Yassine Lamrhary, Aissam Jebrane, Pierre Argoul, A. Boukamel, A. Hamdaoui
The understanding of crowd behavior dynamics holds immense significance in ensuring public safety across a range of situations, including emergency evacuations and large-scale events. Our research focuses on two primary objectives: investigating the impact of emotions on crowd movement and gaining valuable insights into collective behavior within crowds. To achieve this, we present a coupled model, incorporating an enhanced ASCRIBE model with an agent displacement model. We introduce heterogeneity into our model by incorporating specific mobility laws for different categories of panicked crowds, considering the influence of emotions on both speed and direction. Through numerical simulations, we analyze the model's parameters, observe the behavior of uniform crowds, and explore the collective dynamics within diverse crowds. By conducting comprehensive simulations and analyses, the findings from this study can contribute to the development of more effective crowd management strategies and emergency evacuation protocols.
{"title":"A Coupled SFM-ASCRIBE Model To Investigate the Influence of Emotions and Collective Behavior in Homogeneous and Heterogeneous Crowds","authors":"Yassine Lamrhary, Aissam Jebrane, Pierre Argoul, A. Boukamel, A. Hamdaoui","doi":"10.17815/cd.2024.147","DOIUrl":"https://doi.org/10.17815/cd.2024.147","url":null,"abstract":"The understanding of crowd behavior dynamics holds immense significance in ensuring public safety across a range of situations, including emergency evacuations and large-scale events. Our research focuses on two primary objectives: investigating the impact of emotions on crowd movement and gaining valuable insights into collective behavior within crowds. To achieve this, we present a coupled model, incorporating an enhanced ASCRIBE model with an agent displacement model. We introduce heterogeneity into our model by incorporating specific mobility laws for different categories of panicked crowds, considering the influence of emotions on both speed and direction. Through numerical simulations, we analyze the model's parameters, observe the behavior of uniform crowds, and explore the collective dynamics within diverse crowds. By conducting comprehensive simulations and analyses, the findings from this study can contribute to the development of more effective crowd management strategies and emergency evacuation protocols.","PeriodicalId":93276,"journal":{"name":"Collective dynamics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139788275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Information propagation in crowds tends to have a negative image. A common narrative is that information about a danger spreads like wildfire and leads to panic. In contrast, using person-to-person information sharing in crowd management as a complement to other communication channels has been discussed less. Even though previous research indicated that information does not propagate easily in crowds, more detailed research is lacking. In this study, two different experiments are presented to provide initial insights. In the main experiment, five groups of 33-41 participants took part in a total of 35 runs. In each run, a person in a waiting group was given a message or command that had to be passed on, whereby the knowledge about the task, the relevance of the message and the input side were varied. In the second experiment, this procedure was repeated with two larger groups of participants (n = 91 and n = 101). Overall, results showed that information propagated better when people were properly briefed on their task and have performed it several times. There was also a tendency for a higher density to foster faster propagation and for participants to rely on the spoken word rather than seeing a behavior performed. Yet, some participants did not receive the information at all or did not pass it on. In general, the direction of communication (e.g., back to front or left to right) was not always the same but information was usually passed along in a similar direction from where it came.
{"title":"A Rumor has Spread like Wildfire? - Empirical Investigation of Information Propagation in Waiting Crowds","authors":"Helena Lügering, A. Sieben","doi":"10.17815/cd.2024.146","DOIUrl":"https://doi.org/10.17815/cd.2024.146","url":null,"abstract":"Information propagation in crowds tends to have a negative image. A common narrative is that information about a danger spreads like wildfire and leads to panic. In contrast, using person-to-person information sharing in crowd management as a complement to other communication channels has been discussed less. Even though previous research indicated that information does not propagate easily in crowds, more detailed research is lacking. In this study, two different experiments are presented to provide initial insights. In the main experiment, five groups of 33-41 participants took part in a total of 35 runs. In each run, a person in a waiting group was given a message or command that had to be passed on, whereby the knowledge about the task, the relevance of the message and the input side were varied. In the second experiment, this procedure was repeated with two larger groups of participants (n = 91 and n = 101). Overall, results showed that information propagated better when people were properly briefed on their task and have performed it several times. There was also a tendency for a higher density to foster faster propagation and for participants to rely on the spoken word rather than seeing a behavior performed. Yet, some participants did not receive the information at all or did not pass it on. In general, the direction of communication (e.g., back to front or left to right) was not always the same but information was usually passed along in a similar direction from where it came.","PeriodicalId":93276,"journal":{"name":"Collective dynamics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139624935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Road traffic flow models allow the development and testing of intelligent transportation solutions. Macroscopic intersection models are especially relevant for the simulation of large traffic networks. In this article, we study four first-order signalized and unsignalized intersection models. The two unsignalized approaches are the first-in-first-out (FIFO) model (roundabout-type intersection) and an optimal non-FIFO model (highway-type intersection). The optimal control operates upstream for the first signalized intersection model. It occurs downstream for the second signalized model. All four models satisfy the expected physical constraints of vehicle conservation, traffic demand, and assignment. The models are minimal and allow a comprehensible analysis of the results. We determine mathematical relationships between the intersection models and empirically analyze the performances using Monte Carlo simulations. The numerical simulations assume random demand, supply, and assignment. Besides average performances, the approach accounts for the flow ranges of variation. A benchmark analysis compares the intersection models. We observe that the optimal signalized intersection models overcome the performances of the FIFO model in congested states. They may even reach the performances of the idealistic non-FIFO model. Further applications for the four intersection models are discussed.
{"title":"Signalized and Unsignalized Road Traffic Intersection Models: A Comprehensive Benchmark Analysis","authors":"Ibrahima Ba, A. Tordeux","doi":"10.17815/cd.2023.144","DOIUrl":"https://doi.org/10.17815/cd.2023.144","url":null,"abstract":"Road traffic flow models allow the development and testing of intelligent transportation solutions. Macroscopic intersection models are especially relevant for the simulation of large traffic networks. In this article, we study four first-order signalized and unsignalized intersection models. The two unsignalized approaches are the first-in-first-out (FIFO) model (roundabout-type intersection) and an optimal non-FIFO model (highway-type intersection). The optimal control operates upstream for the first signalized intersection model. It occurs downstream for the second signalized model. All four models satisfy the expected physical constraints of vehicle conservation, traffic demand, and assignment. The models are minimal and allow a comprehensible analysis of the results. We determine mathematical relationships between the intersection models and empirically analyze the performances using Monte Carlo simulations. The numerical simulations assume random demand, supply, and assignment. Besides average performances, the approach accounts for the flow ranges of variation. A benchmark analysis compares the intersection models. We observe that the optimal signalized intersection models overcome the performances of the FIFO model in congested states. They may even reach the performances of the idealistic non-FIFO model. Further applications for the four intersection models are discussed.","PeriodicalId":93276,"journal":{"name":"Collective dynamics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138971033","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We use six existing sources about past crowd crushes and accident to build a merged data base. By doing so, we show that every source has a partial view of the crowd crushes, with coverage rates between 14% and 59% of our merged data base. Each of the sources contains crowd crushes that are cited by none of the other sources. We then may have a very partial view of past crowd crushes. We examine several biases that can explain under reporting of crowd crushes, notably the less recent ones and the smaller. This partial view affects any statistical study that we can do on the evolution of crowd crushes. However, our data analysis suggests that the number of crowd crushes par capita is not steadily increasing. Crowd crushes may not be a growing tendency in regard to global population. Our analysis suggests it is necessary to continue studying crowd crushes, both globally and in-depth, to gain a more global view of their reasons and their tendencies. We propose to use collaborative projects such as Wikidata to do so.
{"title":"How to Navigate Crowd Crushes History? A Compilation of Six Existing Sources","authors":"Capucine-Marin Dubroca-Voisin","doi":"10.17815/cd.2023.145","DOIUrl":"https://doi.org/10.17815/cd.2023.145","url":null,"abstract":"We use six existing sources about past crowd crushes and accident to build a merged data base. By doing so, we show that every source has a partial view of the crowd crushes, with coverage rates between 14% and 59% of our merged data base. Each of the sources contains crowd crushes that are cited by none of the other sources.\u0000We then may have a very partial view of past crowd crushes. We examine several biases that can explain under reporting of crowd crushes, notably the less recent ones and the smaller.\u0000This partial view affects any statistical study that we can do on the evolution of crowd crushes. However, our data analysis suggests that the number of crowd crushes par capita is not steadily increasing. Crowd crushes may not be a growing tendency in regard to global population.\u0000Our analysis suggests it is necessary to continue studying crowd crushes, both globally and in-depth, to gain a more global view of their reasons and their tendencies. We propose to use collaborative projects such as Wikidata to do so.","PeriodicalId":93276,"journal":{"name":"Collective dynamics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138974656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Crowds, subjects of considerable complexity, have been extensively studied both as homogeneous entities and as collective sums of individual movements in various studies. However, crowd models, being grounded in physics, are limited in terms of incorporating psychological perspectives on individual behavior. Building upon the premise that crowd behavior is heterogeneous and dynamic, particularly in bottleneck scenarios, this study aims to explore the nuances of forward motion. Adopting the category system proposed by Lügering et al. (2022) (consisting the following categories: strong pushing, mild pushing, just walking, falling behind), this paper investigates the circumstances and locations where pushing or non-pushing behaviors arise, intensify, or cease within crowds approaching bottlenecks. The study utilized 14 video materials obtained from previous laboratory pedestrian experiments to examine the spatial characteristics of forward motion and pushing behavior in relation to corridor widths and varied motivational instructions. Two trained raters independently annotated these videos, achieving satisfactory inter-rater agreement (KALPHA = .65) , and a joint dataset was then created for each video. These videos consisted both high (7 videos) and low (7 videos) motivation scenarios. The importance of corridor width was also considered: four videos featured a 5.6m width, another four featured a 4.5m width, and the remaining videos displayed widths of 3.4m, 2.3m, and 1.2m twice. Our findings suggest a tendency for increased pushing behavior or an increase in the categories as individuals approach the bottleneck, regardless of the width of the corridor or the motivational instruction. Furthermore, non-pushing behaviors were predominantly observed in the areas farther away from the bottleneck. A noticeable trend was observed in high motivation scenarios, which generally exhibited more instances of pushing behavior. The effect of corridor width indicated that, in certain cases, pedestrians who push in wider corridors experience faster access to the bottleneck. However, this effect is less significant in narrower widths.
{"title":"Exploring the Dynamic Relationship between Pushing Behavior and Crowd Dynamics","authors":"Ezel Uesten, Jette Schumann, Anna Sieben","doi":"10.17815/cd.2023.143","DOIUrl":"https://doi.org/10.17815/cd.2023.143","url":null,"abstract":"Crowds, subjects of considerable complexity, have been extensively studied both as homogeneous entities and as collective sums of individual movements in various studies. However, crowd models, being grounded in physics, are limited in terms of incorporating psychological perspectives on individual behavior. Building upon the premise that crowd behavior is heterogeneous and dynamic, particularly in bottleneck scenarios, this study aims to explore the nuances of forward motion. Adopting the category system proposed by Lügering et al. (2022) (consisting the following categories: strong pushing, mild pushing, just walking, falling behind), this paper investigates the circumstances and locations where pushing or non-pushing behaviors arise, intensify, or cease within crowds approaching bottlenecks. The study utilized 14 video materials obtained from previous laboratory pedestrian experiments to examine the spatial characteristics of forward motion and pushing behavior in relation to corridor widths and varied motivational instructions. Two trained raters independently annotated these videos, achieving satisfactory inter-rater agreement (KALPHA = .65) , and a joint dataset was then created for each video. These videos consisted both high (7 videos) and low (7 videos) motivation scenarios. The importance of corridor width was also considered: four videos featured a 5.6m width, another four featured a 4.5m width, and the remaining videos displayed widths of 3.4m, 2.3m, and 1.2m twice. Our findings suggest a tendency for increased pushing behavior or an increase in the categories as individuals approach the bottleneck, regardless of the width of the corridor or the motivational instruction. Furthermore, non-pushing behaviors were predominantly observed in the areas farther away from the bottleneck. A noticeable trend was observed in high motivation scenarios, which generally exhibited more instances of pushing behavior. The effect of corridor width indicated that, in certain cases, pedestrians who push in wider corridors experience faster access to the bottleneck. However, this effect is less significant in narrower widths.","PeriodicalId":93276,"journal":{"name":"Collective dynamics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135193705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Game theory models provide very powerful tools for evaluating strategies that are beneficial to both rail and road operators competing for passengers on parallel routes. This study examines how game theory can help rail operators who are incurring losses on passenger transport to identify strategies that can minimise costs, using the methodology of dual linear programming to analyse strategies. In identifying the best strategies for minimising costs for the railway operator, the best strategies for maximising profits for the road operators are also identified. The game model is set up between two passenger transport operators (rail and road) and is based on the income earned by the road operators from passengers. This study illustrates the following: how the strategies of the two competitors (rail and road) are determined; the formation of the payoff matrix and the presentation of the mathematical problem for the two competitors; and the results and verification of the best strategies for both competitors. The Leonid Hurwicz criterion was used to verify the optimal strategies.
{"title":"How a Game Theoretic Approach Can Minimize the Cost of Train Passenger Services: An Intermodal Competition between Rail and Road Transport","authors":"Tryson Yangailo","doi":"10.17815/cd.2023.142","DOIUrl":"https://doi.org/10.17815/cd.2023.142","url":null,"abstract":"Game theory models provide very powerful tools for evaluating strategies that are beneficial to both rail and road operators competing for passengers on parallel routes. This study examines how game theory can help rail operators who are incurring losses on passenger transport to identify strategies that can minimise costs, using the methodology of dual linear programming to analyse strategies. In identifying the best strategies for minimising costs for the railway operator, the best strategies for maximising profits for the road operators are also identified. The game model is set up between two passenger transport operators (rail and road) and is based on the income earned by the road operators from passengers. This study illustrates the following: how the strategies of the two competitors (rail and road) are determined; the formation of the payoff matrix and the presentation of the mathematical problem for the two competitors; and the results and verification of the best strategies for both competitors. The Leonid Hurwicz criterion was used to verify the optimal strategies.","PeriodicalId":93276,"journal":{"name":"Collective dynamics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45678205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ann Katrin Boomers, M. Boltes, Juliane Adrian, Mira Beermann, M. Chraibi, S. Feldmann, F. Fiedrich, Niklas Frings, Arne Graf, Alica Kandler, Deniz Kilic, Krisztina Konya, M. Küpper, Andreas Lotter, Helena Lügering, Francesca Müller, Sarah Paetzke, Anna-Katharina Raytarowski, Olga Sablik, Tobias Schrödter, A. Seyfried, A. Sieben, Ezel Üsten
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 factors. In the context of the project CroMa (Crowd Management in transport infrastructures), experiments were conducted with about 1000 participants to test various physical and social psychological hypotheses focusing on people's behaviour at railway stations and crowd management measures. The following experiments were performed: i) Train Platform Experiment, ii) Crowd Management Experiment, iii) Single-File Experiment, iv) Personal Space Experiment, v) Boarding and Alighting Experiment, vi) Bottleneck Experiment and vii) Tiny Box Experiment. This paper describes the basic planning and implementation steps, outlines all experiments with parameters, geometries, applied sensor technologies and pre- and post-processing steps. All data can be found in the pedestrian dynamics data archive.
{"title":"Pedestrian Crowd Management Experiments: A Data Guidance Paper","authors":"Ann Katrin Boomers, M. Boltes, Juliane Adrian, Mira Beermann, M. Chraibi, S. Feldmann, F. Fiedrich, Niklas Frings, Arne Graf, Alica Kandler, Deniz Kilic, Krisztina Konya, M. Küpper, Andreas Lotter, Helena Lügering, Francesca Müller, Sarah Paetzke, Anna-Katharina Raytarowski, Olga Sablik, Tobias Schrödter, A. Seyfried, A. Sieben, Ezel Üsten","doi":"10.17815/cd.2023.141","DOIUrl":"https://doi.org/10.17815/cd.2023.141","url":null,"abstract":"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 factors. In the context of the project CroMa (Crowd Management in transport infrastructures), experiments were conducted with about 1000 participants to test various physical and social psychological hypotheses focusing on people's behaviour at railway stations and crowd management measures. The following experiments were performed: i) Train Platform Experiment, ii) Crowd Management Experiment, iii) Single-File Experiment, iv) Personal Space Experiment, v) Boarding and Alighting Experiment, vi) Bottleneck Experiment and vii) Tiny Box Experiment. This paper describes the basic planning and implementation steps, outlines all experiments with parameters, geometries, applied sensor technologies and pre- and post-processing steps. All data can be found in the pedestrian dynamics data archive.","PeriodicalId":93276,"journal":{"name":"Collective dynamics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42439816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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.
{"title":"Towards a Reference Database for Pedestrian Destination Choice Model Development","authors":"C. King, N. Bode","doi":"10.17815/cd.2022.140","DOIUrl":"https://doi.org/10.17815/cd.2022.140","url":null,"abstract":"\u0000The 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.\u0000","PeriodicalId":93276,"journal":{"name":"Collective dynamics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45644862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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.
{"title":"Pushing and Non-pushing Forward Motion in Crowds: A Systematic Psychological Observation Method for Rating Individual Behavior in Pedestrian Dynamics","authors":"Ezel Üsten, Helena Lügering, A. Sieben","doi":"10.17815/cd.2022.138","DOIUrl":"https://doi.org/10.17815/cd.2022.138","url":null,"abstract":"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.","PeriodicalId":93276,"journal":{"name":"Collective dynamics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49495061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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 CO2 emission rates dependent on the stochastic delay (p) only for low vehicular densities. We also detected that the larger EC and CO2 emission rates were 45.4 kW and 26.7 g/s with no dependence on p. With NS and NS+FI driving styles, the larger energy consumption and CO2 emission rates occurred for small stochastic delays, 18.4 kW and 6.6 g/s and 61.1kW and 30.2 g/s for p = 0.2. On average, for NS, FI, and NS+FI models (p = 0.2), we obtained energy consumptions of 1.88, 2.60, and 2.76 MJ/km, fuel consumptions of 0.08, 0.12, and 0.13 L/km, and CO2 emissions of 0.158, 0.460, and 0.562 kgCO2/km. Our results agree with those (3.37 MJ/km and 0.235 kgCO2/km) of petrol combustion car engines at 10 km/L. This work may help in designing flow and driving style scenarios to optimize vehicular traffic EC and reduce PE.
{"title":"Effects of Driving Style on Energy Consumption and CO2 Emissions","authors":"Susana Carreón-Sierra, A. Salcido","doi":"10.17815/cd.2022.137","DOIUrl":"https://doi.org/10.17815/cd.2022.137","url":null,"abstract":"\u0000\u0000\u0000The 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 CO2 emission rates dependent on the stochastic delay (p) only for low vehicular densities. We also detected that the larger EC and CO2 emission rates were 45.4 kW and 26.7 g/s with no dependence on p. With NS and NS+FI driving styles, the larger energy consumption and CO2 emission rates occurred for small stochastic delays, 18.4 kW and 6.6 g/s and 61.1kW and 30.2 g/s for p = 0.2. On average, for NS, FI, and NS+FI models (p = 0.2), we obtained energy consumptions of 1.88, 2.60, and 2.76 MJ/km, fuel consumptions of 0.08, 0.12, and 0.13 L/km, and CO2 emissions of 0.158, 0.460, and 0.562 kgCO2/km. Our results agree with those (3.37 MJ/km and 0.235 kgCO2/km) of petrol combustion car engines at 10 km/L. This work may help in designing flow and driving style scenarios to optimize vehicular traffic EC and reduce PE. \u0000\u0000\u0000","PeriodicalId":93276,"journal":{"name":"Collective dynamics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46494378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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