Dynamic Train Platform Distribution
RSA Student Competition
2020
RSA Student Competition
2020
A system to reduce dwell time by adaptive platform distribution through an agent-based particle structure, dynamic alighting and boarding formation and improvements in real-time information display.
In an ideal rail system, every train would arrive and depart at its intended station without delay. However in reality, trains are behind schedule very frequently. Delayed trains are the largest factor of customer dissatisfaction.
Dwell time, the time from wheel stop to wheel start at a station, is one of the major factors that cause the train delays. Excessive dwell times cause delays to singular trains, which can have a knock-on effect to escalating to severe delays in the entire railway/underground system.
System constraints, platform layouts and mechanical aspects of the train system have an impact on solutions such as platform distribution.
In an ideal rail system, every train would arrive and depart at its intended station without delay. However in reality, trains are behind schedule very frequently. Delayed trains are the largest factor of customer dissatisfaction.
Dwell time, the time from wheel stop to wheel start at a station, is one of the major factors that cause the train delays. Excessive dwell times cause delays to singular trains, which can have a knock-on effect to escalating to severe delays in the entire railway/underground system.
System constraints, platform layouts and mechanical aspects of the train system have an impact on solutions such as platform distribution.
The number of friction surfaces and physical energy exerted by the passenger is affected by the alighting and boarding formation.
There are 3 main types of alighting and boarding formations and scenarios. Studies show that the advantages of the scenarios vary depending on the crowd level and physical aspects of the system.
With a projected graphic system, the formation can be altered dynamically to reduce conflict between passengers, making their movements smoother and more efficient.
There are 3 main types of alighting and boarding formations and scenarios. Studies show that the advantages of the scenarios vary depending on the crowd level and physical aspects of the system.
With a projected graphic system, the formation can be altered dynamically to reduce conflict between passengers, making their movements smoother and more efficient.
Heat-mapping units equipped with RGB & infrared cameras and depth sensors are installed in the carriages of the train.
They are used to predict behaviour and in turn to minimise friction surfaces. Bi-directional movements where cooperation and negotiation play an important role can be simulated using crowd simulation software such as Legion. Using both the social force model and grid-based models, an intelligent AI system could be installed to identify concentration of crowd on the train and platform, predict the passengers’ behaviours and relay the information in order to distribute passengers accordingly.
They are used to predict behaviour and in turn to minimise friction surfaces. Bi-directional movements where cooperation and negotiation play an important role can be simulated using crowd simulation software such as Legion. Using both the social force model and grid-based models, an intelligent AI system could be installed to identify concentration of crowd on the train and platform, predict the passengers’ behaviours and relay the information in order to distribute passengers accordingly.
Overhead projectors with Lightform sensors (projection mapping and edge detection technologies) equipped are installed on the platform.
Projection mapping method provides a non-destructive and adaptable solution to way-finding and real-time information display.
Projection mapping method provides a non-destructive and adaptable solution to way-finding and real-time information display.
1. During transit, heat-mapping units records and analyse the crowd concentration levels within the train, identifying the least concentrated areas. Machine learning technology is used to study the behaviour of the passengers. The information is then sent to the upcoming platform where feedback is performed.
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2. Once the data is received at the upcoming platform, the overhead projectors project an agent-based swarm of particles which is emitted from the entry points, leading the passengers to the appropriate areas of the platform. Waiting areas and door/carriage number graphics are also projected on the ground.
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3. Particle system continues to guide and nudge passengers towards entry points that lead to the least crowded areas of the train. Passenger is provided with the most comfortable option, therefore increasing satisfaction. When the train arrives, the projectors equipped with projection mapping and edge detection technologies turn the train exterior into a canvas where more information is projected.
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4. The system shows information such as: where the train is going and is calling next stop, as well as information on the next train arriving at the platform, to provide passengers the option of waiting and boarding a less crowded train. This provides a positive feedback to counter passengers rushing onto the train last minute. The projected ground graphics completes the alighting and boarding sequence.
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Dynamic Projections
Experience Prototype.
A mock-up of the system was created to refine and further develop the service experience Feedback was gathered to identify and reinforce design decisions.
Grid-based AI analysis tool.
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A mock-up of the system was created to refine and further develop the service experience Feedback was gathered to identify and reinforce design decisions.
Grid-based AI analysis tool.
Agent-based particle system mock-up, passenger chooses the path with more arrows/particles, as well as choosing the path colour coded green. A combination of particle density and colour gradients should be implemented to ensure intuitive directions.
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Alighting and boarding formations. Creating a path of least conflict.
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Direction for exit projected directly in front of the alighting passenger to prevent congestion.
- Non-destructive solution, graphics are projected, therefore reducing the need of stakeholders altering existing infrastructure.
- Passengers are presented with intuitive directions that lead them to a more enjoyable and efficiently operated journey, without the need of compromising.
User Journey Map:
A map of the user journey including train operaing phase, pain points from primary and secondary research, emotional state of the customer, digital and physcial touchpoints, organisation activities, policies, challenges and the objective/ vision of the proposal.
RnD
