Realizing collective perception in a vehicle

The introduction of Vehicle-to-X (V2X) communication enhances the perception range of a vehicle significantly. The technology, however, is subjected to the network effect: a minimum number of communication partners need to be within range, in order for V2X applications to work. Taking current vehicle replacement rates on the market into account, the time of market introduction is critical, as early adopters are likely not to profit from the technology, whilst having to account for the development costs. This contribution picks up the concept of collective perception, in which vehicles share their information gathered by their local perception sensors about objects in their vicinity. This work extends our earlier research by introducing a new message format, the Environmental Perception Message (EPM) for exchanging sensor information. Additionally, a high-level data fusion framework is presented, which separates the fusion process of local sensor data and V2X information, along with the required coordinate transformations for representing another vehicle's sensor information in the recipient's reference frame. We also realized the introduced framework and message in two automated vehicles and provide a performance analysis in an obstacle avoidance scenario for these vehicles on a race track. Since the vehicles share their sensor data with each other, the resulting available reaction time for avoiding the obstacle on the track increases significantly.