Beijing Baidu Netcom Science Technology Co., Ltd

Baidu Online Network Technology (beijing) Co., Ltd.

Beijing Baidu Netcom Science and Technology Co., Ltd.

Netcom Science Technology Co., Ltd.

Baidu Online Network Technology Co., Ltd.

Deguo Xia

Jizhou Huang

Haifeng Wang

Hui Zhao

Zhen Lu

Liuhui Zhang

Yuting Liu

Jianzhong Yang

Kai Zhong

Hongxia Bai

Tianyu Zhang

Xiaoqing Ye

Man Li

Jinyi Lei

Zhuang Li

Junjie Cai

Hailu Jia

Tongbin Zhang

Chengzhou Li

Jinggang Li

Tingting Cao

Dejin Ge

Keyu Pan

Wenwen Yu

A method and apparatus for processing an image. The method may include: acquiring a top view of a road; identifying a position of a lane line from the top view; cutting the top view into at least two areas, and determining, according to the position of the lane line in each area, a width of a lane in the each area and an average width of the lane in the top view; calculating a first perspective correction matrix by optimizing a first loss function, the first loss function being used to represent a difference between the width of the lane in the each area and the average width of the lane in the top view; and performing a lateral correction on the top view through the first perspective correction matrix to obtain a first corrected image.

Method and apparatus for correcting perspective of road image

Provided are a road network extraction method, a device, and a storage medium, which relate to the technical field of artificial intelligence and, in particular, to the fields of image processing, computer vision, and the like and are specifically applicable to scenarios such as intelligent transportation and a smart city. A specific implementation scheme includes: extracting a first road network of a target region according to user trajectories of the target region; extracting a second road network of the target region according to a satellite aerial image of the target region; and extract a target road network of the target region according to the first road network, the second road network, and the user trajectories. Efficient and accurate road network extraction can be achieved through techniques in embodiments of the present disclosure.

Road network extraction method, device, and storage medium

A method of updating map data, an electronic device, and a storage medium, which relate to a field of computer technology, and in particular to intelligent transportation technology. The method of updating map data includes: acquiring a traffic event text, where the traffic event text includes location data and reference direction data; determining candidate road data in the map data based on the location data; determining target road data from the candidate road data based on the reference direction data; updating the target road data based on the traffic event text.

Method of updating map data, electronic device and storage medium

A method and an apparatus for generation a high definition map, a device and a computer storage medium, which relate to automatic driving and deep learning technologies in the field of artificial intelligence technologies, are disclosed. An implementation includes: acquiring point cloud data and front-view image data which are collected respectively by a plurality of collecting devices at a plurality of location points to obtain a sequence of point clouds and a sequence of front-view images; performing registration of the front-view images and the point clouds on the sequence of point clouds and the sequence of front-view images; transforming the sequence of front-view images into a top-view image based on the result of the registration and determining coordinate information of each pixel in the top-view image; and identifying map elements of the top-view image to obtain the high definition map.

Method for generating high definition map, device and computer storage medium

The present disclosure provides a method and apparatus for automatically producing map data. The method includes: performing track rectification on crowdsourcing tracks based on corresponding standard tracks, and locating each map element included, based on depth information of track point images included in the rectified crowdsourcing tracks; comparing a latest map element obtained based on the rectified crowdsourcing tracks locating and an old map element at a corresponding locating position using a pre-built entity semantic map; determining, in response to a change in the latest map element compared to the old map element, a target processing method according to a processing standard of a changed map element pre-abstracted from a map element update specification; and processing the latest map element according to the target processing method to obtain a processed latest map.

Method for automatically producing map data, and related apparatus

A vehicle control method and apparatus, a device and a computer storage medium are disclosed, which relates to the technical fields of autonomous driving and intelligent transportation. A specific implementation solution involves: determining vehicles in a preset geo-fencing region; determining a vehicle weight of each said vehicles according to a vehicle type and a waiting duration of each said vehicles; estimating, according to the vehicle weights of the vehicles in each of lanes in the geo-fencing region and positions of the vehicles in each said lanes, a duration to be waited in each said lanes; and generating a control instruction for each said vehicles according to the respective durations to be waited in each said lanes and the respective positions of the vehicles in each said lanes, the control instruction including a state instruction and/or a target speed instruction.

Vehicle control method and apparatus, device and computer storage medium

The present application discloses a method and apparatus for identifying an updated road, a device and a computer storage medium, and relates to the field of big data technologies. A specific implementation solution is as follows: comparing a road area extracted based on the latest satellite image with a road area extracted based on a historical satellite image, to obtain a candidate updated road; mapping the candidate updated road into road network data according to a coordinate position of the candidate updated road; acquiring a user trajectory set corresponding to the candidate updated road within a recent preset period; and identifying, based on a matching result between the user trajectory set and the road network data, whether the candidate updated road is an actual updated road. Updated roads can be more accurately identified through the method according to the present application.

Method and apparatus for identifying updated road, device and computer storage medium

The present disclosure provides a method and apparatus of estimating a road condition, and a method and apparatus of establishing a road condition estimation model, which relates to a field of big data and intelligent traffic. The method includes: acquiring, for a first preset duration before a first moment, a sequence of user tracks for a road and a sequence of road images for the road; extracting a track-related feature of the road from the sequence of the user tracks, and extracting an image-related feature of the road from the sequence of the road images; and inputting the track-related feature of the road and the image-related feature of the road into a pre-trained road condition estimation model, so as to determine, for a second preset duration after the first moment, a road condition information of the road by using an estimated result of the road condition estimation model.

Method and apparatus of estimating road condition, and method and apparatus of establishing road condition estimation model

The present application discloses a map data updating method, an apparatus, a device and a readable storage medium. The specific implementation solution is: after receiving road information reported by an electronic device, a server obtains multiple sequences according to the road information, and each road information belonging to the same sequence has the same type and location. After that, the server inputs each road information contained in the sequences to a pre-trained neural network model, so that the neural network model outputs a recognition result according to the sequences. The server updates map data according to the recognition result. With such solution, valid road information is recognized by combining context of each road information in the sequences and the neural network technology, and the map data is updated, which achieves the purpose of accurately updating the map data.

Map data updating method, apparatus, device, and readable storage medium

The present disclosure discloses a navigation method, a device, and a medium. The method includes: planning candidate routes based on a start position and an end position of a user, and obtaining a sequence of candidate road sections in each candidate route; matching each candidate road section in the sequence of candidate road sections in each candidate route with an association relationship between an actual road section and actual road auxiliary information, to obtain a sequence of auxiliary information of each candidate route; and sorting the auxiliary information in the sequence of auxiliary information of each candidate route to obtain a sorted result corresponding each candidate route, and selecting target road auxiliary information from the sequence of auxiliary information of each candidate route based on the sorted result, so as to select a target route from the candidate routes based on the target road auxiliary information.

Navigation method and apparatus based on electronic map, device and medium

The present disclosure discloses a method, apparatus and electronic device for early-warning, relates to the field of internet of vehicle and used for an intelligent traffic scenario. The specific implementations are: determining a target object crossing a road at a current moment, the road crossed by the target object being a first road; determining a target area based on a location of the target object; determining a target vehicle on the first road based on locations of vehicles on the first road as well as the target area; and sending an early-warning message to the target vehicle. It is using the locations of vehicles on the first road as well as the location of the target object crossing the road to determine the target vehicle during determination of the target vehicle among the vehicles on the first road, in order to send early-warning message to the target vehicle to achieve early-warning of the target vehicle and increase precision of the early-warning.

Method, apparatus and electronic device for early-warning

A method and an apparatus for visual positioning based on mobile edge computing are provided. In the method, the mobile edge computing node receives an environment image captured by a to-be-positioned device in an area covered by the mobile edge computing node; the mobile edge computing node determines a target image matching the environment image from multiple candidate images, and calculates the position and pose information of the to-be-positioned device based on the position and pose information of the device for capturing the target image; and the mobile edge computing node sends the position and pose information of the to-be-positioned device to the to-be-positioned device, so that the to-be-positioned device determines the positioning information in an electronic map according to the position and pose information.

Growing community of inventors

Beijing, China

Deguo Xia