Sample size is not a simple concept when it comes to Massive Mobile Data Analytics - see our prior blog post for some examples. In this post, we're analyzing our commercial vehicle data’s sample size in California based on a Daily Trip Sample Ratio. The results are that our archival data captures ~11.8% of commercial vehicle trips that took place in California in 2015.
A major strength of Massive Mobile Data Analytics is that it's, well, massive, and we can easily “scan” across large geographies to identify specific patterns of actual travel behavior. To leverage this, we scanned every kilometer in California for truck stops throughout 2015 -- and found some fascinating patterns about the movement of these big (and medium) rigs throughout the state.
Get the latest news about Big Data and mobility analytics for the transportation, retail, and real estate industries.
Here at StreetLight, we provide analytics for many projects aimed at analyzing commercial and freight vehicles. We support improved freight demand modeling, analyze internal/external routes, explore how trucks going freight hubs like ports move through cities, etc. See our blog for more use cases.
This blog is a recap of a presentation with the same title that StreetLight CEO Laura Schewel gave at TRB 2016. Thanks to TRB and Don Ludlow at CPCS Transcom for organizing the great panel, and to co-panelists Daniel Morgan from US DOT and Peeter Kivestu from Teradata for their excellent presentations.
TRB is a great place to learn and talk about all the big things happening in Transportation, and StreetLight Data is proud to be on a panel that dicusses the use of Big Data in Freight Transporation.