Research On Coordinated Control Of Freeway On-ramp Based On SWARM1 Algorithm

Demand of short intercity travel is piling up with the rapid development of economy and society and the increasing motor vehicles, but as a result of the enlargement of city scale, freeway which reaches inside of city and combines with urban expressway shares great pressure from inner-city traffic. Freeway and urban expressway differs from technology class to service level, so the lack of control measures and the traffic information island in the connecting areas of two kinds of roads strangled the service level of freeway. And made the connecting area not only the blind zone of traffic management, but also the scene of traffic jams. So ramp control can raise operation efficiency and service level of freeway, at the same time reduce rush-hour traffic jam.Firstly, the achievements and applications of traffic prediction and ramp control in China and abroad are roundly summarized and comparative analyzed, after this technical proceeding of the research is confirmed. Then taking Beijing-Tianjin-Tanggu Freeway as an example, the traffic characteristic is analyzed and the traffic state is divided applying CA Fuzzy Clustering. Particularly 14 inference rules are set by Fuzzy Reasoning choosing traffic volume and density as parameters to divide the traffic crowding using the adaptive Neural Network-Fuzzy Reasoning System. Secondly, ramp control model based on SWARM1 algorithm is established and traffic crowding generated from traffic volume prediction which got by nonparametric regression is used to help control the ramp. Taking both single point control and multi-point coordinated control into consideration to improve the ramp control model. Finally, simulation analysis of freeway ramp coordinated control is accomplished applying VC6.0. Both results are satisfied:in prediction, the precision of 2 minutes traffic prediction are above average 85%; in control, it turns out to lessen traffic pressure and expand the capacity.