Abstract: The present disclosure provides a camera calibration method based on vehicle localization, mainly considering that a vehicle is not of an ideal rigid structure, and shaking of a vehicle body during operation, uneven road surfaces, or different loads will cause variations in extrinsic parameters of a camera system, resulting in perceptual information errors. Therefore, through perceptual information from a fused image, an inertial measurement unit, a speedometer, and the like, combined with the road and marking information provided by a high-definition map, the relative motion between the vehicle body and a vehicle chassis is simultaneously described with a mass-spring-damper model, so as to complete the determination of six-degree-of-freedom positions of the vehicle body and the vehicle chassis, and finally the extrinsic parameters of cameras are immediately calibrated with the vehicle chassis as reference coordinates.

Abstract: The present disclosure provides a camera calibration method based on vehicle localization, mainly considering that a vehicle is not of an ideal rigid structure, and shaking of a vehicle body during operation, uneven road surfaces, or different loads will cause variations in extrinsic parameters of a camera system, resulting in perceptual information errors. Therefore, through perceptual information from a fused image, an inertial measurement unit, a speedometer, and the like, combined with the road and marking information provided by a high-definition map, the relative motion between the vehicle body and a vehicle chassis is simultaneously described with a mass-spring-damper model, so as to complete the determination of six-degree-of-freedom positions of the vehicle body and the vehicle chassis, and finally the extrinsic parameters of cameras are immediately calibrated with the vehicle chassis as reference coordinates.

Abstract: An electronic device and a method for determining scenario data of a self-driving car are provided. The method includes: obtaining training scenario data by using scenario data, a loss function and a self-driving program module; training an encoding module and a decoding module by using the training scenario data, and generating a scenario space by using the trained encoding module; obtaining a monitoring module by using the scenario space; and executing the monitoring module to determine whether current scenario data belongs to an operational design domain by using the current scenario data and the trained encoding module.

Abstract: In an example, a speaker device may include a first transducer and a second transducer. The first transducer may include a first diaphragm, a first magnetic circuit, and a first voice coil disposed in a magnetic gap of the first magnetic circuit to cause vibration of the first diaphragm. The second transducer may include a second diaphragm, a second magnet circuit, and a second voice coil disposed in a magnetic gap of the second magnetic circuit to cause vibration of the second diaphragm. Further, the speaker device may include a magnetic plate having a first surface coupled to the first transducer and a second surface coupled to the second transducer. The first surface is opposite to the second surface.

Abstract: A safe following distance estimation system and an estimation method thereof are provided. The safe following distance estimation system adapted for an autonomous vehicle includes a sensor and a processor. The sensor senses an adjacent vehicle to generate first sensing data, and senses the autonomous vehicle to generate second sensing data. The processor estimates a first friction parameter between wheels of the adjacent vehicle and a pavement according to pavement material data, and estimates a second friction parameter between wheels of the autonomous vehicle and the pavement according to the second sensing data. The processor calculates a safe following distance between the autonomous vehicle and the adjacent vehicle according to the first sensing data, the second sensing data, the first friction parameter, the second friction parameter.

Abstract: In an example, a speaker device may include a first transducer and a second transducer. The first transducer may include a first diaphragm, a first magnetic circuit, and a first voice coil disposed in a magnetic gap of the first magnetic circuit to cause vibration of the first diaphragm. The second transducer may include a second diaphragm, a second magnet circuit, and a second voice coil disposed in a magnetic gap of the second magnetic circuit to cause vibration of the second diaphragm. Further, the speaker device may include a magnetic plate having a first surface coupled to the first transducer and a second surface coupled to the second transducer. The first surface is opposite to the second surface.

Abstract: A safe following distance estimation system and an estimation method thereof are provided. The safe following distance estimation system adapted for an autonomous vehicle includes a sensor and a processor. The sensor senses an adjacent vehicle to generate first sensing data, and senses the autonomous vehicle to generate second sensing data. The processor estimates a first friction parameter between wheels of the adjacent vehicle and a pavement according to pavement material data, and estimates a second friction parameter between wheels of the autonomous vehicle and the pavement according to the second sensing data. The processor calculates a safe following distance between the autonomous vehicle and the adjacent vehicle according to the first sensing data, the second sensing data, the first friction parameter, the second friction parameter.