Designing a Smart Traffic Light Algorithm (HMS) Based on Modified Round Robin Algorithm
https://doi.org/10.24017/science.2017.1.8
Abstract views: 1629 / PDF downloads: 1043Abstract
Nowadays, traffic light system is very important to avoid car crashes and arrange traffic load. In the Sulaimani City / Iraq, there are many traffic problems such as traffic congestion or traffic jam and the amount of time provided manually to the traffic light system. This is the main difficulty that we try to solve. The traffic lights exist but still do not manage traffic congestion due to the fixed time provided for each lane regardless of their different load. Therefore, we are proposing to change the traditional traffic system to smart traffic system (adaptive system). This paper Focuses on the existing system (fixed system), then propose the adaptive one. The main crucial side effects of the existing system are:
- Emergency cases: congested traffics might block the way of emergencies for instance ambulance, which transports people to the hospital
- Wasting time of people generally and specially
- Delays, which lead people to not to be punctual, this means people arrive late to the work
- Wasting more fuels as staying more in the traffics, which affects the environment by increasing pollution.
Keywords:
Smart Traffic Light, HMS Algorithm, Modified Round Robin.
References
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[11].(http://www.brocade.com/content/html/en/configuration-guide/nos-700-l2guide/GUID-B75BD370-B251- 45A3-B3FD-87F54E35DC6E.html)
[2]. Wen and Yang, "A dynamic and automatic traffic light control system for solving the road Congestion problem", WIT Transactions on the Built Environment (Urban Transport),vol. 89, (2006), pp 307-316.
https://doi.org/10.2495/UT060311
[3]. Greater Amman Municipality, "Traffic report study 2007," (2007), http://www.ammancity, gov.jo/arabic/docs/GAM4-2007.pdf.
[4]. M. Tubaishat, Q. Qi, Y. Shang and H. Shi, "Wireless sensor-based traffic light control," IEEE CCNC, LasVegas, NV, USA, (2008), pp. 702-706.
https://doi.org/10.1109/ccnc08.2007.161
[5]. Y. Chong, C. Quek and P. Loh, "A novel neuro-cognitive approach to modelling traffic control and flow based on fuzzy neural techniques," Elsevier Expert Systems with Applications, vol. 36, (2009), pp. 4788- 4803.
https://doi.org/10.1016/j.eswa.2008.06.043
[6]. C. Xiangjun and Y. Zhaoxia, "Distributed traffic signal control approach based on multi-agent," IEEE FSKD,Tianjin, China, (2009) August, pp. 582-587.
[7]. W. Wu, W. Min and X. Sai, "A traffic signal control method based on large phase using fuzzy system and GA," IEEE FSKD, Tianjin, China, (2009), pp. 530-543.
[8]. C. Cai, C. K. Wong and B. G. Heydecker, "Adaptive traffic signal control using approximate dynamic programming," Elsevier Transportation Research Part C, vol. 17, (2009), pp. 456-474.
https://doi.org/10.1016/j.trc.2009.04.005
[9]. G. F. List and M. Cetin, "Modeling traffic signal control using petrinets," IEEE Transactions On Intelligent Transportation Systems, vol. 5, no. 3, (2004) September, pp. 177-187.
https://doi.org/10.1109/TITS.2004.833763
[10].J. Yousef and Ali, "Intelligent Traffic Light Flow Control System Using Wireless Sensors Networks," Journal of Information Science and Engineering, vol. 26, no. 3, (2010), pp. 753-768.
[11].(http://www.brocade.com/content/html/en/configuration-guide/nos-700-l2guide/GUID-B75BD370-B251- 45A3-B3FD-87F54E35DC6E.html)
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How to Cite
[1]
H. K. Hamarashid, M. H. R. Saeed, and S. Saeed, “Designing a Smart Traffic Light Algorithm (HMS) Based on Modified Round Robin Algorithm”, KJAR, vol. 2, no. 1, pp. 27–30, Jun. 2017, doi: 10.24017/science.2017.1.8.
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Published
30-06-2017
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Section
Pure and Applied Science
