Age of Information and Transmission Cost Trade-Off in NR-V2X SL Perception Messages

Connected automated vehicles are key components of Intelligent Transport Systems, acting as information sources that share their onboard sensor data with other road users. This paper introduces a novel queueing theory-based model to characterize a connected vehicle as a data source, determining the average number of objects perceived over time. This serves as a foundation for assessing how frequently the vehicle should broadcast update messages. To identify the most suitable update period, we formulate an optimization problem that minimizes an objective function accounting for both transmission and freshness costs. The transmission cost is quantified by the average data rate, while the freshness cost is evaluated using the average Peak Age of Information, an end-to-end metric that captures the timeliness of the received information. A closed-form solution is derived for this optimization problem under the Dynamic Scheduling scheme of the 5G New Radio Vehicle-to-Everything Side Link standard. Results indicate that the optimal update period depends on the velocity of the road occupants, their spatial rate, and the detection range of the connected vehicle, which is determined by its onboard equipment. Furthermore, when information timeliness is prioritized over transmission cost, it is shown that the optimal periodicity almost exclusively depends on the velocity of the objects along the road.