Review of Computational Based Algorithms for Avoiding Congestion in Intelligence Traffic Management
Abstract
Roadways remain a primary mode of commuting, and increasing population has led to escalating traffic congestion. In our era of rapid technological advancements, traffic signals require continual improvement as they are central to the traffic system. Efficiency and optimization are crucial for modern cities, making Intelligent Transportation Systems (ITS) vital in addressing traffic challenges. Technological advancements now allow for the storage and processing of vast amounts of data, facilitating effective and efficient traffic management. This paper reviews various algorithms that have been tested and evaluated to ensure optimal traffic management.
Full Text:
PDFReferences
S. Rakesh & Nagaratna P H., (2022). A New Method to Control Traffic Congestion by Calculating Traffic Density International Journal of. Intelligent Systems and Applications in Engineering ,ISSN:2147-6799 www.ijisae.org.
Samir A., Elsagheer M &Khaled A., Alsalfan: Intelligent Traffic Management System Based on the Internet of Vehicles (IoVTh) ;Hindawi Journal of Advanced Transportation, Article ID 4037533, https://doi.org/10.1155/2021/4037533.
Nikolaev A.B., Aung M. T., Myo L. A., Myo M. K.& Aung N. Z. (2017) Algorithms For Traffic Management In The Intelligent Transport Systems. International Journal of Advanced Studies, Vol. 7.
Ang L. M., Seng K. P., Ijemaru G. K., and Zungeru A. M., (2019). Deployment of IoV for smart cities: applications, architecture, and challenges. IEEE Access 7/6473–6492.
Chao, K. H., & Chen, P. Y. (2014). An intelligent traffic flow control system based on radio Frequency identification and wireless sensor networks. International journal of distributed sensor networks 10(5)/694545.
Drapalyuk M., Dorokhin S., and Artemov A.,(2020). Estimation of efficiency of different traffic management methods in isolated area. Transportation Research Procedia, 50/106–112.
Mirialys M. Julio A. S. Piedad G., & Francisco J. M., (2020). On the use of Artificial Intelligence techniques in Intelligent Transportation Systems. iNiT Research Group University of Zaragoza, Spain.
Roopa R. & Shanta R., (2021). Intelligent Traffic Management: A Review Of Challenges, Solutions, And Future Perspectives; Transport and Telecommunication Journal, 22(2)/163–182.
Tang F. Kawamoto Y. Kato N. & Liu J., (2020). Future intelligent and secure vehicular network toward 6G: machine-learning approaches. Proceedings of the IEEE, 108(2)/292–307.
Unadkat V. Sayani P. Kapadia H. Shah P. & Dalvi H., (2018). Automated System for Detecting Distracted Driver. 4th International Conference on Computing Communication and Automation (ICCCA), Greater Noida, India.
Vedant S. Vyom U. & Pratik K, (2019). Intelligent Traffic Management System International Journal of Recent Technology and Engineering. (IJRTE) ISSN: 2277-3878, 8(3).
Vishnu M., Rajalakshmi M., & Nedunchezhian, R., (2018). Intelligent traffic video surveillance and accident detection system with dynamic traffic signal control. Cluster Computing. 21. 10.1007/s10586-017-0974-5
Yousef A., Shatnawi A., and Latayfeh M., (2019). Intelligent traffic light scheduling technique using calendar-based history information. Future Generation Computer Systems, 91/124–135.
Zhou H. Xu W. Chen J. & Wang W., (2020). Evolutionary V2X technologies toward the internet of vehicles: challenges and opportunities. Proceedings of the IEEE, 108(2) 308–323.
Refbacks
- There are currently no refbacks.