Engineering Innovation in
Smart Transportation
Our end-to-end solution for travellers' crowd management.
Approach & Solution
Approach
An operator in the rail sector commissioned Engineering to create an integrated crowd management solution with the following two objectives:
- to carry out a layout assessment: to study and approve the impact of the positioning of new gates in the stations ex-ante;
- to identify critical situations: to anticipate potential overcrowding and identify, through a what-if approach, possible ex-post mitigation actions.
Solution
We developed a crowd management solution that includes a model of the main reference station, with a focus on the shopping arcade, the ticket check area in front of the access gates and the platform area.
This digital model is used to perform different simulations using the following parameters: the topological configuration of the gates, data on passengers and visitors, the technical configuration of the trains, and the relevant timetables, to return data such as the percentage of the floor space that is occupied over time, the dwelling time for each area, alerts for predicted congestion, and the evacuation time.
The solution reproduces the flows of people moving within the station on the model, using the greatest possible detail for each individual visitor.
This allows for a more precise understanding of the reasoning that guides a person within the spaces, which typically depends on external variables such as their arrival/departure time, train delays or cancellations, the type of traveller they are, the station layout, and the presence of security features or other obstacles.
This digital model is used to perform different simulations using the following parameters: the topological configuration of the gates, data on passengers and visitors, the technical configuration of the trains, and the relevant timetables, to return data such as the percentage of the floor space that is occupied over time, the dwelling time for each area, alerts for predicted congestion, and the evacuation time.
The solution reproduces the flows of people moving within the station on the model, using the greatest possible detail for each individual visitor.
This allows for a more precise understanding of the reasoning that guides a person within the spaces, which typically depends on external variables such as their arrival/departure time, train delays or cancellations, the type of traveller they are, the station layout, and the presence of security features or other obstacles.
Results
Better prediction of critical situations such as overcrowding
More timely simulations of the possible impact on the system
Accuracy in tracking traveler flows
Improved station organization through data
Project value
Innovation
Cost cutting
Process performance
Enabling Technologies
Digital Twin
AI Advanced Analytics
IoT
Engineering proprietary products & other technologies
Project Team
Transport and Infrastructures
Industries eXcellence
Data & Analytics