Smart junctions are the subject of many researches in the past few years. This research deals with the case of a smart intersection, handling traffic loads while taking into consideration different aspects of social prioritization. While learning the problem of traffic and its flow in an optimal way to save time and fuel for all travelers on the way, giving preference to urgent cases (dilemmas) and different types of vehicles (size and number of passengers), creates a more morally accurate picture of the traffic as a human interface. An example of such priority at the junction could be a woman in labor in a private vehicle, that is not formally prioritized since it is not an emergency vehicle. Traffic lights around the world are based on orderly programming of passage between the different traffic directions. The technology that measures the amount of traffic can change the duration of green light that is activated or even skip an instance of passage in case of sensor detection of an empty lane. Our research and system, presented in this paper, unlike all other systems, is not based on a specific order of traffic flow at the junction, but reopens each sample and analyzes the junction by its passenger data, prioritizing the social aspect of the vehicle's travelers. The system performs each sampling in a certain time period by the physical aspect of the vehicle and uses a prioritization system, which performs a parametric calculation of these social aspects. The system checks all the possibilities of allowing green light for larger traffic and considers the criteria for prioritizing a traffic load. The algorithm that was developed for this system can calculate each green time according to real-time data of the junction's vehicles and chooses the optimal traffic route, accordingly.