Since the inception of Traveler, we’ve sought to give you an open door to explore the world of your riders. We’ve had an abundance of great ideas, and not nearly enough time to tackle them all!
To this point you have viewed travel data in an accumulative historical style that did not help you understand time-sensitive scenarios. You wanted the answers to some very good questions, like “How do our riders travel differently on weekends?” and “How do our riders use this route differently during off-peak hours?”
Today, we are proud to announce you can answer those questions and more, with Time Filtering. Now you can define a filtering criteria based on an aggregate of hours, days and months to explore rider travel habits more precisely. Time Filtering allows you to explore a narrower slice of time and gain deeper insight into your ridership, equipping you with the knowledge to make more precise decisions.
One way we recommend using Time Filtering is within the recently released Travels context. Travels shows you how people move around your city – regardless of their mode of transportation – and by adding Time Filtering, you can understand how transportation demand changes across time.
Time Filtering will be a major part of Traveler, and like the rest of the application, continue to receive further enhancements and optimizations.