Abstract: The embodiments of the present disclosure provide a detection method, apparatus for automatic driving sensor, and electronic device. The method includes: pre-establishing a standard association relationship, the sensor to-be-detected is used for capturing in a fixed scene, and a corresponding capturing result is displayed.

Abstract: Embodiments of the present disclosure relate to an autonomous vehicle and a system for the autonomous vehicle. The system may include: a power supply including a first power output and a second power output; a master computing unit arranged to be powered by the first power output, configured to control operations of the autonomous vehicle in response to detecting the second power output, and configured to provide a third power output by adjusting the first power output; and a slave computing unit arranged to be powered by the second power output, and configured to control the operations of the autonomous vehicle in response to detecting a failure of the master computing unit.

Abstract: A method and an apparatus for controlling a mobile robot, and a control system are provided. The method includes: in response to receiving a start request sent by a mobile robot, obtaining at least one of the position information or condition information of the mobile robot; determining a speed limit value of the mobile robot according to the obtained information; and sending a start instruction including the speed limit value to the mobile robot, so as to control the mobile robot to move at a speed smaller than or equal to the speed limit value. The implementation improves the motion safety of a mobile robot.

Abstract: Embodiments of the present disclosure provide a method for processing vehicle driving mode switching, a vehicle and a server. The method includes: determining (S103) a target switching reason upon detecting that a driving mode of a vehicle is switched from unmanned driving to manned driving; acquiring (S104) status information and/or traveling environment information of the vehicle corresponding to the target switching reason; and sending the status information and/or the traveling environment information, and the target switching reason to a server, to enable the server to analyze the target switching reason, and improve the automatic driving system continuously according to the analysis result.

Abstract: A method for simulating an obstacle in an unmanned simulation scene includes: for obstacle information in a three-dimensional scene map, determining Gaussian distribution information of obstacle position detected by using a perception algorithm to be tested based on actual perception performance of the perception algorithm; adjusting each position of the simulated obstacle in the initial motion trajectory sequence, such that a position deviation between each adjusted position point in the target motion trajectory sequence and the corresponding position point in the initial motion trajectory sequence follows a Gaussian distribution; and adding the target motion trajectory sequence of the simulated obstacle to the three-dimensional scene map.

Abstract: A method, device and apparatus for processing a control parameter, and a storage medium are provided. The method includes: acquiring first information input to a control system; acquiring second information output after the first information is processed by the control system; obtaining a first parameter characteristic for characterizing a system parameter, according to the first information and the second information; obtaining a second parameter characteristic for adjusting the control parameter, according to the first parameter characteristic and a corresponding relation between the system parameter and the control parameter; and adjusting the control parameter according to the second parameter characteristic. Thus, an adaptive adjustment of the control parameter based on the variation of the scene is realized, and the parameter adjustment efficiency is improved.

Abstract: Embodiments of the present application disclose a positioning method and apparatus, an autonomous driving vehicle, an electronic device and a storage medium, relating to the field of autonomous driving technologies, comprising: collecting first pose information measured by an inertial measurement unit within a preset time period, and collecting second pose information measured by a wheel tachometer within the time period; generating positioning information according to the first pose information, the second pose information and the adjacent frame images; controlling driving of the autonomous driving vehicle according to the positioning information. The positioning information is estimated by combining the first pose information and the second pose information corresponding to the inertial measurement unit and the wheel tachometer respectively. Compared with the camera, the inertial measurement unit and the wheel tachometer are not prone to be interfered by the external environment.

Abstract: Embodiments of a method, apparatus, device and computer readable storage medium for classifying driving scenario data includes: acquiring a first driving scenario data set from a crowdsourcing platform, driving scenario data in the first driving scenario data set having been classified; generating a driving scenario classification model at least based on the first driving scenario data set, for classifying driving scenario data collected by a collection entity; acquiring a rule for classifying the driving scenario data, the rule is generated based on a result of classifying the driving scenario data collected by the collection entity using the driving scenario classification model; updating the driving scenario classification model at least based on the rule.

Abstract: Embodiments of the present provide a cross-camera obstacle tracking method, system and medium. The method includes: obtaining obstacle tracking results of images captured by at least two cameras, wherein each obstacle tracking result comprises results after identifying and tracking at least one obstacle in the image captured by each camera, and each obstacle is labeled with a local identifier for each camera; in response to a triggering condition of a main camera in the cameras to fusion of cross-camera obstacles being satisfied, establishing a mapping relation between local identifiers of the obstacles in the cameras and global identifiers according to the obstacle tracking result of each of the cameras; determining similarities of obstacles according to the obstacle tracking result of each of the cameras, and performing fusion of the global identifiers on the same obstacle according to the similarities; and obtaining final obstacle tracking results labeled with the global identifiers.

Abstract: A vehicle control technical solution is provided. The solution relates to the field of computer technologies, and particularly to the field of artificial intelligence technologies, such as autonomous driving technologies, intelligent transportation technologies. A vehicle control method includes: acquiring a state quantity error between a desired state quantity at a current moment and a real state quantity at a previous moment of a vehicle; determining a control quantity of the vehicle at the current moment based on the state quantity error and a mapping relationship between the control quantity of the vehicle and the state quantity error; and controlling a driving behavior of the vehicle based on the control quantity at the current moment to obtain a real state quantity at the current moment.

Abstract: The present disclosure discloses a method for generating a parking model, an electronic device and a storage medium, and relates a field of autonomous parking technologies. The detailed implementing solution includes: obtaining multiple sample sets; constructing a parking cruise space for the target vehicle based on each sample set, and extracting a first parking trajectory corresponding to each sample set from each parking cruise space; recognizing an abnormal position on each first parking trajectory, and deleting driving data corresponding to the abnormal position from a sample set corresponding to each first parking trajectory to obtain target sample data in each sample set; and performing model training based on the target sample data in each sample set to generate a target parking model.

Abstract: The present disclosure provides a vehicle positioning method implemented by an electronic device, including: obtaining sensor data about N frames of a vehicle through a sliding window, N being a positive integer; creating a target function for a factor graph model in accordance with the sensor data about the N frames, and performing optimization solution on the target function; and determining a pose and a position of the vehicle in accordance with a target value obtained through the optimization solution on the target function.

Abstract: The present disclosure provides a method, an apparatus, a computer device and a computer-readable storage medium for positioning, and relates to the field of autonomous driving. The method obtains inertial measurement data of a device to be positioned at a current time and point cloud data collected by a LiDAR on the device at the current time; determines, by integrating the inertial measurement data, inertial positioning information of the device in an inertial coordinate system at the current time; and determines, based on the inertial positioning information, the point cloud data and at least one local map built in a local coordinate system, a positioning result of the device in the local coordinate system at the current time. Techniques of the present disclosure can provide an effective and stable local positioning result.

Abstract: A method, including: acquiring a point cloud frame including point cloud data of a pedestrian; projecting the point cloud data of the pedestrian to a ground coordinate system to obtain projection point data of the pedestrian; determining a direction of a connection line between the two shoulders of the pedestrian, based on a location distribution of the projection point data; extracting a point cloud of a stable region from the point cloud data of the pedestrian based on the direction of the connection line between the two shoulders of the pedestrian, a form change range of the stable region when the pedestrian moves being smaller than form change ranges of other regions of the pedestrian; and determining movement information of the pedestrian based on a coordinate of a center point of the point cloud of the stable region in a plurality of consecutive point cloud frames.

Abstract: The embodiments provide a method for unmanned vehicle cruising, an unmanned vehicle and a storage medium, the method includes: in a state that a slow cruising function is started, cruising according to a preset cruising mode, and collecting running data through a sensing device, where the running data is data of an environment in which a vehicle locates, collected by the vehicle during a running process; and generating a map based on the collected running data. The embodiments of the present disclosure solve the problem that an unmanned vehicle in the prior art cannot update a map in time and, in particular, cannot develop a more suitable map according to different surrounding environments.

Abstract: The method comprises: creating a 3D scenario model of a calibration scenario, based on data of the calibration scenario collected by an already-calibrated 3D scanner; obtaining point cloud data collected by a to-be-calibrated multi-line laser radar at a plurality of position points in the calibration scenario respectively; aligning the point cloud data collected by the multi-line laser radar at the respective point points and point cloud data in the 3D scenario model into the same coordinate system on a principle that the respective position points are aligned with corresponding position points in the 3D scenario model; building a target function between data of points collected by the multi-line laser radar and data of matching points nearest to the points in the 3D scenario model, under the same coordinate system; calibrating the parameters of the multi-line laser radar according to the target function.

Abstract: Embodiments of the present disclosure provide a method, an apparatus and a device for an illegal vehicle warning. The method includes: detecting an illegal vehicle in a preset area; and performing the illegal vehicle warning on a target vehicle entering the preset area according to vehicle information of a detected illegal vehicle in the preset area. In the embodiments of the present disclosure, the traffic control unit detects the illegal vehicle in the preset area, and the illegal vehicle warning is performed on the target vehicle entering the preset area according to the vehicle information of the detected illegal vehicle in the preset area, thereby avoiding or mitigating the collision of the target vehicle with the illegal vehicle, and improving the traffic safety of the target vehicle.

Abstract: A method, apparatus and storage medium for implementing a discrete frame-based scene section are disclosed. The method comprises: obtaining at least one first tag for mapping a discrete frame to a scene section; for any second tag in the at least one first tag, performing polling query on to-be-processed first discrete frames respectively to determine whether there is a second discrete frame matched with the second tag in the first discrete frames; if there is the second discrete frame, marking the second discrete frame with the second tag corresponding to a scene section; if the polling query corresponding to the second tag ends, storing start frame timestamp information and end frame timestamp information of the scene section.

Abstract: A method and apparatus for determining a turn-round path of a vehicle, a device and a storage medium are provided. An embodiment of the method includes: determining a starting position and a target position for the vehicle to turn round on a road; determining, based at least partially on road information associated with the road and vehicle information associated with the vehicle, a candidate turn-round path between the starting position and the target position; evaluating the feasibility of the candidate turn-round path; and determining, based on the evaluation on the feasibility, a turn-round path by which the vehicle is to turn round on the road.

Abstract: A method for three-dimensional modeling. The method may include: acquiring coordinate points of obstacles in a surrounding environment of an autonomous driving vehicle in a vehicle coordinate system; determining a position of eyes of a passenger in the autonomous driving vehicle, and establishing an eye coordinate system using the position of the eyes as a coordinate origin; converting the coordinate points of the obstacles in the vehicle coordinate system to coordinate points in the eye coordinate system, and determining a visualization distance between the obstacles in the surrounding environment based on an observation angle of the eyes; and performing three-dimensional modeling of the surrounding environment, based on visualization distance between the coordinate points of the obstacles in the eye coordinate system and the obstacles.