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The analysis of pedestrian GPS datasets is fundamental to further advance on the study and the design of walkable cities. The highest resolution GPS data can characterize micro-mobility patterns and pedestrians' micro-motives in relation to…

Cities are complex systems that demand integrated approaches, with increasing attention focused on the neighborhood level. This study examines the interplay between expert-based mapping and citizen science in the Primer de Maig neighborhood…

物理与社会 · 物理学 2025-05-20 Ferran Larroya , Josep Perelló , Roger Paez , Manuela Valtchanova

Studies using massive, passively data collected from communication technologies have revealed many ubiquitous aspects of social networks, helping us understand and model social media, information diffusion, and organizational dynamics. More…

物理与社会 · 物理学 2015-02-04 Jameson L. Toole , Carlos Herrera-Yague , Christian M. Schneider , Marta C. Gonzalez

Social navigation and pedestrian behavior research has shifted towards machine learning-based methods and converged on the topic of modeling inter-pedestrian interactions and pedestrian-robot interactions. For this, large-scale datasets…

计算机视觉与模式识别 · 计算机科学 2024-10-28 Allan Wang , Daisuke Sato , Yasser Corzo , Sonya Simkin , Abhijat Biswas , Aaron Steinfeld

The growth of mobile sensor technologies have made it possible for city councils to understand peoples' behaviour in urban spaces which could help to reduce stress around the city. We present a quantitative approach to convey a collective…

人机交互 · 计算机科学 2020-07-07 Thomas Johnson , Eiman Kanjo , Kieran Woodward

This study presents an initial framework for distinguishing group and single pedestrians based on real-world trajectory data, with the aim of analyzing their differences in space utilization and emergent behavioral patterns. By segmenting…

计算机视觉与模式识别 · 计算机科学 2025-08-27 Amartaivan Sanjjamts , Morita Hiroshi

Citizen science biodiversity data present great opportunities for ecology and conservation across vast spatial and temporal scales. However, the opportunistic nature of these data lacks the sampling structure required by modeling…

机器学习 · 计算机科学 2025-04-15 Nahian Ahmed , Mark Roth , Tyler A. Hallman , W. Douglas Robinson , Rebecca A. Hutchinson

This study analyzes mobile phone data derived from 10 million daily active users across the United States to better understand the spatio-temporal activity patterns of users in Central Park, New York. The aim of this initial investigation…

计算机与社会 · 计算机科学 2018-01-09 Wenfei Xu

Mobility is a fundamental feature of human life, and through it our interactions with the world and people around us generate complex and consequential social phenomena. Social segregation, one such process, is increasingly acknowledged as…

物理与社会 · 物理学 2025-05-23 Yitao Yang , Erjian Liu , Bin Jia , Ed Manley

We report on two series of experiments, conducted in the frame of two different collaborations designed to study how pedestrians adapt their trajectories and velocities in groups or crowds. Strong emphasis is put on the motivations for the…

The current state-of-the-art in user mobility research has extensively relied on open-source mobility traces captured from pedestrian and vehicular activity through a variety of communication technologies as users engage in a wide-range of…

计算机视觉与模式识别 · 计算机科学 2024-08-15 Sinjoni Mukhopadhyay King , Faisal Nawab , Katia Obraczka

In animal societies as well as in human crowds, many observed collective behaviours result from self-organized processes based on local interactions among individuals. However, models of crowd dynamics are still lacking a systematic…

物理与社会 · 物理学 2009-09-30 Mehdi Moussaid , Dirk Helbing , Simon Garnier , Anders Johansson , Maud Combe , Guy Theraulaz

Recently, pedestrian behavior research has shifted towards machine learning based methods and converged on the topic of modeling pedestrian interactions. For this, a large-scale dataset that contains rich information is needed. We propose a…

计算机视觉与模式识别 · 计算机科学 2023-10-02 Allan Wang , Abhijat Biswas , Henny Admoni , Aaron Steinfeld

Understanding driving behaviors is essential for improving safety and mobility of our transportation systems. Data is usually collected via simulator-based studies or naturalistic driving studies. Those techniques allow for understanding…

人工智能 · 计算机科学 2018-01-15 Josh Warren , Jeff Lipkowitz , Vadim Sokolov

Understanding the movement behaviours of individuals and the way they react to the external world is a key component of any problem that involves the modelling of human dynamics at a physical level. In particular, it is crucial to capture…

计算机视觉与模式识别 · 计算机科学 2025-12-09 Gabriele Galatolo , Mirco Nanni

Understanding how people move in the urban area is important for solving urbanization issues, such as traffic management, urban planning, epidemic control, and communication network improvement. Leveraging recent availability of large…

社会与信息网络 · 计算机科学 2019-05-27 Yuren Zhou , Billy Pik Lik Lau , Chau Yuen , Bige Tunçer , Erik Wilhelm

Bikesharing schemes are transportation systems that not only provide an efficient mode of transportation in congested urban areas, but also improve last-mile connectivity with public transportation and local accessibility. Bikesharing…

社会与信息网络 · 计算机科学 2019-06-06 Fernando Munoz-Mendez , Konstantin Klemmer , Ke Han , Stephen Jarvis

Many aspects of life are associated with places of human mobility patterns and nowadays we are facing an increase in the pervasiveness of mobile devices these individuals carry. Positioning technologies that serve these devices such as the…

机器学习 · 计算机科学 2019-09-26 Thiago Andrade , Brais Cancela , João Gama

Understanding pedestrian dynamics and the interaction of pedestrians with their environment is crucial to the safe and comfortable design of pedestrian facilities. Experiments offer the opportunity to explore the influence of individual…

Analysing patterns of engagement among citizen science participants can provide important insights into the organisation and practice of individual citizen science projects. In particular, methods from statistics and network science can be…

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