How do cyclists make their way? - A GPS-based revealed preference study in Copenhagen
How do cyclists make their way? - A GPS-based revealed preference study in Copenhagen
复制标题
骑自行车的人如何前行？
DOI：
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发表时间：
2018
影响因子：
5.7
通讯作者：
J. Jacobsen
中科院分区：
文献类型：
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作者：
H. Skov;B. Barkow;T. Lundhede;J. Jacobsen
摘要本研究的目的是确定人类导航在多大程度上受到我们周围环境的感知或已经建立的认知地图知识的影响。动机是有助于人类导航的知识，并告知规划与骑自行车的路线偏好和“支付意愿”（在运输距离与效用/负效用的路线特征）的估计。其核心方法是观测路径数据的选择建模。在哥本哈根（丹麦）的183名骑自行车的人进行了一千二百六十七次旅行的GPS记录。这些行程与数字道路和路径网络进行了地图匹配，从而生成了选择集：一个用于导航，其受直接环境感知的影响，包括连接到网络节点的边一个用于基于先验知识的导航，包括行程本身和由标记算法生成的多个替代路线（下文称为路线数据集）。结果表明，基于路线和边缘数据的特性的选择可以被估计，并提供关于骑自行车者的偏好的合理且重要的参数估计。长度是重要的和消极的，说明骑自行车的人-其他一切保持平等-更喜欢骑自行车较短的距离。关于自行车道的特性，存在的交通信号灯和道路类型的偏好显示出类似的结果，两种类型的数据，最重要的是，与设施，如遏制轨道和隔离自行车道的路线，显着首选。该研究的结论是，骑自行车的寻路可以建模为基于边缘数据集和路线数据集的选择，因此，可能会受到感知信息和先验知识的影响。我们建议，未来的分析运动和路线偏好考虑到这两种模式的实际运动可能是基于两者的组合，因为评估的直接，可感知的环境的影响，可以提供信息不被认为是在寻路的方法。在我们的情况下，例如发现了沿路线沿着的偏好差异，但这可以在未来的研究中扩展到还包括动态方面，如天气和拥挤。
ABSTRACT It is the objective of the study to determine the extent to which human navigation is affected by perceptions of our immediate surroundings or by already established knowledge in terms of a cognitive map. The motivation is to contribute to the knowledge about human navigation and to inform planning with estimates of bicyclists’ route preferences and ‘willingness-to-pay’ (in terms of transport distance vs. utility/disutility of route characteristics). The core method is choice modelling of observed route data. Thousand two hundred and sixty seven trips performed by 183 cyclists in Copenhagen (Denmark) were recorded by GPS. The trips were map-matched to a digital road and path network, which enabled the generation of choice sets: one for navigation as influenced by perception of immediate surroundings, comprising edges connected to network-nodes (hereafter called the edge dataset), and one for navigation based on a priori knowledge, comprising the trip itself and a number of alternative routes generated by a labelling algorithm (hereafter called the route dataset). The results document that choices based on characteristics of both the route and the edge data can be estimated and provide reasonable and significant parameter estimates regarding cyclists’ preferences. Length was significant and negative, illustrating that cyclists – everything else kept equal – prefer to bike shorter distances. Preferences regarding characteristics of bike path, presence of traffic lights and road types show similar results to the two types of data; most importantly that routes with facilities, such as curbed tracks and segregated bikeways, were significantly preferred. The study concludes that cyclists’ wayfinding can be modelled as choices based on both an edge dataset and a route dataset and, thus, may be influenced by both perceived information and a priori knowledge. We suggest that future analyses of movement and route preferences take both modes into account as actual movement may be based on a combination of the two and because assessment of the influence of the immediate, perceivable surroundings can provide information not to be considered in a wayfinding approach. In our case differences in preferences along the route is for example found, but this can be expanded in future studies to also include dynamic aspects such as weather and crowding.