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Five Bike Share Trends to Watch in 2018

When I talk to people at events, I see how business models have changed over the last year. Bike Share operators are constantly challenged to keep up with the rapidly changing industry and offer better rider experiences to its users.

 

A big opportunity for operators in 2018 is in how Bike Share Schemes are managed. It will not be enough to just supply the bikes, questions will be asked about how operators cater to the local market needs.

 

Intelligent operations will be at the heart of Bike Share Schemes in 2018 with operators focused on delivering the best experience to compete in the highly saturated market.

 

As Bike Share continues to grow across the globe, I see the following trends changing the marketplace:

 

  1. Rise in App-Based & Dockless Bike Share Models

App-based Bike Share Schemes are being deployed in more markets globally. In many urban cities, you now have access to free-floating bikes that can be picked up and dropped off virtually anywhere. In 2018, we will see an increase in cities adopting these schemes in an effort to reduce the strain on existing transport infrastructure and facilitate the move from personal vehicles.

 

  1. Growth of Multi-Operator Environments

Multi-operator environments are not new. We are already seeing many cities where more than one operator is running a scheme. Throughout 2018, this is likely to grow to more cities around the world and operators will be asked to deliver an optimised Bike Share Scheme to keep up with the competition. Cities will also need assuring that resources will be better managed to avoid bikes being damaged or left in unsuitable places.

 

  1. Optimised Redistribution with New Technology & Incentives

The growth in Bike Share Schemes and multi-operator environments will be the driving force for better redistribution. Operators will be challenged to offer schemes that work well and is not a nuisance to cities or its citizens. Fortunately, new technology such as geo-fencing and incentives including financial rewards will drive better rebalancing processes. From the events I’ve been to, it’s clear that operators are looking to do more to improve their redistribution efforts.

 

  1. Increased Bike Share Regulations

Bike Share operators have welcomed the prospect of more regulations. While some may hinder current operations, most regulations will help Bike Share Schemes to thrive. It will guide operators as to what is required and enable them to grow into new markets much easier.

 

  1. Driving Intelligent Bike Share Scheme Operations

In 2018, operators will look towards better ways to manage their schemes and to grow their ridership. We see growth in technology such as Artificial Intelligence (AI) simplifying the management process. It enables operators to sort through vast amounts of data to gain actionable insights that has a direct impact on their operation. That kind of information makes management of Bike Share Schemes simple and efficient.

 

In 2018, we will continue to see disruption in all parts of Bike Share and the wider transportation industry. It will impact how operators do business. How these schemes are managed will still be the main focus for many cities and its citizens.

 

Users expect transportation to be as simple and efficient as the other services they consume on a day-to-day basis. That puts the pressure on operators to deliver a well-run Bike Share Scheme.

 

An optimised scheme enables users to rely on its services and use it regularly. It reduces unnecessary costs and complications for operators while driving profits to their business.

 

Fortunately, I see new technology, incentives and processes enabling operators to transform their current business model.

 

At Stage Intelligence, we combine citywide data with AI technology to deliver real value to Bike Share Scheme operators. Our BICO platform makes it easy for operators to simplify their operations and deliver Bike Share Schemes that works for both cities and the users.

 

To find out more about how Stage Intelligence is transforming Bike Share Schemes around the world with AI technology, please contact  tom.nutley@stageintelligence.co.uk

 

2018: A Tipping Point for Artificial Intelligence in Transportation

2018 will be the tipping point for Artificial Intelligence (AI) in the transportation industry. It will be a year where AI becomes an essential tool with new understanding and recognition that it is critical to success. In our business and beyond, we’ve seen how influential this technology can be in changing business models and creating better transport solutions.

 

At Stage Intelligence, we’re seeing this become a reality. In 2017, we’ve seen tremendous momentum behind our business and growing demand for real AI solutions in transportation. We’re rolling out our AI-based Bike Share management solution in cities across the globe and changing the perception that Bike Share isn’t a viable, reliable transport option.

 

We are helping to accelerate transformation in transportation and utilising self-organising algorithms and elements of machine learning to simplify and empower Bike Share management.

 

2018: Challenges in AI

The future of transportation will be defined by AI. Research firm Gartner predicts that by 2020 almost every new software product will have AI technologies. In transportation, we are starting to see widespread application and development of AI technology that is being powered by the collection of data and use of algorithms.

 

That said, it is still a very young market with challenges ahead. I see three big challenges for AI in transportation:

 

  1. Not All “AI” is the Same – Many businesses that say they use AI don’t actually have it deployed. It is a buzzword and many businesses are doing data visualisations or pretty interfaces but when you look under the hood there’s nothing there. Operators eager to benefit from AI don’t get what they paid for and won’t see the best of it.

 

  1. Transportation Expertise and Focus – AI solutions need to address specific challenges. They need to be purpose built for transportation and developed by both experts in transportation and AI. Otherwise, you get generic solutions that solve generic problems rather than enabling real innovation and agility in transportation.

 

  1. Nurturing AI – AI isn’t just about building solutions. It is about training it and nurturing it to deliver the results you want. It requires people, time, effort and a lot of data to continuously maintain and develop the technology. You don’t just flip a switch. It requires an expert experienced in developing and growing successful solutions.

 

As we see more AI-based solutions adopted, there will be a move towards quality and performance. Solutions that are based more on buzzwords than results will fade away.

 

In 2018, more people will understand the basics of AI and make better decisions about the solutions they deploy. That’s good for transportation and will accelerate its growth.

 

Building Better Bike Share Schemes

We’ve seen tremendous growth in our business over the past year. In 2017, we deployed our solutions in new corners of the world.

 

Our business development team led by Tom Nutley was out and about at events and meetings almost on a monthly basis. We’ve been successful in sharing our belief in automated rebalancing and using self-organising algorithms to build better Bike Share Schemes and that has led to trials and deployments around the world.

 

Our flagship BICO Bike Share Scheme management platform has been adopted and is supporting ridership growth in unique markets in the Americas and Europe. In 2017, We added greater functionality to BICO including a successful internationalisation process that helped us to better serve our partners abroad and dynamic replenishment values for greater predictive management of a scheme. Both have made it easier for operators to deploy and benefit from our solution.

 

We are also proud to have partnered with industry bodies to accelerate transformation in Bike Share Schemes. We are a member of the platform for European Bicycle Sharing & Systems (PEBSS), created by European Cyclist’s Federation (ECF). Our work with ECF and PEBSS highlights our commitment to growing a healthier cycling market for all.

 

In November, our usability data was shared around the world and is influencing conversation about how to create Bike Share Schemes that give riders an optimised experience. We are sharing our data and analytics to show what is possible in Bike Share when you take a new approach.

 

This Time Next Year

Throughout 2018, we will develop our AI technology for the shared mobility market, innovate for Bike Share operators and continue to roll our solutions around the world. It is an exciting time for our industry and we are ready to help our partners benefit from our solution and encourage the continued growth of Bike Share.

 

As cities around the globe continue to push towards cleaner and more sustainable transportation, we will see increased demand for user-friendly Biker Share. How cities and operators manage their schemes and support riders will define their success.

 

The tipping point in Bike Share will be seen when automated rebalancing becomes a critical part of any Bike Share operator’s conversations about growth. AI will at least be considered when discussing a path forward for schemes looking to grow. That’s a big step forward in an industry that is constantly changing.

 

There are a few things that I believe will define the Bike Share in 2018:

 

  • Growing Bike Share Schemes

As more Bike Shares use AI-based management solutions, riders will get a better experience and schemes will grow. It will enable faster decision making for bike distribution, ensuring that riders get bikes and docks where and when they need them. That drives growth and creates new efficiencies.

 

  • Move Towards Electric

We will see a greater push in electric cars, bikes and scooters in an effort to reduce emissions and drive down costs. We will see more Bike Share offering e-bikes and even further introduction of e-scooter sharing in cities around the world. With greater range and a larger, more diverse user base, schemes will need better management solutions to drive efficiency.

 

  • Mobility as a Service

We will see mobile phones play a greater role in traditional transportation. Mobility as Service (MaaS) showed its potential in 2017 and now MaaS will begin being rolled out in cities around the globe. It will streamline how we travel and deliver even more data about how we commute.

 

  • The End of the Free-For-All in Free Floating

The free-for-all in Free Floating Bike Share has to come to an end. Healthy markets do not tolerate massive oversupply and as we’ve seen in some cities in China it leads to failing schemes. Free Floating Bike Share Schemes need to be managed and follow policies set out by local governments to be successful. In 2018, we hope to see less mistakes made and a lesson to be learned.

 

All of these things will drive demand for AI-based solutions and the evolution of Bike Share Scheme management. Bike Share operations should be simpler to manage with better experiences for riders. In 2018, we will solve some of the challenges in transportation and deliver solutions that benefit cities, citizens and the environment. I see tremendous potential in our business and our industry. 2018 will be a phenomenal year for AI in transportation.

 

Big Data Innovation in Bike Share Schemes

Big data is changing how we experience cities and enabling us to live healthier, happier and more productive lives. As cities become smarter, big data is being used to reimagine transportation and how we get from A to B.

Every city is producing vast amounts of data every hour and every day. Increasingly this data is being captured and put to work creating new solutions, processes and experiences that improve how a city functions and is enjoyed by citizens.

Data can be used to improve, urban planning, health care, sustainability, transportation and just about every aspect of a city. The “smart” in Smart Cities is about taking this data and rapidly turning it into actionable insights.

According to IBM, a Smart City “makes optimal use of all the interconnected information available today to better understand and control its operations and optimise the use of limited resources”. It makes cities better places to live and enables the best use of what a city’s budgets, space, people and technologies.

By 2021, open and shared data has the potential to add $2.83 billion (10.4 Billion AED) to Dubai’s economy every year, according to a report produced by KPMG. That is a lasting and long-term impact on the city of Dubai and results from using data in a Smart City environment.

While Smart City deployments continue to grow, transportation is an area where we are already seeing the direct impact of data on how citizens live day-to-day. In modern cities, Bike Share Schemes have emerged as a healthy and efficient means of commuting and navigating a city.

These schemes are taking the Smart City concept and applying it to local challenges and succeeding in growing ridership and providing more citizens with healthy and efficient transportation.

It’s this citywide data that is at the heart of the three pillars of smarter public bike sharing system as set out in the Policy Framework for Smart Public-Use Bike Share by the Platform for European Bicycle Sharing & Systems (PEBSS). Data influences how rider priorities are met and how cities offer suitable conditions with sustainable technologies and innovation. Smart Cities support Bike Share Schemes by considering the people, infrastructure and technology elements.

To make data work for Bike Share Scheme operators, it needs to be collected, managed and analysed effectively. This is where Artificial Intelligence (AI) plays a crucial role. AI-based platform manages all available data to deliver valuable insights to operators. The illustration below highlights this.

 

 

 

 

 

 

 

 

 

 

 

 

 

Solving Distribution Challenges in Bike Share Schemes

Effective distribution, in some of the best Bike Share Schemes, require immense amounts of citywide data to be captured, processed and used. Increasingly, schemes around the world are using city data to not only optimise its redistribution but to also show complete visibility to its users as to where the bikes are on its system map.

It’s how Bike Share Schemes use this data that drives value for operators, riders and cities. Bike Share Scheme operators are often familiar with rider statistics and patterns but the challenge is to use this data to accelerate growth within a scheme.

Tracking growth and stimulating growth are often two very different things. At the heart of new growth is rider experience. Bike Share Schemes are challenged to offer a consistent rider experience across a city while ensuring that using a Bike Share Scheme is easy, convenient and enjoyable for the rider. A positive and consistent Bike Share Scheme begins and ends with two questions:

 

  1. “Can I get a bike where I want one?”
  2. “Can I dock my bike at the end of my journey?”

 

If a Bike Share Scheme can guarantee these two things, it is likely that a rider will have a positive riding experience. When a rider can borrow a bike and dock it, they are more likely to use the scheme again and make it part of their routine.

That’s good for the Bike Share Scheme as it will help to grow overall ridership and new people will experience the city using shared bikes. A Bike Share Scheme with an active and growing ridership is able to invest and expand its schemes.

The data available in a city can be used to ensure that riders can access bikes and docks where and when they want them. Different days of the week, weather, events, seasons, local conditions and scenarios, and a whole range of criteria can shape how a Bike Share Scheme is used.

On a rare rainy day in Los Angeles, people may not cycle at all. In Amsterdam, there may only be a slight variance in usage patterns. At the same time, different events can be connected like a sunny day in a city, matched with a train drivers strike and major sporting event being held in one area of the city. All of these factors can influence how a scheme is functioning and where more or less bikes are needed.

Artificial Intelligence (AI) can be an excellent tool for simplifying Bike Share Scheme operations while using the power of data to drive decision making. AI can process a variety of data both historically and in real-time
to deliver actionable insights for Bike Share Scheme operators. Operators gain visibility into all of the criteria shaping a cityscape and benefit from useful insights to optimise bike distribution to match changing conditions.

AI accelerates how decisions are made by operators while taking the guess work out of bike distribution. The AI technology can predict peak times up to 12 hours in advance, enabling operators to manage supply and meet requirements in those areas. This ultimately leads to bikes and docks being available and riders getting a better Bike Share experience.

 

To find out more about the role data and AI has on a Bike Share Scheme, read our full whitepaper on ‘How to Grow a Smart City Bike Share Scheme’

 

7 Benefits of an AI-Optimised Bike Share Scheme for Smart Cities

Smart Cities that have active and growing Bike Share Schemes create urban environments that are healthier, with less congestion and better placed to manage growing populations.

In 2016, 1.7 billion people or 23% of the world’s population lived in a city with at least 1 million inhabitants, according to the United Nations. By 2030, that will grow to 27%. Urbanisation is continuing to grow and that puts strain on transportation networks.

Public Transport in its current state is already stretched and cities are often challenged to fund new projects. With optimised Bike Share Schemes, cities can encourage citizens to cycle and avoid crowded transport systems.

As more Smart City initiatives are deployed, cities become data-rich environments that can benefit Bike Share Schemes. The emergence of the Internet of Things (IoT) and a growing number of connected devices deployed across a city will only expand the potential of Artificial Intelligence (AI) in Bike Share Schemes and transportation overall.

Expanding data sets managed with AI can deliver results that directly benefit riders and influence how a city functions and grows.

All cities can benefit from an AI-driven Bike Share Scheme but as smart technologies are rolled out widely, the depth of data will grow. Operators benefit from new and increasingly precise insights while riders will see Bike Share Schemes optimised in new ways.

With AI, operators can ensure a well-run Bike Share Scheme that offers:

 

A Cleaner Transport Option:

For cities to help tackle climate change and deliver a better environment for citizens to live in

 

Healthier and Happier Riders:

Through daily exercise

 

Effective First & Last Mile Solution:

Since it can be significantly cheaper and faster than other public transport options for short distances

 

Reduced Strain on Infrastructure:

As less people are using public transport that requires continuous upkeep and maintenance

 

More Investment in Cities:

With less need for maintenance and new projects, Smart Cities can use funding on other much needed transport infrastructure such as cycling lanes and incentives

 

Manage Rising Transport Demand:

With increasing urban-dwellers, cities can offer more transport options with a Bike Share Scheme to accommodate this rise

 

City’s Brand Image:

Can be shaped by a cycling culture, supporting tourism and other thriving economic industries

 

Bike Share Schemes are like no other modes of transport. It offers a viable transportation option to many crowded cities that deliver a range of benefits to both cities and its citizens.

To find out more about the benefits of Bike Share Schemes to operators, cities and citizens, read our full white paper on ‘How to Grow a Smart City Bike Share Scheme’.

AI Technology and Big Data are Building Smarter Cities

As technology continues to advance, cities don’t want to be left behind. Cities around the world are turning to Artificial Intelligence (AI) to facilitate and support the drive towards ‘Smart Cities’.

Organisations are realising the potential of cities in collecting and using valuable data to benefit its citizens. Big Data and AI are helping to drive new innovations and disruptions, especially within the transport sector.

We give a round-up of key advancements in AI technology with city environments. These articles show a future where AI could be at the heart of how we get from A to B.

 

  • AI Traffic Lights

AI Traffic lights, set to be implemented in Milton Keynes, UK for 2018, will aim to offer a more reactive solution to managing rush hour. Traffic lights at present run in sequence. The AI fitted lights will cover a 50 square mile area around busy zones to monitor traffic and lower congestion, making it safer for cyclists, buses and other vehicles.

The AI traffic lights are the first step to improve traffic by integrating with existing road signs and management systems. In the future, the traffic lights will be able to communicate with driverless cars to ensure they work effectively.

 

  • NVIDIA’s AI Security Camera

According to NVIDIA, there are hundreds of millions of surveillance cameras around the globe, expected to reach approximately 1 billion by 2020. The amount of data that this creates is difficult to manage by human beings alone.

This is where AI technology can play a huge part. AI can be used to analyse vast amounts of data and accurately drive insights. Connected to the Cloud, AI-powered systems can track and monitor behaviour as well be a solution to a lot of city problems.

 

  • Connecting the Car Industry with AI

 AI has transformed the transportation industry with new business models and ways of operating. The car industry is not any different. AI has bought new features and increased connectivity options while promising a future of driverless cars.

The advancements in AI are making vehicles safer, smarter and cost efficient for people. From major automotive brands to start-ups, AI is proving its value in improving operations and bringing innovations.

 

  • Launching a ‘Pop-up’ Bus

Citymapper’s CMX1, dubbed the ‘pop-up bus’, aims to offer bus routes that change dynamically according to traffic and demand. It analyses vast amounts of data to find where demand is and offer a bus route to meet that demand.

Public transport has remained unchanged over the years. Citymapper’s pop-up bus is a good example of how optimising your resources can find new efficiencies and benefits to operators, even in old traditional models.

 

At Stage, we use Artificial Intelligence to remove complexity in Bike Share Schemes. Through using real-time data, we can predict demand and manage supply to increase ridership and grow Bike Share schemes.

To find out more about how Stage Intelligence’s AI solution can simplify logistics within your Bike Share Scheme, please contact tom.nutley@stageintelligence.co.uk

 

Bike Share

Bike Share Schemes – In the Battle of Traditional vs Free-Flowing

As increasing number of people look to get healthier, save money and time and preserve the environment, it’s no surprise that Bike Share Schemes are growing in popularity around the world.

With traditional schemes doing well in many cities, more and more start-ups are bringing out dockless Bike Share Schemes in the hope to take advantage of the rising on-demand culture. It gives riders convenience, choice and transparency over the more traditional docked schemes.

With a free-flowing Bike Share Scheme, riders can use their smartphones to find, pay for and unlock bikes and leave the bike anywhere once they are done. It’s this level of simplicity that is making such schemes very popular.

In fact, in China, the most mature market for Bike Share Schemes, start-ups have had massive success entering the market, raising significant amount of funding and supplying vast amounts of bikes.

At the same time, the news in this market dominates around dockless bikes being stolen, damaged and left in an unsuitable place by their millions. For operators, they are constantly replacing bikes while cities and its citizens are seeing more cluttered bikes on their streets.

This raises the question; which schemes should cities adopt? Free-flowing Bike Share Schemes are a topic of heavy debate for many cities due to the problems they can create if it remains unmanaged. The solution for many companies was to supply more bikes to the market, which only added to the problem.

But operators are now becoming savvier. They are offering parking spaces, rewards for good riders and improved apps to track their bikes. This is a step in the right direction to tackling the problem. With dockless bikes being a good way to get people cycling, it would be wrong to completely rule out the free-flowing schemes.

Instead, operators should focus on how they can effectively manage existing resources to benefit themselves, the cyclists and cities. By effectively managing logistics, operators can remove bikes from overcrowded and unsuitable areas to supply it to areas that need them.

Through collecting and organising huge amounts of data available in cities, operators gain real insight into their schemes as well as the market. They gain cost efficiencies as they are not unnecessarily purchasing bikes and riders can trust that bikes are available when and where they need them.

At Stage Intelligence, we use close to infinite amount of data and Artificial Intelligence technology to offer a simple management process for Bike Share Schemes. By predicting demand and managing supply, operators see real benefits to their schemes.

To find out more about how Stage Intelligence can drive growth within your Bike Share Scheme, please contact tom.nutley@stageintelligence.co.uk