Movatterモバイル変換


[0]ホーム

URL:


CN118097972B - Track point optimization method and device for vehicle running track - Google Patents

Track point optimization method and device for vehicle running track
Download PDF

Info

Publication number
CN118097972B
CN118097972BCN202410508445.4ACN202410508445ACN118097972BCN 118097972 BCN118097972 BCN 118097972BCN 202410508445 ACN202410508445 ACN 202410508445ACN 118097972 BCN118097972 BCN 118097972B
Authority
CN
China
Prior art keywords
track
point
represent
vehicle speed
points
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN202410508445.4A
Other languages
Chinese (zh)
Other versions
CN118097972A (en
Inventor
武海防
谭雪
吕建洋
魏庆余
强荡荡
邱伟
赵同磊
颜卫
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Taian Jiuzhou Jincheng Machinery Co ltd
Original Assignee
Taian Jiuzhou Jincheng Machinery Co ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Taian Jiuzhou Jincheng Machinery Co ltdfiledCriticalTaian Jiuzhou Jincheng Machinery Co ltd
Priority to CN202410508445.4ApriorityCriticalpatent/CN118097972B/en
Publication of CN118097972ApublicationCriticalpatent/CN118097972A/en
Application grantedgrantedCritical
Publication of CN118097972BpublicationCriticalpatent/CN118097972B/en
Activelegal-statusCriticalCurrent
Anticipated expirationlegal-statusCritical

Links

Classifications

Landscapes

Abstract

The application relates to the field of traffic control, in particular to a track point optimization method and a track point optimization device for a vehicle running track, wherein the method comprises the following steps: acquiring historical data of a vehicle driving track, wherein the driving track is provided with a plurality of track points, and the historical data comprises: the method comprises the steps of constructing a speed curve about recording time and vehicle speed according to the recording time of track points, the vehicle speed at the track points and the traffic light position in a running track; calculating the vehicle speed change degree of each track point; calculating the state rationality of each track point; calculating the road condition feature of each track point; and adjusting the vehicle speed of each track point according to the road condition characteristic degree of all the track points to obtain an optimal speed curve. The application has the effect of optimizing the track points in the running track of the vehicle.

Description

Track point optimization method and device for vehicle running track
Technical Field
The application relates to the field of traffic control, in particular to a track point optimization method and device for a vehicle running track.
Background
The track points in the vehicle running track refer to recorded vehicle position data points according to a preset route or path information provided by a navigation system in the vehicle running process. These data points may be continuous or discrete and together form a map of the vehicle's path. By analyzing these trajectory points, information such as the running state, speed, and direction of the vehicle can be known.
In the running process of the vehicle in the city, the method can be used for planning the activity time and optimizing the path selection by keeping the path details, namely, the change of long-term road conditions.
However, the long-term road condition includes an emergency, such as a car accident occurring in front of the road, or a pedestrian suddenly passing through the road to avoid the accident, and the emergency cannot describe the actual state of the road section, if the road is planned according to the speed data of all the track points, the data corresponding to the emergency will affect the result of the road planning, and unnecessary steering, accelerating or decelerating operations in the running of the vehicle are increased, so that the track points in the running track of the vehicle need to be optimized.
Disclosure of Invention
In order to optimize track points in a vehicle running track so as to reduce the influence of data corresponding to emergency on a path planning result and improve the rationality of the path planning result, the application provides a track point optimization method and a track point optimization device of the vehicle running track.
In a first aspect, the present application provides a method and an apparatus for optimizing a track point of a vehicle running track, which adopt the following technical schemes:
A track point optimization method of a vehicle running track comprises the following steps: acquiring historical data of a vehicle driving track, wherein the driving track is provided with a plurality of track points, and the historical data comprises: the method comprises the steps of constructing a speed curve about recording time and vehicle speed according to the recording time of track points, the vehicle speed at the track points and the traffic light position in a running track; dividing a speed curve into a plurality of speed sections according to the time point when the vehicle passes through the traffic light; dividing a driving track into a plurality of road sections according to the positions of the traffic lights, wherein a track point closest to the starting position of the road section is used as a starting point of the road section, and a track point closest to the ending position of the road section is used as an ending point of the road section; the vehicle speed change degree of each track point is calculated, and the calculation formula of the vehicle speed change degree is as follows: wherein, the method comprises the steps of, wherein,Represent the firstThe degree of change in vehicle speed at each locus point,Represent the firstThe vehicle speed at the point of the trajectory,Represent the firstThe vehicle speed average value of the speed section where the track points are located,Represent the firstVehicle speed and first track pointThe slope of the coordinate connecting line where the vehicle speeds of the track points are located; the state rationality of each track point is calculated, and the calculation formula of the state rationality is as follows: wherein, the method comprises the steps of, wherein,Represent the firstThe state of the individual trace points is rational,Represent the firstThe degree of speed variation of the individual track points,Represent the firstThe vehicle speed at the point of the trajectory,Represent the firstThe degree of tortuosity of the road section where the track points are located,Represent the firstThe degree of tortuosity of the location of the individual trace points,Represent the firstThe path distance between the individual track points and the nearest traffic light,Representing a normalization function; the road condition characteristic degree of each track point is calculated, and the calculation formula of the road condition characteristic degree is as follows: wherein, the method comprises the steps of, wherein,Represent the firstThe road condition characteristic degree of each track point,Represent the firstThe state of the individual trace points is rational,Represent the firstThe state rationality average value of all track points of the road section where the track points are located; and adjusting the vehicle speed of each track point according to the road condition characteristic degree of all the track points to obtain an optimal speed curve.
Optionally, in adjusting the vehicle speed of each track point according to the road condition feature degree of all track points to obtain the optimal speed curve, the adjusting method includes the steps of: calculating the dissatisfaction of the vehicle speed, wherein the calculation formula is as follows: wherein, the method comprises the steps of, wherein,Represent the firstThe inconsistency of the vehicle speed at the individual track points,Represent the firstThe road condition characteristic degree of each track point,Representing a normalization function; the adjustment distance is calculated, the calculation formula is as follows,Wherein, the method comprises the steps of, wherein,The adjustment distance is indicated as such,Represent the firstThe inconsistency of the vehicle speed at the individual track points,Represent the firstThe vehicle speed at the point of the track,Represent the firstVehicle speed at each track point; according to the adjustment distance, the vehicle speed at the track point is adjusted according to the adjustment formula: wherein, the method comprises the steps of, wherein,Represent the firstThe adjusted vehicle speed at each of the track points,Represent the firstThe vehicle speed at the point of the track,Represent the firstThe vehicle speed at the point of the track,The adjustment distance is indicated as such,Representing the maximum function.
Optionally, in the calculation formula of state rationality, the degree of tortuosity of the road section where the track point is located is: first, theThe start point and the first point of the road section where the track points areThe variances of the angles of the included angles of all the track point connecting lines and the horizontal lines on the road sections where the track points are located.
Optionally, in the calculation formula of state rationality, the degree of tortuosity of the position where the track point is located is: setting the firstThe start point and the first point of the road section where the track points areThe connecting line between the track points is a first connecting lineThe end point of the road section where each track point is locatedThe connecting line between the track points is a second connecting line, and the included angle between the first connecting line and the second connecting line is the first angleThe degree of tortuosity of the location of each trace point.
Optionally, the method further comprises the steps of: and carrying out revolving door compression on the optimal speed curve according to a revolving door compression algorithm, and storing the optimal speed curve.
In a second aspect, the present application provides a track point optimizing apparatus for a vehicle running track, which adopts the following technical scheme:
The track point optimizing device for the vehicle running track comprises a processor and a memory, wherein the memory stores computer program instructions which are executed by the processor to realize the track point optimizing method for the vehicle running track.
The application has the following technical effects:
1. The speed curve of the vehicle at the track point is optimized, namely the track point is optimized, so that the influence of data corresponding to emergency conditions on a final planning result is eliminated, meanwhile, the real road condition of road congestion is reserved, the vehicle driving path can be designed by optimizing the track point, the rationality of the path planning result is improved, the path planning result is smoother and more continuous, unnecessary steering, accelerating or decelerating operation in the vehicle driving process can be reduced, and accordingly, the fuel consumption and the emission are reduced.
2. According to the traffic flow, road conditions, time and other factors, the optimal driving path and driving strategy are selected, so that the traffic efficiency is improved, the congestion phenomenon is reduced, and the traffic pressure is relieved. The optimized track points can provide more intelligent and accurate navigation guidance for the driver and assist the driver in making optimal driving decisions. This helps to improve the driving experience, driving safety and driving efficiency of the driver.
Drawings
The above, as well as additional purposes, features, and advantages of exemplary embodiments of the present application will become readily apparent from the following detailed description when read in conjunction with the accompanying drawings. In the drawings, several embodiments of the application are illustrated by way of example and not by way of limitation, and like or corresponding reference numerals refer to like or corresponding parts.
Fig. 1 is a flowchart of a method for optimizing a track point of a vehicle running track according to an embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
It should be understood that when the terms "first," "second," and the like are used in the claims, the specification and the drawings of the present application, they are used merely for distinguishing between different objects and not for describing a particular sequential order. The terms "comprises" and "comprising" when used in the specification and claims of the present application are taken to specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
The embodiment of the application discloses a track point optimization method of a vehicle running track, which comprises the following steps of S1-S8 with reference to FIG. 1:
s1: acquiring historical data of a vehicle driving track, wherein the driving track is provided with a plurality of track points, and the historical data comprises: the recording time of the track point, the vehicle speed at the track point and the traffic light position in the driving track, a speed curve is constructed concerning the recording time and the vehicle speed.
In one embodiment, the track points are coordinates of the vehicle position at each time, and the interval between the time may be set according to the actual implementation. In the constructed speed curve, the abscissa is the recording time of the track point, and the ordinate is the vehicle speed at the track point.
S2: and dividing the speed curve into a plurality of speed sections according to the time point when the vehicle passes through the traffic light.
The speed profile is divided by the time the vehicle passes the traffic light, which in one embodiment is the time the vehicle is driving off or into the traffic light.
S3: according to the traffic light position, dividing the driving track into a plurality of road sections, wherein the track point closest to the starting position of the road section is used as the starting point of the road section, and the track point closest to the ending position of the road section is used as the ending point of the road section.
S4: the degree of change in vehicle speed for each locus point is calculated.
The calculation formula of the vehicle speed variation degree is as follows:
wherein, the method comprises the steps of, wherein,Represent the firstThe degree of change in vehicle speed at each locus point,The larger the value of (c) is, the more likely the track point is that a burst state occurs, and conversely, the less likely the burst state occurs.
Represent the firstThe vehicle speed at the point of the trajectory,Represent the firstThe average vehicle speed of the speed segment where the track points are located.Represents the firstVehicle speed and first track pointThe difference between the average vehicle speeds in the speed segment of the track points is greater when the difference is greaterThe greater the likelihood of a bursty state occurring at each trace point, and conversely, the less the likelihood of a bursty state occurring.
Represent the firstVehicle speed and first track pointThe slope of the coordinate line at which the vehicle speed of the individual track points is located,The larger the value of (c) is, the faster the speed change is explained, the firstThe greater the likelihood of a bursty state occurring at each trace point, and conversely, the less the likelihood of a bursty state occurring.
S5: and calculating the state rationality of each track point.
The calculation formula of the state rationality is:
wherein, the method comprises the steps of, wherein,Represent the firstThe state of the individual trace points is rational,Represent the firstThe degree of speed variation of the individual track points,Represent the firstThe vehicle speed at the point of the trajectory,Represent the firstThe degree of tortuosity of the road section where the track points are located,Represent the firstThe degree of tortuosity of the location of the individual trace points,Represent the firstThe path distance between the individual track points and the nearest traffic light,Representing the normalization function.
In one embodiment, the normalization function is maximum-minimum normalization, which is a common data preprocessing method, mainly used for scaling data to fall into a smaller specific interval, usuallyThis allows the data to be compared at the same scale or dimension.
In one embodiment, the degree of tortuosity of the road segment where the track point is located is: first, theThe start point and the first point of the road section where the track points areThe variance of the angle between the connecting line of all the track points and the horizontal line on the road section where the track points are located showsThe greater the value of the degree of tortuosity of the road section where the track point is located, the more tortuosity the path of the road section is indicated. And constructing a rectangular coordinate system of the position of the shutdown track point by taking the coordinate of the first track point closest to the departure point of the running track as an origin, wherein the horizontal axis of the rectangular coordinate system represents the horizontal coordinate of the track point, the vertical axis represents the vertical coordinate of the track point, and the horizontal axis of the rectangular coordinate system is the horizontal line.
In one embodiment, the degree of tortuosity of the locus of points is: setting the firstThe start point and the first point of the road section where the track points areThe connecting line between the track points is a first connecting lineThe end point of the road section where each track point is locatedThe connecting line between the track points is a second connecting line, and the included angle between the first connecting line and the second connecting line is the first angleThe degree of tortuosity of the location of each trace point.
Indicating whether the speed of the vehicle is reasonable for each track point, the larger the value is, the higher the tortuosity degree is, the slower the speed of the vehicle is, the more reasonable the vehicle is, otherwise, the faster the speed of the vehicle is, the more reasonable the vehicle is,The more the value of (2) approaches 1, the more reasonable.
It is shown whether the degree of change in the vehicle speed at each locus point is reasonable, the closer the value is to 1, the more reasonable the degree of change in the vehicle speed at that locus point is.
The traffic light can be decelerated and accelerated when the vehicle runs, so that analysis is carried out according to the road section characteristics of the track points, the speed change is obvious at the track points close to the traffic light, and the speed is recovered after deceleration at the turning of the path, and the speed change is obvious.
S6: and calculating the road condition feature of each track point.
The calculation formula of the road condition feature is as follows:
wherein, the method comprises the steps of, wherein,Represent the firstThe road condition characteristic degree of each track point,The larger the value of (c) is, the more the track point accords with the real road condition,Represent the firstThe state of the individual trace points is rational,Represent the firstThe state rationality average value of all track points of the road section where the track points are located.
S7: and adjusting the vehicle speed of each track point according to the road condition characteristic degree of all the track points to obtain an optimal speed curve.
Calculating the dissatisfaction of the vehicle speed, wherein the calculation formula is as follows: wherein, the method comprises the steps of, wherein,Represent the firstThe inconsistency of the vehicle speed at the individual track points,Represent the firstThe road condition characteristic degree of each track point,Representing the normalization function.
The adjustment distance is calculated, the calculation formula is as follows,Wherein, the method comprises the steps of, wherein,The adjustment distance is indicated as such,Represent the firstThe inconsistency of the vehicle speed at the individual track points,Represent the firstThe vehicle speed at the point of the track,Represent the firstVehicle speed at each locus of points.
According to the adjustment distance, the vehicle speed at the track point is adjusted according to the adjustment formula:
wherein, the method comprises the steps of, wherein,Represent the firstThe adjusted vehicle speed at each of the track points,Represent the firstThe vehicle speed at the point of the track,Represent the firstThe vehicle speed at the point of the track,Indicating the adjustment distance.Representation fetchAndMaximum value between.Is a maximum function, is provided withTo prevent the denominator from being 0.
For example, whenIn the time-course of which the first and second contact surfaces,Is adjusted toWhen (when)In the time-course of which the first and second contact surfaces,Is adjusted toWhen (when)In the time-course of which the first and second contact surfaces,Not adjusted.
S8: and carrying out revolving door compression on the optimal speed curve according to a revolving door compression algorithm, and storing the optimal speed curve.
The revolving door compression algorithm is a data compression algorithm, is suitable for processing a data set with the characteristics of high proximity and large data acquisition, and has the main function of performing linear fitting on the data so as to greatly reduce the storage space of the data.
The revolving door compression is performed through an optimal speed curve, and the door width in the revolving door compression algorithm is set to be half of the initial speed value of the vehicle speed, and the compressed speed data is used for storage. The revolving door compression algorithm is the prior art and will not be described in detail herein.
The speed curve of the vehicle at the track point is optimized, namely the track point is optimized, so that the influence of data corresponding to emergency conditions on a final planning result is eliminated, meanwhile, the real road condition of road congestion is reserved, the vehicle running path can be designed through optimizing the track point, so that the vehicle running path is smoother and more continuous, unnecessary steering, accelerating or decelerating operations in the vehicle running process can be reduced, and the fuel consumption and the emission are reduced.
In one embodiment, the vehicle travel path may be designed by optimizing the trajectory points as: and obtaining the speed data of a plurality of vehicles in the same way after obtaining an optimal speed curve of one vehicle, obtaining the vehicle speed of at least one vehicle of the road at the historical moment for the same road section, taking the average value of all the vehicle speeds of each road section at different historical moments as the speed data of the road section at the moment, and similarly obtaining the speed data of each road section at each moment and constructing a GCN-LSTM-BP road section short-time traffic speed prediction model according to the speed data of each road section at different historical moments.
The GCN-LSTM-B model is a composite model that combines the graph rolling network (Graph Convolutional Network, GCN), long Short-Term Memory (LSTM), and back propagation (Backpropagation, BP) algorithms.
And inputting the speed data of each road section at a plurality of continuous moments into a trained GCN-LSTM-BP road section short-time traffic speed prediction model to obtain road section speed prediction information, constructing a dynamic travel time shortest path selection model based on the road section speed prediction information, and obtaining an optimal path according to the shortest path selection model to provide navigation guidance for a driver.
The construction and training of the GCN-LSTM-BP model and the construction and training of the shortest path selection model are all the prior art, and are not described in detail herein.
The embodiment of the application also discloses a track point optimizing device of the vehicle running track, which comprises a processor and a memory, wherein the memory stores computer program instructions, and the track point optimizing method of the vehicle running track is realized when the computer program instructions are executed by the processor.
The above-described apparatus further includes other components, such as a communication bus and a communication interface, which are well known to those skilled in the art, and the arrangement and function of which are known in the art, and thus are not described in detail herein.
In the context of this patent, the foregoing memory may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. For example, the computer-readable storage medium may be any suitable magnetic or magneto-optical storage medium, such as, for example, resistance change memory RRAM (Resistive Random Access Memory), dynamic random access memory DRAM (Dynamic Random Access Memory), static random access memory SRAM (Static Random Access Memory), enhanced dynamic random access memory EDRAM (ENHANCED DYNAMIC Random Access Memory), high bandwidth memory HBM (High Bandwidth Memory), hybrid storage cube HMC (Hybrid Memory Cube), etc., or any other medium that may be used to store the desired information and that may be accessed by an application, a module, or both. Any such computer storage media may be part of, or accessible by, or connectable to, the device.
While various embodiments of the present application have been shown and described herein, it will be obvious to those skilled in the art that such embodiments are provided by way of example only. Many modifications, changes, and substitutions will now occur to those skilled in the art without departing from the spirit and scope of the application. It should be understood that various alternatives to the embodiments of the application described herein may be employed in practicing the application.
The above embodiments are not intended to limit the scope of the present application, so: all equivalent changes in structure, shape and principle of the application should be covered in the scope of protection of the application.

Claims (4)

CN202410508445.4A2024-04-262024-04-26Track point optimization method and device for vehicle running trackActiveCN118097972B (en)

Priority Applications (1)

Application NumberPriority DateFiling DateTitle
CN202410508445.4ACN118097972B (en)2024-04-262024-04-26Track point optimization method and device for vehicle running track

Applications Claiming Priority (1)

Application NumberPriority DateFiling DateTitle
CN202410508445.4ACN118097972B (en)2024-04-262024-04-26Track point optimization method and device for vehicle running track

Publications (2)

Publication NumberPublication Date
CN118097972A CN118097972A (en)2024-05-28
CN118097972Btrue CN118097972B (en)2024-07-30

Family

ID=91157584

Family Applications (1)

Application NumberTitlePriority DateFiling Date
CN202410508445.4AActiveCN118097972B (en)2024-04-262024-04-26Track point optimization method and device for vehicle running track

Country Status (1)

CountryLink
CN (1)CN118097972B (en)

Citations (2)

* Cited by examiner, † Cited by third party
Publication numberPriority datePublication dateAssigneeTitle
WO2023274229A1 (en)*2021-06-282023-01-05中移(上海)信息通信科技有限公司Vehicle trajectory deviation correction method and apparatus, and electronic device
CN117593908A (en)*2023-11-022024-02-23网络通信与安全紫金山实验室 Vehicle trajectory estimation method, device, computer equipment and storage medium

Family Cites Families (6)

* Cited by examiner, † Cited by third party
Publication numberPriority datePublication dateAssigneeTitle
DE102013208521B4 (en)*2013-05-082022-10-13Bayerische Motoren Werke Aktiengesellschaft Collective learning of a highly accurate road model
CN111591307B (en)*2020-04-152021-10-01毫末智行科技有限公司Obstacle avoidance track planning method and system and vehicle
DE112020007765T5 (en)*2020-11-122023-08-24Automotive Artificial Intelligence (Aai) Gmbh COMPUTER SYSTEM AND METHOD FOR TRAJECTORY PLANNING IN A SIMULATED ROAD DRIVING ENVIRONMENT
CN112988938A (en)*2021-03-312021-06-18深圳一清创新科技有限公司Map construction method and device and terminal equipment
CN113895463B (en)*2021-11-252023-06-06北京航空航天大学 A U-turn Path Planning Method for Autonomous Driving Vehicles
CN116977943A (en)*2022-12-292023-10-31腾讯科技(深圳)有限公司Road element identification method, device, electronic equipment and computer storage medium

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication numberPriority datePublication dateAssigneeTitle
WO2023274229A1 (en)*2021-06-282023-01-05中移(上海)信息通信科技有限公司Vehicle trajectory deviation correction method and apparatus, and electronic device
CN117593908A (en)*2023-11-022024-02-23网络通信与安全紫金山实验室 Vehicle trajectory estimation method, device, computer equipment and storage medium

Also Published As

Publication numberPublication date
CN118097972A (en)2024-05-28

Similar Documents

PublicationPublication DateTitle
CN110466516B (en)Curve road automatic vehicle lane change track planning method based on nonlinear programming
CN111267830B (en) A hybrid electric bus energy management method, device and storage medium
CN111216713A (en) A kind of automatic driving vehicle speed preview control method
CN115257724B (en) A plug-in hybrid vehicle safety and energy-saving decision control method and system
CN108257418A (en)Vehicle collision prewarning method and device
CN107215339A (en)The lane-change control method and device of automatic driving vehicle
US11814073B2 (en)Learning based controller for autonomous driving
CN107664504A (en)A kind of path planning apparatus
CN112249008A (en)Unmanned automobile early warning method aiming at complex dynamic environment
CN114407898B (en)Road changing path planning method and device, intelligent driving automobile and storage medium
CN111891116A (en)Method for improving stability of lateral control of automatic driving
CN115683140B (en)Method, system, equipment and medium for planning over-bending vehicle speed of passenger parking tracking
CN114384919B (en)Vehicle obstacle avoidance path planning method and system based on large obstacle form information
CN115092167A (en)Urban area automatic driving curve speed control method, storage medium and automobile
CN114355909A (en)Path planning method and device, computer equipment and storage medium
CN112519779A (en)Location-based vehicle operation
CN118097972B (en)Track point optimization method and device for vehicle running track
CN116513171A (en)Automatic driving collision risk detection method, system and medium based on lane information
CN115098821A (en)Trajectory reference curvature determination method, apparatus, device, medium, and program
CN119085688A (en) An improved RRT vehicle path planning method based on taboo search in V2X environment
CN115230688A (en)Obstacle trajectory prediction method, system, and computer-readable storage medium
CN111784142B (en)Method for establishing task complexity quantitative model of advanced driving assistance system
CN118665535A (en)Vehicle transverse-longitudinal coupling control method, device, equipment and storage medium
CN117238286A (en)Electric bicycle riding control method, system and storage medium based on voice medium
CN115880889B (en) Method, device and electronic device for determining variable lanes

Legal Events

DateCodeTitleDescription
PB01Publication
PB01Publication
SE01Entry into force of request for substantive examination
SE01Entry into force of request for substantive examination
GR01Patent grant
GR01Patent grant

[8]ページ先頭

©2009-2025 Movatter.jp