The availability of advanced mobile devices at a very low cost generates massive amounts of signaling data in cellular networks that can be turned into spatio-temporal observations of human mobility. These observations will fundamentally change how we understand human travel behavior and how to operate and optimize our transport systems. Better estimation of travel demand, mode choice and route choice is central for a key functionality of future smart cities with dynamic and integrated multimodal control of the transport system.
The project is a continuation of the project "Travel demand estimation based on cellular network data" (MODE), that ended in December 2016. Within the project, key functionalities for efficient management of cellular network data have been developed and evaluated based on operator data. The project has developed one of few platforms in the world for analysis of large amounts of cellular network data for transport applications. For the continuation project, a mobile operator together with more end users are joining the consortium, which now constitutes an internationally unique competence in the intersection of cellular networks, traffic modelling and big data analytics. The aim is to achieve both fundamentally new understanding of mobility patterns as well as a product that offers access to estimated travel demand.
The project will focus on a number of unexplored applications of dynamically estimated mobility patterns. The applicatrions are highly prioritized by the end users of the project: 1) Public transport planning, 2) Traffic management, 3) ex-post evaluation of infrastructure investments, 4) estimation of long distance travels, and 5) ride sharing potential of Mobility as a Service (MaaS).
The project is funded by Vinnova for 2017-2020. Project partners are Ericsson, SICS, Trafikverket, City of Stockholm, Sweco, Tele2, SJ, Nobina, Samtrafiken.