Search arXivSearch

arXiv · 1801.00276

Some Indications on how to Calibrate the Social Force Model of Pedestrian Dynamics

Abstract

The Social Force Model of pedestrian dynamics is formulated in a way that a) most of its parameters do not have an immediate interpretation, b) often one single parameter has an impact on many aspects of walking behavior and c) a certain aspect of walking behavior results from the values of more than one parameter. This makes calibration difficult. The aim of this paper is to give practitioners an indication of how to proceed in the calibration process. For this by analytical transformations the parameters of the Social Force Model are related to real properties that have a clear and immediate meaning and which are also highly relevant result properties of a simulation: extent and clearance time of a queue, respectively maximum density and capacity flow. The theory for this is presented as well. As a side effect it can give a deeper understanding of the model for everyone interested in theoretical aspects.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Tobias Kretz, Jochen Lohmiller, Peter Sukennik. 2017-12-31. Some Indications on how to Calibrate the Social Force Model of Pedestrian Dynamics. https://arxiv.org/abs/1801.00276

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Assessment of Latent Pedestrian-Vehicle Interaction Risk Profiles at Midblock Crossing in VR

Pedestrian safety at midblock crossings is a critical concern in mixed traffic environments where autonomous vehicles (AVs) and human-driven vehicles (HDVs) share the road. Pedestrians often infer intent from vehicle motion in AV encounters, making them vulnerable to small shifts in conflict margins. This study investigates whether virtual reality (VR) crossing sessions separate into distinct interaction risk profiles and whether AV-only sessions shift profile prevalence compared to HDV-only sessions. Using large-scale immersive VR experiments from Toronto, Canada, and Newcastle, England, we compute surrogate safety measures (SSMs) and apply latent profile analysis (LPA) to identify distinct pedestrian crossing stances, ranging from risk-accepting to highly cautious. Key findings show that Newcastle exhibits a higher prevalence of high-urgency risk profiles in AV-only sessions, indicating that AVs contribute to higher-risk encounters. In contrast, Toronto shows no significant difference between AV-only and HDV-only sessions, suggesting that contextual factors influence the impact of AVs on pedestrian safety.

physics.soc-ph

Unused power surge compromises U.S. road vehicles sustainability

Material and energy flows underpin sociotechnical metabolism. However, despite growing sustainability concerns over expanding material stocks and declining stock productivity, the link between material use and energy consumption remains poorly understood. This gap reflects a limited distinction between structures and the activity they enable, and the lack of quantification of the installed power of energy consuming structures. Here we reconstruct the long-term growth dynamics of U.S. road vehicles, distinguishing professional and consumer assets. We show that installed power, mass, and fuel energy use follow divergent patterns within and across vehicle categories. By introducing the usage factor as a metric linking structure to activity, we quantify decoupling mechanisms such as engine oversizing and fleet redundancy, which drive up material immobilization. As electrification requires large-scale fleet replacement, our findings highlight that avoiding power oversized vehicles could reduce material demand, emphasizing the need to account for structure-activity decoupling in energy transition policies.

physics.soc-ph

Environmental sustainability in basic research: a perspective from HECAP+

The climate crisis and the degradation of the world's ecosystems require humanity to take immediate action. The international scientific community has a responsibility to limit the negative environmental impacts of basic research. The HECAP+ communities (High Energy Physics, Cosmology, Astroparticle Physics, and Hadron and Nuclear Physics) make use of common and similar experimental infrastructure, such as accelerators and observatories, and rely similarly on the processing of big data. Our communities therefore face similar challenges to improving the sustainability of our research. This document aims to reflect on the environmental impacts of our work practices and research infrastructure, to highlight best practice, to make recommendations for positive changes, and to identify the opportunities and challenges that such changes present for wider aspects of social responsibility.

physics.soc-ph