投稿論文 施設種間推移を考慮した歩行者回遊行動シミュレーション・モデルの開発
投稿論文 施設種間推移を考慮した歩行者回遊行動シミュレーション・モデルの開発
复制标题
提交论文：考虑设施类型之间变化的行人迁移行为模拟模型的开发
作者：
兼田 敏之;横井 祥晃;高橋 俊一
我们在本文中的目的是建立和测试一个模型，该模型通过使用时空选择启发式对购物中心的行人购物行为进行分类和识别。特别是，将时间局部距离最小化、总距离最小化和全局距离最小化启发式选择规则与空间最近目的地导向、最远目的地导向和中间目的地导向的启发式选择规则相结合，对购物行人的停车顺序和路径选择进行分类识别。首先，研究了几种具有单个入口节点和几个停止节点的线性网络。对于这些网络，全局距离最小化和空间选择启发式方法可以很好地分类和识别站点序列。虽然局部距离最小选择规则可以很好地识别行人的路径选择，但还需要另一种启发式方法来改进识别。为了提高模型的识别能力，本文提出了一种新的、面向吸引力街道的启发式算法。这条选择规则表明，购物行人在完成购物之前永远不会离开有吸引力的购物街。然后将该模型应用于荷兰费尔德霍芬市中心行人购物行为的实证数据。应用结果表明，基于选择启发式的模型可能有助于分类和识别购物中心中购物行人的停车顺序和路线选择行为。
Our aim in this paper is to build and test a model which classifies and identifies pedestrian shopping behaviour in a shopping centre by using temporal and spatial choice heuristics. In particular, the temporal local-distance-minimising, total-distance-minimising, and global-distance-minimising heuristic choice rules and spatial nearest-destination-oriented, farthest-destination-oriented, and intermediate-destination-oriented choice rules are combined to classify and identify the stop sequences and route choices of shopping pedestrians. First, several linear networks with a single entry node and a few stop nodes are investigated. For these networks, the global-distance-minimising and spatial choice heuristics classify and identify the sequences of stops very well. Although the local-distance-minimising choice rule identifies pedestrian route choice quite well, another heuristic is needed to improve the identification. In this paper a new, attractive-street-oriented heuristic is suggested to improve the identification ability of the model. This choice rule suggests that shopping pedestrians will never leave the attractive shopping streets before completing their shopping. The model is then applied to empirical data of pedestrian shopping behaviour in Veldhoven City Centre in The Netherlands. The findings of this application suggest that the model based on choice heuristics might be useful to classify and identify the sequences of stops and route choice behaviour of shopping pedestrians in a shopping centre.