Cerioli Adamo, Caselli Barbara, Jeanne Marinelli Lea, Vezzani Alessandro, Burioni Raffaella
Department of Mathematics, Physics and Computer Science, University of Parma, Parco Area delle Scienze, 7/A, 43124, Parma, Italy.
Department of Engineering and Architecture, University of Parma, Parco Area delle Scienze, 181/A, 43124, Parma, Italy.
Sci Rep. 2025 Sep 2;15(1):32274. doi: 10.1038/s41598-025-17185-w.
When discussing urban life, pedestrian accessibility to all main services is crucial for fostering social interactions, promoting healthy lifestyles, and reducing pollution. This is especially relevant in coherent urban agglomerations like university campuses, which feature a high concentration of streets and social facilities. Using WiFi data, we study pedestrian movements within a confined geometric network representing the pathways on a university campus. We estimate the level of crowding in each arc of the network and identify pedestrian flows along all possible paths, measuring the entropy and robustness of the network. In particular, we calculate the information gain achieved through the use of WiFi data and we assess how pedestrian traffic redistributes within the network after the removal of individual arcs. Our results can be used to facilitate the investigation of the current state of walkability across the university campus while also testing a set of methods for analyzing urban complex networks, potentially allowing us to pinpoint areas in urgent need of road maintenance and enhancement.
在讨论城市生活时，行人能够便捷地到达所有主要服务设施对于促进社交互动、倡导健康生活方式以及减少污染至关重要。这在诸如大学校园这样连贯的城市聚集体中尤为重要，大学校园街道和社会设施高度集中。我们利用WiFi数据，研究在一个代表大学校园路径的有限几何网络内的行人移动情况。我们估计网络中每条弧段的拥挤程度，并识别所有可能路径上的行人流量，测量网络的熵和稳健性。特别是，我们计算通过使用WiFi数据所实现的信息增益，并评估在移除单个弧段后行人交通如何在网络内重新分布。我们的结果可用于促进对大学校园当前步行适宜性状况的调查，同时还能测试一套分析城市复杂网络的方法，这有可能使我们精准定位急需道路维护和改善的区域。
