Sensor-based accident research and prevention: Exploring legal and technological opportunities
At a glance
- Project leader : Dr. Niclas Meyer
- Deputy of project leader : Dr. Sylvain Métille
- Project team : Dr. Eric Bouillet, Markus Hackenfort, Heinz Reber, Tanja Stoll
- Project budget : CHF 249'700
- Project status : completed
- Funding partner : Federal government (Bundesamt für Strassen ASTRA)
- Project partner : BSS Volkswirtschaftliche Beratung AG, HDC, DTC Dynamic Test Center AG, Swiss Data Science Center SDSC
- Contact person : Markus Hackenfort
Description
The data recorded by an increasing number of sensors installed in cars, e-bikes, mobile phones etc. has the potential to revolutionize the field of accident research and prevention. The opportunities are limitless. But so are the challenges:
- Accident researchers and prevention specialists often do not have access to the relevant data. For the most part, car and equipment manufacturers control access to the data.
- There are strong public interests that can be cited in favour of legally forcing companies to share their data. However, private companies, too, have legitimate interests that are protected by a range of legal norms.
- The privacy rights of the individual need to be balanced carefully against the broader public interest of preventing accidents. To prevent the misuse and the missed use of data, we urgently need to adapt and strengthen the legal and technological means to both access and share sensor data where there is a legit-imate and strong public interest.
The project will take stock of all sources of sensor data (today or in the future) with relevance to accident research and prevention. We will reach out to the research and prevention community and enquire their data needs. Finally, we will explore legal and technological means for enabling the sharing of the sensor data to the benefit of accident research and prevention. Legal opportunities may include the amendment of existing law. Technological solutions may include data clearing house models.