In this work, a methodology has been developed that allows to receive in a device on board a vehicle, information from a set of traffic lights in real time beyond the capacity of vision of vehicle’s sensors. This includes the status of each traffic light that affects a vehicle, and the changes that occur in it, in real time. The mobile network has been exploited and a data model and algorithm for the distribution of high-speed notifications have been created. This data model integrate geographical, topological and absolute sequence traffic light information. The use of communications between vehicles and traffic infrastructure, and more recently, between clouds and vehicles, is a field that is growing and full of challenges. One of them is to be able to take the information from traffic lights to the vehicle in the shortest possible time. Until recently, radio communications based on the 802.11p [1] [2] protocol was the most effective means. These have the disadvantage of being short-range and have a high cost in their deployment. Taking advantage of the 4G and 5G microlantency networks that are coming opens the possibilities of using a cloud-based architecture, which complements short-range communications with large ones. The advantage is a cost reduction in the necessary hardware because the software can be installed in small computers or even mobile phones and the possibility to include more context information from sources integrated into the cloud and no more radio communication hardware is required.