Tracking Accuracy Based Generation Rules of Collective Perception Messages

TL;DR

This paper proposes an accuracy-based method for generating collective perception messages in intelligent transport systems, improving communication efficiency and object tracking accuracy by considering local and received tracking information.

Contribution

It introduces a novel algorithm that uses tracking accuracy and relative entropy to decide object inclusion in messages, enhancing existing ETSI CPS methods.

Findings

Reduced Channel Busy Ratio (CBR) in simulations

Improved Object Tracking Accuracy (OTA)

More efficient communication resource utilization

Abstract

The Collective Perception Service (CPS) enables the enhancement of environmental awareness of Intelligent Transport System Stations (ITS-S) through the exchange of tracking information between stations. As the market penetration of CPS is growing, the intelligent distribution of the limited communication resources becomes more and more challenging. To address this problem, the ETSI CPS proposes dynamic-based object selection to generate Collective Perception Messages. However, this approach has limits and barely considers detection accuracy and the recent information available at other ITS-Ss in the transmission range. We show a proposal considering the current object tracking accuracy in the local environment and the object tracking from messages received by other stations in order to intelligently decide whether to include an object in a CPM. The algorithm decides based on the relative entropy between the local and V2X tracking accuracy if the object information is valuable for the nearby stations. Our simulation according to the ITS-G5 standard shows that the Channel Busy Ratio (CBR) can be reduced with accuracy-based generation of CPM while improving Object Tracking Accuracy (OTA) compared to generation based on ETSI rules.