A method for controlling slip of at least one wheel of a vehicle. In the method, at least one parameter of an action to be performed is read out from a matrix using a slip state of the wheel if the slip state is outside a target slip region of the matrix, wherein, for reading this out, a data field of the matrix associated with the slip state is determined and the at least one parameter is read out from the data field, wherein, for performing the action, at least one actuator of the vehicle is actuated using the parameter.

A system and method of mu estimation may include the steps of collecting vehicle travel data on a road surface via a plurality of a sensors including at least one of an accelerometer or microphone; collecting external source data over a network; and aggregating the vehicle travel data and external source data to form an aggregated data set. The method may include performing feature extraction processing of the aggregated data set to transform the aggregated data set and into a processed aggregated data set; communicating the processed aggregated data set to a machine learning model; and generating at least one of an estimated mu value of the road surface or road surface classification via the machine learning model.

A system and method of mu estimation may include the steps of collecting vehicle travel data on a road surface via a plurality of a sensors including at least one of an accelerometer or microphone; collecting external source data over a network; and aggregating the vehicle travel data and external source data to form an aggregated data set. The method may include performing feature extraction processing of the aggregated data set to transform the aggregated data set and into a processed aggregated data set; communicating the processed aggregated data set to a machine learning model; and generating at least one of an estimated mu value of the road surface or road surface classification via the machine learning model.

An apparatus for controlling a braking force of a vehicle is provided. The apparatus includes a sensor device that obtains information about an image in front of the vehicle and driving information of the vehicle and a controller that determines a road surface state including a left road surface state and a right road surface state based on the information about the image and the driving information and controls a braking force of left wheels of the vehicle and a braking force of right wheels of the vehicle respectively based on the left road surface state and the right road surface state of the vehicle.

A braking method for a vehicle, an electronic device and a storage medium are provided, and relates to the field of intelligent vehicles. The method includes: generating, in a case where a braking trigger signal is received, a first braking control signal according to a first braking parameter of the vehicle, wherein the first braking control signal is used to control a braking traction mechanism to draw a brake pedal according to the first braking parameter, to perform braking; collecting braking data of a current braking process; evaluating a braking effect of the current braking process according to the collected braking data; and determining whether to adjust the first braking parameter according to a result of the evaluating, wherein the determined first braking parameter is used for a next braking process of the vehicle.

A braking method for a vehicle, an electronic device and a storage medium are provided, and relates to the field of intelligent vehicles. The method includes: generating, in a case where a braking trigger signal is received, a first braking control signal according to a first braking parameter of the vehicle, wherein the first braking control signal is used to control a braking traction mechanism to draw a brake pedal according to the first braking parameter, to perform braking; collecting braking data of a current braking process; evaluating a braking effect of the current braking process according to the collected braking data; and determining whether to adjust the first braking parameter according to a result of the evaluating, wherein the determined first braking parameter is used for a next braking process of the vehicle.

Disclosed is an adaptive autonomous emergency braking (AEB) control method. An adaptive AEB control method includes identifying a front vehicle to be avoided on the basis of front-view information acquired through a front-view sensor, setting a steering avoidable area on the basis of speed information and lateral acceleration information of a host vehicle, adaptively determining an AEB activation time point on the basis of whether a vehicle is present in the set steering avoidable area, and controlling AEB activation on the basis of the adaptively determined AEB activation time point.

Disclosed is an adaptive autonomous emergency braking (AEB) control method. An adaptive AEB control method includes identifying a front vehicle to be avoided on the basis of front-view information acquired through a front-view sensor, setting a steering avoidable area on the basis of speed information and lateral acceleration information of a host vehicle, adaptively determining an AEB activation time point on the basis of whether a vehicle is present in the set steering avoidable area, and controlling AEB activation on the basis of the adaptively determined AEB activation time point.

The vehicle includes: a sensor part configured to acquire occupancy information of an surrounding area of the vehicle and a speed of the vehicle; a camera configured to acquire a surrounding image of the vehicle; and a controller configured to form map information based on the occupancy information according to movement of the vehicle, determine presence or absence of an obstacle around the vehicle based on the map information and the surrounding image, and control, in response to presence of the obstacle, the vehicle based on the presence of the obstacle and a possibility of collision of the vehicle derived from the speed of the vehicle and the map information.

The vehicle includes: a sensor part configured to acquire occupancy information of an surrounding area of the vehicle and a speed of the vehicle; a camera configured to acquire a surrounding image of the vehicle; and a controller configured to form map information based on the occupancy information according to movement of the vehicle, determine presence or absence of an obstacle around the vehicle based on the map information and the surrounding image, and control, in response to presence of the obstacle, the vehicle based on the presence of the obstacle and a possibility of collision of the vehicle derived from the speed of the vehicle and the map information.