Current projects
Mobile network data is emerging as one of the most powerful- yet most complex - data sources for understanding how people and goods move through our cities. This project, led by LiU in collaboration with Telia, develops the methods and tools needed to turn highly granular, sensitive and noisy mobile network signals into reliable mobility insights that can support future transport planning, monitoring and traffic management.
T-Twin: Digital Twin Sandbox for Network-Level Traffic Control
T-Twin develops a next-generation Digital Twin platform to modernise Sweden’s traffic management. Building on the GEMINI pilot in Kista, the project integrates real-time data, simulation and AI to move beyond today’s local and reactive control systems. By testing coordinated motorway and urban strategies - such as dynamic speed limits and adaptive signal control - on the Södra länken corridor, T-Twin aims to create a scalable DT Sandbox that supports safer, more efficient, and more proactive traffic operations.
eSMART Dynamic Electrified Traffic Systems
Electrification of road transport is accelerating, but today’s static charging infrastructure requires large, expensive batteries and puts high peak loads on the grid. eSMART investigates how mobile autonomous charging stations (MACS) – self-driving battery vehicles that charge buses and trucks where and when needed – can complement static chargers and electric roads. Using traffic simulation and optimisation, the project evaluates how MACS can reduce battery size, costs and grid impact for electric buses and heavy trucks in Greater Stockholm and beyond.
Demand Management for Reducing Urban Traffic Congestion
This project explores how tourists and visitors to major events shape congestion in Stockholm – and how smart demand management can keep the city moving. Using rich data from public transport, road traffic and micromobility, the research identifies when and where these traveller groups strain capacity, and tests strategies to better distribute demand across modes, places and time.
IMTRACS - Improving traffic signal control utilizing connected vehicle data and surface detection
The aim of the project is to investigate if, and how, the control of Swedish traffic signals can be improved by using such new types of data to improve traffic efficiency, safety and environment.
T2 – TerminalTrängsel (Terminal Congestion)
T2 aims at developing a method that from freely accessible data constructs network models suitable for microscopic simulation of bus traffic within terminals and quantify congestion effects. In a succeeding project this method can be further developed towards automatic construction, calibration and validation of simulation models. The purpose is to enable cost-effective creation of simple simulation models of terminals and evaluation of capacity improving measures or effects of traffic demand changes.
Future forecast models for regional travel – Combining different data sources in the best way (FRID)
This project investigates how alternative data sources such as mobile phone network data, public transport automatic fare collection data, and GPS trajectories of car traffic, can complement survey data with low response rates, to estimate mode and destination choice models for regional passenger travel using data fusion.
Bicycle traffic simulation 1 & 2
The purpose of the project is to investigate how bicycle traffic simulation can be improved to capture cyclists' behavior more accurately and enable microscopic traffic simulation analyses of bicycle traffic.
Large-scale transport model for cycling
In this project, the overall goal is to develop a regional transport model for better predicting bicycle demand as well as facilitating cost-benefit analysis for bicycle infrastructure investments.
Multimodal Traffic Management (MMTL) 1 & 2
The project aims to develop new methods for estimating travel demand as well as mode and route choice for multimodal traffic management. Potential effects of multimodal traffic management will also be analyzed in the project.
Modelling of micro-mobility (M3) 1 & 2
The purpose of this project is to create a better understanding of how people use the shared e-scooter services and what their travel patterns look like, in order to identify the type of travel that constitutes the market niche in total mobility.
Public transport prioritization by dynamic bus lanes
This project will investigate for which traffic situations, in a Swedish context, that dynamic bus lanes are a suitable measure and how such bus lanes influence energy usage and traffic performance for both public transport vehicles and other traffic.
The aim of the project is to enhance and further develop todays state-of-the-art traffic models in order to enable analysis of future traffic systems.