Hundreds of roads, bridges, mountain crossings and junctions in Norway are continuously monitored through advanced sensor technology and digital twins. Itera assists Trafsys in developing and testing solutions that contribute to increased traffic safety through monitoring and handling of incidents such as queue formation or accidents, so that the effects of an incident can be minimized or avoided completely.
Trafsys is a leading Nordic competence company that develops intelligent transport systems. Trafvision is their main product - a powerful and modular system for traffic control and monitoring. Trafvision provides the user with a clear and accurate picture of the traffic situation through status messages and alarms from a number of different data collection and detection systems along the road, including video, radar, telephone, weather data systems and fire alarms.
Trafvision has been continuously developed since 1999. With the very strong emergence of advanced sensor technology, there has been explosive growth in the number of sensors deployed. Trafvision’s existing database-centric architecture was eventually going to become a bottleneck in terms of processing in real time the enormous and rapidly growing volumes of data being created. Hence, Itera contributed to the work of modernising the architecture by switching to using microservices and Kafka message bus.
The new architecture is well suited to processing the data stream of millions of messages in real time, and it thus enables events that would adversely affect traffic safety to be handled quickly and without delay. In the event of an incident, traffic is quickly redirected by the system automatically initiating the measures required on the basis of data from on-site sensors, such as signal management, road barrier, variable signs, radio messages and emergency lighting. Examples of events that automatically generate alarms are traffic accidents, fires/the use of fire extinguishers, lost loads, excessive CO2 levels, pedestrians in the road, queues and stopped vehicles.