Abstract: A vehicle control system includes a vehicle state estimator, a delay simulator and an error compensation optimizer. The vehicle state estimator is configured to generate an estimated future vehicle state at a future time point. The delay simulator is configured to determine a delay time based on the estimated future vehicle state and a current vehicle state, and obtain a delayed future vehicle state based on the delay time. The error compensation optimizer is configured to generate a driving parameter estimation compensation to the vehicle state estimator based on a difference between the delayed future vehicle state and a target vehicle state being outside the error range.

Abstract: A loading calculation module includes a storage unit, an inertial sensing unit and a calculation unit. The first storage unit is configured to store a relationship between an engine performance and a load, a sprung mass, a centroid distance between a sprung centroid, a rotation center and a moment of inertia. The inertial sensing unit is configured to detect a tilt angle, a tilt angular velocity, a tilt angular acceleration and a lateral acceleration. The calculation unit is configured to obtain a load corresponding to the engine performance according to the relationship between the engine performance and the load; and obtain a load position according to the moment of inertia, the tilt angle, the tilt angular velocity, the tilt angular acceleration, the lateral acceleration, the load and the centroid distance.

Abstract: A loading calculation module includes a storage unit, an inertial sensing unit and a calculation unit. The first storage unit is configured to store a relationship between an engine performance and a load, a sprung mass, a centroid distance between a sprung centroid, a rotation center and a moment of inertia. The inertial sensing unit is configured to detect a tilt angle, a tilt angular velocity, a tilt angular acceleration and a lateral acceleration. The calculation unit is configured to obtain a load corresponding to the engine performance according to the relationship between the engine performance and the load; and obtain a load position according to the moment of inertia, the tilt angle, the tilt angular velocity, the tilt angular acceleration, the lateral acceleration, the load and the centroid distance.

Abstract: A point cloud positioning error detection method, performed by a processing device, includes: obtaining a plurality of pieces of first point data and a target point cloud map, wherein the target point cloud map includes a plurality of pieces of target point data, registering the first point data and the target point data to obtain a plurality of pieces of second point data, selecting a plurality of pieces of third point data from the second point data according to a first default distance, calculating a plurality of matching scores of the third point data relative to the target point data, obtaining a plurality of step vectors corresponding to the third point data, respectively, when said registering converges, and obtaining a plurality of effective values according to directions of the step vectors, and outputting a localization fault detection result based on an intersection of the matching scores and the effective values.

Abstract: A navigation and positioning device including a storage, a mark feature analyzer, a first coordinate fusion component and a second coordinate fusion component is provided. The storage stores map information including a traffic mark feature and its mark coordinate. The mark feature analyzer is used for analyzing whether a captured image has the traffic mark feature. When the captured image has the traffic mark feature, the mark feature analyzer analyzes the traffic mark feature in the captured image and calculates a device coordinate according to the mark coordinate. The first coordinate fusion component fuses the device coordinate and a first fusion coordinate and uses fused coordinate as a second fusion coordinate. The second coordinate fusion component fuses the second fusion coordinate, traffic carrier inertial information and a global positioning coordinate and uses fused coordinate as an updated first fusion coordinate.

Abstract: A navigation and positioning device including a storage, a mark feature analyzer, a first coordinate fusion component and a second coordinate fusion component is provided. The storage stores map information including a traffic mark feature and its mark coordinate. The mark feature analyzer is used for analyzing whether a captured image has the traffic mark feature. When the captured image has the traffic mark feature, the mark feature analyzer analyzes the traffic mark feature in the captured image and calculates a device coordinate according to the mark coordinate. The first coordinate fusion component fuses the device coordinate and a first fusion coordinate and uses fused coordinate as a second fusion coordinate. The second coordinate fusion component fuses the second fusion coordinate, traffic carrier inertial information and a global positioning coordinate and uses fused coordinate as an updated first fusion coordinate.