Data Association Between Perception and V2V Communication Sensors

TL;DR

This paper presents a real-time, low-complexity Mahalanobis distance-based data association algorithm for fusing camera and V2V communication sensor data, enhancing automotive safety systems.

Contribution

The paper introduces a novel real-time data association algorithm specifically designed for combining camera and V2V communication sensors in ADAS.

Findings

Algorithm operates in real-time with low computational complexity

Effective sensor fusion for ADAS applications demonstrated

Potential for improved safety decision-making

Abstract

The connectivity between vehicles, infrastructure, and other traffic participants brings a new dimension to automotive safety applications. Soon all the newly produced cars will have Vehicle to Everything (V2X) communication modems alongside the existing Advanced Driver Assistant Systems (ADAS). It is essential to identify the different sensor measurements for the same targets (Data Association) to use connectivity reliably as a safety feature alongside the standard ADAS functionality. Considering the camera is the most common sensor available for ADAS systems, in this paper, we present an experimental implementation of a Mahalanobis distance-based data association algorithm between the camera and the Vehicle to Vehicle (V2V) communication sensors. The implemented algorithm has low computational complexity and the capability of running in real-time. One can use the presented algorithm for sensor fusion algorithms or higher-level decision-making applications in ADAS modules.