5G-IANA - Parking circulation & high-risk driving hotspot detection

Home » 5G-IANA - Parking circulation & high-risk driving hotspot detection

This use case aims to develop a feature that will be integrated into the 5G-IANA platform, which will detect aggressive and distracted driving (hazardous events), and transmit warning notifications on road risk levels to other vehicles. UC5 leader, OSeven, has a long experience in the development of telematics and driving behaviour assessment products, having developed an innovative smartphone application, which rates a driver’s driving behaviour, in terms of safety and eco, according to specific metrics (e.g., speeding, harsh breaks/accelerations, distraction/mobile use).

The two kinds of risky behaviour the UC5 novel feature aims to detect are:

  • Aggressive driving: harsh braking, harsh acceleration, speeding, and crashes
  • Distracted driving: mobile use.

UC5 will use two different sources of data: i) the driver’s mobile phone, which will provide data from the smartphone sensors (e.g., gyroscope, compass, accelerometer), and ii) an OBU installed on the vehicle, which will provide GPS and position data.

OSeven will develop an ML model to be trained on the edge for the assessment of road risk levels, which will be combined with real-time notifications. This ML model will assign a risk level along roads based on aggregated data over a specified model training period. In addition, UC5 will employ real-time hazardous events detection in order to inform drivers of the increase in risk levels on the road they are driving on. The developed feature will inform drivers in advance regarding risky and distracted driving in the road network while also improving driving driver information, increasing their awareness and “decreasing” their reaction time. It will provide this information on a many-to-many integrated approach, detecting hazardous events from many vehicles and notifying many vehicles in real-time. In addition, it will assist drivers in enhancing their visibility in low visibility cases, such as fog and low lighting conditions.


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