Use Case Networking Parking
Stress less and travel easy with car-captured data
This innovation aims to improve the mobility services in urban areas. Current navigation
applications such as Google Maps or Waze include some online functionalities powered by
crowdsourcing that enhance the traditional navigation devices based on offline maps. These applications usually consist on some basic traffic congestion information. However, they are limited to the possibilities offered by 4G and by the data sent by other service users. 5GMETA will go some steps further by making the most of 5G related technologies (edge computing, slicing, etc.) to process in real-time roadside sensor data (cameras, radar, etc), enhancing the
understating of the mobility situation at microscopic and macroscopic levels.
Ana has two tickets to attend a football match next Saturday afternoon with her friend Chloe. They do not live together, so the plan is that Ana takes a shared car and then picks up Chloe to go together to the stadium. Ana books a shared car in a new application (Lazarus) inserting the departure and arrival spots and arrival time to be at the stadium. Ana invites Chloe to add her location in the app to update the route plan, especially since Chloe will be working out of the office, so her pick-up location could change on the go. Thanks to the Lazarus mobile app, which crawls camera data from vehicles around the city to understand the different travel variables (e.g. incidents, estimated travel duration, road assistance, etc), both users can be notified: Ana
can detect an unusual congestion on the location where she has to pick up the car, as well
as be notified about real time events that could impact her route, while Chloe can be automatically informed about Ana’s delay.
The Lazarus systems also capture the available parking slots from the cameras and position
of cars already driving to the stadium parking, guiding Ana to quickly find a free parking lot.
5G enabled scenario
- This use case needs massive Machine Type Communications (5G mMTC), as the volume of data coming from vehicles in a congested and parking area is huge and has to be instantly uploaded to edge services, which get context awareness from cameras using computer vision computing algorithms. The processed results are then centralised to update the mobility model of the city in real-time.