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Artificial Intelligence for Modern Transport Operators

With an AI-based management platform, transport operators benefit from utilising a variety of data sources. For Bike Share Schemes, the platform can give insights as to where bikes are required and instantly inform distribution trucks about where bikes need to be picked up and dropped off. When information is being processed instantly and communicated to drivers, there is no lag between new demand emerging and that demand being served.

The value of AI is its ability to process vasts amount of data across a Smart City and make it useful for operators. Citizens get the resources they need and that supports the long-term sustainable growth of public transport.

As a form of modern transport, AI platforms simplify the management of Bike Share Schemes and deliver unique benefits to operators:

 

User Satisfaction

Increased user satisfaction by ensuring bikes and docking points are available when and where required

 

Cost Reductions

Improved operational efficiency and reduced requirement of operational resources

 

Remove Unnecessary Processes

Move away from traditional schedule or dispatch-based approaches and eliminate wasted journeys

 

New Visibility

Real-time truck locations, colour coded station status and station clustering as well as access to advanced analytics and actionable reports via a single dashboard

 

Increased Autonomy

Drivers receive direct communications often via a mobile app, allowing them to work independently of each other and the back office with less wasted time

 

Greater Control

Autonomous operation of a Bike Share Scheme that reflects real time conditions, offers consistent delivery instruction and a detailed overview of the scheme

 

Scenario Simulation

The simulation engine in such management platforms offers the ability to see responses to “what if” scenarios, allowing improved and more efficient resource planning

 

Scale Up

Increase the size of a Bike Share Scheme without the need to simultaneously increase available resource to maintain operation levels

 

The demand for public transport is growing with more citizens turning to Bike Share Schemes as a viable mode of transport. In a growing and competitive Bike Share market, AI could be the key to success for many operators. It has already proven its value to some of the largest schemes in the world and will continue to be at the heart of modern transportation in the future.

 

To find out more about the advantages of utilising AI in transportation read our full whitepaper on ‘How to Grow a Smart City Bike Share Scheme’.

Bike Share Schemes Are Starting to Realise the Potential of AI

As Bike Share Schemes around the world become more popular, how we manage the resources such as bikes and docking stations defines the success and growth of such programs.

For Bike Share Schemes to truly be a solution to last mile problems, riders need bikes and docking stations to be available when and where they need them. It is up to the operators to ensure this happens every time.

But many operators fail to provide this basic level of service as they lack the actionable data and operations to manage the schemes effectively.

For a long time, the solution to ridership problems in Bike Share Schemes has been to supply the market with more bikes. In reality this does little to increase efficiency and often adds to the problem.

Now, Bike Share Scheme operators are seeing the value of data and AI in predicting demand and managing supply. Mobike, one of the start-ups in China, is beginning to use AI to manage how its Bike Share Schemes are run.

Mobike’s ‘Magic Cube’, uses data and AI to forecast supply and demand for its bike-rentals. In a fierce competition for market share, Mobike is seeing the value of using AI to simplify scheduling and operations of its scheme.

Mobike has also released its whitepaper outlining what Bike Share Schemes can do with citywide data. The report goes a long way in highlighting the potential for operators in collecting and using data.

The importance of data and AI is clear. For operators, the key is in not only collecting the data but also having a process that works with its systems and resources to drive growth and increase ridership.

In the future, we are going to see more operators turn to data and AI, especially since cities have the potential to collect and store vast amounts of valuable data. With actionable data, operators save money, cities aren’t cluttered with bikes and citizens can rely on a reliable Bike Share Scheme that they can use in their day-to-day lives.

At Stage Intelligence, we have been using Artificial Intelligence (AI) and self-organising algorithms to solve complex problems in Bike Share Schemes from the beginning. Our BICO solution is easily incorporated into existing platforms to simplify logistics and increase ridership.

To find out more about how Stage Intelligence can drive growth 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