Data freshness is an indicator of the timing of a status update which is of utmost significance for many real-time applications,such as connected vehicles,autonomous vehicles,and sensor networks.The age of information（AoI）metric is useful for quantifying the data freshness for messages delivered to the entities concerned.In this thesis,we averaged the peak AoI（PAoI）over time for each vulnerable road user（VRU）in the network with a proposed algorithm namely,priority based push-out last-generated first-served（PPLGFS）strategy,for safety-critical usage cases to address the issue of maintaining timely VRU status updates across all nearby connected vehicles.A multi-VRU system that supports the cellular network is assumed in which status updates arrive and should be transmitted over the network to the intended vehicle.We model the worst-case information freshness（i.e.,PAoI）for VRUdestination vehicle links,using a queuing model with the proposed algorithm to manage the packets on arrival.It gives priority messages which have arrived recently,and blocks stale packets to avoid wasting network resources for the transmission of old information.Then,we analyze the effect of increasing the number of VRUs of information freshness in the network and use stochastic process to compare our strategy with each strategy in the space.Results show that the proposed algorithm used with PAoI gradually achieves a better performance than other queuing models as the packets arrival rate increases.Besides it also achieves a better average AoI and enhances the maintenance of timely VRU status updates in the intended vehicle.