Telia launches the service Travel Emission Insights, which makes it possible for municipalities and regions to determine CO2 emissions from road passenger transport. This in turn enables better-informed decisions about specific measures that can help reduce emissions.

The new service, Travel Emission Insights, which is launched in the Nordics and Baltics, gives municipalities insights about the number of people travelling, the type of vehicle, the routes used and the emission levels that the journey causes.

The service is based on anonymized and aggregated mobile network data from 16 million Telia subscribers in the Nordics and Baltics, representative of the population in each country (Crowd Insights*). From the data, one can determine, for example, movement patterns, the number of people in different locations and how crowds move. This data is then applied to the CERO model, a calculation model developed in 2007 at the Royal Institute of Technology in Stockholm, by Markus Robért. The model has been used since 2014 and today, it has been implemented by over 100 companies and authorities to develop financially sustainable strategies for achieving climate goals. The CERO model, in turn, is based on more than 300,000 travel-habit surveys assessing modes of travel and journey times, as well as on calculations for CO2 emissions. Hence, it can illustrate in figures the probability of people choosing different mode of transport people in given circumstances, as well as the level of CO2 emissions for each mode of transport.

Telia Travel Emission Insights combines Telia’s data with the CERO calculation model, which provides municipalities with information about which routes most people travel, which mode of transport they use and the levels of CO2 emissions that are generated – in all an important part of the efforts to achieve set climate goals. The data can be broken down into particular routes. Then, with simulation, it’s possible to compare and quantify different efforts to determine how the changes would affect the emission levels.

In Sweden, road passenger transport accounts for approximately a quarter of the total CO2 emissions and reducing travel by car and other road vehicles is therefore an important part of the efforts to achieve the climate goals set out in the Paris Agreement. During the pandemic, Swedish municipalities have seen a reduction in travelling by up to 30 percent, which has contributed to a an unprecedented reduction in the total amount of CO2 emissions. But as people are returning to a more normal life, travelling has increased yet again – and emissions are again on the rise.

“We believe that municipalities and regions will be able to take more effective measures if the decisions are based on clear data. With Travel Emission Insights, you can simulate and receive recommendations on which transport changes will have the greatest effect,” says Kristofer Ågren, Head of Data Insights at Telia.

Järfälla municipality in the northeast of Stockholm, with its 80,000 inhabitants, is first to use the service. Read more about this here.

Telia’s own sustainability goals are today thoroughly integrated into the Group’s overall strategy, and Telia works intensively to create better, more sustainable societies and services. For example, you can read about Telia’s focus area Climate & Circularity, and about how we support our customers in reducing their emissions.

Article originally published on Telia’s web page.

* In Telia Crowd Insights, all data is completely anonymized and aggregated to protect the personal integrity and privacy and can never be traced back to an individual. Analysis takes place solely on the level of crowd movement patterns, disconnected from individual and person.

IT service company CGI and Finnish rail transport provider VR Group are deepening their cooperation to accelerate VR’s digital transformation. The contract now signed will make CGI VR’s primary partner in utilising AWS cloud technologies.

In line with its strategy, VR Group is migrating most of its IT systems to the cloud. The transformation will improve the company’s ability to serve its customers and respond better and faster to market changes.

“At VR, we rely on digitalisation and new technologies to improve customer experience and efficiency. Growth can only be achieved through agile innovations. Transitioning to the cloud enables faster development activities and also allows various experimenting,” says Ilkka Heiskanen, acting CDO and SVP, Strategy & Corporate Development, at VR Group.

CGI was chosen through competitive tendering as the company’s primary partner for cloud native application development based on Amazon Web Service (AWS) technology. CGI also won another VR Group tender for testing specialist services. The total value of the contracts is up to EUR 6–8 million, if fully realised.

“At CGI, we have invested heavily in recent years in the development of cloud services and expertise. We already have hundreds of cloud specialists in Finland alone, and as the world is becoming increasingly cloud-driven, we are constantly training and recruiting more. We’ve also opened a CloudOps service centre in Finland to complement our comprehensive cloud offering,” says Martti Reilander, Director of CGI’s Commercial Business Unit.

CGI and VR Group have a long history together. Now the cooperation is expanding not only to cloud development, but also testing services.

By automating and harmonising testing functions, we can bring even more cost-effectiveness and speed to VR’s cloud operations. At the same time, we can effectively optimise our customer’s cloud use,” Reilander explains.

Original article by CGI.

Unmanned aviation is now really taking off. The electric-powered and locally emission-free flying devices know as drones are coming under the magnifying glass of both companies and researchers. In order to ensure efficient, safe and professional operations, several major challenges need to be addressed. These include, for example, air navigation services for low-level airspace, control of flights when out of visual line of sight, and the possibility of performing several tasks with a single flight. These and many other challenges are being tackled by the Drolo project, which promises to be an undertaking of international significance.

The Drolo project will examine, develop and pilot solutions for traffic management in lower airspace, 5G connections and the utilisation of printed and embedded electronics. The project will test out smart drone services for use in ports, the use of drones in the vicinity of an airport, a drone weather service and the suitability of hydrogen as an energy source for drones. The project will also develop business models for Finnish drone operators from an export perspective. For example, performing several jobs or multiple customers during the same flight improves the cost-effectiveness of drones. The project will involve setting up Finland’s first drone air traffic control test area in the Oulu region.  The project’s partners include a number of key drone-related Finnish commercial and research actors. The project will create an ecosystem that will generate innovations and new drone-related business opportunities.

Business models and technology developed in ecosystems

Drone performance is rapidly evolving in terms of flight times, load carrying capacity and resistance to rain, snow and frost. The development of drones’ radio connections, autonomy and airspace management will enable new and safe use applications in both urban and rural areas. Examples include extensive use of drones in goods logistics, agriculture, forestry, harbours, airports and the construction sector as well as for official duties and in maintenance and inspection tasks. Within research activities, drones offer an excellent platform for the collection of many types of data. Drones are also seen as a platform for developing digital solutions for traditional aviation.

‘In addition to the performance of the technology and equipment, it is also important to develop operating models. Understanding the needs of different actors and how to fit these together with the aviation regulation and opportunities offered by the new technology is at the core of our research and development activities. Drolo provides a good framework for delivering realistic solutions in a multi-actor environment’, notes Ville Somppi, Director of Product Business and Sales at Insta.

Learn more and read the full article on VTT’s webpage.

A ground-breaking global autonomous train development project in Finland is moving on to its test phase. The aim of the initiative is to create completely new railway transportation services and to even double the amount of railway transport. The initiative, led by Finnish Proxion in conjunction with around 20 other tech organisations, innovates an agile, low-emission transportation concept for large industrial enterprises. In the future, aim is to also bring autonomous passenger traffic to the rails.

The autonomous train initiative, led by the Finnish railway transport, logistics and infrastructure expert company Proxion, has received a funding decision in June and is moving on towards the pilot phase where the software and equipment of the autonomous train will be tested, simulated and test-driven. The project is a significant leap towards the transportation of the future, and Proxion is leading the way in developing the usability and agility of all rail transport.

“The strict environmental targets set by the EU are in favour of developing the electric modes of transport, and railway transport is the most energy efficient way to transport goods by land. The innovative development of rail transport is therefore in key position, as the goals are to develop transportation that is lower in emissions and to achieve better rail utilization,” says Reijo Viinonen, the Project Manager of Proxion’s autonomous train initiative.

The piloting of Proxion’s autonomous train will begin already later this year. The autonomous train is expected to be operational in 2023.

The autonomous train reduces emissions and increases rail safety

Autonomy in transportation is a global trend, and its execution is being innovated constantly. While the development is well under way on roads, in the air and in maritime transport, the progress on railways has been slower.

The autonomous train unit in development is intended to be a low-emission and more cost-effective solution for short-distance industrial transport that is currently handled mainly by road transport.  An increasingly important feature of the train is safety. Technical Research Centre of Finland VTT, the innovation partner of the development project, is involved in enabling safe automation on the rails.

“It is important to ensure that the autonomous train operates reliably in all conditions and on a wide range of track connections. It is a leap towards safer railway transport. For example, sensor interpretation technology for the train unit is being developed as is combining a thermal camera and radar observations in order to be able to react correctly and in time to any obstacles or situations ahead,” says Pertti Peussa, Principal Scientist at VTT.

The advantages of an autonomous train unit also include agility and the longevity of the invested infrastructure. In addition, it offers a solution to the problem of available drivers, because, as the name implies, an autonomous train runs independently without a driver.

High international demand for autonomous rail transport

The first step of Proxion’s ambitious project is to pilot automatic railway traffic for freight transport in Finland that can be commercialized and is in high demand internationally.

The objective of the pilot is at first to improve the operating conditions of the metal and wood processing industries that are important to Finland. The project has collaborated with the steel company Outokumpu’s unit in Tornio and the forest industry company Stora Enso’s unit in Imatra.

Later on, the focus will be aimed more broadly on rail transport, where both goods and people are transported.

“The development of railway automation and ecosystems is currently a national interest for several European countries. All transportation will require AI-based data utilization solutions, that are also at the heart of the autonomous train project. The whole project represents a bold, innovative pilot that creates cost-effective, dynamic new services that support business needs,” says Janne Hauta, Finnish Ministry of Transport and Communications Ministerial Advisor specialized in rail automation.

The co-innovation development project of the autonomous train is funded by Business Finland and the companies Proxion, VTT, Teräspyörä Oy and Electric Power Finland Oy. Proxion coordinates and is responsible for the project and the information systems. VTT produces for the project the sensor technology and software needed to observe the environment, Teräspyörä Oy is responsible for fleet development and Electric Power Finland Oy for the digitization of rail equipment.

Further information:

Reijo Viinonen, Project Director, Autonomous Train Development Project, reijo.viinonen@proxion.fi, +358 40 630 0631

Featured image: Proxion

The United Nations has estimated that by 2040 almost 60% of people are living in cities across the globe and at the same time number of trucks, cars and air kilometres will double and the amount of emissions keep rising. In addition, millions of people and animals are killed in traffic – directly (accidents) and indirectly (emissions).

Solita‘s Account Director Aki Aapaoja writes about AI’s possibilities in traffic management.

Through the ages, traffic congestion has been prevented by building new roads and lanes but more than often it is a temporary cure as it triggers latent traffic aka induced traffic. It is a phenomenon where people decided to travel by car when they otherwise would not have. So basically it is about increased demand i.e., trips caused by increased supply i.e., road capacity.

In recent years, however, there has been more and more discussion that maybe data and data-driven solutions could be cost-efficient as well as long-lasting impacts on making transport greener, more adaptive, and more accessible. Being data-driven or using data doesn’t mean throwing all the existing and working traffic management procedures into the trash can but rather it is about gradual improvements alongside existing ones. Even today, 164 EB (1018) traffic data per month is generated and hence a range of potential use cases for data solutions exists.

Daunted by traffic and congestions

The challenges of transport are global but one of the worst affected countries when it comes to sustainability, congestion, and safety of transportation. Solely in China, there are more than 160 cities over 1 million people and over 254 million registered vehicles. It goes without saying that together urbanisation and motorisation as prevailing trends lead to massive adverse effects like 1500 megatons of CO2 and almost 1 million emissions-related deaths annually. In addition, the congestion is overwhelming – the average Chinese motorist loses nine days a year stuck in traffic. If nothing is done, the future of road transport does not look rosy. Doesn’t it?

Data weaves traffic management together

Together with a Chinese partner, Enjoyor co., we started a joint research pilot at Hangzhou city in Zhejiang province, China. Enjoyor is a leading Chinese traffic management company having annual revenue of over 400 million euros and it is responsible for traffic management in many Chinese cities such as Hangzhou, Fuzhou and Nanchang.

Hangzhou is the home of world-know Alibaba and over 13 million people are living in the metropolitan area, and it is a typical crowded city that is ranked top ten among China’s most congested cities. The first phase of the pilot aims at predicting traffic speeds in different road sections for the next 10-15 minutes in three minutes intervals by using historical data crunched with sophisticated machine learning algorithms. The pilot area consists of 309 road sections and 118 intersections while the used data includes several parameters like road topology, road section speeds, and signalling schemes. Data will be also enriched with traffic and weather incident data.

The overall, long-term objective of the research pilot activities is building enabling capabilities to identify traffic phenomena e.g. congestions in advance through advanced analytics and using the information for managing and optimising traffic at a regional level. Basically, it means that different trigger points indicating the possible emergence of a traffic phenomenon should or could be identified as early as possible.

The thing that makes it both interesting and challenging is the fact that issues impacting the traffic vary over time, their relations are not fixed and there are many of them. Hence, traditional management models are no longer suitable and there is a call for AI-based models which can be continuously updated or update themselves.

AI spiced digital twin with cloud and edge computing

In many cases we highlight the meaning of data, having a crystal clear business case and how important it’s to have tangible outcomes. In some of the cases we just experiment, learn and have a bit of fun. This is exactly that latter case when you have the freedom to play around – why not. We just throw trash to ideas that someone really knows the problem or there is something called business able to understand more than normal human beings. Based on the famous Agile manifesto we could just say we value the unknown more than something we think we know. We as people are sometimes biased, and look at things in a very narrowed way and especially when it comes to traffic – building a digital twin of traffic would be fun?

The challenge to build smart systems has been Conway’s law is an adage stating that organisations design systems that mirror their own communication structure. We are dedicated to trying a model where everyone in the team can time-box a bit of their study and work in parallel and together to vote for winning ideas so we would not be building a “one-size-fits” nobody solution. That was a huge success – in a few days we had already spatial data on visualisations, ongoing data replications going and tiny ML running on the edge. Now comes the interesting part – how to integrate all together for something you might see on PowerPoints as the future-proof architecture?

It’s the communication, team motivation, and keeping things small when possible so it’s easy to adapt. The team chose to use Amazon SageMaker Autopilot that can train and optimise hundreds of models based on these algorithms to find the model that is a good candidate for us. Same time few were working with AWS SageMaker to run machine learning models to find anomalies of data and anything suspicious – and immediately found time series data was fixed (typical on machine learning cases when we lack data). This incorrect way of fixing data resulted in bad models. This was not possible to be detected using any visualisation or typical data engineering tools.

After a few coffee breaks the first data API product was available on AWS serverless API development portal. Taking all this machine learning (EdgeOps) to Edge where resources are very limited can be accomplished using a rule of thumb – keep it very small and simple. Running all interference at Edge will bring few benefits like improved latency, security, and resilience. End of the week we were able to see which parts are common, automate all using AWS CDK and keep only the parts that are really needed to avoid feature creeps.

So did we build a full-blown digital twin? Not yet, and it does not matter. We found relevant feature importances from data assets and we can not wait to proceed on to the next step. Setting up even crazy goals and making experiments using new services from hyper scalers like AWS can be a first step to start something new. We now have rock solid scaleable edge, cloud, and MLOps solutions with few rock-solid models to teach us something new. Technology capabilities are outstanding and on that hype, it’s good to remember that a good team and trust in it is equally important. We encourage you to set your data and machine learning models free!

From tech to business and vice versa

For Solita, V2X is a spearhead project when it comes to holistic industrial internet of things capability development the whole funnel from mobile vehicle (car, truck, ship, machine) or stationary device (process, production) to end-user via cloud system including data pipes, real-time data processing, edge computing, and access control in some cases data farming when source data is not available yet. Technology development is not the main thing, but novelty comes from the collaboration between different people and ecosystems.

Read the original article on Solita’s web page.

In autumn 2021, Helsinki saw various pilot projects both on the ground and in the air. The newest kind of pilot was the delivery of products from a pharmacy to a customer by drone, which took place in late August. In the week-long pilot, products from the Lauttiksen Apteekki pharmacy in the Lauttasaari district were flown on a drone to the Jätkäsaari district.

At the same time, another pilot has brought shared electrically-assisted cargo bikes as an expansion of zero-emission alternatives, as hoped for by the residents of Helsinki. Soon, another ground-based logistics pilot is about to start with autonomous delivery robots bringing packages closer to the customers at virtual drop-off points.

Helsinki also has other ongoing operations to improve logistics through accessibility data.

Read more on testbed.helsinki about the pilots and the partners behind the innovations.

Picture credit: city of Helsinki

It has been 50 years since Semel Oy was founded. Known mainly as a taximeter manufacturer, Semel Oy has gone through many business challenges throughout the years. Technology of systems has shifted from analogy to digital, payment systems from offline to online etc.

Today, Semel markets state-of-the-art taximeter services that are world-class. We are a clear market leader in the Nordic countries and the only one to offer equipment as a service. Taximeter-As-A-Service and collaboration with Modulsystem Sweden AB have opened to new businesses for public transport, parking solutions as well as electric car charging services. We will continue to focus on our main perspectives and look forward into a successful future.

Picture credit: Semel

The automatic traffic test area in Hervanta, Tampere, is an example of the future of urban development. The digital twin of Hervanta is a versatile and user-friendly service design tool.

Just one click and you are there: On the screen, you have a bird’s-eye view of a 3D model of Hervanta, a suburb of Tampere. When you scroll closer to the streets, you will be surprised how detailed the model is. All the traffic signs and bus stops are in place and the weather conditions are realistic. Another click and you are inside a car. You can drive the car around the model and activate various data streams that you might find useful.

In the near future, services created by using digital twins will become a more normal part of urban life.

A digital twin is like an ever-growing and developing sandbox for urban developers to play in. It is a framework for real-life services. In the near future, services created by using digital twins will become a more normal part of urban life. Their global market value is increasing at dazzling speed – even the most conservative estimates predict that the market value will increase tenfold over the next five years.

Finnish developers have also jumped on this bandwagon. In addition to the tests in Tampere, digital twins have been utilised in urban development in Helsinki and Oulu. In Oulu, Sitowise created an accurate model of the city port.

Digital modelling is not exactly a new phenomenon. Digital twins have been used in shipbuilding and designing of factory production lines for several years. Now urban development has adopted the technology. Thanks to cities creating 3D models of urban spaces, visual digital twins have become more accessible and less cumbersome tool of urban development. In Hervanta, the model is being used for training automated vehicles, for example.

Automated vehicles take digital driving lessons

Tramway traffic operation will begin in Tampere in August 2021. There are plans to introduce driverless vehicles to assist tramway feeder traffic. These vehicles would transport people to tramway stops.  The vehicles would operate in an area of about one square kilometre around the Ahvenisjärvi lake. In this case, the digital twin is a platform for teaching vehicles to move safely around the area.

The pilot project is linked to a larger European project called SHOW (SHared automation Operating models for Worldwide adoption). The project pilots automatic traffic solutions. Sitowise is acting as the Finnish coordinator of SHOW. The City of Tampere supports the development of smart mobility strongly, and all their projects benefit each other.

To a user, the digital twin of Hervanta created by Sitowise looks like a combination of several visualised data streams and pleasing graphics. This is not the first digital twin created of Tampere. 3D simulation of urban spaces have been used for training tram drivers, for example.

– Digital twins have been utilised in Tampere for a few years now. All the new areas in the city centre have already been modelled. For example, the locations of buildings under development can be viewed digitally before construction has even begun. This makes urban development easier, says Jari Ikonen from Business Tampere.

In order to provide reliable support for ambitious projects such as training driverless cars, digital twins must meet high quality standards and depict the real word as accurately as possible. VTT Technical Research Centre of Finland played a key role in the project. VTT modelled unnoticeable but important objects, such as traffic signs and bus stops, and measured the coverage of a 5G test network in the area.

– In the Hervanta project, the accuracy of the model was, at best, as close as 10 centimetres. This helped us ensure that the model’s traffic signs and public transport stops took exactly the same amount of space as they take in real life, says Automated Vehicle Scientist Kimmo Kauvo from VTT.

Sensors and growing data streams support development

Over the past few years, digital twins have been introduced in urban development along with several significant technological leaps. The current level of 3D modelling, availability and amount of sensor data and standardisation of important technologies make utilising digital models easier than ever before.

– Telecommunication networks are now so fast that they allow almost real-time utilisation of sensor data. The City of Tampere is a pioneer in making city interfaces accessible and piloting new services. For example, anyone can access the city’s traffic light data if they are interested, says Riihentupa.

Game engines have also become more useful tools of urban development.

– The digital twin of Hervanta was created using a Unity game engine, which works well for projects of this scale. The rapid development of game engines has helped digital twins become more common in the field, says Technical advisor Niko Moreira at Sitowise.

Sitowise has a extensive expertise in field of digital twins, both accumulated from previous projects and constantly evolving. Elena Lassila, junior advisor at Sitowise who was involved in the project, is currently doing her master’s thesis on the topic. The actual digital twin exists in Sitowise’s virtual environment AURA. All the data generated via modelling and measuring is easily visualised and utilised in this virtual environment. Other people will also be able to benefit from the final product. The 3D model created through the digital twin will be released to the public.

This project clearly serves general interests. Here at Sitowise, our goal is to promote open digitality and apply it to different business models as widely as possible. – The digital twin of Hervanta is laying the foundations for countless of end uses that utilise the digitalisation of new urban spaces, Moreira adds.

Picture credit: Sitowise

 

The City of Vaasa aims to reach carbon neutrality by the end of the 2020s. The target is tough – carbon emissions must be cut considerably and rapidly. With the recently launched Vaasa Traffic 202x project, the City of Vaasa, in collaboration with Ramboll, is developing a new tool to support climate management.

The Vaasa Traffic 202x project aims to produce up-to-date information concerning developments in transport performance and carbon emissions in the city of Vaasa. It also aims to lead design work and measures so that the ambitious carbon emission goals are achievable.

In Vaasa, carbon emissions have decreased by about 30 percent between 2011 and 2019, the most significant reductions coming from electricity consumption and district heating. The biggest challenge is in road transport, where emissions have fallen by only 10 percent over the same period.

– The Vaasa Traffic 202x project is very important for the city’s carbon neutrality goals. Presumably, the development of vehicle technology will provide some of the required emission reductions, but at the moment, no one can say whether the car fleet is being renewed fast enough or what measures are needed to increase the popularity of walking, cycling and public transport, says Jukka Talvi, Municipal Technology Director in Vaasa.

– With the help of the tool that is now being developed, we will study various scenarios to achieve the goal and implement a system that can be used to monitor developments. Another important aspect is making the emissions target visible to every Vaasa resident, Talvi continues.

The strategic traffic modelling utilised in the project aims to depict the effects of various land use and transport planning projects on future volumes of traffic, the use of different modes of transport and CO2 emissions.

– The development project with the City of Vaasa is interesting for many reasons. The project fits well with Ramboll’s commitment to lead the way in sustainable development solutions. On the other hand, combining real-time data sources with strategic traffic modelling is an interesting development target that will enable new applications in the future, says Teemu Sihvola, Ramboll’s project manager.

Because of its accuracy, the BRUTUS traffic demand simulation model developed by Ramboll is very suitable for modelling sustainable modes of transport. The individual nature of the model allows the impact to be assessed in terms of socio-economic factors.

The project, funded by the Ministry of the Environment, is being implemented as a joint development project between the City of Vaasa and Ramboll, which is also co-financing the project. In the project, both new technology and a product with international novelty value are being developed. The monitoring group also includes parties from other parts of Finland.

Picture credit: Chrisfoffer Björklund: