ABSTRACT
Routing and navigation services are a set of ideas and technologies that transform lives by understanding the physical world, knowing and communicating relations to places in that world, and navigating through those places. From Google Maps to consumer global positioning system devices, society is benefiting immensely from transportation services. In this chapter, the authors present advances of spatial network big data (SNBD) techniques in transportation applications such as eco-routing. They discuss the challenges posed by SNBD in transportation applications. Generally, SNBD refers to spatial network data sets that exhibit one or more of the following characteristics: a large volume, variety, and/or velocity that exceed the capabilities of computing technologies. A computationally efficient algorithm for the all start-time Lagrangian shortest path problem is important in the face of SNBD. This is because SNBD magnifies the impact of partial information and the ambiguity of a traditional routing query specified by a start location and an end location.
