Meteo Value Live
July 09, 2019 to July 31, 2022
The aim of the Meteo Value Live project is to support trucking companies and long-distance bus companies in route and deployment planning so that the arrival of deliveries and passenger buses at their destination can be better planned. This includes storm forecasts and forecasts of parking space availability (as a further development of the project “Intelligent Truck Parking ITP” mFUND).
Within the project, four components are being developed to improve supply chains and bus connections:
1. Specific routing solutions for trucks and buses, taking into account weather and parking space parameters,
2. an intelligent system that analyzes the effects of weather conditions on the driving speed of trucks and long-distance buses,
3. a support system that helps dispatchers to identify the right strategy depending on the situation
4. a dashboard that provides an overview of the weather and parking situation and displays critical tours
In addition, the technologies developed and used in the project make a significant contribution to reducing the number of “misplaced” trucks and buses, reducing greenhouse gas emissions through trip optimization, and finally to increasing road safety by warning of weather-related impairments such as black ice.
MeteoValue preliminary project
The aim of the MeteoValue preliminary project was to minimize the risk of threats to road users and roads through reliable and high-resolution weather forecasts. Road users are protected by warnings immediately before the weather event occurs. The early detection of infrastructure under heavy strain is ensured by recording extreme weather data over an appropriate period of time. If, for example, a bridge is exposed to extreme temperature fluctuations more often than average, the system sounds an alarm and the structure can be checked.
Fraunhofer FOKUS' role in the MeteoValue project was to create use cases and system architectures for sending personalized alerts to road users and infrastructure operators. Cause-and-effect relationships between extreme weather events and disruptions to traffic flow are analyzed and evaluation rules are generated that enable information to be sent out effectively. Furthermore, interviews are conducted with representatives from the insurance industry and requirements are identified.