Abstract: To describe the interaction and influence of urban transit pricing and travel choice behavior under traffic network, travel mode choice and route choice were integrated in the same network and a bi-level programming model of urban transit pricing uas established. There were three objectives in the upper programming model, enterprise profit maximization, passenger travel cost minimization and the maximization of social welfare. The lower model uas a stochastic user equilibrium assignment model under multimodal urban transportation network with elastic demand. An improved genetic algorithm uas used to solve the whole model, and an iterative algorithm based on diagonalization and MSA uas provided to solve the lower model. Finally a simple numeral example use given. The results indicate that the government, enterprises and passengers can get higher earnings with bus transit price determined by using bi-level programming model than traditional static price. And the upper model to maximize social welfare as the objective function can represent most people's interest in social groups, whose optimization effect is the most ideal.

Key words: traffic engineering, pricing model, bi-level planning, urban transit, multimodal urban transportation network

摘要： 为描述多方式城市交通网络下公交定价与出行选择行为的相互作用与影响,将出行方式选择与路径选择涵盖于同一网络,建立了上层模型分别以企业利润最大化、乘客出行成本最小化和社会福利最大化为目标函数,下层模型为多方式弹性需求随机用户配流模型的公交定价双层规划模型。运用改进遗传算法对模型整体进行求解,下层模型采用综合对角化算法和MSA算法的组合求解算法。最后,设计了一个算例以说明模型应用。结果表明:运用双层规划模型所确定的公交票价较传统静态票价可使政府、企业及出行者三方都获得更高收益,且上层模型以社会福利最大化为目标函数能代表社会群体中多数人利益,优化效果最为理想。

关键词: 交通工程, 定价模型, 双层规划, 公共交通, 多方式城市交通网络