The Mobility Observation Box (MOB) makes it possible to measure the safety of traffic infrastructures according to objective criteria and thus make them comparable. After data acquisition, machine learning is used to automatically recognize and classify different groups of road users (pedestrians, cyclists, cars, trucks, e-scooters, etc.), evaluate their traffic behavior and create a basis for targeted improvement measures.
The Mobility Observation Box (MOB) from the AIT Austrian Institute of Technology makes it possible to measure road safety. Thanks to this innovative development, the safety of transport infrastructure systems can be screened; i.e., measured according to objective criteria and then compared. After the data is collected, various road user groups – such as pedestrians, cyclists, cars, trucks, and e-scooters – are automatically detected, classified, and their road use behavior assessed using machine learning. This is used to help produce targeted improvements to increase road safety.