The City of Westminster is the largest parking authority in the UK, with 41,000 parking bays. And with half a million vehicles driving into the borough every day, it is also one of the busiest.
Until recently, however, Westminster City Council did not have a holistic view of which streets were under greatest demand for parking, and which were underused.
That was not for a lack of data. The council’s Parking Services division collects all manner of data, such as parking tickets and pay-by-phone transactions, that describe the use of parking services.
Westminster City Council’s smart street lighting infrastructure
However, that data was spread across a number of departments and outsourced suppliers, and was typically collected in spreadsheets. That meant that pulling the data together to analyse a single street was a laborious task.
“The biggest problem really was that a lot of data was sitting in disparate sources,” explains Lewis Johnson, information analyst at the Parking Services unit. “Collating all that information to work out how occupied a street was at a certain time of day was a manual task that took four days.”
In April, the council decided that it needed a better overview of parking trends, so that it could direct drivers to streets with low occupancy.
To do this, it migrated three years’ worth of parking data into an existing departmental data warehouse. To analyse and visualise that data, it used QlikView’s in-memory business intelligence solution.
That has greatly accelerated the speed with which the Parking Services unit can interrogate historical data to identify trends. “We can now return the data within about half an hour,” says Johnson.
Furthermore, it has allowed the unit to integrate the data with its geographical location systems, creating a heat map of parking bay occupancy.
The council has used this data to deploy parking marshals in busy streets, to tell drivers where they could find a better parking spot. This, says Johnson, is preferable to drivers who cannot find somewhere to park legitimately using an illegal spot.
“It’s more expensive for us to manage the process of issuing a ticket,” says Johnson. “Instead, we far prefer marshals to interact with delivery companies, visitors, and other motorists in the area to try and encourage them to change their parking behaviour by telling them where they’re more likely to find available space.”
Deploying marshals in busy spots has already improved the occupancy of parking spots in less busy streets, the council has found. “Other than a dip during the Olympics, in the first month we hit a 3% increase followed by a 5% increase the month after,” says Johnson. “We could see it happening and it formed part of our business justification for adopting the BI system.”
Parking in real time
Having got its historical data under control, the council is now working to give parking marshals real-time data to direct drivers based on up-to-the-minute trends.
The council is currently trialing a new system to help drivers find free parking spots. It has installed sensors in parking bays in popular streets (as revealed by the QlikView deployment) that record when a car enters and leaves the spot. Drivers can access that data through a smartphone app, which shows them which spots are free right when they need it.
Johnson is now analysing that data within QlikView. “It really gives us a much greater level of understanding as to how parking bays are used,” he says. “We have found that vehicles parking at 9am stay for just over an hour, whereas cars at 5pm tended to stop for just five or 10 minutes.”
Marshals are now using the app themselves to direct traffic in real time and in future, Johnson says, it will allow drivers to pre-book parking bays and the council to vary pricing based on demand.
In less than a year, then, Westminster City Council has gone from a position in which the disintegrated nature of its parking data prevented it from performing even simple analyses, to one in which it is preparing to use real-time data to offer innovative and responsive services to citizens.