Tags
AI, Artificial intelligence, BICO, Big Data, Bike Share, Bike Share Scheme, Bike Share SLA, Cycling, GBFS, Logistics, Machine Learning, NABSA, Open Data, Tech, Transport
Solving City Transport with Artificial Intelligence
While there is currently no one international body that runs bike share schemes, members of the North American Bikeshare Association (NABSA) have developed an open standard for schemes across North America, and made its data available for public use.
The open data standard, GBFS (General Bikeshare Feed Specification), means that anyone can access the data, and makes life much easier for app and software developers such as ourselves to create new innovative ideas for bike share schemes globally. A unified data feed now enables us to access data without coding too much.
We have integrated the GBFS with our BICO system to capture new intelligence and make the BICO recommender smarter, ultimately improving customer experience. As the data drives the decision making process in real-time, it is important to know the status of the network at any given moment and be able to make informed decisions. The unified data source enables bike share schemes to be more proactive and innovative in certain cities by reviewing real-time data.
Now that there is a standardised way of seeing the data across North America, we can easily discover what makes certain bike share schemes work, why people struggle in others, if there are size or distribution issues, and how they can be overcome. It enables us to look at real-time traffic data and provide recommendations easily for schemes looking to set up or grow and become more efficient.
It allows systems like the BICO recommender to identify where the bikes in each scheme go, where they come from, and any seasonal trends that develop such as in summertime near parks and major landmarks, and decline in winter.
It will also impact users as we are also looking to improve customer experience and change the perception of transport. We can start to reduce the traffic on the roads and think about our future as a community. We can also promote the health benefits of bike share schemes by reducing pollution, as well as improving the fitness of those using the bike share schemes.
Despite its niche market placement, bike share schemes generate and share large amounts of data for free, spurring innovative solutions such as TransitApp as developers have access to the data they need to build these apps.
However, other modes of transport don’t currently share this open approach and therefore chances of development for more efficient systems are stunted. Where data isn’t openly available, developers can’t advance technologies and create solutions for users getting around cities. With open integration in other modes of transport, we can look to create faster, integrated transport solutions and evolve our smart cities.
