Google Adds Predictive Travel Time to Maps API

Google recently announced the addition of its predictive travel time feature to the Google Maps APITrack this API. Predictive travel time stands as one of the most powerful features of the consumer Google Maps offering, and Google decided to extend the functionality to developers and business partners. Predictive travel time digests historical time-of-day and day-of-week traffic data to estimate future travel times.
 
"Location-based and time-relevant data are changing the way we live, work and travel. As consumers, we can access incredibly detailed information about where we are and where we're going with a few taps on our mobile devices," Elena Kelareva, Google Maps APIs Product Manager, commented in a blog announcement. "Location and time-relevant data play an important role in helping to answer everyday questions like 'what's the best route to take when running errands?'....Google Maps APIs have played a key role in helping us make these decisions, both at home and at work."
 
Google envisions a number of use case scenarios for API integration with the feature. For instance, an app used to schedule deliveries can better determine how much time a driver needs between deliveries. Specific methods within the API benefit such an integration by offering more guidance than a straightforward predicted travel time. Because traffic conditions vary by day, API users can implement traffic model parameters. Instead of offering an exact travel time, the API determines optimistic, pessimistic, or best guess estimate of the traffic conditions. 
 
Standard Plan and Premium Plan customers gain access to predictive travel time through the Direction and Distance Matrix APITrack this API. Premium Plan customers also have access to the feature within the JavaScript Maps API. To learn more, visit the Directions and Distance Matrix API docs. For those interested without a current plan, sign up for a Standard Plan online, or reach out to the team for a Premium Plan.
Eric Carter Eric the founder of Dartsand and Corporate Counsel for a specialty technology distributor. He is a frequent contributor to technology media outlets and also serves as primary legal counsel for multiple startups in the Real Estate, Virtual Assistant, and Software Development Industries. Follow me on Google+

Comments

Comments(1)

sklearn

I've used the distance matrix API through a Python library with much success in our company. Previously, we relied on geodesic (as-the-crow-flies) distance.

I'm curious whether Google incorporates weather + known traffic incidents into travel predictions.