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| Funder | Vinnova |
|---|---|
| Recipient Organization | Chalmers University of Technology |
| Country | Sweden |
| Start Date | Jul 01, 2023 |
| End Date | Jun 30, 2025 |
| Duration | 730 days |
| Number of Grantees | 1 |
| Roles | Principal Investigator |
| Data Source | Swedish Research Council |
| Grant ID | 2023-01041_Vinnova |
Purpose and goal:
Projektet VIASAFETY, will study how traffic safety can be improved, in connection with the use of small vehicles, at low speed, in Gothenburg, for example electric mopeds and electric scooters. The vehicles will generate data that can be used in the project, by processing, analyzing and sharing with the project parties. The project will develop AI-based analysis methods and tools to find risk zones in the traffic environment with small vehicles, at low speed.
After the project, some of this generated data will be made available, on SAFER, for future research. Expected results and effects:
The project aims to create new knowledge about the working conditions and traffic safety situation of independent couriers, through the possibility of following their movements via a central vehicle fleet. The vehicles´ driving patterns will be processed, in order to create new knowledge about where the risks for them arise and hopefully what can be done to reduce them.
This access to large amounts of data from electric vehicles. and then analyzed with different AI methods, opens up new opportunities to identify metrics for road safety. Approach and implementation:
The project collects data from drivers of small, electric vehicles, at low speed, who drive their daily routes in Gothenburg.
- SAFER is responsible for leading the project and monitoring the project from a research perspective, as well as making data available for future research. - Ciklo provides electric mopeds used to collect data. - Vialumia provides the telematics sensors on Ciklo´s vehicles, and is responsible for data collection and storage.
- Vianova is responsible for the processing of data collected from the vehicles and develops algorithms for processing driving behavior.
Chalmers University of Technology
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