Simulation-Aided Crowd Management: A Multi-scale Model for an Urban Case Study

Safety, security, and comfort of pedestrian crowds during large gatherings are heavily influenced by the layout of the underlying environment. This work presents a systematic agent-based simulation approach to appraise and optimize the layout of a pedestrian environment in order to maximize safety, security, and comfort. The performance of the approach is demonstrated based on annual “Salone del mobile” (Design Week) exhibition in Milan, Italy. Given the large size of the scenario and the proportionally high number of simultaneously present pedestrians, the computational costs of a pure microscopic simulation approach would make this hardly applicable, whereas a multi-scale approach, combining simulation models of different granularity, provides a reasonable trade off between a detailed management of individual pedestrians and possibility to effectively carry out what-if analyses with different environmental configurations. The paper will introduce the scenario, the base model and the alternatives, discussing the achieved results.

[1]  P. Mendes,et al.  Multi-scale modelling and simulation in systems biology. , 2011, Integrative biology : quantitative biosciences from nano to macro.

[2]  Kai Nagel,et al.  The MATSim Network Flow Model for Traffic Simulation Adapted to Large-Scale Emergency Egress and an Application to the Evacuation of the Indonesian City of Padang in Case of a Tsunami Warning , 2009 .

[3]  Jun Zhang,et al.  Transitions in pedestrian fundamental diagrams of straight corridors and T-junctions , 2011, 1102.4766.

[4]  Karsten Lehmann,et al.  User equilibrium Route Assignment for Microscopic Pedestrian Simulation , 2014, Adv. Complex Syst..

[5]  John A. Michon,et al.  A critical view of driver behavior models: What do we know , 1985 .

[6]  A. Schadschneider,et al.  Simulation of pedestrian dynamics using a two dimensional cellular automaton , 2001 .

[7]  J. Nash,et al.  NON-COOPERATIVE GAMES , 1951, Classics in Game Theory.

[8]  Jean-Baptiste Lesort,et al.  Mixing Microscopic and Macroscopic Representations of Traffic Flow: Hybrid Model Based on Lighthill–Whitham–Richards Theory , 2003 .

[9]  Serge P. Hoogendoorn,et al.  DYNAMIC USER-OPTIMAL ASSIGNMENT IN CONTINUOUS TIME AND SPACE , 2004 .

[10]  Stefania Bandini,et al.  An Approach for Managing Heterogeneous Speed Profiles in Cellular Automata Pedestrian Models , 2017, Journal of Cellular Automata.

[11]  Giuseppe Vizzari,et al.  Multi-scale Simulation for Crowd Management: A Case Study in an Urban Scenario , 2016, AAMAS Workshops.

[12]  Isabella von Sivers,et al.  How Stride Adaptation in Pedestrian Models Improves Navigation , 2014, ArXiv.

[13]  Alexis Drogoul,et al.  A hybrid macro-micro pedestrians evacuation model to speed up simulation in road networks , 2011, AAMAS'11.

[14]  Gregor Lämmel,et al.  Multidestination Pedestrian Flows in Equilibrium: A Cellular Automaton‐Based Approach , 2016, Comput. Aided Civ. Infrastructure Eng..

[15]  Edsger W. Dijkstra,et al.  A note on two problems in connexion with graphs , 1959, Numerische Mathematik.

[16]  Mohcine Chraibi,et al.  Hybrid Multimodal and Intermodal Transport Simulation: Case Study on Large-Scale Evacuation Planning , 2016 .

[17]  Armin Seyfried,et al.  Influence of Geometry Parameters on Pedestrian Flow through Bottleneck , 2011 .

[18]  Nitish Chooramun.  Implementing a hybrid spatial discretisation within an agent based evacuation model , 2011 .

[19]  L. F. Henderson,et al.  The Statistics of Crowd Fluids , 1971, Nature.

[20]  Dirk Helbing,et al.  Micro- and macro-simulation of freeway traffic , 2002 .

[21]  Kai Nagel,et al.  The representation and implementation of time-dependent inundation in large-scale microscopic evacuation simulations , 2010 .

[22]  Helbing,et al.  Social force model for pedestrian dynamics. , 1995, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[23]  Gunnar Flötteröd,et al.  Bidirectional pedestrian fundamental diagram , 2015 .

[24]  Lorenza Manenti,et al.  MAKKSim: MAS-Based Crowd Simulations for Designer's Decision Support , 2013, PAAMS.

[25]  Patrick Taillandier,et al.  GAMA: A Simulation Platform That Integrates Geographical Information Data, Agent-Based Modeling and Multi-scale Control , 2010, PRIMA.

[26]  Gunnar Flötteröd,et al.  A CA Model for Bidirectional Pedestrian Streams , 2015, ANT/SEIT.

[27]  Armin Seyfried,et al.  Performance of stairs: fundamental diagram and topographical measurements , 2013 .

[28]  Daniel Krajzewicz,et al.  Recent Development and Applications of SUMO - Simulation of Urban MObility , 2012 .

[29]  Armin Seyfried,et al.  Experimental Study on Pedestrian Flow through Wide Bottleneck , 2014 .

[30]  Gunnar Flötteröd,et al.  Towards System Optimum: Finding Optimal Routing Strategies in Time-Dependent Networks for Large-Scale Evacuation Problems , 2009, KI.

[31]  Kai Nagel,et al.  Iterative route planning for large-scale modular transportation simulations , 2004, Future Gener. Comput. Syst..

[32]  Haris N. Koutsopoulos,et al.  Hybrid Mesoscopic-Microscopic Traffic Simulation , 2004 .

[33]  Kai Nagel,et al.  Simple queueing model applied to the city of Portland , 1998 .

[34]  E. Cascetta.  A stochastic process approach to the analysis of temporal dynamics in transportation networks , 1989 .

[35]  Wilco Burghout,et al.  Hybrid Traffic Simulation with Adaptive Signal Control , 2007 .

[36]  A. Schadschneider,et al.  Ordering in bidirectional pedestrian flows and its influence on the fundamental diagram , 2012 .

[37]  C. Gawron,et al.  An Iterative Algorithm to Determine the Dynamic User Equilibrium in a Traffic Simulation Model , 1998 .

[38]  Armin Seyfried,et al.  Large scale and microscopic: a fast simulation approach for urban areas , 2014 .

[39]  Mohcine Chraibi,et al.  Generalized centrifugal-force model for pedestrian dynamics. , 2010, Physical review. E, Statistical, nonlinear, and soft matter physics.

[40]  J L Adler,et al.  Emergent Fundamental Pedestrian Flows from Cellular Automata Microsimulation , 1998 .