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Algorithm for Creating Optimized Green Corridor for Emergency Vehicles with Minimum Possible Disturbance in Traffic


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[1] Yadav, S. & Rishi, R. (2021). Secure and Authenticate Communication by using SoftSIM for Intelligent Transportation System in Smart Cities. Journal of Physics: Conference Series 1767, 2021, 012049. DOI: 10.1088/1742-6596/1767/1/012049. Search in Google Scholar

[2] Yadav, S. & Rishi, R. (2021). A systematic and critical analysis of the developments in the field of intelligent transportation system. Advances in Dynamical Systems and Applications 16(2), 901-912. Retrieved November 15, 2021, from the World Wide Web: https://www.ripublication.com/adsa21/v16n2p39.pdf Search in Google Scholar

[3] Karmakar, G., Chowdhury, A., Kamruzzaman, J. & Gondal, I. (2020). A Smart Priority Based Traffic Control System for Emergency Vehicles. IEEE Sensors Journal. DOI: 10.1109/JSEN.2020.3023149. Search in Google Scholar

[4] Wu, W., Huang, L. & Du. R. (2020). Simultaneous Optimization of Vehicle Arrival Time and Signal Timings within a Connected Vehicle Environment. Sensors 191(20). DOI: 10.3390/s20010191. Search in Google Scholar

[5] Firooze, S., Ra, M. & Zenouzzadeh, S.M. (2018). An optimization model for emergency vehicle location and relocation with consideration of unavailability time. Scientia Iranica E 25(6), 3685-3699. DOI: 10.24200/sci.2017.20022. Search in Google Scholar

[6] Ližbetin, J., Kampf, R., Jeřábek, K. & Caha. Z. (2016). Practical Application of the Comparative Analysis of Direct Road Freight Transport and Combined Transport. Transport Means – Proceedings of the International Conference. (pp. 1083 – 1087). DOI: 10.1186/s12544-018-0319-3. Search in Google Scholar

[7] E. Nelson & D. Bullock. (2000). Impact of Emergency Vehicle Preemption on Signalized Corridor Operation. Transportation Research Record: Journal of the Transportation Research Board, SAGE Journals 1727(1), 1-11. DOI: 10.3141/1727-01. Search in Google Scholar

[8] Anderson, P. & Daganzo, C. (2018). Effect of Transit Signal Priority on Bus Service Reliability. arXiv.org- math - arXiv:1806.09254, 2018. Retrieved November 1, 2021, from the World Wide Web: https://arxiv.org/abs/1806.09254 Search in Google Scholar

[9] Christofa, E. & Skabardonis, A. (2011). Traffic Signal Optimization with Application of Transit Signal Priority. Transportation Research Record: Journal of the Transportation Research Board, SAGE Journals 2259(1), 192-201. DOI: 10.3141/2259-18. Search in Google Scholar

[10] Singh, M. & Tamura. H. (1974). Modelling and hierarchical optimization for oversaturated urban road traffic networks. International Journal of Control, T&F online 20(6), 913-934. DOI: 10.1080/00207177408932791. Search in Google Scholar

[11] Nguyen, J., Farrenkopf, T., Guckert, M., Powers, S. & Urquhart, N. (2021). An Overview of Agent-Based Traffic Simulators. Retrieved November 29, 2021, from the World Wide Web: https://arxiv.org/pdf/2102.07505.pdf Search in Google Scholar

[12] Song, J., Wu, Y., Xu, Z. & Lin., X. (2014). Research on car-following model based on SUMO. In Proc. of the 7th IEEE/International Conference on Advanced Infocomm Technology, Fuzhou, China, 2014. DOI: 10.1109/ICAIT.2014.7019528. Search in Google Scholar

[13] Krajzewicz, D. & Erdmann, J. (2013). SUMO’s Road Intersection Model. In Institute of Transport Research: Publications, First International Conference, SUMO, Berlin, Germany, 2013. Retrieved October 12, 2021, from the World Wide Web: https://core.ac.uk/download/pdf/31007126 Search in Google Scholar

[14] Alemzadeh, S., Moslemi, R., Sharma, R. & Mesbahi, M. (2020). Adaptive Traffic Control with Deep Reinforcement Learning: Towards State-of-the-art and Beyond. arXiv - CS - Machine Learning (IF), 2020. Retrieved October 9, 2021, from the World Wide Web: https://arxiv.org/abs/2007.10960 Search in Google Scholar

[15] Bartuška, L., Čejka J & Caha Z. (2015). The Application of Mathematical Methods to the Determination of Transport Flows. Nase More. Dubrovnik: University of Dubrovnik, Special Issue 62, 91-96. DOI:10.17818/NM/2015/SI1. Search in Google Scholar

[16] Bartuška, L., Jeřábek K. & Chenguang, Li. (2017). Determination of Traffic Patterns on urban roads. Communications. Žilina: University of Žilina, EDIS 19(2), 103-108. DOI: 10.26552/com.C.2017.2.103-108. Search in Google Scholar

[17] Gomez, J., Romo, J., Cabrera, R., Cruz, A. & Molina. J. (2021). Traffic system Control System Based on Inteligent Transportation System and Reinforcement Learning. Electronics, MDPI 10(19), 2363. DOI: 10.3390/electronics10192363. Search in Google Scholar

[18] Mnih, V., Kavukcuoglu, K., Silver, D., Graves, A., Antonoglou, I., Wierstra, D. & Riedmiller, M. (2013). Playing Atari with Deep Reinforcement Learning. arXiv.org - cs - arXiv:1312.5602, 2013. Retrieved October 2, 2021, from the World Wide Web: https://arxiv.org/abs/1312.5602 Search in Google Scholar

[19] Palmer, P. & O’Connell, D. (2009). Regression Analysis for Prediction: Understanding the Process. Cardiopulmonary Physics Therapy Journal 20(3), 23–26. Retrieved November 1, 2021, from the World Wide Web: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2845248/ Search in Google Scholar

[20] Huang, B., Zhou, M. & Zhang, G. (2015). Synthesis of Petri net supervisors for FMS via redundant constraint elimination Automatica, Elsevier 61, 156-163. DOI: 10.1016/j.automatica.2015.08.011. Search in Google Scholar

eISSN:
2336-3037
Language:
English
Publication timeframe:
Volume Open
Journal Subjects:
Business and Economics, Business Management, Industries, Transportation, Logistics, Air Traffic, Shipping