A Model-Based Joint Detection and Tracking Approach for Multi-Vehicle Tracking With Lidar Sensor

Abstract

This paper presents a method for joint detection and tracking of vehicles with a scanning laser rangefinder. The lidar measurements of an object have the particularity to be spatially distributed, which generally leads to a detection step before any tracking. Differently, the proposed method relies on the raw measurement processing without any detection step, which improves the overall performance in multiobject tracking while providing good estimation accuracies. The solution uses the sequential Monte Carlo methods by incorporating the geometric invariant of the objects of interest (vehicles). This approach also offers an efficient solution to the problem of multitarget tracking by integrating naturally the track management in the filtering process.Index Terms-Extended target tracking, sequential Monte Carlo methods, track-before-detect, scanning laser range finder, advanced driver assistance systems.

A review of essential technologies for collision avoidance assistance systems

“…Radar perception technology. Radars in vehicles can be classified as ultrasonic, millimeter wave, 28 and LiDAR 29,30 according to their working principle. Ultrasonic radars are simple and inexpensive but are influenced by weather, and the sensing distance is limited to 4-5 m. Hence, they are generally used in reversing and parking alarm systems.…”

“…LiDAR has many favorable characteristics, such as a detection range of up to 100 m, high speed, high stability, and 3D imaging, but it is expensive and easily influenced by the environment. Millimeter-wave radars, [28][29][30] by contrast, is relatively less expensive, is not easily influenced by environmental elements, and has precision; thus, they are suitable for use in CAA systems. 32 Radar cross-section, multi-target recognition, wave studies, signal processing, and transceiver isolation are essential technologies in millimeter-wave radar sensing.…”

Fast Dynamic Vehicle Detection in Road Scenarios Based on Pose Estimation with Convex-Hull Model

“…Feature extraction could be summed up in the detection of triangles in the cumulative function and property estimation. A model-based joint detection and tracking method was proposed in [20], which is a track-before-detect method. The method improved estimation-accuracy performance, robustness to false alarms, and track continuity based on a bounding-box model.…”

Desenvolvimento de Instrumentação para geração de nuvem de pontos usando sensores inerciais e LiDAR

“…Outra ferramenta utilizadaé o sensor LiDAR (Light Detection and Ranging). Esta tecnologiaé utilizada para captação de dados de uma região através de nuvem de pontos, Fortin et al (2015). Esses dados são tratados de acordo com o interesse de estudo, podendo ser aplicados também em diversasáreas.…”