NL2028206B1 - Automatic tracking control system for low-speed electric vehicle - Google Patents

Automatic tracking control system for low-speed electric vehicle Download PDF

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Publication number
NL2028206B1
NL2028206B1 NL2028206A NL2028206A NL2028206B1 NL 2028206 B1 NL2028206 B1 NL 2028206B1 NL 2028206 A NL2028206 A NL 2028206A NL 2028206 A NL2028206 A NL 2028206A NL 2028206 B1 NL2028206 B1 NL 2028206B1
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electric vehicle
module
differential gps
lane
planned route
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NL2028206A
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Dutch (nl)
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NL2028206A (en
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Xie Dong
Wang Xuanyao
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Univ Anhui Sci & Technology
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/005—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 with correlation of navigation data from several sources, e.g. map or contour matching
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
    • B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
    • B60W30/095—Predicting travel path or likelihood of collision
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/02—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to ambient conditions
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W60/00—Drive control systems specially adapted for autonomous road vehicles
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W60/00—Drive control systems specially adapted for autonomous road vehicles
    • B60W60/001—Planning or execution of driving tasks
    • B60W60/0015—Planning or execution of driving tasks specially adapted for safety
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/13—Receivers
    • G01S19/14—Receivers specially adapted for specific applications
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
    • G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/42—Determining position
    • G01S19/48—Determining position by combining or switching between position solutions derived from the satellite radio beacon positioning system and position solutions derived from a further system
    • G01S19/485—Determining position by combining or switching between position solutions derived from the satellite radio beacon positioning system and position solutions derived from a further system whereby the further system is an optical system or imaging system
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
    • G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/53—Determining attitude
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
    • G01S5/16—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using electromagnetic waves other than radio waves
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/77—Processing image or video features in feature spaces; using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
    • G06V10/80—Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level
    • G06V10/809—Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level of classification results, e.g. where the classifiers operate on the same input data
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/50—Context or environment of the image
    • G06V20/56—Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
    • G06V20/58—Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2420/00—Indexing codes relating to the type of sensors based on the principle of their operation
    • B60W2420/40—Photo, light or radio wave sensitive means, e.g. infrared sensors
    • B60W2420/403—Image sensing, e.g. optical camera
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2552/00—Input parameters relating to infrastructure
    • B60W2552/53—Road markings, e.g. lane marker or crosswalk
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2554/00—Input parameters relating to objects
    • B60W2554/20—Static objects
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2554/00—Input parameters relating to objects
    • B60W2554/40—Dynamic objects, e.g. animals, windblown objects
    • B60W2554/402—Type
    • B60W2554/4029—Pedestrians
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2554/00—Input parameters relating to objects
    • B60W2554/60—Traversable objects, e.g. speed bumps or curbs
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2554/00—Input parameters relating to objects
    • B60W2554/80—Spatial relation or speed relative to objects
    • B60W2554/801—Lateral distance
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2556/00—Input parameters relating to data
    • B60W2556/45—External transmission of data to or from the vehicle
    • B60W2556/50—External transmission of data to or from the vehicle of positioning data, e.g. GPS [Global Positioning System] data

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  • Engineering & Computer Science (AREA)
  • Remote Sensing (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Mechanical Engineering (AREA)
  • Transportation (AREA)
  • Theoretical Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Multimedia (AREA)
  • Human Computer Interaction (AREA)
  • Electromagnetism (AREA)
  • Artificial Intelligence (AREA)
  • Health & Medical Sciences (AREA)
  • Software Systems (AREA)
  • Databases & Information Systems (AREA)
  • Evolutionary Computation (AREA)
  • Computing Systems (AREA)
  • Medical Informatics (AREA)
  • General Health & Medical Sciences (AREA)
  • Mathematical Physics (AREA)
  • Control Of Driving Devices And Active Controlling Of Vehicle (AREA)
  • Traffic Control Systems (AREA)

Abstract

The present invention relates to an automatic tracking control system for a low-speed electric vehicle. The system includes a visual recognition module, a differential global positioning system (GPS) module, a coordination control module, and an automatic driving control module. The system performs automatic tracking through a combination of the visual recognition module and the differential GPS module, thereby ensuring tracking accuracy and stability for the vehicle. As coupling between the two modules may cause a negative influence during the control, a coordination control policy is designed to eliminate mutual interference between the two modules, thereby giving play to the advantages of visual tracking and differential GPS tracking.

Description

P100663NL00 AUTOMATIC TRACKING CONTROL SYSTEM FOR LOW-SPEED
ELECTRIC VEHICLE
BACKGROUND Technical Field The present invention relates to the field of automatic driving, and in particular, to an automatic tracking control system for a low-speed electric vehicle. Related Art Nowadays, with technological advancement and rapid change of technologies, automation and intellectualization become the mainstream of modern life and industrial production. In the field of vehicle driving, it has been challenging to free hands of drivers and improve safety and stability of vehicles. Therefore, intelligent driving comes into being, which is to be applied to various fields. In industry, vehicles can work independently without drivers. In transportation, through an Internet of Vehicles technology, digitalization and visualization of a transportation network are achieved, greatly improving production efficiency and traffic efficiency. At present, intelligent driving is developing rapidly, and is mainly achieved in the following manners. In a first manner, intelligent driving is achieved based on a guide rail. Guide rails are laid so that a vehicle body and wheel sets can complete travelling of a fixed route on the guide rails. Alternatively, inductors (such as iron wires, magnetic strips, or the like) are laid along a planned route, and sensors are mounted on a vehicle, so that the vehicle recognizes the travelling route and travels along the route on which the inductive bodies are laid. In such manners, travelling reliability and stability of vehicles are pretty high, and the route is not prone to deviation. However, since the guide rails or the inductors are laid in advance, costs are high, flexibility is poor, and a travelling route of the vehicles can be changed only by laying the route again. In a second manner, intelligent driving is achieved based on visual recognition. A camera disposed at a front of a vehicle captures images, and lane lines and obstacles are recognized by using an image processing module, and a connection is established to an automatic driving control module to achieve automatic tracking and obstacle avoidance. In such a manner, a vehicle travelling route is more flexible and can be used for a wider range of automatic driving, but a correct route cannot be determined from a plurality of routes (for example, at a fork). Moreover, such a manner relies too much on road conditions. Lane lines are blurred and uneasily to recognize as a result of friction or dust deposition after a long time, impeding automatic tracking.
In a third manner, intelligent driving is achieved based on infrared detection, which is also a common method for achieving tracking and obstacle avoidance through infrared sensors. However, disadvantages are unavoidable. Such a manner is significantly affected by an external environment and is prone to interference from other heat sources and light sources.
In a fourth manner, intelligent driving is achieved based on radar detectors, such as a lidar, an ultrasonic radar, or the like. Such a manner has very accurate ranging and positioning capabilities, good concealment, and strong anti-active interference capabilities, but price and costs are prohibitive.
SUMMARY In order to resolve the problems in the prior art, the present invention is intended to provide an automatic tracking control system for a low-speed electric vehicle, which enhances stability of automatic driving through a combination of a visual recognition module and a differential GPS module through coordination control, thereby achieving a good automatic tracking effect.
In order to achieve the above objectives, the present invention provides an automatic tracking control system for a low-speed electric vehicle. The system includes a visual recognition module, a differential global positioning system (GPS) module, a coordination control module, and an automatic driving control module.
The visual recognition module is configured to recognize a lane line of a lane in which the electric vehicle is travelling and an obstacle within a preset range ahead.
The differential GPS module is configured to obtain position coordinates of the electric vehicle to generate a planned route.
The coordination control module is configured to coordinate the visual recognition module and the differential GPS module. The automatic driving control module is connected to the coordination control module to receive a coordination control signal to perform tracking and brake when encountering the obstacle.
Preferably, the visual recognition module includes: a camera disposed in the front of the electric vehicle and configured to capture an image of two lane lines of the lane in which the electric vehicle is located and an image of the obstacle within the preset range ahead; and an image processing unit connected to the camera and configured to process the captured images of the lane lines and the obstacle to obtain a relative position of the electric vehicle in the lane in which the electric vehicle is located as well as obstacle information.
Further, preferably, the obstacle includes a pedestrian, a block of wood, or a block of stone which has a height greater than a minimum chassis height or has a width greater than a safe travelling width, and the obstacle information includes the position and a geometric shape of the obstacle.
Preferably, the differential GPS module includes: two differential GPS receivers longitudinally arranged on a top of the electric vehicle, spaced apart from each other by not less than one meter, and configured to obtain real-time position coordinates and a real-time vehicle posture of the electric vehicle during travelling; and a computing center connected to the differential GPS receivers to receive travelling information of the electric vehicle to generate planned route information in a program.
The planned route information includes planned route coordinates and decoupling points set at a road section with a plurality of routes (for example, at a fork).
Preferably, the coordination control module is connected to an image processing unit and a computing center to receive information about a position of the electric vehicle relative to the lane and the obstacle information which are outputted by the image processing unit and planned route information generated by the computing center, coordinate the visual recognition module and the differential GPS module by using a coordination control algorithm, and output the coordination control signal.
Further, preferably, the coordination control algorithm includes three determination criteria: is an obstacle detected, is a decoupling point detected, and is a distance between the planned route and a center line of the lane less than or equal to Ad. The following three coordination control signals are outputted by the coordination control algorithm: braking; tracking based on a differential GPS; and tracking based on a differential GPS and assisted by the visual recognition module. Preferably, the automatic driving control module includes: a driver 41 configured to control ignition and driving of the electric vehicle 10; a steering gear 42 configured to control steering of the electric vehicle 10; and a brake 43 configured to control the electric vehicle 10 to brake when the obstacle appears within the preset range ahead.
The automatic driving control module is connected to the coordination control module to receive the coordination control signal to control the electric vehicle to brake and travel according to the planned route information, while further, within a specified difference range, deciding to correct a travelling direction of the electric vehicle according to information about a position of the electric vehicle relative to the lane so that the electric vehicle travels along a center line of the lane. The present invention has the following beneficial effects: The visual recognition module is combined with the differential GPS module. The differential GPS module is a main component and the visual recognition module is an auxiliary component, and coupling and decoupling between the two modules are achieved through a coordination control algorithm. Completeness of the automatic tracking 1s achieved by using the differential GPS module, and details of the automatic tracking are corrected in combination of the visual recognition module, greatly giving play to respective advantages, and improving the accuracy and the stability of the automatic tracking.
BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 is a structural block diagram of an automatic tracking control system according to the present invention.
FIG. 2 is an algorithm flowchart of a coordination control module according to the present invention.
FIG. 3 is a schematic diagram of a travelling state of an electric vehicle in operating condition I according to the present invention.
FIG. 4 is a schematic diagram of a travelling state of the electric vehicle in operating condition II according to the present invention. 1: Visual recognition module, 11: Camera, 12: Image processing unit; 2: Differential GPS module, 21: Differential GPS receiver, 22: Computing center; 3: Coordination control module; 5 4: Automatic driving control module, 41: Driver, 42: Steering gear, 43: Brake; 10: Electric vehicle, 13: Lane line.
DETAILED DESCRIPTION The following clearly and completely describes the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Apparently, the described embodiments are some of the embodiments of the present invention rather than all of the embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the disclosed embodiments without creative efforts shall fall within the protection scope of the present invention.
As shown in FIG. 1, the present invention provides an automatic tracking control system for a low-speed electric vehicle. The system includes a visual recognition module 1, a differential GPS module 2, a coordination control module 3, and an automatic driving control module 4.
The visual recognition module includes a camera 11 disposed in the front of the electric vehicle 10 and configured to capture an image of two lane lines 13 of a lane in which the electric vehicle 10 1s located and an image of the obstacle within the preset range ahead; and an image processing unit 12 connected to the camera 11 and configured to process the captured images of the lane lines 13 and the obstacle to obtain a relative position of the electric vehicle in the lane in which the electric vehicle is located as well as obstacle information.
The obstacle includes a pedestrian, a block of wood, or a block of stone which has a height greater than a minimum chassis height or has a width greater than a safe travelling width, and the obstacle information includes the position and a geometric shape of the obstacle.
The differential GPS module 2 includes two differential GPS receivers 21 longitudinally arranged on a top of the electric vehicle 10 and configured to obtain real-time position coordinates and a real-time vehicle posture of the electric vehicle 10 during travelling, where the two receivers are spaced apart from each other by not less than one meter to ensure positioning accuracy; and a computing center 22 connected to the differential GPS receivers 21 to receive travelling information of the electric vehicle to generate planned route information in a program.
The planned route information includes planned route coordinates and decoupling points set at a road section with a plurality of routes (for example, at a fork).
The coordination control module 3 is connected to the image processing unit 12 and the computing center 22 to receive information about a position of the electronic vehicle relative to the lane and the obstacle information which are outputted by the image processing unit 12 and the planned route information generated by the computing center 22, coordinate the visual recognition module 1 and the differential GPS module 2 by using a coordination control algorithm, and output the coordination control signal.
The automatic driving control module 4 includes: a driver 41 configured to control ignition and driving of the electric vehicle 10; a steering gear 42 configured to control steering of the electric vehicle 10; and a brake 43 configured to control the electric vehicle 10 to brake when the obstacle appears within the preset range ahead. Before the electric vehicle 10 performs automatic tracking, the electric vehicle 10 is manually driven to travel on the planned route in advance, the planned route coordinates are collected by using the differential GPS module 2, and the planned route information is generated. The planned route information includes the planned route coordinates and decoupling points set before a road section with a plurality of routes (for example, before a fork).
Since both the visual recognition module and the differential GPS module can direct automatic tracking, a coordination control algorithm is provided for coordinating the two modules.
As shown in FIG. 2, in the embodiments of the present invention, the coordination control algorithm includes three determination criteria: is an obstacle detected, is a decoupling point detected, and is a distance between the planned route and a center line of the lane less than or equal to Ad. The following three coordination control signals are outputted by the coordination control algorithm: braking, tracking based on a differential GPS; and tracking based on a differential GPS and assisted by the visual recognition module.
The coordination control module 3 first detects whether an obstacle appears, then detects a decoupling point, and further detects whether the distance between the planned route and the center line of the lane is less than or equal to Ad.
The coordination control algorithm is described in detail below based on two operating conditions.
Operating condition I: As shown in FIG. 3, the automatic driving control module 4 controls the electric vehicle 10 to travel on a single route, and the coordination control module 3 detects the following information in real time. In order to ensure safety of the automatic tracking, the coordination control module 3 detects in real time whether there is an obstacle, and sends a brake signal if detecting obstacle information, and the automatic driving control module 4 controls the brake 43 to perform brake. If no obstacle information is detected, it is further detected whether there is a decoupling point. Since no decoupling point is set on a single route, it is further detected whether the distance between the planned route and the center line of the lane is less than or equal to Ad. If the distance between the planned route and the center line of the lane is less than or equal to Ad, it means that there is no large deviation between the planned route and the center line of the lane. In this case, the automatic tracking manner is tracking based on a differential GPS and assisted by the visual recognition module. As shown in FIG. 3, at this time, the electric vehicle 10 is travelling according to the planned route, and the distance between the planned route and the center line of the lane is d. If d is less than or equal to Ad, the electric vehicle performs tracking according to the differential GPS under assistance of the visual recognition module, and the automatic driving module 4 controls the driver 41 and the steering gear 42 to correct a travelling direction the electric vehicle 10 to a center line of the lane. If d is greater than Ad, the electric vehicle performs tracking according to the differential GPS.
Operating condition II: As shown in FIG. 4, at this time, there are a plurality of routes ahead the electric vehicle (for example, at a fork), which include a straight route and a turning route. If the visual recognition module is still used to assist automatic driving at this time, the following situations may occur.
(1) The planned route is a straight route, and the electric vehicle travels along the center line of the lane through assistance of the visual recognition module at this time. If the visual recognition module recognizes a turning lane line, the electric vehicle is controlled to steer. However, the coordination control module 3 detects that the distance d between the planned route and the center line of the lane is greater than Ad, indicating that the electric vehicle deviates significantly from the planned route, and therefore the automatic tracking manner is changed to tracking based on the differential GPS to control the electric vehicle to return to the planned route.
(2) The planned route is a turning route. If the visual recognition module recognizes a straight lane line, the electric vehicle is controlled to continue to travel along a straight line. However, the coordination control module 3 detects that the distance d between the planned route and the center line of the lane is greater than Ad, indicating that the electric vehicle deviates significantly from the planned route, and therefore the automatic tracking manner is changed to tracking based on the differential GPS to control the electric vehicle to return to the planned route. Both situations (1) and (2) cause large travelling deviations, resulting in a failure of the electric vehicle to return to the planned route, causing traffic jams and even traffic accidents. Therefore, in order to avoid the above situations, decoupling points are set at a road section with a plurality of routes (for example, at a fork). In this case, if the electric vehicle performs tracking according to the differential GPS under assistance of the visual recognition module, when the electronic vehicle enters the road section at the fork, the coordination control module 3 detects the decoupling point, and cancels the coupling between the differential GPS module and the visual recognition module, and therefore the automatic tracking manner is changed to tracking based on the differential GPS. When the electric vehicle travels out of the road section at the fork, the coordination control module 3 cannot detect the decoupling point, and therefore the automatic tracking manner is the same as that in operating condition I. In addition, when the electric vehicle encounters an obstacle and performs brake, after the obstacle is cleared, the coordination control module 3 does not detect the obstacle, and therefore the automatic driving control module controls the driver 41 to drive the electric vehicle again. The automatic tracking manner is obtained according to the coordination control algorithm. Finally, the following is to be noted. First of all, it should be noted that, in the description of this application, unless otherwise specified and limited, terms "mounted", "coupled", and "connected" should be interpreted in a broad sense, which may be a mechanical connection or an electrical connection, or may be internal communication between two elements, or may be a direct connection. "Up", "down", "left", "right", and the like are merely used for indicating relative positional relationships. When absolute positions of described objects change, relative positional relationships may change.
Secondly, the drawings of the disclosed embodiments of the present invention involve only structures involved in the embodiments of the present disclosure. For other structures, reference may be made to common designs. In case of no conflicts, the same embodiment may be combined with different embodiments of the present invention.
Finally, the foregoing descriptions are merely preferred embodiments of the present disclosure, but are not intended to limit the present disclosure. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present disclosure shall fall within the protection scope of the present disclosure.

Claims (7)

P100663NL00 CONCLUSIESP100663NL00 CONCLUSIONS 1. Automatisch volgcontrolesysteem voor een elektrisch voertuig met lage snelheid, met het kenmerk dat het automatisch volgcontrolesysteem voor een elektrisch voertuig met lage snelheid een visuele herkenningsmodule, een differentiële GPS-module, een gecoördineerde besturingsmodule en een automatische rijbesturingsmodule omvat, waarbij de visuele herkenningsmodule wordt gebruikt om de rijstrooklijn in de rijbaan van het elektrische voertuig en de obstakels in het vooraf ingestelde bereik ervoor te identificeren en de differentiële GPS-module wordt gebruikt om de positiecoördinaten van het elektrische voertuig te verkrijgen en de geplande route te genereren en de gecoördineerde besturingsmodule wordt gebruikt om de visuele herkenningsmodule en de differentiële GPS-module te coördineren en de automatische rijbesturingsmodule verbonden is met de gecoördineerde besturingsmodule om het gecoördineerde besturingssignaal te ontvangen, dat wordt gebruikt voor het rijden volgens het traject en het remmen bij het tegenkomen van obstakels.1. Automatic low-speed electric vehicle tracking control system, characterized in that the automatic low-speed electric vehicle tracking control system includes a visual recognition module, a differential GPS module, a coordinate control module and an automatic driving control module, wherein the visual recognition module is used to identify the lane line in the roadway of the electric vehicle and the obstacles in the preset range for it, and the differential GPS module is used to obtain the position coordinates of the electric vehicle and generate the planned route, and the coordinated control module is used used to coordinate the visual recognition module and the differential GPS module, and the automatic driving control module is connected with the coordinated control module to receive the coordinated control signal, which is used for driving according to the trajectory and h Braking when encountering obstacles. 2. Het systeem volgens conclusie 1, met het kenmerk dat de visuele herkenningsmodule de volgende elementen omvat: Een camera, geplaatst aan de voorkant van het elektrische voertuig, wordt gebruikt om het beeld vast te leggen van de twee rijstrooklijnen op de rijstrook waar het elektrische voertuig zich bevindt en de obstakels in het vooraf ingestelde bereik ervoor; Een beeldverwerkingseenheid, verbonden met de camera, wordt gebruikt om de vastgelegde beelden van rijstrooklijnen en obstakels te verwerken en de relatieve positie in de rijstrook te verkrijgen waar het elektrische voertuig zich bevindt, naast informatie over obstakels.The system according to claim 1, characterized in that the visual recognition module comprises the following elements: A camera, placed at the front of the electric vehicle, is used to capture the image of the two lane lines on the lane where the electric vehicle is vehicle is located and the obstacles in the preset range in front of it; An image processing unit, connected to the camera, is used to process the captured images of lane lines and obstacles and obtain the relative position in the lane where the electric vehicle is located, in addition to information about obstacles. 3. Het systeem volgens conclusie 2, met het kenmerk dat de obstakels voetgangers, houten blokken en stenen omvatten, waarvan de hoogte groter is dan de minimale hoogte van het chassis of de breedte groter is dan de veilige breedte van de doorgang en de obstakelinformatie de positie en geometrische vormen van de obstakels.The system according to claim 2, characterized in that the obstacles comprise pedestrians, wooden blocks and stones, the height of which is greater than the minimum height of the chassis or the width of which is greater than the safe width of the passage and the obstacle information position and geometric shapes of the obstacles. 4. Het systeem volgens conclusie 1, met het kenmerk dat de differentiële GPS- module de volgende elementen omvat: Twee differentiële GPS-ontvangers, aangebracht op de bovenkant van het elektrische voertuig, in de lengterichting opgesteld en niet minder dan een meter uit elkaar, wordt gebruikt om de real-time positiecoördinaten en positie van het elektrische voertuig tijdens het rijden te verkrijgen;The system according to claim 1, characterized in that the differential GPS module comprises the following elements: Two differential GPS receivers mounted on the top of the electric vehicle, arranged longitudinally and not less than one meter apart, is used to obtain the real-time position coordinates and position of the electric vehicle while driving; Een rekencentrum, verbonden met de differentiële GPS-ontvanger om de rij- informatie van elektrische voertuigen te ontvangen, wordt gebruikt om de geplande routeinformatie in het programma te genereren; De geplande routeinformatie omvat de coördinaten van de geplande route en ontkoppelingspunten die zijn ingesteld op secties van meerdere routes (zoals kruispunten).A computer center, connected to the differential GPS receiver to receive the driving information of electric vehicles, is used to generate the planned route information in the program; The planned route information includes the coordinates of the planned route and disconnect points set on sections of multiple routes (such as intersections). 5. Het systeem volgens conclusie 1, met het kenmerk dat de coördinatiebesturingsmodule verbonden is met de beeldverwerkingseenheid en het rekencentrum om de relatieve rijstrookpositie-informatie en obstakelinformatie te ontvangen van het elektrische voertuig dat wordt uitgevoerd door de beeldverwerkingseenheid en de geplande routeinformatie die gegenereerd wordt door het rekencentrum, gebruikt een gecoördineerd besturingsalgoritme om de visuele herkenningsmodule en de differentiële GPS-module te coördineren om een gecoördineerd besturingssignaal uit te voeren.The system according to claim 1, characterized in that the coordination control module is connected to the image processing unit and the computer center to receive the relative lane position information and obstacle information of the electric vehicle output from the image processing unit and the planned route information generated by the computer center, uses a coordinated control algorithm to coordinate the visual recognition module and the differential GPS module to output a coordinated control signal. 6. Het systeem volgens conclusie 5, met het kenmerk dat het gecoördineerde besturingsalgoritme drie beoordelingsbases omvat, respectievelijk of een obstakel wordt gedetecteerd, of een ontkoppelingspunt wordt gedetecteerd en of de afstand tussen de geplande route en de middenlijn van de rijstrook < d is en het gecoördineerde besturingsalgoritme voert de volgende drie gecoördineerde besturingssignalen uit: remmen; het traject volgen op basis van differentiële GPS; het traject volgen op basis van differentiële GPS en ondersteund door de vision-module.The system according to claim 5, characterized in that the coordinated control algorithm comprises three judgment bases, respectively, whether an obstacle is detected, whether a disconnection point is detected and whether the distance between the planned route and the center line of the lane is < d and the coordinated control algorithm outputs the following three coordinated control signals: braking; track the trajectory based on differential GPS; follow the trajectory based on differential GPS and supported by the vision module. 7. Het systeem volgens conclusie 1, met het kenmerk dat de automatische rijbesturingsmodule de volgende elementen omvat: Een bestuurder, die wordt gebruikt om de besturing van het elektrische voertuig te besturen; Een stuurinrichting, die wordt gebruikt om het starten en rijden van het elektrische voertuig te regelen; Een rem, die wordt gebruikt om het elektrische voertuig te laten remmen wanneer het obstakel binnen het vooraf ingestelde bereik verschijnt; De automatische rijbesturingsmodule is verbonden met de gecoördineerde besturingsmodule om gecoördineerde besturingssignalen te ontvangen, het remmen van het elektrische voertuig te regelen en te rijden volgens de geplande routeinformatie en tegelijkertijd verdere correcties aan te brengen op basis van de informatie over de rijstrookpositie binnen het gespecificeerde verschilbereik om de elektrische auto in het midden van de rijstrook te laten rijden. -0-0-0-0-0-The system according to claim 1, characterized in that the automatic driving control module comprises the following elements: A driver, which is used to control the control of the electric vehicle; A steering device, which is used to control the starting and driving of the electric vehicle; A brake, which is used to make the electric vehicle brake when the obstacle appears within the preset range; The automatic driving control module is connected with the coordinated control module to receive coordinated control signals, control the braking of the electric vehicle and drive according to the planned route information, and at the same time make further corrections based on the lane position information within the specified difference range to to drive the electric car in the middle of the lane. -0-0-0-0-0-
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