Intelligent transportation systems (ITSs) have been extensively studied in recent years to improve the safety and efficiency of transportation. The use of a radar system to enable the ITSs monitor the environment is robust to weather conditions and is less invasive to user privacy. Moreover, equipping the roadside units (RSUs) with radar modules has been deemed an economical and efficient option for ITS operators. However, because the detection and tracking parameters can significantly influence the radar system performance and the best parameters for different scenarios are different, the selection of appropriate parameters for the radar systems is critical. In this study, we investigated radar parameter selection and consequently proposes a parameter selection approach capable of automatically choosing the appropriate detection and tracking parameters for radar systems. The experimental results indicate that the proposed method realizes appropriate selection of parameters, thereby significantly improving the detection and tracking performance of radar systems.

To enhance safety and efficiency in the traffic environment, developing intelligent transportation systems (ITSs) is of paramount importance. In ITSs, roadside units (RSUs) are critical components that enable the environment awareness and connectivity via using radar sensing and communications. In this paper, we focus on RSUs with multiple radar systems. Specifically, we propose a parameter selection method of multiple radar systems to enhance the overall sensing performance. Furthermore, since different radars provide different sensing and tracking results, to benefit from multiple radars, we propose fusion algorithms to integrate the tracking results of different radars. We use two commercial frequency-modulated continuous wave (FMCW) radars to conduct experiments at Hsinchu city in Taiwan. The experimental results validate that our proposed approaches can improve the overall sensing performance.