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Interactive simulation

Crowd evacuation & emergency route planning

A shopping-mall concourse full of shoppers has to clear through a handful of exits. Each occupant follows a navigation field flooded outward from every exit, but they also avoid one another — so where routes converge, congestion builds. Turn up panic and people move faster yet cooperate less, clogging the doorways: the counter-intuitive “faster-is-slower” effect at the heart of this research.

Adjust the crowd size, panic level, and the number and width of exits. Click the floor to add or remove a wall and watch the crowd re-route in real time.

DEMO

This interactive is a faithful re-design of the research, simplified for illustrative and teaching purposes. It conveys the idea and behaviour of the model — it is not the paper’s full method, data, or results.

Crowd evacuation · agent-based · navigation-field + congestion
Evacuated 0/0clearance 0sflow 0/s

Green = exits · blue → red = shoppers coloured by local congestion (red = jammed) · orange rings = crowd start hotspots. Panic updates live; crowd size and exits rebuild the run. Click the floor to add or clear a wall block and watch the crowd re-route.

How the model works

Every exit seeds a breadth-first flood fill across the walkable floor, giving each cell its shortest distance to safety — a navigation field the whole crowd can read at once. An agent steps toward the neighbouring cell with the lowest cost, where cost combines that distance with the local occupancy, so a shorter route that is already jammed can lose out to a slightly longer one that is clear.

Panic scales two things at once: desired speed up, and the tendency to keep clear of neighbours down. At low panic the crowd flows in orderly lanes; at high panic it surges and locks up at the exits — evacuating the whole floor can take longer even though everyone is trying to move faster. Editing a wall re-runs the flood fill instantly, so you can watch a blocked corridor push the flow onto a different route.

The research behind it

This demo is a teaching stand-in for a body of work on optimizing emergency route planning and crowd guidance. The full methods, case studies, and results are in these papers.

Journal2018 · Safety science
Dynamic crowd evacuation approach for the emergency route planning problem: Application to case studies
Journal2015 · International Journal of Innovative Computing, Information and Control
Survey on crowd guidance's optimization algorithm for emergency route planning and management problems
Journal2015 · ICIC Express Letters
Immune-based approach for optimizing emergency route planning problem: application to case studies
Journal2015 · ICAART
An artificial immune approach for optimizing crowd emergency evacuation route planning problem
Conference2015 · 2015 4th International Conference on Software Engineering and Computer Systems (ICSECS)
Incorporating dynamism in emergency route planning problem using immune-based approach
Journal2014 · Aust. J. Basic Appl. Sci
A crowd modelling considering group cohesion in the emergency route planning problems