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A Study of Destination Selection Model Based on Link Flows

机译:基于链接流的目的地选择模型研究

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Generating travel behavior based on artificial population and an activity plan is a conventional method for traffic simulation. As a complicated and important constituent of travel behavior, destination selection is a decision-making process for space transfer and has been studied extensively in the disaggregate model. However, existing selection models only focus on the psychology or custom of individuals from a microscopic perspective and rarely take account of the actual traffic state. This causes a large deviation in simulation results and thus results in some obstacles for application. In this paper, a new destination selection model based on link flows is proposed. Further, a searching algorithm for an observed link set is given, and compressed sensing is used in the model solution. Experiments demonstrate that this model can predict the actual traffic state in rush hours quite well. Therefore, it contributes to the credible simulation and computational experiments.
机译:基于人工种群和活动计划生成旅行行为是交通模拟的常规方法。作为旅行行为的一个复杂而重要的组成部分,目的地选择是空间转移的决策过程,并且在分类模型中得到了广泛的研究。但是,现有的选择模型仅从微观角度关注个人的心理或习惯,很少考虑实际的交通状况。这会导致模拟结果出现较大偏差,从而导致一些应用障碍。提出了一种基于链接流的目的地选择模型。此外,给出了用于观察的链接集的搜索算法,并且在模型解决方案中使用了压缩感知。实验表明,该模型可以很好地预测高峰时段的实际交通状况。因此,它有助于可靠的仿真和计算实验。

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