基于出行链的弹性需求随机网络配流模型

Trip-Chain-Based Stochastic Network Equilibrium Model with Elastic Demand

基于传统的4阶段模型在进行交通分配时忽略了出行链各出行间的相互关系,构造了一个基于出行链的弹性需求随机用户平衡分配模型,出行者数是整个出行链期望最小成本的函数,模型在配流时以整个出行链上的成本为基础.基于K最短路算法和连续平均法,设计了求解模型算法.通过算例验证了模型的合理性和算法的有效性,并比较了基于出行和出行链模型对分配结果的影响.文中结果有助于加深对交通行为的理解,为开发更为精确的交通规划模型打下了基础.

Traditional four-step travel forecasting model treats trip as separate, independent entities and fails to recognize the existence of linkage among trips. So this paper proposed a trip-chain-based stochastic network equilibrium formulation with elastic demand model. The total travel demand depends on the expected minimum perceived trip-chain travel cost and the model assigns traffic flow based on the total tripchain travel cost. A solution algorithm was developed to solve the trip-chain-based equilibrium model. It is based on K-shortest-paths algorithm coupled with the method of successive averages. A numerical example was used to illustrate the application of the proposed model and algorithm. This study can help to deepen the understanding of travel behavior and lay the foundation for the development of more accurate transportation planning model.