Although, there are many platforms and companies offering bike-ped travel data acquired through smartphone apps, location-based services, fitness apps, etc., the choice can be very confusing and at times expensive. A recent paper from Texas A&M Transportation Institute discusses the top sources for this travel data. This could help us understand how to solve the complexities of incorporating active transportation modes into traditional planning practices.
The new 2017 National Household Travel Survey gives us our first look at changing travel habits since the recession. From what we can tell, the average American drives less in 2017 than eight years earlier. Driving also seems to have increased considerably among Millennials—but mostly among those with the lowest incomes—bucking expectations. The results may indicate that those with higher incomes are now choosing to live where they need to drive less.
New applications in big data could soon let us understand precisely how people move around by bike and on foot, for all types of trips, almost anywhere in the country. SSTI has worked with several providers to better understand the available trip data and its useful applications. We recently tested preliminary pedestrian data, provided by StreetLight Data, with promising results.
The bike sharing system in Washington, DC has gathered and analyzed travel data about members’ usage of both the system bicycles and other travel modes. Evidence on mode choice comes from user surveys. It is intuitive to suspect that the emergence of a new mode would both substitute for other modes and induce new travel. And that is what the Capital Bikeshare survey finds.