TYPE: Group Work
COLLABORATOR: Chenyu Xu, Ruilan Jia, Shuting Han, Yicheng Xu
TUTOR: Prof. Violet
LOCATION: Global Cities
DATE: Fall 2017
1.Background
When facing unpredictable disasters such as hurricane, earthquake, fire, car accident and terror attack, human can be very vulnerable. For terror attack alone, there are 1076 attacks and 7396 fatalities worldwide in 2017 so far. In densely populated cities, there is a higher chance of accidents in hotspots resulting in relevantly more injuries and fatalities.
Lately, on May 18, 2017, a car was crashed in Times Square, New York City. One person was killed and 20 were injured.
On December 31, 2014, a deadly stampede occurred in Shanghai, near Chen Yi Square on the Bund, where around 300,000 people had gathered for the New Year celebration. 36 people were killed and there were 49 injured, 13 seriously.
Cities should contain complex refuge, acting as shelter from emergency. The roles of urban fabric and physical infrastructure are crucial not only in preventing terrorists’ actions but also determining the way of evacuating people. Even though security might be the most effective way to prevent accidents directly, city design should be improved to evacuate people as fast as possible to reduce the impact.
Among all the different types of disasters mentioned above, we assumed one extreme case when the damage source(Attacker) is mobile meaning that it could have huge potential impact, and visualized it in realistic urban areas.
This project uses an agent-based model to simulate human behaviors during an emergency in global cities, aiming to evaluate efficiency of evacuation in different types of urban fabric. The efficiency is assessed by quantifying fatalities over the same time.
2.Methodology
2.1 Define objects
2.2 Define Behavior
2.2 People Behaviors
2.2.1 Move Towards Center Of Nearby People
2.2.2 Turn Away From Closest Person
2.2.3 Turn To Average Direction
2.2.4 Move Towards Exit
2.2.5 Turn Away From Wall
2.2.6 Turn Away From Attacker
2.2.7 People Get Injured By Attacker
2.2.8 Speed Up (SelfBehavior)
2.2.9 Speed Up (Interaction)
2.3 Attacker Behaviors
2.3.1 Move Towards Center Of Nearby People
2.3.2 Speed Up
3.Site Context
We select 4 urban locations all highly populated in new year celebration from 4 typical urban gathering space.
I. Small-size street intersection square_Times Square, New York.
II. Large-size open square surrounded by urban roads_Trafalgar Square, London.
III. Large-size enclosed square surrounded by buildings_Piazza Del Campo, Siena.
IV. Urban linear open space_Victoria Harbour, Hong Kong.
4.Evacuation Stimulation in Processing
5. Analysis and Conclusion
5.1 Analysis
A. Regular experiment
B. When double the exit closeness distance
I. Small-size street intersection square_Times Square, New York.
II. Large-size open square surrounded by urban roads_Trafalgar Square, London.
III. Large-size enclosed square surrounded by buildings_Piazza Del Campo, Siena.
IV. Urban linear open space_Victoria Harbour, Hong Kong.
II. Large-size open square surrounded by urban roads_Trafalgar Square, London.
III. Large-size enclosed square surrounded by buildings_Piazza Del Campo, Siena.
IV. Urban linear open space_Victoria Harbour, Hong Kong.
5.2 Result Analysis
People are more likely to die in the large-size open square.
More people escaped from small-size street intersection square and urban linear space.
People are more likely to be trapped in large-size enclosed square.
5.3 Conclusion
Create more signage to help people clearly know their locations and correct direction in large-size squares.
Enhance exit capacity and efficiency in enclosed squares.