In this work, a complementary metal-oxide semiconductor (CMOS) based transceiver with a sensitivity time control antenna is successfully implemented for advanced traffic signal processing. The collected signals from the CMOS radar system are processed with optimization algorithms for vehicle-type classification and speed determination. The high recognition rate optimization algorithms are mainly based upon the information of short setup time and different environmental installation of each sensor. In the course of optimization, a video recognition module is further adopted as a supervisor of support vector machine and support vector regression. Compared with conventional circuit-based detector systems, the developed CMOS radar integrates submicron semiconductor devices and thus not only possesses low stand-by power but also is ready for production. In the meantime, the developed algorithm of this study simultaneously optimizes the vehicletype classification and speed determination in a computationally cost-effective manner, which benefits real-time intelligent transportation systems.
A video recognition model based on the use of a support vector machine was proposed for classifying vehicle types and determining the vehicle speeds REF .
A support vector machine approach to CMOS-based radar signal processing for vehicle classification and speed estimation
Math. Comput. Model.
Math. Comput. Model.
Computer Science Mathematics