CrowdDNA | TECHNOLOGIES FOR COMPUTER-ASSISTED CROWD MANAGEMENT

Summary
CrowdDNA is a radically new concept to assist public space operators in the management of crowds, i.e., mass event organization, heavy pedestrian traffic management, crowd movement analysis and decision support. CrowdDNA technology is based on a new generation of crowd simulation models, which are capable of predicting the dynamics, behaviour and risk factors of crowds of extreme density. The main idea behind CrowdDNA is that analysis of some specific macroscopic features of a crowd, such as its apparent motion (that can be easily measured in real mass events) can reveal a valuable information about the internal structure and provide a precise estimate of a crowd state. This challenges the existing paradigms in the field that rely on simulation technologies and require measuring the simulation variables to initialize it, such as density, counts or individual features which are each difficult to estimate. This vision raises one main scientific challenge, which can be summarized as the need for a deep understanding of the relations between the smallest scales of crowd behaviours (e.g., contact and pushes at the limb scale) and the largest ones up to the entire crowd. CrowdDNA is a first attempt to combine biomechanical and behavioural simulation in complex scenarios of interactions between many humans. It will revolutionize the practices of crowd management to answer the requirements of modern society on safety and comfort at mass events or in crowded transportation facilities. CrowdDNA builds the foundations of new research on crowds, and opens up new opportunities for studies on physical interaction across cognitive sciences and biomechanics, as well as robotics and autonomous vehicles for safe navigation among people.
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More information & hyperlinks
Web resources: https://cordis.europa.eu/project/id/899739
Start date: 01-11-2020
End date: 31-10-2024
Total budget - Public funding: 2 998 557,50 Euro - 2 998 557,00 Euro
Cordis data

Original description

CrowdDNA is a radically new concept to assist public space operators in the management of crowds, i.e., mass event organization, heavy pedestrian traffic management, crowd movement analysis and decision support. CrowdDNA technology is based on a new generation of crowd simulation models, which are capable of predicting the dynamics, behaviour and risk factors of crowds of extreme density. The main idea behind CrowdDNA is that analysis of some specific macroscopic features of a crowd, such as its apparent motion (that can be easily measured in real mass events) can reveal a valuable information about the internal structure and provide a precise estimate of a crowd state. This challenges the existing paradigms in the field that rely on simulation technologies and require measuring the simulation variables to initialize it, such as density, counts or individual features which are each difficult to estimate. This vision raises one main scientific challenge, which can be summarized as the need for a deep understanding of the relations between the smallest scales of crowd behaviours (e.g., contact and pushes at the limb scale) and the largest ones up to the entire crowd. CrowdDNA is a first attempt to combine biomechanical and behavioural simulation in complex scenarios of interactions between many humans. It will revolutionize the practices of crowd management to answer the requirements of modern society on safety and comfort at mass events or in crowded transportation facilities. CrowdDNA builds the foundations of new research on crowds, and opens up new opportunities for studies on physical interaction across cognitive sciences and biomechanics, as well as robotics and autonomous vehicles for safe navigation among people.

Status

SIGNED

Call topic

FETOPEN-01-2018-2019-2020

Update Date

27-04-2024
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Horizon 2020
H2020-EU.1. EXCELLENT SCIENCE
H2020-EU.1.2. EXCELLENT SCIENCE - Future and Emerging Technologies (FET)
H2020-EU.1.2.1. FET Open
H2020-FETOPEN-2018-2020
FETOPEN-01-2018-2019-2020 FET-Open Challenging Current Thinking