Collective Dynamics https://collective-dynamics.eu/index.php/cod <p><span style="font-weight: 400;">Collective Dynamics is a diamond open-access multidisciplinary journal for pedestrian dynamics, vehicular traffic and other systems of self-driven particles or interacting agents (further information <a href="https://collective-dynamics.eu/index.php/cod/about">here</a>). <br /></span></p> en-US <p>Authors contributing to <strong><em>Collective Dynamics</em></strong><em> </em>agree to publish their articles under the <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">Creative Commons Attribution 4.0</a> license.</p><p>This license allows:</p><p><strong>Share</strong> — copy and redistribute the material in any medium or format</p><p><strong>Adapt</strong> — remix, transform, and build upon the material</p><p>for any purpose, even commercially.</p><p>The licensor cannot revoke these freedoms as long as you follow the license terms.</p><p>Authors retain copyright of their work. They are permitted and encouraged to post items submitted to <strong><em>Collective Dynamics</em></strong><em> </em>on personal or institutional websites and repositories, prior to and after publication (while providing the bibliographic details of that publication).</p> info@collective-dynamics.eu (Editorial Team) info@collective-dynamics.eu (Editorial Team ) Wed, 11 May 2022 17:28:32 +0200 OJS 3.3.0.13 http://blogs.law.harvard.edu/tech/rss 60 Towards a Reference Database for Pedestrian Destination Choice Model Development https://collective-dynamics.eu/index.php/cod/article/view/A140 <div> <div>The move towards publishing research data openly has led to the formation of reference databases in many fields. The benefits of such resources are numerous, particularly in the development of models. While these exist in research on other aspects of pedestrian behaviour, no reference database is available for modelling pedestrian destination choice, the process by which pedestrians choose where they wish to visit next. This work seeks to construct such a database from the literature. The resulting data obtained are described and potential ways in which they could be used to calibrate a simple pedestrian destination choice model are presented. It contains four datasets that include destination choices for hundreds of pedestrians in settings ranging from university campuses and music festivals to highly structured stated preference surveys. A case study using one of these datasets to calibrate a simple pedestrian destination choice model is provided. These efforts highlight some general issues from creating and using reference data openly. Discussing these issues will hopefully guide the development of reference data and accelerate the development of accurate pedestrian destination choice models that can be applied generally.</div> </div> Christopher King, Nikolai Bode Copyright (c) 2022 Christopher King, Nikolai Bode http://creativecommons.org/licenses/by/4.0 https://collective-dynamics.eu/index.php/cod/article/view/A140 Thu, 12 Jan 2023 00:00:00 +0100 Microscopic insights into pedestrian motion through a bottleneck, resolving spatial and temporal variations https://collective-dynamics.eu/index.php/cod/article/view/A139 The motion of pedestrians is subject to a wide range of influences and exhibits a rich phenomenology. To enable precise measurement of the density and velocity we use an alternative definition using Voronoi diagrams which exhibits smaller fluctuations than the standard definitions. This method permits examination on scales smaller than the pedestrians. We use this method to investigate the spatial and temporal variation of the observables at bottlenecks. Experiments were performed with 180 test subjects and a wide range of bottleneck parameters. The anomalous flow through short bottlenecks and non-stationary states present with narrow bottlenecks are analysed. Jack Liddle, Armin Seyfried, Bernhard Steffen, Wolfram Klingsch, Tobias Rupprecht, Andreas Winkens, Maik Boltes Copyright (c) 2022 Jack Liddle, Armin Seyfried, Bernhard Steffen, Wolfram Klingsch, Tobias Rupprecht, Andreas Winkens, Maik Boltes http://creativecommons.org/licenses/by/4.0 https://collective-dynamics.eu/index.php/cod/article/view/A139 Wed, 10 Aug 2022 00:00:00 +0200 Pushing and Non-pushing Forward Motion in Crowds: A Systematic Psychological Observation Method for Rating Individual Behavior in Pedestrian Dynamics https://collective-dynamics.eu/index.php/cod/article/view/A138 <p>Pushing behavior impairs people’s sense of well-being in a crowd and represents a significant safety risk. There are nevertheless still a lot of unanswered questions about who behaves how in a crowded situation, and when, where, and why pushing behavior occurs. Beginning from the supposition that a crowd is not thoroughly homogenous and that behavior can change over time, we developed a method to observe and rate forward motion. Based on the guidelines of quantitative content analysis, we came up with four categories: (1) falling behind, (2) just walking, (3) mild pushing, and (4) strong pushing. These categories allow for the classification of the behavior of any person at any time in a video, and thereby the method allows for a comprehensive systematization of individuals’ actions alongside temporal crowd dynamics. The application of this method involves videos of moving crowds including trajectories. The initial results show a very good inter-coder reliability between two trained raters demonstrating the general suitability of the system to describe forward motion in crowds systematically and quantify it for further analysis. In this way, pushing behavior can be better understood and, prospectively, risks better identified. This article offers a comprehensive presentation of this method of observation.</p> Ezel Üsten, Helena Lügering, Anna Sieben Copyright (c) 2022 Ezel Üsten, Helena Lügering, Anna Sieben http://creativecommons.org/licenses/by/4.0 https://collective-dynamics.eu/index.php/cod/article/view/A138 Fri, 05 Aug 2022 00:00:00 +0200 Effects of Driving Style on Energy Consumption and CO2 Emissions https://collective-dynamics.eu/index.php/cod/article/view/A137 <div class="page" title="Page 1"> <div class="layoutArea"> <div class="column"> <p><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L';">The tractive force developed by energy consumption (EC) in a car engine produces its acceleration and sustains the motion against velocity dependent resistance forces. In internal combustion engines, fuel burning entails pollutant emissions (PE) released into the atmosphere. In vehicular traffic, EC and PE depend on the driving style. This paper assumed that the transition rules in a traffic cellular automata (TCA) represent a driving style, and its effect on EC and PE in TCA is studied. Extending empirical relationships, we proposed models to estimate EC and PE in TCA from the velocity and acceleration distributions, which we obtained by computer simulations for three well-known TCA. The Nagel-Schreckenberg (NS) and Fukui-Ishibashi (FI) models, and a variant (NS+FI) defined by combining the NS and FI rules, were considered. The FI driving style revealed EC and CO</span><span style="font-size: 9.000000pt; font-family: 'NimbusRomNo9L'; vertical-align: -2.000000pt;">2 </span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L';">emission rates dependent on the stochastic delay (</span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L'; font-style: italic;">p</span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L';">) only for low vehicular densities. We also detected that the larger EC and CO</span><span style="font-size: 9.000000pt; font-family: 'NimbusRomNo9L'; vertical-align: -2.000000pt;">2 </span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L';">emission rates were 45</span><span style="font-size: 12.000000pt; font-family: 'CMMI10';">.</span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L';">4 </span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L'; font-style: italic;">kW </span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L';">and 26</span><span style="font-size: 12.000000pt; font-family: 'CMMI10';">.</span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L';">7 </span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L'; font-style: italic;">g</span><span style="font-size: 12.000000pt; font-family: 'CMMI10';">/</span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L'; font-style: italic;">s </span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L';">with no dependence on </span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L'; font-style: italic;">p</span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L';">. With NS and NS+FI driving styles, the larger energy consumption and CO</span><span style="font-size: 9.000000pt; font-family: 'NimbusRomNo9L'; vertical-align: -2.000000pt;">2 </span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L';">emission rates occurred for small stochastic delays, 18</span><span style="font-size: 12.000000pt; font-family: 'CMMI10';">.</span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L';">4 </span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L'; font-style: italic;">kW </span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L';">and 6</span><span style="font-size: 12.000000pt; font-family: 'CMMI10';">.</span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L';">6 </span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L'; font-style: italic;">g</span><span style="font-size: 12.000000pt; font-family: 'CMMI10';">/</span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L'; font-style: italic;">s </span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L';">and 61</span><span style="font-size: 12.000000pt; font-family: 'CMMI10';">.</span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L';">1</span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L'; font-style: italic;">kW </span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L';">and 30</span><span style="font-size: 12.000000pt; font-family: 'CMMI10';">.</span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L';">2 </span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L'; font-style: italic;">g</span><span style="font-size: 12.000000pt; font-family: 'CMMI10';">/</span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L'; font-style: italic;">s </span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L';">for </span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L'; font-style: italic;">p </span><span style="font-size: 12.000000pt; font-family: 'CMR10';">= </span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L';">0.2. On average, for NS, FI, and NS+FI models (</span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L'; font-style: italic;">p </span><span style="font-size: 12.000000pt; font-family: 'CMR10';">= </span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L';">0</span><span style="font-size: 12.000000pt; font-family: 'CMMI10';">.</span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L';">2), we obtained energy consumptions of 1</span><span style="font-size: 12.000000pt; font-family: 'CMMI10';">.</span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L';">88, 2</span><span style="font-size: 12.000000pt; font-family: 'CMMI10';">.</span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L';">60, and 2</span><span style="font-size: 12.000000pt; font-family: 'CMMI10';">.</span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L';">76 </span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L'; font-style: italic;">MJ</span><span style="font-size: 12.000000pt; font-family: 'CMMI10';">/</span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L'; font-style: italic;">km</span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L';">, fuel consumptions of 0</span><span style="font-size: 12.000000pt; font-family: 'CMMI10';">.</span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L';">08, 0</span><span style="font-size: 12.000000pt; font-family: 'CMMI10';">.</span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L';">12, and 0</span><span style="font-size: 12.000000pt; font-family: 'CMMI10';">.</span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L';">13 </span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L'; font-style: italic;">L</span><span style="font-size: 12.000000pt; font-family: 'CMMI10';">/</span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L'; font-style: italic;">km</span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L';">, and CO</span><span style="font-size: 9.000000pt; font-family: 'NimbusRomNo9L'; vertical-align: -2.000000pt;">2 </span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L';">emissions of 0</span><span style="font-size: 12.000000pt; font-family: 'CMMI10';">.</span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L';">158, 0</span><span style="font-size: 12.000000pt; font-family: 'CMMI10';">.</span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L';">460, and 0</span><span style="font-size: 12.000000pt; font-family: 'CMMI10';">.</span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L';">562 </span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L'; font-style: italic;">kgCO</span><span style="font-size: 9.000000pt; font-family: 'NimbusRomNo9L'; vertical-align: -2.000000pt;">2</span><span style="font-size: 12.000000pt; font-family: 'CMMI10';">/</span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L'; font-style: italic;">km</span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L';">. Our results agree with those (3</span><span style="font-size: 12.000000pt; font-family: 'CMMI10';">.</span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L';">37 </span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L'; font-style: italic;">MJ</span><span style="font-size: 12.000000pt; font-family: 'CMMI10';">/</span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L'; font-style: italic;">km </span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L';">and 0</span><span style="font-size: 12.000000pt; font-family: 'CMMI10';">.</span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L';">235 </span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L'; font-style: italic;">kgCO</span><span style="font-size: 9.000000pt; font-family: 'NimbusRomNo9L'; vertical-align: -2.000000pt;">2</span><span style="font-size: 12.000000pt; font-family: 'CMMI10';">/</span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L'; font-style: italic;">km</span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L';">) of petrol combustion car engines at 10 </span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L'; font-style: italic;">km</span><span style="font-size: 12.000000pt; font-family: 'CMMI10';">/</span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L'; font-style: italic;">L</span><span style="font-size: 12.000000pt; font-family: 'NimbusRomNo9L';">. This work may help in designing flow and driving style scenarios to optimize vehicular traffic EC and reduce PE. </span></p> </div> </div> </div> Susana Carreón-Sierra, Alejandro Salcido Copyright (c) 2022 Susana Carreón-Sierra, Alejandro Salcido http://creativecommons.org/licenses/by/4.0 https://collective-dynamics.eu/index.php/cod/article/view/A137 Wed, 11 May 2022 00:00:00 +0200