19 Jun KI_IDENT
Clear roads for emergency vehicles thanks to AI
What are neuralgic traffic junctions and why can they be life-threatening in situations, where every second counts? In the mFUND project KI_IDENT, we are supporting rescue services, such as emergency doctors or firefighters, to reach places of accident without any disruptions – despite treacherous crossroads known as ‘neuralgic points’.
The supply traffic of critical and social infrastructure – for example, emergency services, buses, clearance or waste disposal vehicles – places certain demands on a road network.
Firstly, they often are oversized and thus more difficult to maneuver in tight spaces. Secondly, the journeys are often particularly urgent, for example in the case of fixed timetables or emergencies.
Detecting repeated obstructions, such as those caused by illegal parking, physical blockades and infrastructural weaknesses, can help to identify neuralgic points in the road infrastructure supply network and inform the planning authorities and operators alike.
Together with the Smart Mobility Research Group of Universität Göttingen, SETLabs is working on a feasibility study for a novel software-based information system that identifies neuralgic traffic points and thus supports public planning authorities in the detection and elimination of recurring obstructions.
The automated detection of obstructions at neuralgic traffic points supports public planning authorities in ensuring clear roads for emergency vehicles.
Flow data, especially from public traffic, are used to train AI models for automated detection of obstructions. A mathematical aggregation of these space-time trajectories supports an application-oriented information presentation.
KI_IDENT: Machbarkeitsstudie zur KI-gestützten Identifikation von neuralgischen Punkten in Verkehrsnetzen basierend auf Verkehrsflussdaten von Versorgungsverkehren
Duration: 01/2023 – 06/2024