Bike Share Systems Get Artificial Intelligence

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Clever bike share management from Stage Intelligence
Clever bike share management from Stage 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.

Data can be used to improve urban planning, healthcare, 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 a city’s budgets, space, people and technologies.

Stage Intelligence confirms that in some of the best Bike Share Schemes, immense amounts of citywide data are being captured, processed and used to ensure an optimal rider experience. 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 this citywide data that is at the heart of the three pillars of smarter public bike share 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 Systems by considering the people, infrastructure and technology elements.

Tracking growth and stimulating growth are often two very different things. At the heart of new growth is rider experience. Bike Share Systems 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. Positive and consistent Bike Share Systems begin and end 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 System 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.

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 such as 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 fewer bikes are needed.

This is where Artificial Intelligence (AI) can be an excellent tool for simplifying Bike Share System operations while using the power of data to drive decision making. AI is able to 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 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.

AI for Bike Share Systems

Stage Intelligence has launched its Artificial Intelligence (AI) program to support small-to-medium Bike Share Scheme operators with up to 2,000 bikes.

Tom Nutley, Business Development Director at Stage Intelligence explains the commercial advantage “Up until now, AI has been limited to the largest players in the market and required significant investment to develop and implement. Our accessible AI programme allows small and medium-sized players to adopt new technology and use it to grow. Bike Share Scheme operators globally can deploy AI and simplify how they manage their schemes. We are enabling more riders to enjoy an optimised Bike Share experience.”

Toni Kendall-Troughton, CEO at Stage Intelligence added “The shared mobility market is only the beginning for Stage and there are applications of our software in all aspects of transportation from public transit to optimising delivery. We have spent years enhancing our AI technology to support operators and ensure resources are there when and where people need them. Ultimately, this is what will help us to move beyond shared mobility and address the challenges of the wider industry.”

Stage’s BICO solution has been proactively managing one of biggest challenges in Bike Share, the availability of bikes and docking stations. Through AI, self-organising algorithms, historic and real-time data, the software has simplified management and optimised operations for Bike Share Scheme operators worldwide. Stage’s state-of-the-art AI technology will be at the forefront of how people move from A to B in the future.

This international experience has led to Stage’s BICO Bike Share management platform being selected by BKT bicipública, a leading Central American Bike Share operator. BKT operates the MIBICI system in Guadalajara and will use the Artificial Intelligence-based platform to offer citizens an optimised rider experience and grow their scheme.

Stage’s deployment with BKT is the first time AI will be used in a Bike Share Scheme in Mexico. BICO will enable BKT to rapidly and efficiently distribute cycles across the city and ensure that riders have bikes and docks available when and where they need them.

“BKT and Stage have a shared vision for simple, efficient and user-centric transportation. Together, we are bringing innovation to Guadalajara’s Bike Share Scheme and using AI to give riders the best possible Bike Share experience,” Tom Nutley confirms. “AI makes it simple to grow a Bike Share Scheme and provide services that create life-long riders. This is a great opportunity for Guadalajara to innovate in clean and sustainable transportation.”

The Guadalajara Bike Share Scheme is the second largest and the most important Bike Share Scheme in Mexico serving an estimated population of over five million people.

The rebalancing is one of our biggest challenges in the operation of the public bicycle system in Guadalajara. BICO has allowed us to take better advantage of our resources to improve our service. We focus our efforts on achieving user satisfaction. BICO is an essential part to provide a better service and now satisfaction is also for our staff,” said Noé Santana, Operation Manager at BKT bicipública.

BKT’s director Mario Delgado was equally enthusiastic, saying “BICO has been very useful for the improvement of our services, the performance of our staff and the understanding of the system. We are very happy to have integrated it into our tools for the operation.”

 

 

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