Identifying mode of transport for partial trips - when analyzing movement using mobile network data
| Reference number | |
| Coordinator | Commuter Computing AB |
| Funding from Vinnova | SEK 1 282 000 |
| Project duration | December 2023 - March 2025 |
| Status | Ongoing |
| Venture | Strategic Innovation Program Drive Sweden |
Purpose and goal
The objective of the project is to develop a scalable, automated and self-learning pattern recognition model that shows which means of transport people choose during an entire journey - door to door. The model vill be based on the Movement Analytics-method of analysing human movement using mobile network data This project intends to carry out two pilot projects to achieve an automated and general/scalable vehicle identification model - also for partial journeys. Purpose is, among other things, to be able to better monitor behavioral change when we transition to sustainable mobility.
Expected effects and result
** Denna text är maskinöversatt ** - Better understanding of travel by means of transport in traffic planning - The possibility to follow up behavioral changes when society changes to sustainable travel - Make visible the consequences measures to reduce car use in city centers have on people´s travel habits - per means of transport Results from this project will be used in follow-up off behavioral change in Stockholm´s and Lund´s decided system demonstrators for faster climate change
Planned approach and implementation
Model development, Testbädd Göteborg (January - June 2024) Model validation, Testbädd Helsingborg (Januari-Juni 2024) Automation and testing (January-Juni 2024) Internal communication and utilization in Gothenburg and Helsingborg (Mars-Juni 2024) Final reporting and presentation of results s ( August 2024)