Alstom Mastria manages people flows in the means of transport

This multimodal mobility and monitoring solution, makes use of Artificial Intelligence, Big Data and machine learning allowing you to offer greater visibility into the distribution and flow of passengers in trains and stations.

Alstom has released a new version of Mastria, a multimodal monitoring and mobility solution that uses artificial intelligence to provide transport operators and authorities with tools for managing passenger flow.

Allows operators to adapt, easily and in real time, its offer to the various social distancing and public gathering requirements that have arisen due to the COVID-19 pandemic.

Thanks to Big Data and machine learning, Mastria offers greater visibility into the distribution and flow of passengers in trains and stations, as well as predictive functionalities. With this solution you can anticipate and control passenger density and operations in real time, adapting the frequency of the train, the capacity and required number of trains, as well as passenger flows to stations, among other things.

Makes it easier to match train supply with demand, optimizing operating conditions, including costs, and is especially useful for managing fluctuating demand spikes, as during peak hours, special mobility events or restrictions, as in the case of COVID-19.

Mastria's new implementation adds information on passenger demand for train sensors, ticket machines, traffic signaling, management systems, surveillance cameras and mobile networks to provide a real-time picture of passenger flows.

From this point, processes the information and transmits it to operators to ensure and anticipate specific occupancy levels, as a percentage of maximum capacity, at all times. May suggest increasing the frequency of trains, redistribute the flow of people to particular stations, readjustments to other transport systems, restrict entry to stations or even manage the distribution of passengers on the platform to align them with cars with more space on a train.

“Predicting is preventing. The ability of this tool to analyze millions of data in real time makes it an indispensable ally for operators at all times, but especially in the current context. Experts agree that public transport, and particularly the railway, continue to be the backbone of urban mobility. Artificial intelligence will be our best travel companion in this new era of mobility”, comment stephane feray-beaumont, Vice President of Innovation and Intelligent Mobility at Alstom Digital Mobility.

Panama's experience

Alstom implemented Mastria in the Panama metro late last year. The goal was to analyze passenger flows and offer a way to avoid the saturation that appeared at unpredictable times and only in certain seasons.

In just three months, and thanks to deep learning techniques (artificial neural networks that enable self-learning algorithms), localized saturation can be predicted up to 30 minutes before it can be visibly observed, allowing corrective actions that reduce waiting times at stations.

Currently, in response to the Covid-19 situation, the same technology is being used to adapt the operational actions that keep the train's freight to the 40% of its maximum capacity, as recommended by the country's health authorities.

Using various data sources, such as the user's travel information and car weight, new features have been developed: real-time monitoring of passenger density and flows at stations and trains, with new predictive alerts, simulation of opening and closing access to stations, and analysis of passenger distribution along trains.

Mastria Technology

Mastria is based on four standard functions: multimodal monitoring, traffic management, operations coordination and predictive analytics. These are highly configurable and can be combined according to the needs of operators and the global mobility network environment.

This technology ingests data from external information and control systems through secure network connections. It is flexible and scalable, and adapts to different transport networks of any size. In addition, can be extended to include new lines or additional means of transport.

Numerous pilot implementations of Mastria's artificial intelligence technology have already taken place in Paris, Florence, Zaragoza and Panama.

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