MONTPELLIER MÉDITERRANÉE MÉTROPOLE EXPERIMENTS WITH arlas.city

As Part Of A Research And Development Contract

3 February 2022, Media Release

Media release, 3 February 2022

In a quest to expand its smart city initiatives, Montpellier Méditerranée Métropole has chosen a consortium that includes Gisaïa among 10 others consortia in a smart city initiative for digital technology at the service of the territory’s project. It is a one year experimental work for the metropolis to offer new services to the city.

The competitive call for projects received over 30 innovation applications covering diverse themes: mobility, culture, energy, the environment, living in the city, digital inclusion and IOT.

Gisaïa, ICIA Technologies, and Patrick Gendre, who is a mobility expert, proposed the “Open Mobility Dashboards” project.

This project responds to the Montpellier Méditerranée Métropole mobility plans for 2030. The Métropole is looking to develop mobility indicators that will support data-backed decision making to improve travel for its citizens. arlas.city, our public transportation data analytics solution will support the initiative in developing public transport indicators. The Open Mobility Dashboard will also include mobility indicators for pedestrians and cyclists.

The projects were selected based on the the following criteria

The service: level of utility, added value,
The innovative nature of the project
Potential economic benefits: visibility and development potential of the project
The ability to be experimented (the quality of the protocol and the monitoring of uses)
Interoperability and reuse
The overall coherence of the project in terms of sustainable development, resilience and contribution to the quality of life of citizens

In France, Montpellier, joins Tisseo collectivities in using arlas.city for public transportation decision making.

Arlas.city supports public transport operators, authorities and researchers in ensuring that their decisions are founded on data. Various business departments in the Montpellier Méditerranée Métropole will provide their expertise to improve feedback and knowledge of the application contexts of the services developed by the winners.

Request for a demonstration of arlas.city here.

GET IN TOUCH For more details

contact@gisaia.com

About Gisaïa:

Gisaïa brings seven years of geo-big data analytics expertise, and a robust geo-analytics solution, “ARLAS^Ⓡ. The ARLAS framework has been tried and tested in diverse use cases for geospatial intelligence, especially in Earth observation data optimisation.

ITS Congress in hamburg

INNOVATING FOR THE FUTURE OF MASS TRANSIT & FLEET MANAGEMENT

October 04, 2021

THE TREND POST COVID 19

Globally, property pricing has always been tied to essential amenities. As agents often say “Location. Location. Location.” Up in the list of coveted ‘should haves’ is ‘public transport nearest to me’. The ‘near me’ phenomena means that people are increasingly demanding easily accessible efficient services from their mass transit providers.

Google trends record of the searches with the term ‘near me’ between 2004-2021

Even with COVID 19’s triggered migration out of city centres (where public transportation is often better connected) to suburbs, properties closer to public transportation still top buyers’ and renters’ requirements. This means that public transport has a future way beyond COVID 19. Current data already shows positive heat maps around mass transit areas. Decision makers are of course interested in the trend as they seek to optimise their offer. The answers they know, lie in analysing past activities against new trends. Historical and real data merged into one platform can start drawing a clear picture.

OPTIMISING TRANSPORTATION SERVICES WITH DATA

Arlas.city is designed to help authorities and operators to have a global view of their offer and make necessary changes backed by data. As the near me trend continues, a great combination of key user indicators; frequency, accessibility and reliability offers services that ensures riders get as close as possible to their destination, and in the least amount of time. These indicators are already set in arlas.city. But that’s not all, there is room to add as many datasets as required to expand the analytics for even more nuanced analysis.’

Isochrons calculations of the Toulouse mass transit network showing how much time it takes to go from one point to diverse destinations.

ITS CONGRESS IN HAMBURG

The need for better systems often draws the mobility sector together to explore innovative ways to move the industry forward. One such event is the ITS (Intelligent Transport Systems) Congress which is one of the biggest occasions that brings together the mobility industry to discuss smart mobility and the digitalisation of transport. The event takes either as a regional or global assembly. This year, Hamburg will be hosting the world congress from the 11th to the 15th of October. It is a great platform to promote innovative solutions for sustainable mobility. The participants, who are also drawn from the mass transit sector, are invited to ‘Experience Future Mobility Now’. The event offers various activities; exhibitions, academic track, plenary sessions, thematic conferences and live demonstrations.

ITS Congress Hamburg 2021 already has over 300 exhibitors confirmed, and expects over 15,000 visitors invested in the transit industry from all over the world, including public transport authorities and operators who will be seeking solutions for smarter, cleaner and greener mobility.

Gisaïa is part of the Business France entourage. We will be happy to receive congress participants at the French Pavilion to demonstrate our solutions for data-backed decisions for public transportation and fleet management analytics.

You can book a live demo with us during your visit by sending an email to: contact@gisaia.com .

References

COVID Mobility Trends – Google

Residential Hotspots Post Pandemic – CBRE Global Investors

Public Transit Boosts Residential & Commercial Real Estate Value – APTA

Time spent in traffic congestion in Europe

PUBLIC TRANSPORT DATA Analytics

THE CITY WHOSE RESIDENTS RAVE ABOUT THEIR PUBLIC TRANSPORTATION

January 19, 2021

What can public transportation authorities and operators do to get more people using public transport? Is there a solution that brings; population data, public transportation data and residents activity data together to help public transport decision-makers? Yes, we propose arlas.city, a geo-analytic SaaS.

Toulouse tram and metro lines displayed on arlas.city, composed from Tisséo’s GTFS data.

But first, let us look at the challenges in public transportation data analysis.

“A developed country is not a place where the poor have cars. It’s where the rich use public transportation.”

This statement by Enrique Penalosa can’t be truer. In other words, using public transport should be a choice and not a need.

A recent study by the European Commission on ‘quality of life’ in cities surveyed nearly 60,000 European city residents with a section on how public transportation affected residents. It revealed that:

Men, people with a higher income and families were less likely to use public transport.
Retired people, younger folks – between 15 and 24 years old, and those with only secondary education – frequently used public transportation.
Big-city residents like London, Prague and Paris were more likely to use public transportation than their counterparts in smaller cities.

But why would cities experience less public transportation uptake when data indicates that with each passing decade, cities have become even denser? And what would it take to move private transport users to public transportation? One of the many answers is; intermodalism.

Intermodalism not only gives users multiple options to reach their destination, but it also allows public transportation authority to quickly adapt services to growing needs. Creating transfer zones where frequent transport lines intersect. This allows people to reach more destinations faster.

In the European Commission study, it was no surprise to find that there was a strong correlation between efficient public transport and happy residents.

What was surprising was that the cost of public transportation did not have a significant impact on resident’s happiness.

Residents want efficient and reliable transportation.

To promise these, public transportation authorities and operators mix up different modes of travel, ensuring that travellers get the best available option for each stretch of the journey.

Choosing the right mode highly depends on staying connected to the ever-changing needs of the users. This means constantly looking at data to offer seamless mobility.

But if there is an industry that churns out volumes of data every day, then public transportation would definitely be amongst the top. Big data presents a lot of opportunities which of course come coupled with challenges. Challenges that mostly come from data collection that precedes its uses and is often stored in different silos.

Public transportation authorities and Operators now find themselves looking at multiple lakes of data, swimming with diverse dimensions, which then leads to time wasted in decision making. And, sometimes the decisions, arrive when the original scenarios have changed.

Thanks to the advancement in location intelligence, going back in time and referencing volumes of historical data, merging data in silos and aligning it is now possible.

Arlas.city presents public transportation authorities and operators with a robust solution that scales with their data. They are able to easily and quickly dive into their aligned data for a unique analytical perspective of their entire network.

Visual display of ‘Segments speed’ on a network’s lines: bus, metro and tram.

Not only, that, but public transportation data analytics can also now be plugged into the cities’ population data and residents’ activities, so that authorities and operators can really respond to present events and projected trends.

Population density data created and visualised in arlas.city

Arlas.city, a geo-analytic platform for public transportation that can facilitate all this.

Bordeaux Métropole transport network on arlas.city, composed from Keolis GTFS data.

Arlas.city which is designed for public transportation authorities and operators gives decision-makers the opportunity to make timely data-backed decisions, to meet residents’ needs and desires of efficient public transportation.

Aligning data from all modes with other dimensions would save lots of time. But the ability to quickly visualise it and stay ahead of potential roadblocks would result in happier residents.

These residents only want:

efficiency – are public transportation services reliable?
accessibility – are the services where people want them?
comfort – do they meet people’s needs?

Another European Union analysis on transport and mobility found that in 2017, Europe residents spent an average of 29 hours annually in traffic congestion. UK residents were the most unfortunate with an average of about 46 hours annually, up by five hours in just two years where they spent an average of 41 hours annually in 2015. France’s residents, while not recording a significant increase, also went up from 29 hours in 2015 to 30 hours annually in 2017.

Most travellers just want to go from one place to another. They want to take the shortest time getting there. They are willing to pay a fair price for it. Including isochrons in public transportation analysis helps decision-makers to provide multiple short routes to diverse destinations.

Isochrons’ mapping of travel time in minutes, from one point to different destinations.

Travellers choose the services that bring them the closest to their destination for either the lowest cost or in the least amount of time. In the era of smart cities, residents expect their public transportation services to be even more effective, dependable and convenient.

Setting up public transportation services for thousands (let alone) millions of users cannot be easy. What with continuous changes in needs like; a new school in a neighbourhood, a shopping mall or even unpredicted global events like COVID-19 where working and other social habits are affected. By analysing:

ticket validation data
scheduled vs achieved trips
delays
population
residents’ movement

Decision-makers can understand residents’ past trends to respond to current events and even predict future needs.

Get in touch with us if you want to see arlas.city’s application on your data. We are happy to organise a live demonstration and to help you meet your travellers’ diverse needs for public transportation.

References

Smart Cities Report – European Commission

European Cities Still Have Dense Development – Bloomberg

Traffic Commute Grindlock Transportation Study

Road Congestion – European Commission

Urban Transport Challenges – Transport Geography

MEDIA RELEASE

Gisaïa launches arlas.city with Tisséo Collectivités as first adopter.

December, 14, 2020

Arlas.city is a geo-analytical solution for Public Transport Authorities. This innovative SaaS service gives public transport decision-makers the ability to respond to the needs of residents for efficient public transport. Arlas.city enters the market with Tisséo Collectivités.

"Arlas.city offers us a powerful visualization of our transport offer via a reactive and ergonomic interface. The proposed geospatial analysis tools will quickly allow our study managers to enlighten our managers on the state of our network and help them make decisions to develop it. We believe that arlas.city is, at the crossroads of GIS and the public transport business, the solution of excellence that we are looking for."

Tisséo

Collectivités

Tisséo Collectivités’ transport network is vast, complex and includes different modes of transport; metro, tramway, bus and cable car. Tisséo benefits from the harmonious alignment of all their data sources, which are distributed in several silos. Indeed, arlas.city offers a unified, global and instantaneous view of the different Tisséo data silos covering, among other things, the network elements (113 lines and 3674 stops), ticketing, and the advances/delays observed.

This allows Tisséo to measure theoretical, operational and societal performances. Tisséo’s teams can carry out customer analyses and obtain economic indicators to make precise and timely strategic decisions, for example to determine where to place stops, establish a new link between modes or even increase or decrease the frequency of services.

Arlas.city offers a unique analytical perspective on the operational performance of the transport network and its attractiveness to the public through the integration of population and ticketing data. In addition, arlas.city is interoperable with other solutions, eliminating redundancy and providing an efficient and seamless tool chain. This cloud solution offers great flexibility, especially for the growing need for remote working. Its ease of use makes it accessible across all public transport authorities’ command-chain for synchronised, evidence-based choices.

But arlas.city doesn’t stop there, as ongoing developments will allow the integration of demographic data.

Toulouse public transport network data viewed on arlas.city

"It will be possible to directly measure the match between supply and demand and to assess the proportion of the population benefiting from the supply. Not forgetting the power of the isochron calculator directly usable in arlas.city, which allows for instantaneous calculation of accessible areas, according to a network configuration and several origins. It should be noted that the bicycle stations are also used in the isochron calculations."

Sylvain Gaudan,

Technical Director of Gisaia.

Isochrones – curves connecting points accessible to travelers in a given time – are excellent indicators of network performance. Moreover, isochrones, once projected onto population data, allow the social performance of the population to be estimated.

arlas.city is constantly evolving to bring more tangible facts to decision-makers. Decisions are justified and supported by reliable data and analysis. They lead to a balanced and efficient public transport network that ensures mobility, accessibility and passenger satisfaction.