Research On Active On-Ramp Metering Method For Freeway Based On The Stochasticity Of Operational Capacity

In recent years, along with the rapid increase of vehicles in our country, traffic congestions occur frequently. This proposes higher challenges for on-ramp control. The passive control methods are currently used in freeway on-ramps, which is difficult to eliminate future recurrent congestions in advance and solve the problem of coordinated ramp-metering parameter values affected by stochasticity of freeway operational capacity on the mainline. Therefore, this paper raises a new idea and method that the prediction of traffic state mechanism combining with stochasticity of freeway operational capacity is integrated into the heuristic ramp-metering mode:Comparing with the time series prediction methods, the ARIMA(p,d,q) algorithm is selected to predict the traffic flow and occupancy of freeway mainline. Short-term traffic state prediction is realizing by using k-means algorithm and the predicted parameters to estimate traffic state.Based on the traffic state division, the value of the mainline operational capacity is filtered for statistical analysis. By the analysis of the mainline operational capacity distribution function and the derived expression, traverse threshold is obtained reflecting the stochasticity of mainline. The result of the study indicates that the value of the mainline operational capacity is different in different traffic state and it presents normal distribution characteristics in the same traffic state.The heuristic rules are designed utilizing heuristic coordinated ramp-metering type. ALINEA algorithm is selected on the local level and the prediction of traffic state and stochasticity of freeway operational capacity is integrated into the coordination level. Finally, the ramp metering rate is obtained through competitive comparison and ramp inflow causing future mainline congestions is distributed ahead of time. The result of simulation and analysis indicates that the method is better than ALINEA algorithm and it can maintain a stable traffic state and eliminate future recurrent congestions in advance.