The massive volumes of information brought upon by the digital age allow us to move forward in ways that we have never imagined — figuratively and literally. Not only does data power a wide variety of services we use in our day-to-day. Data is also powering developments in urban mobility and public transport.
How data steps in improving mobility
To make the city a better place for the citizens, it is imperative to know them and the surroundings they are interacting with. The best way to do this is by collecting data. Right now, this can easily be done by sensors, especially for cities with existing Internet of Things (IoT) systems.
This is equally true when it comes to mobility and public transport — they can be improved by collecting relevant information.
Data collection methods
But how is data collected from a transportation standpoint? There are sensors attached to public transport and micromobility vehicles (such as scooters) which is used to monitor the flow of people.
In the US, there are two primary means to collect data:
01. General Bikeshare Feed Specification (GBFS)
GBFS is a data standard for bikeshare systems. It provides semi-real time or real-time information to users about the availability of micromobility services in a city.
02. Mobility Data Specification (MDS) GBFS is a requirement within the provider feed of MDS. With this, MDS inherits the ability to inform about the availability of micromobility services. MDS goes beyond this, however.
It provides valuable data about the condition of the vehicles:
- It can check if they are deployed equally among neighbourhoods
- It monitors their parking status, that is, if they are parked safely or if they are in proper parking areas
- It can verify if vehicles are within service areas
- It can measure the length of the trips as well as the routes taken
With a large inflow of information given by GBFS and MDS, city planners and mobility provides are empowered when it comes to making decisions in public transport.
Using the information from these data specification systems, it will be easier to ensure that transport services are equally available across the various neighbourhoods of the city. At the same time, they can also use this information to advise users about the best routes they can take or warn them about emergency road closures and other events.
Taking advantage of data specifications like these, we are getting closer to making transportation a pleasant experience for everyone.
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