Roads, Office of Planning, Urban Planning Division.
Roess, R. P., Prassas, E. S., & McShane, W. R. (2004). Traffic engineering. Pearson/Prentice Hall.
Saberi, M., & Figliozzi, M. A. (2010). A study of freeway volume-to-capacity ratio based travel time approximations using archived loop detector data. In 90th annual meeting of the transportation research board (pp. 1-23).
Shakerian, M., Rajabi, M. S., Tajik, M., & Taghaddos, H. (2022). Hybrid Simulation-based Resource Planning and Con-structability Analysis of RCC Pavement Projects. arXiv preprint arXiv:2204.05659.
Sun, H., Fu, M., Abdussalam, A., Huang, Z., Sun, S., & Wang, W. (2018, May). License plate detection and recognition based on the YOLO detector and CRNN-12. In International Conference On Signal And Information Processing, Networking And Computers (pp. 66-74). Springer, Singapore.
Tan, H. F., Yang, Y., & Zhang, L. R. (2017). Improved BPR function to counter road impedance through OD matrix es-timation of freight transportation. Journal of Highway and Transportation Research and Denelopment, 11(2), 97-102.
Li, Y., & McDonald, M. (2002, September). Link travel time estimation using single GPS equipped probe vehicle. In Proceedings. The IEEE 5th International Conference on Intelligent Transportation Systems (pp. 932-937). IEEE.
Zhao, L., & Li, Y. (2022). Identifying Origin-Destination Trips from GPS Data–Application in Travel Time Reliability of Dedicated Trucks. Promet-Traffic&Transportation, 34(1), 25-38.