Transport Analytics Lab is a platform for data driven research in the area of transportation. The Transport Analytics Lab consists of a number of research projects. All projects make use of large quantities of sensor data, which is processed and analyzed using computational algorithms.
The Mobile Millennium Stockholm (POST, previously MMS) project is an initiative to establish a platform for research and development within real-time traffic information and traffic management in Sweden.
The need for accurate real-time traffic information is growing in almost all big cities around the world. One of these cities is Stockholm, recently named as the fifth most congested city in Western Europe. The purpose of the project is to assimilate the knowledge gained from the Mobile Millennium project at University of California, Berkeley and develop new methods for data fusion, one of the most challenging research areas in the transport community today. The data fusion methods will utilize the potential of each data source in order to improve estimations and predictions of the traffic state. Read more on the POST page.
More information about the MMS project can be found on the Mobile Millennium Stockholm page.
The project is founded by Trafikverket. Project partners are KTH, Trafik Stockholm and Sweco.
The Future Mobility project is a project carried out in cooperation with local actors in Norrköping, Sweden. The project consists of two parts. The first covers fusion of participatory sensing data with cellular network signaling data. The second part covers traffic management based on the sensing data, in the areas of private and commercial traffic. Read more on the FT page.
The project is founded by the Norrköing municipality. Project partners are Geotelix, Ericsson, SICS and Trafikverket.
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. Read more on the MOFT page.
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).
RERUM will develop, evaluate, and trial an architectural framework for dependable, reliable, and secure networks of heterogeneous smart objects supporting innovative Smart City applications. The framework will be based on the concept of security and privacy by design, addressing the most critical factors for the success of Smart City applications.
The part of the project relevant for the Transport Analytics Lab is work made in the area of participatory sensing. A demo of platform for traffic estimation will be made for the cities Heraklion, Greece and Tarragona, Spain.
The project is founded by EU. Project partners are Forth, University of Bristol, University of Passau, City of Tarragona, City of Heraklion, Siemens, Atos, Zolertia, Cyta, and Eurescom.
More info at the web page for RERUM.
The project MODE aims at estimation of travel demand in cities and metropolitan areas, via utilization of signaling data in cellular communications networks. The key applications of using cellular network data range from dynamically managing road traffic to long-term infrastructure planning.
The specific objectives are to enhance the capability of short-term prediction of road traffic and accumulate knowledge on using mobility estimation as an enabler in addressing future challenges in sustainable development of the transport sector.
Press release from the project.
The project was funded by Vinnova. Project partners are Ericsson, SICS, Trafikverket, City of Stockholm, and Sweco. More info at the web page for MODE.