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V2X (Vehicle-to-Everything) technology has the potential to greatly reduce and prevent road collisions. However, it faces a significant limitation: its protective benefits are limited to those road users who are equipped with V2X systems, and currently, adoption rates are low in the early stages of its market introduction.

Collective Perception, also known as sensor sharing, helps to solve this issue. With Collective Perception, vehicles with V2X capabilities don't merely exchange information about their own status; they also relay detailed sensor data about nearby road users - including pedestrians, cyclists, and other vehicles - even if those users lack V2X technology, like in Figure 1. This collective data sharing creates a richer, real-time understanding of the road environment.

The advantages of Collective Perception go beyond single vehicles. By aggregating sensor data from multiple V2X-enabled vehicles and infrastructure components, like roadside units, the network can identify and track road users even in blind spots or at intersections where visibility is limited. This significantly enhances safety by providing alerts about potential hazards before they come into view.

In the case of autonomous vehicles, an extended perception through CPMs allows them to see beyond their own sensor range by receiving data from nearby vehicles and infrastructure. This capability helps detect objects or hazards in blind spots, around corners, or in areas obstructed by buildings or other vehicles. By sharing information in real time, CPMs enhance the vehicle's situational awareness, allowing it to anticipate and respond to potential dangers earlier. This expanded awareness significantly improves safety and decision-making, particularly in complex environments where a single vehicle's sensors may be limited or unable to capture the full picture.

In the end, Collective Perception elevates V2X technology into a comprehensive safety system that benefits all road users, regardless of their V2X status. This feature positions it as a vital asset in the evolution toward fully integrated and safer transportation networks.

In addition to these benefits, we provide a practical example of how to generate Collective Perception Messages (CPM) using Python, allowing you to create your own CPM. In the following implementation, we regularly create a CPM that includes sample Perceived Object data, which is transmitted based on the vehicle's current position,following the ETSI TS 103 324 V2.1.1 standard.

The cpm_provider, as illustrated in Figure 2, is responsible for supplying CPMs to cube-its. It subscribes to position updates and publishes a CPM to the /its/cpm_provided topic, where the CPS facility in cube-its manages the transmission of the CPM. Moreover, the provider consistently generates and sends CPMs according to the current position, ensuring a seamless flow of collective perception data across the network.

This example can help developers easily implement CPM functionality, enhancing V2X communication systems with richer data on nearby road users, including those without V2X technology.

For the complete implementation and more code examples, visit our GitHub repository. Happy coding!!