Real-Time Target Detection System for Intelligent Vehicles Based on Multi-Source Data Fusion

Abstract

To improve the identification accuracy of target detection for intelligent vehicles, a real-time target detection system based on the multi-source fusion method is proposed. Based on the ROS melodic software development environment and the NVIDIA Xavier hardware development platform, this system integrates sensing devices such as millimeter-wave radar and camera, and it can realize functions such as real-time target detection and tracking. At first, the image data can be processed by the You Only Look Once v5 network, which can increase the speed and accuracy of identification; secondly, the millimeter-wave radar data are processed to provide a more accurate distance and velocity of the targets. Meanwhile, in order to improve the accuracy of the system, the sensor fusion method is used. The radar point cloud is projected onto the image, then through space-time synchronization, region of interest (ROI) identification, and data association, the target-tracking information is presented. At last, field tests of the system are conducted, the results of which indicate that the system has a more accurate recognition effect and scene adaptation ability in complex scenes.

Construction Quality Control for Rutting Resistance of Asphalt Pavement Using BIM Technology

“…When the construction process indices are in the degree of fluctuation in various factors defined in this study, it is important to pay special attention to gradation coarsening in the asphalt mixtures' mixing process and gradation becoming finer owing to segregation. [12,13,40] and asphalt mixing plant online detection technology [6,7] can both determine the mixture gradation and asphalt dosage in the mixing process in real time [6]. Currently, the data-logging framework of the asphalt mixing plant can accurately gather data such as the weight of asphalt and aggregate, and accurately calculate the amount of asphalt in the tank.…”

“…Table 15 depicts the current gradation of an asphalt mixed pot. [12,13,40] and asphalt mixing plant online detection technology [6,7] can both determine the mixture gradation and asphalt dosage in the mixing process in real time [6]. Currently, the data-logging framework of the asphalt mixing plant can accurately gather data such as the weight of asphalt and aggregate, and accurately calculate the amount of asphalt in the tank.…”

“…After determining which control indicators need to be monitored, it is also essential to handle the real-time detection of control indicators. Using digital imaging technology [12][13][14][15] or real-time monitoring technology [6,7], the particle size distribution and the asphalt percentage can be prognosticated promptly in the asphalt mixing plant. In addition, GPR can determine the air gap and asphalt surface thickness in actual time [16,17].…”

Logistics Center Selection and Logistics Network Construction from the Perspective of Urban Geographic Information Fusion

“…To surmount these obstacles, Yan et al [ 32 ] devised a collaborative strategy that marries deep learning with machine learning theory to enhance the tracking quality of rice, thereby improving the fusion system’s detection performance. Junyi et al [ 33 ] developed an enhanced real-time target detection system for intelligent vehicles, employing a multi-source fusion method within the ROS Melody software (Melodic) development environment and the NVIDIA Xavier hardware platform (NVIDIA, Santa Clara, CA, USA). To boost the predictive accuracy and efficiency of coal mine gas generation patterns, Huice et al [ 34 ] proposed a method based on multi-source data fusion.…”