Buchanan Computing Launches Traffic Order Data Open API

Buchanan Computing announces the expansion of its ParkMap cloud service with the addition of a new web service for the sharing of traffic order data. This service uses an open API that is part of the company’s ParkMap 7 cloud system, which enables local authorities to capture and manage their parking and traffic controls, providing them with an accurate digital version of what’s on street.

ParkMap 7’s open API conforms to both APDS (Alliance for Parking Data Standards) and the draft TRO D (Traffic Regulation Order Discovery) standards. In addition, the API’s “native” or enhanced TRO D format accommodates all the additional data types and other traffic order controls that can be held within ParkMap and which are required for effective management of the kerbside environment.

Any local authority using the ParkMap Web service (Traffweb) will be able to make its data openly available to developers for incorporating this important dataset into its apps. “As traffic orders are always changing and given that so many local authorities are using ParkMap, this new service will provide a constant stream of live data for a large proportion of the British Isles,” says Alex Smith, Managing Director, Buchanan Computing.

As part of Department for Transport (DfT) funded projects, the first customers are about to start using the open API. Manchester City Council is using ParkMap with APDS data, and the TRO D model is being used and tested by Essex County Council. Continues Smith, “Local authorities using ParkMap will be ready to comply with whichever standard is required, and will be able to provide their traffic order data to the DfT in accordance with the TRO D standard when it is finalised.”

The parameters of the API service will give app developers access to this essential dataset in a number of different map projections so that it can be overlaid with either Ordnance Survey mapping, Apple Maps or Google Maps. When combined with other data services - such as for traffic flow, street works, dynamically available parking spaces, and air pollution - it will be a significant step to providing the inputs needed for the Connected and Automated Vehicles (CAVs) and smart cities of the future.

Smith continues, “The way that all these datasets are spatially referenced needs to be part of the data standards, as the relative position of parking bays and other traffic control will need to be very accurate to enable automated vehicles to drive and interact safely within the real world”. Smith says, “As we already have an excellent national mapping system, MasterMap, which is used by authorities to legally define their traffic orders, this should form the basis for spatial referencing data sets needed for CAVs.”