Intersection Traffic Demand Estimation On Urban Road Using Dynamic Traffic Flow Data

Transportation demand forecast is one of the critical technology of the intelligent transport operation?supervising and controlling for urban highway transportation. The current transportation demand data comes from the traffic capacity detected by detector, but it's apparently unconformity with practical situation. The research aims at pointing out the difference between practical transportation demand and detection transportation demand, and put forward a type of new transportation demand estimation algorithm using the algorithm that based on occupancy and the demand estimation method which based on cumulative curve. The major research emphasis on the algorithm of queue length estimate which based on occupancy and flow, and the demand estimation which based on cumulative curve.Queue length and traffic demand has a close relationship:When the flow rate is less than capacity, the detected flow rate is equal to the traffic demand; when the flow is greater than capacity, more than usual, the queuing at this time of detection has exceeded the detection range, subsequent traffic will undetectable, then you can use the relationship between the queuing length and traffic demand of Cumulative Curve Theory to achieve dynamic estimation of traffic demand. The key research contents are as follows:In the aspect of queue length, this article based on queue length estimate algorithm of occupancy and flow, analyzing and verifying the proportion relation of occupancy^ flow and others parameters between queue length. On this basis, the queue length model of urban highway junction was constructed and the comparability and veracity evaluation was marched.In the aspect of demand estimation, this article based on cumulative curve algorithm, the proportion relation between traffic ability?queue length?queue density and others parameters were analyzed and verified. The queue length acquired before was imported to impetrate transportation demand which was compared with practical transportation to march algorithm veracity evaluation. While flow is less than transportation demand, flow equals to demand. Therefore, the used precondition of this algorithm is traffic flow exceeds traffic capacity.The results which based on occupancy and flow's queue length and cumulative curve's demand estimation indicates:The traffic system which put traffic flow directly as demand has major difference with practical transportation demand. The suggested demand estimation algorithm can decrease the difference. The research provides reference for the demand estimation of transportation planning and correlation research.