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

Baidu USA LLC

Baidu.com Times Technology (beijing) Co. Ltd.

Hongye Li

Zhenguang Zhu

Zhongpu Xia

Xiaoxin Fu

Fan Zhu

Guang Yu Yang

Jingao Wang

Qi Luo

Qi Kong

Yuchang Pan

Xiang Yu

Sen Hu

Chunming Zhao

Jiarui He

Kuan Zhang

Huaizhu Tang

Yifeng Pan

Dayang Hao

Yaqin Chen

Guang Yang

The present application provides a method and apparatus for planning an autonomous vehicle, an electronic device and a storage medium, which relates to the field of autonomous driving. According to the technical solutions of the present application, time points of entering a vehicle-converging area can be accurately predicted according to traveling conditions of two parties, so that a driving behavior of the autonomous vehicle is controlled more accurately. The specific implementation is as follows: acquiring first traveling information of an autonomous vehicle; acquiring second traveling information of at least one obstacle vehicle; predicting a driving intention of the obstacle vehicle according to the acquired second traveling information of the obstacle vehicle; planning a vehicle-converging strategy for the autonomous vehicle according to the first traveling information and the driving intention of the obstacle vehicle; and controlling the autonomous vehicle to travel according to the vehicle-converging strategy.

Method and apparatus for planning autonomous vehicle, electronic device and storage medium

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.

Blacklist-based re-navigation method and apparatus, and storage medium

A decision method, device, equipment in a lane changing process and storage medium are provided. The method includes: acquiring a first planned track of a driverless vehicle for travelling to a first lane and a second planned track of the driverless vehicle for travelling to a second lane within a preset time period, in a lane changing process of the driverless vehicle; predicting a predicted track of at least one obstacle within the preset time period according to a travelling state of the obstacle, wherein the obstacle is in a preset range around the driverless vehicle; and determining a travelling motion of the driverless vehicle according to the first planned track, the second planned track and the predicted track of the obstacle.

Decision method, device, equipment in a lane changing process and storage medium

A lane changing method, device for a driverless vehicle and a computer-readable storage medium are provided. The lane changing method includes: determining candidate lanes, to which a lane changing is to be performed, based on a travelling intention of a main vehicle; screening the candidate lanes based on lane changing conditions of the candidate lanes; selecting, from the screened candidate lanes, a target lane, to which the lane changing of the main vehicle is to be performed; determining whether the lane changing of the main vehicle from a current lane to the target lane is safe; and performing the lane changing, if the lane changing is determined to be safe.

Lane changing method, device for driverless vehicle and computer-readable storage medium

A lane departure detection system detects that an autonomous driving vehicle (ADV) is departing from the lane in which the ADV is driving based on sensor data captured when the ADV contact a deceleration curb such as a speed bump laid across the lane. When the ADV contacts the deceleration curb, the lane departure detection system detects and calculates an angle of a moving direction of the ADV vs a longitudinal direction of the deceleration curb. Based on the angle, the system calculates how much the moving direction of the ADV is off compared to a lane direction of the lane. The lane direction is typically substantially perpendicular to the longitudinal direction of the deceleration curb. A control command such as a speed control command and/or a steering control command is generated based on the angle to correct the moving direction of the ADV.

Deceleration curb-based direction checking and lane keeping system for autonomous driving vehicles

In one embodiment, when an ADV is driving on a road segment, a driving parameter is recorded in response to a first control command. A difference between the first driving parameter and a target driving parameter corresponding to the first control command is determined. In response to determining that the difference exceeds a predetermined threshold, a second control command is issued to compensate the difference and cause the ADV to drive with a second driving parameter closer to the target driving parameter. A slope status of the road segment is derived based on at least the second control command. Map data of a map corresponding to the road segment of the road is updated based on the derived slope status. The updated map can be utilized to generate and issue proper control commands in view of the slope status of the road when the ADV drives on the same road subsequently.

Method and system for updating maps based on control feedbacks of autonomous driving vehicles

In one embodiment, a lane departure detection system detects at a first point in time that a wheel of an ADV rolls onto a lane curb disposed on an edge of a lane in which the ADV is moving. The system detects at a second point in time that the wheel of the ADV rolls off the lane curb of the lane. The system calculates an angle between a moving direction of the ADV and a lane direction of the lane based on the time difference between the first point in time and the second point in time in view of a current speed of the ADV. The system then generates a control command based on the angle to adjust the moving direction of the ADV in order to prevent the ADV from further drifting off the lane direction of the lane.

Lane curb assisted off-lane checking and lane keeping system for autonomous driving vehicles

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Beijing, China

Hongye Li