Research on reliability evaluation method for sensor signals in data reinjection system

The test system for an intelligent driving system is a research priority of intelligent driving, where the perception layer sensor signal used for reinjection must be reliable and effective. To address the insufficient objectivity of horizontal comparison using a single error index, a reliability evaluation method for sensor signal reinjection based on quantification of margins and uncertainties (QMU) was proposed. Based on the core principle of QMU, a reliability evaluation pathway was first established by incorporating evaluation thresholds. Subsequently, a comprehensive fuzzy evaluation system and process, integrating the order relation method (G1) and an uncertainty scale factor, were developed for sensors in the data reinjection system, from which the test results were derived. Finally, a test scenario was built in the simulation software, and the reinjection signals of the millimeter-wave radar and LiDAR received by the domain controller were evaluated. The results show that for the measured data, the characteristic values of the LiDAR maximum elevation error, XY-plane error, X-plane error and Y-plane error are 2.89, 0.45, 1.063 and 0.65, respectively, with a comprehensive evaluation result of 2.82. The characteristic values of the millimeter-wave radar for ranging, angle measurement and velocity measurement are 2.1429, 1.5306 and 1.1705. The comprehensive evaluation result obtained by the proposed method is 1.467. This method can overcome the limitations of horizontal comparison of a single index, and realize the in-depth evaluation and objective quantification of the sensor reinjection system.