###### Abstract  
The combination of onboard sensors on vehicles with wireless communication has great advantages over the conventional driving systems in terms of safety and reliability. This technique is often called cooperative perception. Cooperative perception is expected to compensate for blind spots in dynamic maps, which are caused by obstacles. Few blind spots in dynamic maps can improve the safety and reliability of driving thanks to the additional information beyond the sensing of the onboard sensors. In this paper, we analyzed the required sensor data rate to be exchanged for the cooperative perception in order to enable a new level of safe and reliable automated driving in overtaking scenario. The required sensor data rate was calculated by the combination of recognition and vehicle movement to adopt realistic assumptions. In the end of the paper, we compared the required sensor data rate with the outage data rate realized by the conventional V2V communication and millimeter-wave communication. The results showed the indispensability of millimeter-wave communications in automated driving systems. 5G; automated driving; cooperative perception; collective perception; V2V communication; millimeter-wave communication; extended sensor +
Footnote †: journal: Sensors  
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navigate to a destination. On the other hand, dynamic information provides information about surrounding objects that help to prevent a collision. This dynamic information is gained by onboard sensors such as cameras, radar sensors, and LiDAR sensors, which results in a significant hardware cost. Unfortunately, when obstacles block the sensor view, dynamic information has no way to provide information about blind spots. One solution to this problem is connecting an automated vehicle with other sensors, which is called cooperative perception. The key idea of cooperative perception is to share sensor data obtained from different locations via wireless communication, as shown in Figure 1. It is said that the demands of the data rate for cooperative perception will grow heavily as the level of automated driving grows [5]. This is because the system in an automated vehicle has to recognize the surrounding environment and drive safely by itself. Although many groups have presented the requirements for multiple use cases such as cooperative perception, it is still an open question to find the minimum required sensor data rate to guarantee safe automated driving. Since automated driving roughly consists of obtaining sensor data, processing the sensor data, and reflecting the results of the process in vehicle movement, the requirements for safe automated driving should also consider these processes. Focusing on the sensor data rate, in [6], it was said that an automated vehicle gathers nearly 750 megabytes per second, which will require a high data rate for cooperative perception. Moreover, when raw sensor data are sent for cooperative perception, this high data rate will have a big impact on the performance of wireless communication. From these two facts, it is expected that conventional V2V (Vehicle-to-Vehicle) communications are not enough to support safe automated driving using cooperative perception. In order to discuss the data rate required for safe automated driving, we focused on overtaking on a two-lane road and derived the required data rate to prevent car-car accidents. This scenario selection was due to the statistics in Japan, which say that head-on collisions account for 50% of accidents in basic road sections [7]. The contributions of this paper consist of the derivation of the requirements that consider safety and showing that millimeter-wave communication has a great ability to share raw sensor data and guarantee safety. In this paper, we adopted a vehicle movement and a recognition process in the required data rate analysis to discuss it under a more realistic assumption. Moreover, we adopted raw sensor data sharing for both processed and raw sensor data sharing for high reliability.