Abstract: The present disclosure provides a method and apparatus for determining an attribute value of an obstacle in vehicle infrastructure cooperation. The method includes: acquiring vehicle-end data collected by at least one sensor of an autonomous driving vehicle; acquiring vehicle wireless communication V2X data transmitted by a roadside device; and fusing, in response to determining that an obstacle is at an edge of a blind spot of the autonomous driving vehicle, the vehicle-end data and the V2X data to obtain an attribute estimated value of the obstacle.

Abstract: A method and apparatus for calibrating a camera are provided. A specific embodiment of the method includes: acquiring an image-point cloud sequence, the image-point cloud sequence including at least one group of an initial image and point cloud data collected at a same time, the initial image being collected by a camera provided on an autonomous vehicle and the point cloud data being collected by a radar provided on the autonomous vehicle; determining target point cloud data of initial images corresponding to groups of image-point cloud in the image-point cloud sequence; and matching the target point cloud data with the corresponding initial images in the image-point cloud sequence to determine a correction parameter of the camera.

Abstract: A vehicle performance evaluation method, device and terminal are provided. The method includes: acquiring a labeled ADE score of an ADE item within a time period in which the ADE item occurs, and recording labeled data of an ADE index for indicating a vehicle state; acquiring a correlation between the ADE item and the vehicle state, according to the labeled ADE score and the labeled data of the ADE index; acquiring data of a target ADE index within a preset time period, and acquiring a target ADE score according to the data of the target ADE index and a correlation between the ADE item and the vehicle state; and acquiring a vehicle performance evaluation result according to the target ADE score. The passenger participation is not necessary, costs can be reduced and a vehicle evaluation efficiency can be improved.

Abstract: A blacklist-based re-navigation method and apparatus, and a computer readable storage medium are provided. The blacklist-based re-navigation method includes: detecting whether an obstacle is in a front area of a driverless vehicle in a driving process of the driverless vehicle; if an obstacle is detected in the front area, generating a blacklist associated with the obstacle, wherein the blacklist includes a road on which the obstacle is located; and reporting the blacklist to a navigation system, wherein the navigation system re-plans a navigation route according to the road on which the obstacle is located.

Abstract: A ranging method based on a laser radar system, a device and a readable storage medium are provided. The ranging method includes receiving ranging data obtained by measuring via a plurality of laser radars of a laser radar system, where the ranging data includes distances between the laser radars and obstacles in measurement ranges of the laser radars; establishing a three-dimensional coordinate model according to the ranging data; and determining a distance between a target unmanned device and each obstacle according to the three-dimensional coordinate model. The ranging method can realize a ranging calibration task for a larger distance range, thereby effectively improving a calibration efficiency and accuracy of the visual image algorithm, compared with the existing method of ranging calibration of the visual image algorithm by a single laser radar.

Abstract: Embodiments of the present disclosure disclose a method and apparatus for avoidance control of a vehicle, an electronic device, and a storage medium, where the method includes: obtaining behavior information of a moving obstacle, where the moving obstacle is located in a direction of movement of the vehicle and a distance between the moving obstacle and the vehicle satisfies a preset avoidance distance; determining an avoidance strategy for the vehicle based on the behavior information of the moving obstacle; and controlling movement of the vehicle based on the avoidance strategy. The method in the embodiments of the present disclosure considers the behavior information of the moving obstacle in the process of avoidance control of the vehicle, and the vehicle can be controlled to travel when the moving obstacle takes an avoidance action, thereby improving the accuracy of avoidance for the vehicle and the practicality of intelligent driving.

Abstract: Disclosed are high-precision-map data collection methods, devices and storage mediums, which relate to the field of computer technologies, and particularly to the fields of big data technologies, autonomous driving technologies, intelligent transportation technologies, or the like. The data collection method includes: receiving a collection task generated by a server, where the collection task includes to-be-collected track points; generating a navigation path based on the to-be-collected track points, and displaying the navigation path; and acquiring map data collected at the to-be-collected track points when a vehicle travels based on the navigation path.

Abstract: This disclosure provides a device environment identification method, a device environment identification apparatus, an electronic device and an autonomous vehicle, and relates to the field of artificial intelligence, in particular to the field of autonomous driving technology, sensor technology, etc. The method includes: obtaining data collected by a sensor of a device from an environment where the device is located; extracting feature information from the collected data; and generating an identification result of the environment in accordance with the feature information, the identification result being used for indicating a corresponding relationship between the environment and calibration of the sensor.

Abstract: A method, an apparatus, a storage medium, and an electronic device for testing dynamic parameter of vehicle are provided. The method for testing dynamic parameter of vehicle provided by the present disclosure includes: first obtaining a control parameter for an autonomous vehicle; then controlling the vehicle to travel automatically under a given environment according to the control parameter, detecting and recording traveling data of the vehicle; and at last determining a dynamic parameter of the vehicle according to the traveling data. According to the method for testing dynamic parameter provided by the present disclosure, the characteristic of automatic driving of an autonomous vehicle is utilized to achieve an automatic measurement of the dynamic parameter, thereby reducing cost for calibrating the vehicle and significantly improving safety during the test. Additionally, human error caused by manually driving during the test can be avoided effectively.

Abstract: Embodiments of the present disclosure provide a method and an apparatus for controlling a vehicle, a device and a storage medium. The method includes: in response to determining that a target vehicle is located in a historical takeover area, obtaining historical control information associated with passing through a historical path in the historical takeover area, the historical takeover area indicating an area through which a vehicle in a manual control state passed in a previous period; determining a planned path for the target vehicle to pass through the historical takeover area based on the historical control information; and controlling the target vehicle to pass through the historical takeover area in an automatic control state based on the planned path.

Abstract: Embodiments of the present disclosure relate to a method and apparatus for generating information. The method can include: acquiring first driving environment data of a target road segment; comparing the first driving environment data with pre-stored second driving environment data of the target road segment, and determining a difference between the first driving environment data and the second driving environment data; and generating, in response to determining the difference satisfying a preset condition, road abnormality information.

Abstract: A method and an apparatus for generating a high precision map, and a storage medium for generating a high precision map. The method includes: performing a point cloud splicing process on target point cloud data to obtain a lidar pose corresponding to the target point cloud data; projecting the target point cloud data into a preset two-dimensional area based on the lidar pose to generate a map based on a reflection value and a height value; performing a self-positioning verification on the map based on the reflection value and the height value using the target point cloud data; and integrating, if a result of the self-positioning verification satisfies a preset condition, the map based on the reflection value and the height value into a reference map to generate the high precision map.

Abstract: Embodiments of the present disclosure disclose a method for controlling an autonomous vehicle to pass through a curve, a device and a medium, and relate to the field of autonomous driving technologies. At least one implementation of the method for controlling an autonomous vehicle to pass through a curve includes: determining a curve boundary within a sensing area in a current driving direction of the autonomous vehicle based on a current position of the autonomous vehicle on the curve; determining a current safe stopping distance of the autonomous vehicle on the curve based on current driving parameters of the autonomous vehicle and the curve boundary; determining a speed threshold of the autonomous vehicle based on the current safe stopping distance, braking parameters of the autonomous vehicle and a curve curvature corresponding to the current position; and controlling a speed of the autonomous vehicle not to exceed the speed threshold.

Abstract: A method for fusing road data to generate a map, includes: determining benchmark road data and at least one road data to be fused in a target road area; establishing, successively for each road data to be fused, a first road element association relationship between the first sub road data and the benchmark road data; establishing a second road element association relationship between the second sub road data and the benchmark road data according to the first road element association relationship; and fusing the benchmark road data and the road data to be fused according to the above association relationships to update the benchmark road data.

Abstract: Embodiments of the present disclosure provide a method and apparatus for processing positioning data, a device, a storage medium and a vehicle. In the method according to the embodiments of the present disclosure, the vehicle is controlled to collect positioning data continuously in the five stages including a first stage for performing dynamic alignment, a second stage for traveling along a path of a character “8”, a third stage for collecting map data, a fourth stage for traveling along a path of the character “8”, and a fifth stage for performing the dynamic alignment, and processing of error convergence is performed on the positioning data collected in the third stage, according to the positioning data collected in the first stage, the second stage, the fourth stage and the fifth stage, to obtain the final positioning data after the error convergence.

Abstract: The present disclosure provides a method and an apparatus for remotely controlling a self-driving vehicle, including: a control device receives operation state information of the vehicle to be controlled transmitted by the vehicle, and video data and/or audio data of a passenger in the vehicle; determines a first abnormal parameter of the vehicle according to the operation state information of the vehicle; determines a second abnormal parameter of an emotion of the passenger in the vehicle according to the video data and/or audio data of the passenger in the vehicle; and controls the vehicle remotely according to the first abnormal parameter and the second abnormal parameter. It is possible to avoid the situation that the passenger in the vehicle performs a wrong manipulation on the vehicle due to a large emotional fluctuation in an emergency, thus making the control of the vehicle more safe and reliable in the emergency.

Abstract: The present disclosure provides a vehicle travel control method and apparatus. A specific implementation lies in: acquiring a distance between a vehicle and a first intersection, where the first intersection is an intersection for the vehicle to go across on a first road which the vehicle is currently on; acquiring, on a determination that the distance is less than or equal to a preset distance, intersection information of the first intersection and travelling information of the vehicle, where the intersection information includes lane information of at least two lanes on the first road; determining, according to the intersection information and the travelling information, a target weight of each of the lanes for the vehicle to travel into; and determining, according to the target weight of each of the lanes for the vehicle to travel into, an intended travel route of the vehicle.

Abstract: A vehicle controlling method is provided, which may include: determining current vehicle status information, road condition information and environment information of a road on which the vehicle runs according to data collected by vehicle sensors; processing the current vehicle status information, the road condition information and the environment information according to a preset control strategy model to generate a first operating strategy of the vehicle within a preset time period; determining status adjustment modes of executing mechanisms of the vehicle according to the first operating strategy within the preset time period and a current second operating strategy of the vehicle; and adjusting the first operating strategy when the status adjustment mode of at least one executing mechanism does not meet a preset condition.

Abstract: The present disclosure provides a method, an apparatus and a system for processing unmanned vehicle data, and a storage medium, where the method includes: receiving data acquisition indication information sent by a cloud server; obtaining, according to the data acquisition indication information, target data from a data set; and storing the target data, and/or sending the target data to the cloud server, which can thereby achieve acquisition and storage of data meets a preset condition, reduce amount of data storage of the unmanned vehicle and amount of data sent to the cloud server, save network resources, and improve data transmission efficiency.

Abstract: There is provided an obstacle detection method, an electronic device and a storage medium, which relates to the field of computer technologies, and particularly to the fields of autonomous driving technologies, intelligent transportation technologies, Internet of Things technologies, deep learning technologies, or the like. The method for detecting obstacle includes: detecting an obstacle in a vehicle traveling process using plural obstacle detection manners to obtain plural initial detection results of the obstacle, the plural initial detection results corresponding to the plural obstacle detection manners; fusing the plural initial detection results to obtain a fusion result; and obtaining a final detection result of the obstacle based on the fusion result.