Your browser doesn't support javascript. This means that the content or functionality of our website will be limited or unavailable. If you need more information about Vinnova, please contact us.

e-SAFER - Computational models for a safe interaction between (automated) vehicles and e-scooters

Reference number
Coordinator Chalmers Tekniska Högskola AB - Chalmers Tekniska Högskola Inst f Mekanik & Maritima Vetenskap
Funding from Vinnova SEK 3 693 880
Project duration November 2022 - October 2024
Status Ongoing
Venture Safe automated driving – FFI

Purpose and goal

In this project, we will investigate e-scooters as the present use-case for micromobility to understand this new trend in transportation, its safety implications, and the necessary countermeasures to help motorized vehicles safely interact with e-scooterists and new micromobility vehicles yet-to-come. The main assets for the modelling will be data from test-track and naturalistic data that we will collect in the project. We will use the test-track data to create the models and the naturalistic data to verify the models.

Expected results and effects

The (computational) behavioural models from this project will explain to intelligent transport systems and connected automated vehicles how drivers should interact with e-scooterists in traffic and will inform Euro NCAP testing. The project will organize a final event where the application of the models developed in the project will be demonstrated on a test-track.

Planned approach and implementation

The e-SAFER project will be led by Chalmers and includes Autoliv, Veoneer, Voi, Folksam, and Trafikverket. Voi will be responsible for the collection of naturalistic data from e-scooters. Veoneer will collect data on test-track and demo the results of the project in the final event. Chalmers will create the models and coordinate the project. Autoliv will contribute to the modelling effort. Folksam, Trafikverket, and Autoliv will contribute to the analysis of the contextual circumstances from crash and insurance databases to inform the design of the test-track experiment.

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 15 November 2022

Reference number 2022-01641

Page statistics