Abstract
The millimeter-wave radar has been widely used in traffic applications. However, little research has been done to install the millimeter-wave radar on the top of a road for detecting road traffic flow at a downward looking direction. In this paper, the vehicle parameters, including the distance, angle and radar cross-section energy, are collected by practical experiments in the aforementioned application scenario. The data features are analyzed from the dimensions of single parameter sampling characteristics and multi-parameter relationships. Further, the correlations of different parameter series are given using the grey correlation analysis method. For millimeter-wave radar used in the traffic flow detection, our work can definitely provide significant support for further intelligent transportation applications, such as vehicle trajectory tracking, traffic flow estimation and traffic event identification.
Highlights
The traditional traffic parameter detection methods include: (1) the magneto-electric induction detecting method, in which the section flow data is acquired by loop detectors or geomagnetic detectors placed underground at a certain road section [3,4,5]; (2) the floating vehicle method, which extracts traffic parameters from the trajectory data by intelligent onboard devices, such as bus floating data and taxi floating data [6,7]; (3) the video image detecting methods, for example, the traffic parameter collection by electronic-police camera or using the unmanned aerial vehicles (UAV) [8,9]; and (4) the radar detecting methods
The target vehicle is identified by the differences between the transmitting signal and the echo signal and the vehicle speed is calculated based on the Doppler effect
For millimeter-wave radar used in the traffic flow detection field, our work can provide useful support for further intelligent transportation applications, such as vehicle trajectory tracking, traffic flow estimation and traffic event identification
Summary
Real-time road traffic parameter collection and accurate road congestion evaluation are the prerequisites for applying better traffic congestion avoidance strategies to improve the traffic flow [1,2]. For target identification and trajectory tracking research, [25] proposes a blind spot detection and warning system (BSDWS) using the millimeter-wave radar. We make an attempt that the FMCW millimeter-wave radar is used to detect traffic flow characteristics and analyze the data features. Differing from the onboard installation method for ADAS applications and the orthogonally to traffic flow installation method of traditional radars, we install the radar device above the road, for example, at the cross arm of electronic police devices In this case, the radar detects the vehicles at a downward looking direction. For millimeter-wave radar used in the traffic flow detection field, our work can provide useful support for further intelligent transportation applications, such as vehicle trajectory tracking, traffic flow estimation and traffic event identification.
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