Urban Traffic Spillover Intelligent Coordinated Control Algorithm Study

Traffic has close relationship with the development of human beings. Traffic occurred as long as the birth of human beings, when they walked to find the proper living situation at ancicent time, till now we fly in the sky, ship in the sea, even cruised in atmos, traffic accompanies us everywhere in our life. Just as controdict always exists, traffic not only brings us the convenient living conditions, but causes a series of social problems, such as energy cost, exhaust emission, noise pollution, especially in nowadays China, many problems caused by traffic jam have become the frown topic of both government and general people.Traffic spillover is one the most serious kind of typical traffic jam. When the cumulative traffic flow queue becomes longer than the length of some direction in some link within a period of time because of the improper traffic plan or signal timing, and it is similar with the spillover of fliud in a container, we call this phenomenon traffic spillover. It casues great harm on the normal traffic order, if we do not take measuer in time, it will broadcast to other roads just like infectious virus when more and more roads occur traffic spillover, the cars in the network will be interlocked at signalized cross, and the whole city's traffic turns paralyzed, the city's function loses. It is clear that to carry out study on the mechanism, causes and control method of traffic spillover is meaningful and has great practical significance.Computer simulation is one the best way to verify whether the throries and algorithms we studied right and advanced. The key factor of one traffic flow simulation platform is traffic flow model.On the detailed study of former research paper, especiall the microscopic car following model, we propose random distribution traffic flow following model on the consideration of diverse driver's type, which takes the driver's sensitivity factor as probability distribution. In optimal velocity model, much study has been done on the straight line movement about open and close boundary condition, while we discover that in real life, curved road is also common, so we model the curved road following movement and analyzed its stability condition, the simulation result proved the model's feasibility. Traffic signal is widely used in urban traffic network, its impact on traffic flow is an important factor in traffic flow model, we proposed microscopic car following model with signal influence, and build leading car and following car model, simulation shows our model is in accordance with regular model.To control traffic spillover, we should grasp its mechanism and causes of formation in first, then propose the reasonable and effective recognition algorithm. Recognition is before control, and identification is the base of control, so these are the key problems of our study. On consideration of correlated traffic volume at adjacent crosses, signal timing plans, as well as the intersection delay model, we discussed the formation mechanism and causes of traffic overflow. On analysis of traditional traffic flow model, the transient maximum traffic density in a link is mined, and through the simulation experiment, the relationship among velocity, density, speed vs. density and traffic flow wave phenomenon were studied on the overflow condition sections. As we know, overflow identification is a job with strong subjective cognitive processes, and fuzzy theory in dealing with such problems have more advantages than traditional methods, so we presents a fuzzy theory based traffic overflow recognition algorithm, establishes a fuzzy inference machine, and verify its correctness with simulation.Single traffic overflow is the most common form, from the view of network physical structure, single section overflow is alsothe base unit of this kind of jam form. Compared with single intersection signal control, overflow control relates to overflow much more factors than traditional control algorithm, such as spillover dissipation and the minimum traffic flow delays of adjacent intersections those two composite indexes, therefore it is more complex. Meanwhile, the control process involves numerous artificial empirical and traffic knowledge, so the artificial intelligence was thought as the main instruction, we proposed the overflow intelligent controller. The controller is composed by the spillover relief phase offset fuzzy inference machine, traffic phase number and sequence setting expert system, traffic overflow neural network predictor, and phase time fuzzy reasoning machine four parts. It can implement "overflow recognition, phase offset setting, phase time reasoning, traffic flow prediction,sequence setting,control executive and control effect evaluation logical process. On our self-developed traffic flow simulation platform, many simulations were carried out respectively, and compared with forced control method, the results show that our algorithm has better performance in solving traffic overflow than forced control and can better deal with traffic spillover problem.At present, thouth current microscopic traffic simulation software, i.e. Paramics and VISSIM, provide second development interface, is still inadequate in the study of develop independent traffic flow model and intelligent control algorithm. So we upgrade our own traffic flow simulation system based on this specific traffic overflow problem. It expounds the platform architecture, important simulation entities and their interrelations, vehicle control logic and signal control logic and its relationship to each other, as well as traffic overflow simulation set and an example of its application. The aim is to develop a kind of independent intellectual property rights simulation platform.Finally, the full text of the final research innovations and shortcomings are summarized, and the further research direction is prospected.