Elastic demand with weibit stochastic user equilibrium flows and application in a motorised and non-motorised network
Elastic demand with weibit stochastic user equilibrium flows and application in a motorised and non-motorised network
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DOI：
10.1080/23249935.2014.944241
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发表时间：
2015-02
期刊：
影响因子：
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通讯作者：
S. Kitthamkesorn;A. Chen;Xiangdong Xu
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文献类型：
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作者：
S. Kitthamkesorn;A. Chen;Xiangdong Xu
本文提出了一个新的弹性需求（艾德）随机用户平衡（SUE）模型，并将其应用于组合交通方式划分和交通分配（CMSTA）问题。这个新的模型，称为路径大小weibit（PSW）SUE模型与艾德，是基于威布尔分布，这不需要通常施加在多项logit（MNL）模型与Gumbel分布的同分布假设。此外，还包括一个路径大小因子，以校正并非真正独立的路由的选择概率（即MNL模型中通常需要的另一个假设）。建立了PSW-SUE-艾德模型的等价数学规划（MP）公式，同时考虑出行选择和路径选择。基于艾德函数确定出行选择，该函数基于Weibull分布的对数预期感知成本明确考虑网络服务水平以确定出行需求，而路线选择考虑了相对于不同行程长度的路线重叠和不相同的感知方差。所提出的MP配方的定性性质严格证明。基于路径的部分线性化算法结合自调节平均线搜索策略，解决PSW-SUE-艾德模型及其应用CMSTA问题。数值算例也证明了所提出的PSW-SUE-艾德模型的功能，以及在一个双模态网络与机动化和非机动化模式的选择的真实案例研究。
In this paper, we propose a new elastic demand (ED) stochastic user equilibrium (SUE) model with an application to the combined modal split and traffic assignment (CMSTA) problem. This new model, called the path-size weibit (PSW) SUE model with ED, is derived based on the Weibull distribution, which does not require the identically distributed assumption typically imposed in the multinomial logit (MNL) model with the Gumbel distribution. In addition, a path-size factor is included to correct the choice probabilities of routes that are not truly independent (i.e. another assumption typically required in the MNL model). Equivalent mathematical programming (MP) formulation of the PSW-SUE-ED model is developed to simultaneously consider both travel choice and route choice. The travel choice is determined based on the ED function that explicitly considers the network level of service based on the logarithmic expected perceived cost of the Weibull distribution to determine the travel demand, while the route choice accounts for both route overlapping and non-identical perception variance with respect to different trip lengths. Qualitative properties of the proposed MP formulation are rigorously proved. A path-based partial linearisation algorithm combined with a self-regulated averaging line search strategy is developed for solving the PSW-SUE-ED model and its application to the CMSTA problem. Numerical examples are also provided to demonstrate the features of the proposed PSW-SUE-ED model as well as a real-case study in a bi-modal network with motorised and non-motorised mode choices.