Using Autonomous Vehicles To Manage Bike Share Schemes of the Future

While fully autonomous cars are still years away from being a mode of transportation that we can use day-to-day. We think it could have a positive impact on Bike Share Scheme management in the future.

 

With 68% of the world population projected to live in urban areas by 2050, we believe the future of mobility lies in simpler, cleaner and space saving modes of transportation like walking or cycling. Autonomous cars could play a big part in this.

 

In Bike Share Schemes, driverless cars could open up new opportunities in optimising management to deliver a better scheme to its riders. It can make the redistribution of bikes in the future much easier and more cost-efficient for the operator. Data, Artificial Intelligence (AI) and autonomous technology can all interlink to carry out traditional operational processes.

 

Currently, operators have to rely on manual processes for redistribution with trucks and vehicles being led by operational staff. That requires a significant amount of internal planning on where the drivers need to be, at what time and taking into account shift breaks and patterns.

 

Fortunately, Bike Share operators now have a lot of tools and technology at their fingertips that can help optimise and manage this. AI-based management platforms are helping operators with a lot of the heavy lifting and giving operators the most optimum way to manage operational staff.

 

In a future where driverless cars are commonplace, we can see Bike Share Scheme management moving towards the use of this technology. It has the potential to directly connect with management platforms to optimise how the redistribution trucks move, where they go and how often they go there. That can all be done with minimal human interaction.

 

For Bike Share Scheme operators this can remove the limits on rebalancing its bikes and offer a better and more reliable scheme to its riders. When Bike Share Schemes are better managed, operators can reduce costs and accelerate rider experience.

 

You are able to accurately serve the local market and ensure bikes are available when and where it’s needed. That supports the move towards shared integrated transportation and gets more people cycling.

 

Autonomous cars have a lot of potential for Bike Share Schemes and wider transportation in general, but it is still very far away from reality. At Stage, we’re always looking at the future and seeing how complex challenges of today could be solved by the technologies of tomorrow.

 

We’re excited to see what new technology will bring to the growing shared mobility market and how we can best incorporate it to deliver smarter processes to the wider industry.

 

Please get in touch if you’d like to know more about how we support Bike Share operators with a simplified management processes: tom.nutley(@)stageintelligence.co.uk

 

 

Delivering New Visibility to Bike Share Operations with Spin-off Environments

Management of Bike Share Schemes often come second to operators that are looking to expand to new markets globally. Today, operators can gain new visibility into their existing Bike Share operations by testing in a spin-off environment.

 

A spin-off environment simulates an operator’s current redistribution and management processes in a particular market to find new operational efficiencies. It looks at variables such as the number of trucks in use, capacity of these vehicles, staff shift patterns and other factors to assess if resources can be better utilised.

 

When Bike Share operators have visibility into how their schemes are run they can make quick decisions that can help reduce cost, win riders and grow in local and global markets.

 

Platforms that offer spin-off environments on-demand give Bike Share operators a huge advantage in the local market. With redistribution accounting for over 30% of the total operational costs, spin-off environments enable operators to reduce internal resources and optimise rebalancing to maximise their bottom lines.

 

In an increasingly multi-vendor state, where more than one Bike Share operator compete in the local market, the winners are the ones that are efficiently testing operations and managing resources. It gives them significant cost savings compared to its competitors, build strong ridership through better rebalancing and grow.

 

Operators can see the impact of managing resources with a spin-off environment. They are not unnecessarily spending huge amounts of money and time adding new resources. They gain real insights into management and can build a strong redistribution strategy.

 

Bike Share operators around the world now have the opportunity to test their management processes in spin-off environments. They have the ability to better optimise and manage their schemes day-to-day.

 

From the partners we’ve worked with they have seen real value in the testing in a spin-off environment. They were able to turn up their operations locally with very minimal increases in internal resources. That’s a big win for us. Our goal is to help operators reduce cost through better management of their existing resources.

 

We are able to work closely with operators and leverage our platform’s capabilities to spin-off environments on-demand. They see new opportunities in their operations that can help them compete more efficiently in the local market. They see results almost instantly, reducing the risk of managing a Bike Share Scheme.

 

If you are interested in finding out how our BICO platform is able to spin-off environment on-demand and deliver actionable insights into new markets, please contact us: tom.nutley(@)stageintelligence.co.uk.

4 Reasons Why Scheduled Bike Share Redistribution Doesn’t Work

The biggest challenge in Bike Share Schemes is to provide an optimised service each and every time. Operators that choose schedule-based distribution are often limited in their rebalancing efforts and are not efficiently serving the local rider demand. That impacts ridership and rider experience as a whole.

It’s up to the operators to ensure they have a simple and optimised management process that’s tailored to the cities and the riders. It enables them to offer better services, build stronger ridership and reduce operational costs. Yet many operators still choose to carry out schedule-based redistribution.

Schedule-based distribution means drivers have pre-set information or a schedule of how many bikes to pick-up and drop-off and at what locations. The schedule is created irrespective of the city it’s operating in or its specific needs. This can often mean that by the time the first job is completed the whole schedule could be wrong.

Poor rebalancing and management processes can also add to the growing situation of bikes being left as a nuisance to cities and its citizens. Singapore has seen first-hand the impact of poorly managed resources that have a huge effect on the day-to-day lives of its residents.

To combat indiscriminate bike parking, The Land Transport Authority (LTA) in Singapore passed a legislation earlier this year aimed at tackling this issue for over 100,000 bikes in the area. Since then it has introduced several new measures including reduced fleet size and Bike Share licences to ensure operators are better managing their schemes.

It is now more important than ever to have a smart management process that takes the guess work away from Bike Share redistribution.

Here’s four reasons why schedule-based redistribution doesn’t work for modern Bike Share Schemes:

 

  1. Dynamic Nature of the City

Cities globally are different from one another. They all have different population, city topography, transport hubs and many other factors that make each and every city unique. A schedule that works well in one city could completely fail in another.

  1. Each Day is Different

The day itself plays a huge role in Bike Share ridership. When you combine the changing weather, major city events, transport strikes and a number of other things, the demand for Bike Share Schemes are likely to fluctuate on a daily basis.

  1. Evolving Rider Behaviour

Some riders may take a bike out every morning and every evening to commute between work and home. That makes it predictable and easy to manage. In reality, for many riders their behaviour is constantly changing. Increase in tourists or a rise in public transportation services could affect the demand for bikes in different areas.

  1. Inefficient Use of Staff

What we see every day with schedule-based distribution is that drivers are going from one location to another with no real insights. They often go to a docking station that is expected to be empty and find that it is full. This is huge waste of time, money and resources.

For modern Bike Share Schemes, scheduled-based redistribution doesn’t work. There are too many variables that make schedule-based redistribution time-consuming and inefficient. Operators instead need simpler and smarter processes that can predict demand and manage resources with accuracy.

At Stage Intelligence, we use four weeks of prior ridership data to track rider behaviour and mange redistribution effectively. We predict replenishment values up to 12 hours in advance to enable operators to make quick decision and move quickly to win new riders.

Please get in touch if you’d like to find out how we use data and AI to transform Bike Share redistribution: tom.nutley(@)stageintelligence.co.uk

Delivering On-demand Team Management to Bike Share Operators

Bike Share operators around the world are looking for easier and better ways to manage its operations and operational staff. They need solutions that can make internal team management simple and reliable.

Today, Bike Share operators are struggling with outdated team creation and management processes that restrict how they carry out their day-to-day tasks. They are burdened with manual inputting, time implications and constant miscommunications internally.

When your operational staff are not working together efficiently, your whole scheme could be at risk. Your redistribution and internal operations are not optimised and that could have a negative impact for your riders.

It’s why team management has been a big priority for us. Operators are looking for easier ways for its distribution teams to work together, communicate and collaborate. In BICO version 15.1.0, we made it simple to create and manage multiple teams.

Operational staff can now set up teams in real-time without the need to do so in advance. They are free to start their day and update the app as they pick up new job requests. It saves valuable time and effort for staff and enables them to operate more efficiently when redistributing the bikes.

Bike Share operators really benefit from a dynamic management platform that can keep up with the changing industry. You’ll see better optimised internal processes that enable your teams to work together to better serve the market. That gives riders complete confidence in your scheme.

Riders can trust that your bikes and resources are available when and where they need them. They can rely on your scheme to get to their end location each and every time. That builds strong ridership and helps you grow locally and around the globe.

In BICO v15.1.0, we’ve worked closely with our partners to add new features including:

 

  • Simple Team Creation

Our BICO Android application lets users create teams with the app by selecting a User Name, Shift, Break Time, Vehicle, Depot and Team Name, which can be easily edited.

 

  • User Verification

The latest BICO update includes a simple user verification process that can be set up by entering the username and password. This is an optional feature and can be turned on or off.

 

  • Usability & Stability Improvements

BICO 15.1.0 also comes with a range of usability improvements, general bug fixes and stability improvements.

 

At Stage Intelligence, we’re continually updating our app to deliver a simpler, faster and better way to manage a Bike Share Scheme. We’re improving the usability, stability and performance of the app while adding new features to give partners around the globe a reliable Artificial Intelligence (AI) platform.

 

If you’d like to find out more about the latest BICO update and how that impacts Bike Share operators around the globe, please get in touch: tom.nutley(@)stageintelligence.co.uk

E-bike Sharing

Delivering New Growth for Bike Share Schemes with E-Bikes

Electric bikes (e-bikes) have huge potential for Bike Share Schemes but it brings a new level of management challenges for operators. Over its manual counterpart, e-bikes need to be fully charged for each rider, every time and that requires efficient distribution.

 

E-bike is a pedal bicycle with an electric motor. It assists the rider with additional electric power whilst offering many of the same characteristics as traditional bicycles. Many e-bikes are legally classified as bicycles and subject to the same local laws.

 

E-bikes can be a great way to travel. It can reduce door-to-door time of commutes with a lot less effort and makes transport more accessible to the new or less-experienced cyclists. For operators, it delivers new opportunities to compete in the industry and win new riders.

 

In the recent CES 2018 event, we saw many operators reveal their plans to incorporate e-bikes. Limebike, Spin, Ford GoBikes and Social Bikes all announced the introduction of e-bikes within their operations. It marks the shift in the industry that caters to the end users and their Bike Sharing experience.

 

E-bikes are a convenient way to get from A to B but it is faced with challenges in the market that limit its growth. The perception of e-bikes as ‘cheating’, the added weight of the battery pack to cycles and the cost of purchasing and repairing one all affect e-bike adoption with the public.

 

Manual pedal bikes are also much cheaper and easier to purchase, build and maintain for operators. It makes it simple for operators to grow fast and grow far. It’s one of the reasons why we are seeing thousands of pedal bikes being launched globally and at such a rapid pace.

 

For operators, the key is to deliver a service that people will want to use regularly and e-bikes offer a solution that removes the limit on how and when riders can use the schemes.

 

One major concern I see is in how operators manage their e-bike schemes. The demand for e-bikes is likely to be higher than the current pedal Bike Sharing schemes. It will put pressure on operators to deliver each and every time.

 

E-bikes will also need to be charged at the end of the trip and ready to be used by the next rider. That requires seamless management of resources and expert understanding of the local market.

 

Bike Share operators will need to have a strong management process in place to not only handle the challenges of e-bike sharing but to also take full advantage of the many opportunities it looks to bring for operators. Operators will be required to match local demand with efficient redistribution to succeed in the market.

 

At Stage Intelligence, we are using our expertise in Bike Share management to address the challenges of e-bike sharing. We are incorporating new e-bike technology within the artificial intelligence platform. Our processes enable us to add new features and functionality to cater to the dynamic Bike Share market.

 

To find out more about how Stage Intelligence can support and simplify your Bike Share Scheme operations, please contact tom.nutley(@)stageintelligence.co.uk

Bike Share Systems Get Artificial Intelligence

A company that specialises in developing Artificial Intelligence solutions for the transport and logistics industry has created real-time intelligence for the management of bike share systems.

Stage Intelligence from London has worked with the European Cyclists Federation (ECF) on a white paper describing how to grow a bike share scheme. The report notes that 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.

Read More: https://spycycle.uk/bike-share-systems-get-ai/

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

 

Increasing Rider Satisfaction with Artificial Intelligence

Big data and Artificial Intelligence (AI) provide a valuable opportunity for growth to Bike Share Schemes that have been deployed and developed across the six continents. Both schemes that are in the planning stages and ones that have already been deployed can benefit from leveraging big data and AI

Operators looking to drive growth to their schemes need AI to sort through vast amounts of data. If you combine millions of different criteria across a large urban area, the sheer number of possibilities can be overwhelming.

Every element matters and can influence where bikes are dropped and congestion occurs. In the worst-case scenarios, a rider borrows a bike but can’t find a dock and must travel away from their destination to drop it off and when they return there are no bikes remaining.

Data and AI is key to avoiding this situation. It ensures rider satisfaction by predicting demand in popular areas and managing supply. Only with data and AI technology can Bike Share Schemes look to improve existing processes, operations and logistics, and drive growth to their operations.

Going forward, data needs to be more accessible to operators. Open data allows Bike Share Scheme operators to deliver a transport solution that works for all. Data ensures bikes are available when and where it’s needed to support the growth of Bike Share Scheme deployments around the world.

Regulations such as the General Data Protection Regulation (GDPR) will still be paramount in the push for the openness of data. Cities, operators and all others involved have a duty to follow secure practices and take necessary steps in protecting user information.

Data and AI are ready to help operators to adapt and grow their schemes while refining and simplifying how they manage distribution.

For operators, getting started is simple:

  1. Evaluate long and short-term goals and growth objectives
  2. Explore what AI-based management platforms are available
  3. Look at what open data, shared data and Smart City initiative have been launched or are being developed locally
  4. Collaborate with AI experts and begin the journey towards smarter and more efficient Bike Share Schemes

To find out more about how operators can grow their Bike Share Schemes, read our full whitepaper on ‘How to Grow a Smart City Bike Share Scheme’.

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.

 

 

 

 

 

 

 

 

 

 

 

 

 

Stage Intelligence’s Usability Data Reveals the Need for Better Bike Share Scheme Management

Insights from schemes in London, Paris, New York and Chicago show that data can be used to deliver optimised rider experiences and grow Bike Share Schemes

LONDON, 8 November 2017 – Stage Intelligence, the leading provider of Bike Share Scheme management solutions, has released its 2016 Q4 data on bicycle and docking station usability and availability across Bike Share Schemes in London, Paris, New York and Chicago. Usability is central to providing an exceptional rider experience and supporting the growth of Bike Share Schemes. It ensures bikes and docking stations are available when and where they are needed most.

The data reveals Chicago and London leading the group with an average usability figure for the quarter of 99.3% and 99.4% respectively. Chicago has been consistent in delivering a reliable Bike Share Scheme to its riders. London is also rated highly but this could indicate over servicing its market, which can create unnecessary costs and limit growth.

New York City ranks the lowest of the major cities with an average usability figure of 90.2% for the quarter. It means that on average 10% of riders at any given time cannot access the bikes or docking stations they want. Paris follows New York City with an average usability of 98.1% with usability dipping to lows of 76.7%. The inconsistency in the scheme means that it may be difficult for riders to depend on the scheme on a daily basis.

“Bike Share riders and cities benefit from Schemes that are easy and reliable to use,” said Tom Nutley, Head of Operations at Stage Intelligence. “Operators need to make sure that riders have access to bikes when and where they need them without over servicing the market. This is where the London scheme could be at most risk. The data is very positive for London but it could be using too much city resources to manage its operations especially when there is no need to.”

Stage’s usability measure compares all docking stations that are within easy walking/cycling distance in a published 500m radius from each other, which can be altered by the BICO platform. The platform takes into account each city’s SLAs when measuring the usability of a Bike Share Scheme. A docking station is usable if there are bikes and docking points available at the station itself or at one or more of its neighbours. The BICO platform can also set custom usability defined by a specific threshold or the SLAs of different cities.

“For Bike Share schemes to be seen as a real, public transport solution and a smart answer to urban mobility, they need to work as good or better than existing public transport services,” said Paul Stratta, Director, at Platform for European Bicycle Sharing & Systems (PEBSS), an initiative from the ECF. “Nowadays people go to bus and railway stations expecting the services to be there, and for it to operate on time. It should be the same with Bike Share schemes. Collecting and analysing data allows Bike Share operators, and their city clients, to get a big picture of operations and understand where bike share can improve and how exactly to do it.”

The neighbourhood approach goes beyond the usual cluster and geographic data collection method which may be a sub-optimal approach – especially in larger schemes. It can identify if Bike Share Schemes are managed well and if it is over or under servicing the cities and its riders. The BICO platform is dynamic to each city and considers each city’s user patterns and prioritisation as well as the SLAs they operate under to measure the usability of Bike Share Schemes and provide valuable data for operators.

“Our BICO platform allows us to take a deep dive into individual Bike Share Schemes in different cities and neighbourhoods around the world and find ways to improve usability within them,” said Toni Kendall-Troughton, CEO at Stage Intelligence. “We were particularly impressed with Chicago’s Bike Share scheme which was performing well without over servicing its neighbourhoods or the market. It was consistent throughout the quarter with high usability figures and over-performed on busy summer weekends to meet the rise in demand.”

 

About Stage Intelligence

Stage Intelligence specialises in developing Artificial Intelligence solutions for the transport and logistics industry. Its flagship solution, the BICO recommendation engine, delivers real-time intelligence for the management of bikeshare schemes. BICO enables precise and optimal decision making and has been purpose-built to remove the complexity from managing resources within a bikeshare scheme. Customers choose Stage Intelligence because our solutions increase their agility, adaptability and enable them to move beyond traditional manual processes. We collaborate with customers to solve complex problems and deliver solutions that have a lasting impact on their operations.

www.stageintelligence.co.uk