E-safe pre-study
| Reference number | |
| Coordinator | Autoliv Development AB |
| Funding from Vinnova | SEK 500 000 |
| Project duration | March 2022 - December 2022 |
| Status | Completed |
| Venture | Traffic safety and automated vehicles -FFI |
| Call | Road safety and automated vehicles - FFI - December 2021 |
| End-of-project report | slutrapport 2021-05060engelska.pdf (pdf, 14585 kB) |
Purpose and goal
The project aimed at gaining new knowledge about how e-scooter riders normally ride to improve traffic safety related to e-scooter riding. The project’s fulfilled objective was to collect naturalistic e-scooter riding data and to address three research questions: 1) Can the data loggers provide sufficient data to support crash reconstruction?, 2) Can we identify unsafe riding behaviour based on accelerometer, gyroscope, and GNSS data only?, and 3) Can we use the collected data to model road user interactions?
Expected results and effects
This project has collected naturalistic e-scooter riding data. The analyses of the 2315 trips gave preliminary answers to the project´s three research questions. It was shown that the data could provide valuable information for crash reconstruction. Some unsafe behaviours could be automatically detected. Some aspect of the interaction between pedestrians and e-scooter riders was modelled. The identified limitations of the project, and the promising results open the door for extended research to improve traffic safety.
Planned approach and implementation
The work was done in three steps. First, data from shared e-scooters was gathered. Second, automatic data processing and augmentation together with data exploration tools were set up. Third, Processing algorithms were developed to 1) detect safety-critical events, 2) detect hand placement on handlebar, 3) road surface roughness estimation, and 4) detect, track, and estimation relative position of other road users. The research questions were addressed by combining and interpreted the processed data.