Abstract: Embodiments of the present disclosure disclose a parking space detection method and apparatus, an electronic equipment, a vehicle, and a storage medium, which relate to the field of automatic driving technologies and in particular, to the field of autonomous parking, including: collecting ultrasonic information during a moving process of a vehicle, generating a target grid map, performing feature recognition on the target grid map to obtain a line segment, and generating a parking space according to the line segment and the target grid map. By implementing the present disclosure, a disadvantage of a limited range of application in the prior art caused by that the detection of a parking space requires a travelling direction of a vehicle to be parallel with a side of an obstacle and requires the vehicle to be close to the obstacle is avoided, thereby achieving a relatively wide use and improving detection accuracy.

Abstract: The present disclosure provides a route processing method and apparatus. The solution includes: acquiring an initial traveling route, which includes a plurality of track points, corresponding to a vehicle; determining a vehicle traveling area, which includes an area where the vehicle is located when traveling to the track point, corresponding to each track point; determining at least one target track point in the plurality of track points according to the vehicle traveling area, where a first obstacle exists in the vehicle traveling area; performing updating processing on a position of each target track point in the initial traveling route respectively according to the position of the each target track point and a position of the first obstacle, and obtaining a target traveling route according to the target track point for which the updating processing has been performed; and controlling the vehicle to travel according to the target traveling route.

Abstract: Embodiments of the present disclosure disclose a parking space detection method and apparatus, an electronic equipment, a vehicle, and a storage medium, which relate to the field of automatic driving technologies and in particular, to the field of autonomous parking, including: collecting ultrasonic information during a moving process of a vehicle, generating a target grid map, performing feature recognition on the target grid map to obtain a line segment, and generating a parking space according to the line segment and the target grid map. By implementing the present disclosure, a disadvantage of a limited range of application in the prior art caused by that the detection of a parking space requires a travelling direction of a vehicle to be parallel with a side of an obstacle and requires the vehicle to be close to the obstacle is avoided, thereby achieving a relatively wide use and improving detection accuracy.

Abstract: Method, device, and non-transitory storage medium to obtain program historical data and social network data associated with users that receive one or more programs via one or more channels; calculate a social similarity value; calculate a channel-interest similarity value; calculate a similarity index value based on the social similarity value and the channel-interest similarity value; calculate a program weight value for each program; calculate a stay-time, for each channel, that indicates a time period each of the users remained on each channel; calculate based on each program weight value, each stay-time, and each similarity index value, a channel weight for each channel; and select based on each channel weight, one or more channels to recommend to at least one of the users.

Abstract: A server is configured to receive a request for content from a user of a user device. The server is configured further to obtain a group of bookmarks for the content, the group of bookmarks being obtained based on at least one of viewing behavior of the user or viewing behavior of another user. The server is configured further to provide the content and the group of bookmarks to the user.

Abstract: Method, device, and non-transitory storage medium to obtain program historical data and social network data associated with users that receive one or more programs via one or more channels; calculate a social similarity value; calculate a channel-interest similarity value; calculate a similarity index value based on the social similarity value and the channel-interest similarity value; calculate a program weight value for each program; calculate a stay-time, for each channel, that indicates a time period each of the users remained on each channel; calculate based on each program weight value, each stay-time, and each similarity index value, a channel weight for each channel; and select based on each channel weight, one or more channels to recommend to at least one of the users.

Abstract: A server is configured to receive a request for content from a user of a user device. The server is configured further to obtain a group of bookmarks for the content, the group of bookmarks being obtained based on at least one of viewing behavior of the user or viewing behavior of another user. The server is configured further to provide the content and the group of bookmarks to the user.