# 5G Beyond 3 GPP Release 15 for Connected Automated Mobility in Cross-Border Contexts
## 3 Challenging Cross-Border Use Cases
### Use Cases' Requirements
For a latency of 25 ms or below, the error's 95 th percentile is below 5 cm, which is negligible for a localisation problem. With 50 ms latency, the 95 th percentile is almost 10 cm, and reaches 18 cm with 100 ms latency. Depending on how close the transmitter vehicle's positioning measurement errors are to the error bounds, these decimetre level errors added by the network latency can definitely affect to the localisation of the transmitter vehicle in the receiver vehicle's frame. It is also important to consider that even if the network latency does not increase the localisation error outside of the error bounds, the positioning message needs to be received with enough time in advance to trigger a timely reaction. 3 GPP defined some performance requirements in [32] for use cases involving highly automated driving that are supposed to consider all these aspects. The performance requirements are summarised \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Scenario Name** & **Scenario Class** & **Duration (s)** & **Number of Dynamic Vehicles** \\ \hline CHN\_Cho-2\_8\_T-1 & Highway & 15.0 & 26 \\ CHN\_Cho-2\_10\_T-1 & Highway & 16.5 & 18 \\ DEU\_Stu-1\_5\_T-1 & Highway & 16.0 & 22 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: CommonRoad dataset scenarios used to study the effect of latency in the positioning error. Figure 2: Cumulative distribution function of the positioning error added by the latency in a highway scenario. in Table 3. Note that the latency requirements are in line with previous calculations; thus, a latency lower than 50 ms is required by all use cases, and it is much lower for advanced driving and remote driving due to their safety-critical nature and for extended sensors because of the required synchronisation and alignment of perception data coming from different sensors (e.g., video stitching or Lidar point cloud fusion). Extended sensors stands out as the most demanding use case in terms of data rate and communication range. Previous 5G-V2X requirements compiled by 3 GPP noted modest data rate requirements for remote driving under the assumption that a vehicle only transmits lightweight processed data [40]. However, more advanced remote driving approaches involve transmission of raw sensor data, so the whole onboard sensor suite can be processed in a remote server. This would of course require some data rate requirements similar to or even more demanding than extended sensors. Advanced driving requires a high transmission rate of 100 messages per second. This is exactly the same recommendation given in [33], derived as the time required between successive localisation updates. Vehicle platooning does not stand out in any of the performance indicators proposed by 3 GPP, but the requirements as a whole are still very demanding. The latency of V2V communication under a LTE network for multi-operator environments with regional split was studied in [41] and a latency of 58 ms was estimated in inter-operator communications without inter-operator handover. In the same work, the inter-operator handover, when vehicles have to detach from one operator and then attach to the other one, was estimated to have 300 ms of latency. It is then clear than enhanced 5G features are required to meet the demanding latency requirements. To sum up, the identified CAM use cases have demanding performance requirements that cannot be met by LTE infrastructures. This is even more clear in a cross-border context that requires roaming. The following section proposes some implementation options to overcome this issue that exploit features present at 3 GPP Release 16 and beyond.