Abstract
With the advancement of society, transport plays an increasingly important role in human society, but more and more traffic problems are constantly plagued mankind. Aiming at the problems facing the traffic and improve the traffic situation, the polling system is applied to intelligent traffic control system in this paper. Based on the type of paper feed of the arrival rate theory, the vehicle arrives at different rates, the wait time is different. Arrival rate is high, the longer the waiting time. Then we simulate system and get the simulation results, and compare the theoretical and simulation results. Finally, the theory to practical systems is using in microprocessor hardware simulation, and actual results further validate the correctness. Through the intelligent traffic control system, a good solution to traffic jam phenomenon is got and traffic management plays an important role.
Publisher
Trans Tech Publications, Ltd.
Reference9 articles.
1. NadhirMessai, Philippe Thomas, Dimitri Lefebvre and Abdellah El Moudni, Neural networks for local monitoring of traffic magnetic sensors Control, Engineering Practice, Volume 13, Issue 1, January (2005).
2. Srinivasan, D., Choy, M.C. and Cheu, R.L., Neural Networks for Real-Time Traffic Signal Control, ITS (7), No. 3, September 2006, pp.261-272.
3. Marco Wiering, Jilles Vreeken, Jelle van Veenen, and Arne Koopman. Simulation and optimization of traffic in a city. In IEEE Intelligent Vehicles symposium (IV'04), June (2004).
4. Queue-length analysis of continuous-time polling system with vacations using M-gated services[A]. Applied Mechanics and Materials. 2010, Page(s): 427-430.
5. Liu Qianlin, Zhao Dongfeng,Zhao Yifan. An efficient priority service model with two-level-polling scheme[J]. High Technology Letters, 2011, 17(3): 245-251.