STAM is a multidisciplinary engineering company based in Italy that provides high-tech custom solutions to meet its client’s business challenges. The company leverages its expert knowledge from across engineering domains, including the security and transport sectors, sustainability and the circular economy, defense robotics, industry 4.0, and more. The company is an active participant in European Union research projects.
Due to terrorist attacks in Europe in recent years, the European Commission developed its funding opportunities for projects that improve public security and counter terrorist activities.
STAM worked on one such project. Its engineers created a simulation model of metro station crowd behavior for the purpose of analyzing different attack scenarios.
The objective of the crowd modeling was to simulate passenger behavior in metro station infrastructure during its normal state and facilitate comparison with various attack scenarios. Engineers also wanted to reveal and analyze any critical vulnerabilities in public infrastructure, using the capabilities of the model for evacuation simulation.
Engineers simulated an open-air metro station with two independent entrances and two floors. The train platform is located on the upper floor. The model also included station facilities that can be used by pedestrians during their travel time, such as ATMs, toilets, a coffee point, and shops.
Within the framework of the model, STAM engineers created three metro station attack scenarios:
- Bomb explosion
- Melee weapon attack
- Drone attack
Each type of attack was represented in the model as an agent. For each agent, engineers created a statechart that represented the different phases of an attack. And, by combining statecharts with flowcharts, the agents could move around inside the simulation environment. The only agent without a flow chart was the explosive agent, due to it not needing to move and being represented as a static agent.
Using AnyLogic’s 2D and 3D animation capabilities makes it possible to observe simulation model runs in many different ways, allowing analysts to examine agent behavior for each scenario in a simulation environment.
For the first scenario, with the explosive, the model showed the effects of the bomb’s explosion and the response triggered by it, including the reaction times of pedestrians in the vicinity and their evacuation.
For the scenario with the melee weapon, the model revealed that crowds took longer to react and evacuate due to the localized character of the attack. Also, the model showed the movement of the terrorist trying to leave the station and being stopped by security.
Finally, in the third scenario, with the drone, the attack happens while a train is arriving at the station – when the amount of people on the platform is at a maximum.
The density maps associated with the crowd modeling helped analysts identify critical areas for pedestrian flow and the points where potentially dangerous situations may arise.
All scenarios provided results for comparison, showing the number of casualties, injured, and exposed, as well as the overall evacuation time and critical areas.
The results of the crowd modeling show that the average time of evacuation is approximately the same regardless of the scenario. The explanation is simply that the metro station infrastructure is the same for all scenarios. The capacity and evacuation routes are the same in each case.
Although evacuation times are similar, the number of casualties is not and depends on the type of attack. The drone attack caused the greatest number of casualties and injuries due to its targeting of a train arrival, when pedestrian numbers are at maximum density.
The company continues to collaborate with EU Commission on the terrorism safety project.
Furthermore, STAM plans make additions to their project. For example, a smart signaling system to improve evacuation times. They also intend to implement and simulate security systems that are based on artificial intelligence algorithms that can recognize suspicious objects, such as a bomb. Evaluating these systems can determine how they can best help prevent an attack.
The case study was presented by Pietro De Vito, of STAM, at the AnyLogic Conference 2021.
The slides are available as a PDF >>
Similar case studies
Passenger Flow Simulation at Frankfurt Airport
As the operating company of several major international airports, Fraport AG is one of the main “Global Players” in the airport industry. With more than 140,000 passengers per day and over 80 aircraft movements per hour, Frankfurt airport – an aviation hub of worldwide significance – is Fraport AG's...
Montreal International Airport: Simulation for Early Bag Storage System Implementation
GSS Inc. is a Canadian engineering company that provides strategic and technical consulting services with a strong focus on simulation and optimization in the context of major infrastructure and transformation projects. GSS helps clients in different industries including healthcare, airports, transportation, logistics, and...
Optimizing Airport Processes and Designing Transportation Facilities with Simulation
TranSystems is an architect and engineering company with over 25 years of modeling experience in the transportation industry. The company works on projects related to railroads, airports, seaports, roadways, transit supply chains, industrial facilities automation, and even quick-service type operations in restaurants and...
Crossing the English Channel with AnyLogic
AREP, the subsidiary of «SNCF Gares & Connexions», developed a simulation model which optimized the utilizing of the Transmanche Terminal of Paris’ Gare du nord. The main goal was to reduce the waiting time upstream and at the points of control of passengers. The model enabled to locate, value and represent...
Creating a Smart Baggage Handling System for Montreal International Airport
From 2020, due to the global pandemic, airports saw decreased passenger numbers around the world. As this pandemic starts to subside, airports are looking to increase their traffic numbers. Therefore, Montreal International Airport enlisted GSS, a Canadian based consultancy firm, dealing primarily with Airports, Aerospace &...
Improving Plane Maintenance Process with AnyLogic Simulation Software
The military aircraft maintenance turnaround process (the in-between time when the aircraft touches down, is refueled, rearmed, and inspected, in order to be released) is complex and, being fairly time-consuming, includes multiple interactions and parallel workflows. Engineers from Lockheed Martin, one of the largest companies...
AnyLogic Tackles Eiffel Tower Crowds
The Eiffel Tower operating company (SETE) used AnyLogic software to optimize the flow of tourists at the monument. With its help the engineers increased the number of visitors without redesign, but with people movement control.
Military Aircraft Maintenance Scheduling and Staffing Optimization
The Corps of Royal Electrical and Mechanical Engineers (REME) maintains all electrical equipment within the British Army. Among other duties, engineers maintain the Apache Attack Helicopter, one of the world’s most advanced multi-role combat helicopters. This aircraft is very maintenance demanding: it takes about 35 hours of...
Disaster Response Planning Using Agent-Based Simulation
In an effort to find practical operational solutions for a response to an unexpected crisis or natural disaster, Battelle, the world’s largest, non-profit, independent R&D organization, needed to test the effectiveness of a 48-hour shelter-in-place order for an Improvised Nuclear Device scenario. The goal was to reduce...
Automated Driving Systems Testing Using Agent-Based Modeling
One of the SwRI's research areas is automated driving systems. Engineers decided to make autonomous vehicles free, not only from the driver, but also from a control center. According to this idea, vehicles would communicate in a distributed manner with each other, share information about their current location and environment...