Laser radar driving environmental recognition system based on visual area guidance

Patent metadata

Field	Value
Publication number	US-12411238-B2
Application number	US-202218546090-A
Country	US
Kind code	B2
Filing date	Dec 2, 2022
Priority date	Aug 26, 2022
Publication date	Sep 9, 2025
Grant date	Sep 9, 2025

Abstract

Embodiments of the present disclosure provide a laser radar driving environmental recognition system based on visual area guidance, including a visual system, a laser radar system, a data processing module and a vehicle action control module. The data processing module includes: a streaming media analysis module; a key target spherical coordinate data processing module; a key target three-dimensional trajectory prediction module, wherein the laser radar system is configured for measuring real distances of the key targets, and outputting real spherical coordinates of key targets to the key target three-dimensional trajectory prediction module, the key target three-dimensional trajectory prediction module being configured for generating real-time trajectory prediction data of key targets, and outputting the real-time trajectory prediction data of key targets to the vehicle action control module. The laser radar driving environmental recognition system can achieve accurate measurement of key targets and prediction of movement trajectories.

First claim

What is claimed is:

1. A laser radar driving environmental recognition system based on visual area guidance, comprising a visual system, a laser radar system, a data processor and a vehicle action control processor ( 6 ), wherein the data processor comprises:
a streaming media analysis processor ( 2 ), configured for analyzing and processing streaming media data of a vehicle driving environment sampled by the visual system, to classify and determine moving objects and stationary objects in the vehicle driving environment, and mark the moving objects as key targets and output spherical coordinates of key targets, the streaming media analysis processor ( 2 ) being configured for outputting data of the stationary objects to the vehicle action control processor ( 6 );
a key target spherical coordinate data processor ( 3 ), configured for analyzing and processing spherical coordinate data of key targets output by the streaming media analysis processor ( 2 ), and outputting azimuth coordinates in the processed spherical coordinates of key targets to the laser radar system;
a key target three-dimensional trajectory prediction processor ( 5 ), wherein the laser radar system is configured for measuring real distances of the key targets, and outputting real spherical coordinates of key targets to the key target three-dimensional trajectory prediction processor ( 5 ), the key target three-dimensional trajectory prediction processor ( 5 ) being configured for generating real-time trajectory prediction data of key targets, and outputting the real-time trajectory prediction data of key targets to the vehicle action control processor ( 6 ),
wherein the laser radar driving environmental recognition system is configured for implementing driving environmental recognition and feedback in such a method, the method comprising:
step a: sampling environmental streaming media of a vehicle driving environment through the visual system;
step b: sending by the visual system the sampled environmental streaming media data to the streaming media analysis processor ( 2 ), and analyzing and processing by the streaming media analysis processor ( 2 ) the environmental streaming media data sampled by the visual system to classify and determine moving objects and stationary objects in the vehicle driving environment, and mark the moving objects as key targets and output spherical coordinates of key targets;
outputting stationary object data of the streaming media analysis processor ( 2 ) to the vehicle action control processor ( 6 ), so that the vehicle action control processor ( 6 ) is capable of controlling driving status of vehicle according to the stationary object information;
meanwhile, outputting by the streaming media analysis processor ( 2 ) the spherical coordinate data of key targets to the key target spherical coordinate data processing processor ( 3 );
step c: analyzing and processing by the key target spherical coordinate data processing processor ( 3 ) the spherical coordinates of key targets, and inputting azimuth coordinates in the processed spherical coordinates of key targets to the laser radar system;
step d: accurately measuring by the laser radar system the real distance of the key targets, and outputting the real spherical coordinates of key targets to the key target three-dimensional trajectory prediction processor ( 5 );
step e: generating by the key target three-dimensional trajectory prediction processor ( 5 ) the real-time trajectory prediction data of key targets according to the real spherical coordinate data of key targets;
step f: outputting by the key target three-dimensional trajectory prediction processor ( 5 ) the real-time trajectory prediction data of key targets to the vehicle action control processor ( 6 ), so that the vehicle action control processor ( 6 ) is capable of controlling driving status of a first vehicle according to moving object information,
wherein in the step b, during determining the spherical coordinates of key targets by the streaming media analysis processor ( 2 ), the streaming media analysis processor ( 2 ) performs real-time processing of the streaming media data of the vehicle driving environment sampled by the visual system in a form of streaming media, and determines the spherical coordinates (r′, θ, φ) of key targets with a fixed camera coordinate positioning method, where θ and φ are definite values respectively, and r′ is a value to be corrected;
wherein in the step d, during measuring the real spherical coordinates of key targets by the laser radar system, the laser radar system performs vector control on the laser through electro-optic effect, to detect corrected spherical coordinates (r, θ, φ) of key targets, and then obtains the real spherical coordinates of key targets.

2. The laser radar driving environmental recognition system based on visual area guidance according to claim 1 , wherein in the step d, in case of a driving vehicle as one of the key targets, the laser radar system is configured to select four measuring points of the driving vehicle to measure distances, wherein the laser radar system accurately measures real distances of the above four measuring points of the driving vehicle, and outputs real spherical coordinates of the above four measuring points of the driving vehicle to the key target three-dimensional trajectory prediction processor ( 5 ), wherein two measuring points form a measuring point group and the above four measuring points form two measuring point groups; wherein,
for the driving vehicle traveling in the same direction and located in the left front relative to the first vehicle, the above four measuring points are a right front wheel, a right rear wheel, a left rear light, and a right rear light of the driving vehicle, wherein the measuring point of right front wheel and the measuring point of right rear wheel form a measuring point group, and the measuring point of left rear light and the measuring point of right rear light form a measuring point group;
for the driving vehicle traveling in the same direction and located in the right front relative to the first vehicle, the above four measuring points are a left front wheel, a left rear wheel, a left rear light, and a right rear light of the driving vehicle, wherein the measuring point of left front wheel and the measuring point of left rear wheel form a measuring point group, and the measuring point of left rear light and the measuring point of right rear light form a measuring point group;
for the driving vehicle traveling in the same direction and located in the left rear relative to the first vehicle, the above four measuring points are a right front wheel, a right rear wheel, a left front light, and a right front light of the driving vehicle, wherein the measuring point of right front wheel and the measuring point of right rear wheel form a measuring point group, and the measuring point of left front light and the measuring point of right front light form a measuring point group;
for the driving vehicle traveling in the same direction and located in the right rear relative to the first vehicle, the above four measuring points are a left front wheel, a left rear wheel, a left front light, and a right front light of the driving vehicle, wherein the measuring point of left front wheel and the measuring point of left rear wheel form a measuring point group, and the measuring point of left front light and the measuring point of right front light form a measuring point group;
for the driving vehicle traveling in the same direction and located directly in front relative to the first vehicle, the above four measuring points are a left rear wheel, a right rear wheel, a left rear light, and a right rear light of the driving vehicle, wherein the measuring point of left rear wheel and the measuring point of right rear wheel form a measuring point group, and the meas

Assignees

• Univ Dongguan Technology

Inventors

• Di bo
• Zhang Lifei
• Zheng Yu
• Qin Renyuan
• Ma Hongwei

Classifications

• G01S17/58

  Velocity or trajectory determination systems; Sense-of-movement determination systems · CPC title

• G01S7/4808 Primary

  Evaluating distance, position or velocity data · CPC title

• G01S17/86 Primary

  Combinations of lidar systems with systems other than lidar, radar or sonar, e.g. with direction finders · CPC title

• G01S17/931

  of land vehicles · CPC title

• G01S17/42 Primary

  Simultaneous measurement of distance and other co-ordinates (indirect measurement G01S17/46) · CPC title