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

Beijing Baidu Netcom Science Technology Co., Ltd

Beijing Baidu Netcom Science and Technology Co., Ltd.

Apollo Intelligent Driving Technology (beijing) Co., Ltd.

Qingrui Sun

Fangfang Dong

Chen Yang

Jiming Mao

Dun Luo

Junfei Zhang

Zhuo Chen

Liming Xia

Jingchao Feng

Jing Wang

Pengjie Zheng

Tianxiang Cui

Qian Dou

An image processing method in remote control, a device, an apparatus and a program product are provided and related to the field of automatic driving technologies. The specific implementation solution includes receiving image information sent by a vehicle, wherein the image information includes multiple-channel image data collected by the vehicle; performing a stitching process on the multiple-channel image data, to obtain a stitched image; sending the stitched image to a remote cockpit apparatus for controlling the vehicle.

Image processing method in remote control, device, apparatus and program product

A method for remote control of an autonomous driving vehicle (ADV) includes: sending an assistance request to a cloud server in response to detecting that a current road section in front of the ADV is unable to be passed; obtaining a reference detour route returned from the cloud server; generating control instructions based on the reference detour route and a current driving environment of the ADV; and controlling the ADV based on the control instructions.

Method for remote control of autonomous driving vehicle, autonomous driving vehicle and cloud device

Embodiments of the present disclosure provide a method and an apparatus for generating a simulation scene. The method includes: acquiring scene parameters of a benchmark scene, where a dimensionality of the scene parameters of the benchmark scene is M; inputting the scene parameters of the benchmark scene into an encoder that is trained, and acquiring encoding parameters according to an output result of the encoder, where a dimensionality of the encoding parameters is N, and N<M; adjusting the encoding parameters to obtain adjusted encoding parameters, and inputting respectively the adjusted encoding parameters into a decoder that is trained; and generating a simulation scene according to the scene parameters of the reconstructed scene that are output by the decoder. According to the method, generating massive simulation scenes similar to the benchmark scene based on the benchmark scene can be achieved, which meets the diversity requirements for the simulation scenes.

Method and apparatus for generating simulation scene

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.

Method, apparatus, device and medium for classifying driving scenario data

Embodiments of the present disclosure provide a method and an apparatus for generating a simulation scene. The method includes: acquiring scene parameters of a benchmark scene, where a dimensionality of the scene parameters of the benchmark scene is M; inputting the scene parameters of the benchmark scene into an encoder that is trained, and acquiring encoding parameters according to an output result of the encoder, where a dimensionality of the encoding parameters is N, and N&#x3c;M; adjusting the encoding parameters to obtain adjusted encoding parameters, and inputting respectively the adjusted encoding parameters into a decoder that is trained; and generating a simulation scene according to the scene parameters of the reconstructed scene that are output by the decoder. According to the method, generating massive simulation scenes similar to the benchmark scene based on the benchmark scene can be achieved, which meets the diversity requirements for the simulation scenes.

The present disclosure provides a method and apparatus for simulation test of autonomous driving of a vehicle, an apparatus and a computer-readable storage medium. In embodiments of the present disclosure, a simulation-activating command is sent to the at least two simulation nodes so that each simulation node in the at least two simulation nodes simulates the designated traffic environment and runs the corresponding vehicle decision planning algorithm, then the vehicle state data and the vehicle decision route of said each simulation node are obtained so that the vehicle state data and the vehicle decision route of said each simulation node can be output. Since a plurality of simulation nodes are employed to simultaneously simulate the designated traffic environment and run the corresponding vehicle decision planning algorithm, it is possible to, in completely the same simulated traffic environment, simultaneously run a plurality of vehicles having the autonomous driving function, and visually compare the vehicle decision planning algorithm run by each simulation node, and thereby perform the check processing for the vehicle decision planning algorithm.

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Beijing, China

Qingrui Sun