Coord, which is part of Alphabet Inc’s Sidewalk Labs urban mobility initiative, has released a new toll billing product that will make it easier for car-share, car rental, and fleet operators to understand the cost of tolls incurred by their vehicles.
In order to bill and account for tolls incurred on a trip, companies typically have to wait 4-6 weeks to get billed by the relevant tolling authorities. To overcome this problem, some companies pre-charge their customers or drivers an estimated amount for tolls incurred on the route, which results in inconsistency between the actual cost of a toll and what is charged by the company. Others simply wait until the toll account arrives, and bill the customer well after their ride, resulting in a poor customer experience and additional support time spent explaining these new charges.
Coord’s new Tolls API (application programming interface) endpoint solves this problem by taking in a GPS trace (a series of timestamped latitude/longitude pairs) and returning all tolls along the route with their respective prices at the time they were incurred. Typically, fleet operators are already tracking the locations of their vehicles. All they have to do is to call the Tolls API with the GPS trajectory (latitude, longitude, and timestamp). The Tolls API covers over 80% of tollways in the USA, and the Coord has spent a lot of time aggregating and normalizing this data, which is commonly housed as PDFs or images on tolling authority websites or, in the case of dynamic tollways, as live feeds of various specifications. Structuring this data into a single format makes it easy for developers to query the data and understand the true cost of a trip across cities.
Unfortunately, GPS data has its shortcomings, as coordinates often are not exactly on the roadway, due to street canyon effect and other measurement errors, and it is also unavailable in tunnels. Another common issue is the frequency of GPS measurements. Fleet management systems typically collect vehicle locations only once a minute. And a gap of one minute or even 30 seconds is long enough to make raw GPS reading unreliable for applications like matching with locations of interest. The sparsity of the measurements makes matching GPS traces with the location of toll gantries unreliable.
However, Coord has solved the problem by allowing the raw GPS locations to be processed before being used for toll matching. Such pre-processing is known as map-matching or path-inference, which is snapping GPS coordinates to the underlying road network and finding the most likely path taken by the vehicle. The Tolls API first snaps the GPS coordinates to the road network, then compares the snapped geometry with the toll gantry locations to identify which tolls were crossed. As GPS measurements come with timestamps, the toll gantry cross time can also be estimated accurately by interpolating the time between the closest GPS locations to a toll gantry. The pre-processing step enriches the raw GPS data so that the Tolls API can reliably return the toll rates. The returned toll rates are detailed and categorized by vehicle information (number of axles, weight, height, etc) and payment methods (cash, transponder, credit card, etc).