I’M IMPROVING PASSENGER EXPERIENCEUSING INSIGHTS FROM BIG DATA TO INFLUENCE STRATEGIC DECISION MAKING AND USER BEHAVIOUR

AUTHORS

Lila Tachtsi Atkins Fellow

Richard Bradley Technical Director

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A SUSTAINABLE, TECHNOLOGY ENABLED FUTURE POWERED BY BIG DATA

Mobile technology has put an incredible amount of computing power in people’s hands. Smartphones have changed the way we do business, purchase goods and engage with services, with a wide range of devices, including cars, connected to the internet and each other.

Together with ever faster and more reliable connections, mobile technology has dramatically increased the volume of data we generate, capture and store. So much so, this data is now influencing business decisions and driving innovation like never before. It is transforming the way we think about transport but have we fully realised its potential?Globally, there are currently more than eight billion devices connected to the internet, and that number is expected to increase to 20 billion by 2020.1 In just over a decade it is expected to rise to one trillion. From light bulbs to thermostats, coffee machines and even air fresheners - if it is connected, it is classed as ‘smart’. This connected world, or Internet of Things as it is known, is not just making our own homes smarter, but also making streets and entire cities smarter.

All of these internet-enabled devices are generating an unprecedented volume of information and every time we connect, tweet, like a post or open an app, we are adding to it. The end product is termed ‘big data’. The challenge for businesses and authorities lies in finding new, disruptive ways to deliver better value services and use this big data to make smarter decisions.

In a more connected world Connected and Autonomous Vehicles (CAVs) will also generate big data which, if shared appropriately, will create benefits through greater collaboration. There will be rich and reliable data about the transport network’s condition and operation, about traveller and vehicle behaviour, usage peaks and troughs, about the design and operation of towns and cities, as well as data to understand longer term societal trends.

1http://reports.weforum.org/digital-transformation-of-industries/wp-content/blogs.dir/94/mp/files/pages/files/digital-enterprise-narrative-final-january-2016.pdf

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According to McKinsey&Company: ‘The collection and strategic use of information can improve forecasting and help to nudge behaviour in ways that improve the reliability of transport infrastructure and increase its efficiency and utilisation’.3

We can already see this in action on London’s public transport system. Transport for London (TfL), the organisation responsible for much of the UK capital’s transport network, has been using big data to inform its decision making and improve passengers’ experience for a number of years. According to TfL: ‘Big Data and the Internet of Things have amassed data in ways that regular ticket stands and cash purchasing will never be able to match’.4

As an example, data gathered by the pre-paid Oyster cards that replaced paper tickets is helping TfL gain greater insight into people’s journeys. Bus travellers only have to ‘tap-in’ and don’t ‘tap-out’, so TfL turned to big data to understand where people go next. Lauren Sager-Weinstein, Chief Data Officer at TfL, explained in an interview: “If we see the next tap follows shortly after and is at the entry to a tube station, we know we are dealing with one long journey using bus and tube. This allows us to understand load profiles – how crowded a particular bus or range of

buses are at a certain time, and to plan interchanges, to minimise walk times and plan other services such as retail”.5

Atkins is expanding its use of big data to include mobile phone data, GPS data and a wide range of maintained datasets and connected sensors. This enables us to plan and design future services, address problems on the network more quickly, inform customers of any disruptions, provide personalised travel updates and much more.

And this is only the start. We have a growing portfolio of big data insight projects based on more generic and well-maintained data sources, and built on data analytics platforms that can automate common analysis, which enables substantial productivity and quality improvements. For example: using mobile phone data to estimate travel behaviour; building regional and national transport models from mapping and property ownership data; and using social media data to inform traveller choices.

Data is valuable - it has been described by some analysts as a ‘currency’ or ‘the new oil’.2

In many sectors, including transport, it becomes invaluable when it is gathered, analysed and transformed into operational and business intelligence. Now there is great potential for doing so in real-time, offering even bigger opportunities for enhancing the travel experience.

Using big data to make a big impact

2http://fortune.com/2016/07/11/data-oil-brainstorm-tech/ 3http://www.mckinsey.com/industries/capital-projects-and-infrastructure/our-insights/big-data-versus-big-congestion-using-information-to-improve-transport 4https://data.london.gov.uk/blog/improved-public-transport-for-london-thanks-to-big-data-and-the-internet-of-things/ 5http://www.forbes.com/sites/bernardmarr/2015/05/27/how-big-data-and-the-internet-of-things-improve-public-transport-in-london/#7afc1c33ab38

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More intelligent mobility

As well as adding extra network capacity and delivering a better customer experience, big data offers an incredible opportunity to influence people’s behaviour. Through deeper insight into traveller behaviour we are able to present users with smarter and more sustainable transport choices.

For example, we could influence people’s decision about their commute and, critically, can do that before they leave home for work in their car. This will require reliable and trusted predictions of what traffic will be like in an hour’s time, and even the probability of network conditions later in the day during their return home journey. With historic big data providing context and real-time big data providing accuracy, we can derive insights and deliver personalised reports, travel options, and recommendations straight to a person’s smartphone.

Within a CAV, big data will be used to predict how best to collaborate with nearby CAVs and connected infrastructure to optimise local capacity, for example timing arrivals to traffic signals. It will also allow the creation of vehicle platoons to shared destinations, with the reward of uninterrupted flow through traffic signals via a traffic signal ‘green wave’ and direct routes to areas with the highest probability of parking spaces.

Changing people’s pre-journey and in-journey behaviour will help ‘sweat the assets’. But longer term fixes will require major shifts in people’s investment and ownership choices, including buying cars and houses. Using big data insight, we will be able to encourage and incentivise users of the transport system to move closer to their workplace and popular utilities, as well as to more sustainable transport and urban environments. The maximum value of collaborative CAVs will only be possible with shared vehicle ownership and better planned urban networks. And contemporary planning with big data insight, will help ensure we have the right travel alternatives in the right place and at the right time, making these long-term choices attractive.

To achieve these step-changes in behaviour we need technology to move the focus of the transport system towards a more customer-led dynamic. We need urban planning to make our cities highly efficient, great value and attractive places to live and work, and allow us to give the rural environment back to nature and for the sustainable production of food and clean water, and energy to power this future society.

What is essential now is increasing the sharing, volume and quality of data to enable us to plan, design and operate in a more sustainable future, led by new technology-enabled business models - and not least by people’s willingness to change to better, more sustainable choices.

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So where to now?

To turn raw data into the actionable insights that operators can use to maximise efficiency and improve services we must address several challenges.

Applying the data

The sensors embedded within connected devices are streaming information at an extraordinary rate.We need to capture and organise data, but also, in order to interpret it properly, we need to place it in context - for example, with information on the past.

Cloud computing is making big data more accessible, reducing the need to move data around, and allowing us to automate how to sort and categorise, and interpret information. For example, we can use ‘machine learning’ to find an address from only a point on a map. But the operational usefulness of data increases as the time taken to understand and extract intelligence out of the data decreases. Network operators could more quickly influence someone’s journey, by updating their door-to-door travel forecasts for the next hour, if they can access near real-time data that can be used in reliable and trusted predictive models.

In essence, we need to increase the ‘velocity’ of traditional data analytics from what might be several weeks to a matter of minutes, with big data enabling new forms of algorithms and models to be trained and applied on ‘accelerated’ computer systems.

Interoperability

We are looking for ways to ensure data can be shared seamlessly across systems and sectors so we can maximise the benefits of big data for society as a whole. This sharing has obvious benefits to how we might ‘load-balance’ the system to ensure there is sufficient transport capacity, energy and utilities, with minimal adverse impacts, but there are probably many less obvious benefits. For example, could a change in travel behaviour have an unexpected impact on crime that, if understood, could generate benefits for people? At the moment, a lack of interoperability is not only making sharing expensive and time consuming, but prevents us from realising the full range of benefits that could help influence how we plan, design and operate our cities and transport systems.

Privacy and Security

Questions about who owns data and how secure our personal data is are already being asked. Cyber security is at the forefront of current thinking. Is it the system operator, the developer of the sensor or the individual who is accessing the services? Anonymising and aggregating data to create broad profiles instead of specific details may help make this more acceptable but our need to share and collaborate exposes many security vulnerabilities. These vulnerabilities need to be managed to ensure that the benefits of sharing out-weigh the security requirements, which could move us to more closed systems.

Sharing benefits with the community

We need a shift in public attitude to data sharing. People may be more willing to share their data if they can see a clear benefit to them from doing so. For example, if CAVs occupants’ data is used to improve their journey through collaboration with other CAVs, the occupants might be more willing to accept sharing this information, even if it affects their privacy.

McKinsey&Company surveyed more than 3,000 people in the US, Germany and China and found that 70 percent of American respondents were willing to share personal data for connected navigation and 90 percent of Chinese respondents said they would share personal data to enable predictive maintenance.6

Public vs commercial interests

A report by the UK Government’s Chief Scientific Advisor highlighted the importance of open data to our ability to realise the benefits of the Internet of Things. It made the following recommendation: ‘Open Application Programming Interfaces (APIs) should be created for all public bodies and regulated industries to enable innovative use of real-time public data, prioritising efforts in the energy and transport sectors’.7 But balancing commercial interests is unlikely to be straightforward and will need careful consideration. Other than higher value customer based data, like mobile phone data, it might be that the key commercial benefit is around intelligence added by combining datasets and the insights gained.

6http://www.mckinsey.com/industries/travel-transport-and-logistics/our-insights/will-car-users-share-their-personal-data 7https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/409774/14-1230-internet-of-things-review.pdf

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So, we already know we can do more with big data and technology. A key next step has been identified in Gartner’s ‘Top 10 Strategic Technology Trends for 2016’ as the merging of the real and digital worlds, in what Gartner has dubbed the ‘digital mesh’. The digital mesh refers to the sphere of devices, information, applications, and services that exist around the individual. As the mesh evolves, all of these different elements will become interconnected, creating a seamless link between the user, their data and environment which they occupy.

When we link the digital mesh with advances in Artificial Intelligence (AI) we can, in real-time, collate data surrounding the individual, transform this in to high value intelligence and deliver this to the individual visually through ‘augmented reality’ devices, which are receiving much attention from tech giants like

Apple. Simple examples are already here with Google’s voice controlled audio delivered ‘hands-free’ direct to a pedestrian’s ear piece on route directions, presenting new opportunities for advertising. But as AI is trained and learns more it will speed-up and become more reliable to the point that anything interacting with the individual’s digital sphere can be tailored for their consumption in real-time. Emerging examples include Microsoft’s Translator Speech API, allowing multi-lingual AI interactions by integrating speech translation in the experience, which sounds a bit like the ‘babel fish’ from Hitchhiker Guide to the Galaxy novel that also translates languages in real-time audio.

This digital mesh is expected to drive the expansion of digital business even more towards the ‘algorithmic’ business, with key business decisions made using predictive analytics, built

from the insight gained from big data and automated in real-time using AI. Through enhancing customer insight this will provide new ways to cut costs, optimise performance, deliver reform in the public sector and help us work towards a more sustainable future. It will support a new way of thinking about mobility, allowing businesses to put individuals at the heart of service provision. CAVs, and everything they offer as a technology will use, and enhance, complex flows of information, and will be part of this relationship.

With this vision in mind we need to use data and technology scenario planning to chart our route towards the digital mesh. The opportunities outlined in this paper could be considered as key waypoints to guide us on our way to our more connected, automated and data driven future, and a better passenger experience for us all.

And this is only the beginning

You can follow the intelligent mobility discussion by using #AtkinsMobility on Twitter, Instagram, and Facebook.

Lila Tachtsi is an Atkins Fellow for asset management. She has more than 25 years’ experience in the transport sector in the UK and overseas. Lila leads a growing team of asset management professionals who are helping to shape the future of infrastructure in the UK. Lila has led the development of most of the current national asset management guidance in the UK and supported the sector through the development of tools, processes and training to enable rapid and effective progress with asset management. Her clients include the Department for Transport, Highways England, Transport Scotland, HS2 and numerous local highway authorities. Lila is the vice Chair of the World Road Association UK, and a member of a number of technical committees around the world.

CONNECT Get in touch with Lila at linkedin.com/in/lila-tachtsi or join the discussion with more than 4,000 professionals in our ‘Intelligent Mobility LinkedIn Group.

Richard Bradley is part of Atkins’ intelligent mobility team. Intelligent mobility is about connecting people, places and goods across all transport modes. His primary focus is around data and the holistic simulation of multi-sector systems. This includes understanding the interaction of a wide spectrum of industries, focused around transport, and how personal and corporate behaviour can be influenced to optimise overall effects to society, the economy and the environment. He has over 28 years experience in transport planning and engineering, and developing modelling and appraisal software, and has worked for numerous consultants as well as running his own practice for 11 years.

AUTHOR

Lila Tachtsi Atkins Fellow Lila.Tachtsi@atkinsglobal.com

AUTHOR

Richard Bradley Technical Director Richard.Bradley@atkinsglobal.com

atkinsglobal.com/im

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This whitepaper was originally created by the Atkins Fellows for the Fellows Technical Conference 2016

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