Predictive control of a hysteretic model - with applications to intelligent transportation system

Traffic flow models are used to characterize traffic behavior or to describe fundamental diagram (flow-density relationship) of traffic conditions. From the viewpoint of static traffic characteristic, these models mainly provide information of traffic states (free flow or congestion) and trend of traffic variation in a highway section or intersection. However, dynamic properties observed in short time interval reveal that hysteresis phenomenon are likely to occur during traffic state-transitions. The hysteresis phenomenon is visible in the transition paths both in the flow-density and velocity-density diagrams. The hysteresis is either due to drivers´ asymmetrical desired control speed in anticipation and relaxation modes or on traffic conditions of demand and supply in upstream and downstream. The hysteresis transition shows how the traffic quality evolves during minutes to hours. It is thus expected that a better traffic flow modeling and control can be achieved if hysteresis transition can be correctly modeled and used in traffic prediction. The paper develops a generalized mathematical hysteresis model based on Duhem operator. The proposed hysteresis model can describe hysteresis phenomenon in each state to state transition. An identification process is also applied to make our model more flexible in different traffic conditions. Besides modeling, issue related to flow stage transitions and congested trend can be predicted or estimated, and, accordingly, some traffic control strategies can also be devised. Simulation results are provided to illustrate transitions between free flow states and congested states. The simulation results also show that our model can represent the hysteresis phenomenon in different state transitions. The research is expected to shed light on intelligent transportation systems.