Abstract: The present application relates to the field of data consistency testing, and provides a method and device for testing vehicle data consistency in V2X. The method includes: collecting vehicle V2X test data transmitted based on a V2X-PC5 communication protocol; parsing the V2X test data, and determining whether a format and a data value of parsed data conform to a preset definition, and whether the parsed data is consistent with operating data in testing, to obtain a data structure consistency result; calculating an average error value between dynamic data in the parsed data and data collected by a high-precision inertial navigation device when time stamps are aligned and data sampling frequencies are the same; and according to the data structure consistency result and the average error value, determining whether vehicle data conforms to a preset consistency standard.

Abstract: This application relates to the technical field of connectivity communication, and provides an apparatus and method for testing a connected vehicle's communication distance. The testing apparatus includes a support member, and a first antenna is provided on the support member and connected to a signal transceiver. The signal transceiver is configured to send signals to a tested vehicle or receive signals sent by the tested vehicle. An output terminal of the signal transceiver is connected to an upper computer. Data analysis software is installed on the upper computer, and used for recording a test distance and a number of data packets and calculating a packet loss rate, such that a maximum communication distance is obtained according to the test distance and the corresponding packet loss rate.

Abstract: Disclosed is a test device and method for remote control parking, falling within the technical field of testing. The method provided by the present disclosure includes the following steps: responding to a remote control parking instruction sent by a portable terminal, and acquiring position and pose data of a vehicle in real-time; injecting function loss conditions; determining a stopping position of the vehicle according to the position and pose data if an alarm signal or a parking success signal sent by an in-vehicle infotainment system is received; and determining a test result of remote control parking according to the stopping position of the vehicle and the function loss conditions. The present disclosure is used to test the response of a vehicle parking under the function loss condition.

Abstract: A testing method for a blind spot detection system for an automobile includes: applying an electromagnetic interference signal to the tested automobile through an electromagnetic interference signal application device, meanwhile, simulating a static obstacle or a moving obstacle within a detection range through a testing device, and if the blind spot detection system for the tested automobile is activated, determining that the testing is passed. Repeatable and reproducible testing for the electromagnetic safety of the blind spot detection system may be realized.

Abstract: Disclosed are an OTA test method for a vehicle antenna system, a device and a storage medium. According to the method, the radio frequency performance of a physical layer of a whole vehicle antenna system can be tested, and the problem in the prior art that the test result of parts cannot accurately reflect the performance of the whole vehicle antenna system can be solved.

Abstract: In some embodiments, the present disclosure provides an algorithm for a data-driven intelligent adaptive model of an automobile cab based on a biometric identification technology. The algorithm includes the following steps: acquiring driving posture data, the driving posture data including driver information, automobile man-computer parameter information, and seat position information; building a feature extraction model of the driving posture data and screening feature vectors playing a significant role in predicting a seat position by the feature extraction model; building a prediction model of a comfortable seat position by a back propagation (BP) neural network and inputting the screened feature vectors to perform training on the prediction model; and inputting specific feature vectors to obtain the seat position information and accordingly adjust the seat position.

Abstract: In some embodiments, the present disclosure provides an algorithm for a data-driven intelligent adaptive model of an automobile cab based on a biometric identification technology. The algorithm includes the following steps: acquiring driving posture data, the driving posture data including driver information, automobile man-computer parameter information, and seat position information; building a feature extraction model of the driving posture data and screening feature vectors playing a significant role in predicting a seat position by the feature extraction model; building a prediction model of a comfortable seat position by a back propagation (BP) neural network and inputting the screened feature vectors to perform training on the prediction model; and inputting specific feature vectors to obtain the seat position information and accordingly adjust the seat position.