CN109211247A - A kind of space-time partition model and its application method - Google Patents
A kind of space-time partition model and its application method Download PDFInfo
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- CN109211247A CN109211247A CN201710521991.1A CN201710521991A CN109211247A CN 109211247 A CN109211247 A CN 109211247A CN 201710521991 A CN201710521991 A CN 201710521991A CN 109211247 A CN109211247 A CN 109211247A
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- G—PHYSICS
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- 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
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/28—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network with correlation of data from several navigational instruments
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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
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/28—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network with correlation of data from several navigational instruments
- G01C21/30—Map- or contour-matching
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- H04W—WIRELESS COMMUNICATION NETWORKS
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Abstract
The invention belongs to intelligent driving technical fields, and in particular to a kind of space-time partition model and its application method.The step of space-time partition model construction method of the invention, including building time subregion, building dynamic space subregion and building Static-state Space subregion.The present invention solves existing V2X technology, when the vehicle of different intelligent driving grades mixes row on road, it is impossible to meet the requirements of space-time synchronous and consistency for data fusion between V2X communication system and vehicle intelligent control loop, cause the inefficient technical problem of intelligent driving decision.By using method of the invention, intelligent driving system data processing space-time is synchronized, intelligent driving system data-handling efficiency is improved and optimize, realizes the consistency of the method for driving cycles and accident analysis.
Description
Technical field
The invention belongs to intelligent driving technical fields, and in particular to a kind of space-time partition model and its application method.
Background technique
Pilotless automobile is a kind of intelligent automobile, can also be referred to as wheeled mobile robot, relies primarily on car
Intelligent driving instrument based on computer system is unmanned to realize.Pilotless automobile is perceived by vehicle-mounted sensor-based system
Road environment, automatic planning travelling line simultaneously control the intelligent automobile that vehicle reaches predeterminated target.It using onboard sensor come
Perceive vehicle-periphery, and according to road, vehicle location and obstacle information obtained is perceived, control vehicle steering and
Speed, to enable the vehicle to reliably and securely travel on road.The automatic control of pilotless automobile collection, architecture, people
Numerous technologies such as work intelligence, vision calculating are computer science, pattern-recognition and intelligent control technology high development in one
Product, and an important symbol of national a research strength and industrial level is measured, have in national defence and national economy field
Have broad application prospects.
Bus or train route communication system refers to V2X communication system, both includes onboard system, also includes road side system.Bus or train route communicates
Earliest title.V2X (Vehicle to X), is the key technology of the following intelligent transport system.It makes vehicle and vehicle, vehicle
It can be communicated between base station, base station and base station.To obtain a series of traffic such as real-time road, road information, pedestrian information
Information, thus improve drive safety, reduce congestion, improve traffic efficiency, car entertainment information is provided etc..V2X is that intelligence is driven
One of core technology sailed, many crucial active safety technologies are implemented on V2X technology, for example, crossing collision avoidance, based on handing over
The safe driving strategy etc. of logical modulating signal.
Existing V2X technology, when the vehicle of different intelligent driving grades on road mix row when, V2X communication system with
And the data fusion between vehicle intelligent control loop causes intelligent driving it is impossible to meet the requirement of space-time synchronous and consistency
Decision it is inefficient.
In addition to space-time synchronous, because V2X data use broadcast mode, priority ranking is asking for intelligent driving system processing
One of topic.Priority ranking and the rate of data publication, processing are also to influence the influence factor of the intelligent driving efficiency of decision-making.
Summary of the invention
The technical problem to be solved in the invention are as follows: existing V2X technology, when the vehicle of different intelligent driving grades exists
When mixing row on road, it is impossible to meet space-time synchronous for the data fusion between V2X communication system and vehicle intelligent control loop
With the requirement of consistency, cause the inefficient of intelligent driving decision.
It is described that technical scheme is as follows:
A kind of space-time partition model construction method, comprising the following steps:
Step 1, building time subregion
It is time-consuming according to the behavior of intelligent driving, the behavior time-consuming of intelligent driving is divided into five grades, forms the time point
Area；Specifically, one level temporal subregion, i.e. movement decision level time subregion: 1-200 milliseconds of behavior time-consuming；Second level time subregion, i.e.,
Action control grade time subregion: behavior time-consuming 0.1-2 seconds；Three-level time subregion, i.e. short path decision level time subregion: behavior consumption
When 1-30 seconds；Level Four time subregion, i.e., long path decision grade time subregion: behavior time-consuming 0.5-30 minutes；Pyatyi time subregion,
I.e. full activity time domain time subregion: behavior time-consuming 0.5 hour or more；
Step 2, building dynamic space subregion
Step 2.1 establishes dynamic space subregion coordinate system
Using the vertical point of lane center where main vehicle position location point to main vehicle as coordinate origin, main vehicle driving direction is in the same direction
Lane center direction be X-axis construct dynamic coordinate system；
Step 2.2 establishes first-stage dynamic space partition zone
The minimum space region perceived required for main vehicle driver behavior decision is obtained, which constitutes level-one
Dynamic space subregion；
Step 2.3 establishes the two-stage dynamic space partition zone
The first-stage dynamic space for obtaining all vehicles on the boundary of main vehicle first-stage dynamic space partition zone, by vehicles all on boundary
First-stage dynamic space seek union, and remove the first-stage dynamic area of space of main vehicle from the result for asking union to obtain, form two
Grade dynamic space subregion；
Step 2.4 establishes three-level dynamic space subregion
Obtaining all intelligent driving behaviors in the three-level time subregion of main vehicle makes the spatial dimension of main vehicle movement covering, from this
Firsts and seconds dynamic space subregion is removed in spatial dimension, forms three-level dynamic space subregion；
Step 3, building Static-state Space subregion
High-precision road-map-data is split into the section as 50 to 100 meters long, each unique mark of section setting
Code stores the lane grade map datum in each section, forms Static-state Space subregion；Each section lane grade map datum include
Following content: latitude and longitude coordinates, lane information hand over rule information, information of road surface, road shoulder and trackside facility；In Static-state Space subregion
Data according to recorded renewal time and road Up-to-date state requirement, by V2X trackside communication equipment provide data it is real-time
It updates；Complete the building of space-time partition model.
A method of data fusion and processing being carried out using above-mentioned space-time partition model, specifically includes the following steps:
Step 1, creation dynamic space data
Using the vertical point of lane center where main vehicle position location point to main vehicle as coordinate origin, main vehicle driving direction is in the same direction
Lane center direction be X-axis construct dynamic coordinate system；In this dynamic coordinate system, pass through the vehicle around sensor perception
And moving object position data, and the position data of acquisition is matched in the level-one, second level and three-level dynamic space of main vehicle；
The lane data in Static-state Space subregion are obtained, and the lane data in Static-state Space subregion are mapped into main vehicle
In dynamic space coordinate system；
By in V2X message in Static-state Space vehicle and mobile object information also map to the dynamic space coordinate system of main vehicle
It is interior；
Step 2, data fusion and data processing
Repetition and conflicting information redundancy for vehicle or mobile object in subregion select the data of high confidence level or incite somebody to action
The data in multiple sources are modified by algorithm；The data of the high confidence level be according to sensor or V2X data when
Between error and space error assessment, the relatively small data of space-time error；
If precision is not much different, while knowing vehicle or mobile object form parameter, foundation by V2X or other approach
Form parameter, sensor observation angle and location data calculate position and the posture of vehicle or mobile object, to correct vehicle
Or moving object position information；
Step 3, V2X information exchange
V2X information exchange includes the V2X information exchange of roadside device and the V2X information exchange of vehicle intelligent control loop；
The V2X information exchange of roadside device includes Static-state Space partition data more new demand servicing；The V2X information of roadside device is handed over
What is changed further includes that the vehicle position information that will be received is converted to information of vehicles in Static-state Space subregion and according to time subregion
Summarize together, then issues out to road vehicle；The V2X information exchange of roadside device also includes traffic control or limitation
Information and early warning or warning message；
The V2X information exchange of vehicle intelligent control loop includes the position for issuing main vehicle, speed, vehicle condition, vehicle shape ginseng
The position for the mobile object in first order dynamic space-time subregion that several and main vehicle sensor perceives, velocity information；Main vehicle letter
Breath is issued with Static-state Space position, and sensor information then uses the position of dynamic space to issue.
The invention has the benefit that the space-time synchronous that method of the invention solves intelligent driving system data processing is asked
Topic, improves and optimizes intelligent driving system data-handling efficiency, it is consistent with the method for accident analysis to realize driving cycles
Property.
Detailed description of the invention
Fig. 1 is dynamic space subregion schematic diagram；
Fig. 2 is the two-stage dynamic space partition zone schematic diagram；
Fig. 3 is Static-state Space subregion schematic diagram.
Specific embodiment
The present invention is solved between V2X communication system and vehicle intelligent control loop by building space-time partition model
Data fusion the problem of it is impossible to meet space-time synchronous and coherence requests, specific step is as follows for building space-time partition model:
Step 1, building time subregion
It is time-consuming according to the behavior of intelligent driving, the behavior time-consuming of intelligent driving is divided into five grades, forms the time point
Area.Specifically, one level temporal subregion, i.e. movement decision level time subregion: 1-200 milliseconds of behavior time-consuming；Second level time subregion, i.e.,
Action control grade time subregion: behavior time-consuming 0.1-2 seconds；Three-level time subregion, i.e. short path decision level time subregion: behavior consumption
When 1-30 seconds；Level Four time subregion, i.e., long path decision grade time subregion: behavior time-consuming 0.5-30 minutes；Pyatyi time subregion,
I.e. full activity time domain time subregion: behavior time-consuming 0.5 hour or more.
Step 2, building dynamic space subregion
Dynamic space subregion as shown in Figure 1, building dynamic space subregion specifically includes the following steps:
Step 2.1 establishes dynamic space subregion coordinate system
Using the vertical point of lane center where main vehicle position location point to main vehicle as coordinate origin, main vehicle driving direction is in the same direction
Lane center direction be X-axis construct dynamic coordinate system.
Step 2.2 establishes first-stage dynamic space partition zone
The minimum space region perceived required for main vehicle driver behavior decision is obtained, which constitutes level-one
Dynamic space subregion.
Step 2.3 establishes the two-stage dynamic space partition zone
The first-stage dynamic space for obtaining all vehicles on the boundary of main vehicle first-stage dynamic space partition zone, by vehicles all on boundary
First-stage dynamic space seek union, and remove the first-stage dynamic area of space of main vehicle from the result for asking union to obtain, form two
Grade dynamic space subregion, as shown in Figure 2.
Step 2.4 establishes three-level dynamic space subregion
Obtaining all intelligent driving behaviors in the three-level time subregion of main vehicle makes the spatial dimension of main vehicle movement covering, from this
Firsts and seconds dynamic space subregion is removed in spatial dimension, forms three-level dynamic space subregion.
Step 3, building Static-state Space subregion
As shown in figure 3, high-precision road-map-data is split the section as 50 to 100 meters long, each section setting
Unique identification code stores the lane grade map datum in each section, forms Static-state Space subregion.The lane grade ground in each section
Diagram data includes following content: latitude and longitude coordinates, lane information hand over rule information, information of road surface, road shoulder and trackside facility.It is static
Data in space partition zone are mentioned according to recorded renewal time and the requirement of road Up-to-date state by V2X trackside communication equipment
For data real-time update.Complete the building of space-time partition model.
Data in above-mentioned Static-state Space and dynamic space include Fundamental Geographic Information System and vehicle and mobile object information
And the driving path environmental information of dynamic change, driving path environmental information include temperature, visibility and light.Vehicle and shifting
Animal body information includes position, speed, the direction of motion and athletic posture.
The present invention also provides a kind of methods for carrying out data fusion and processing using above-mentioned space-time partition model, specifically include
Following steps:
Step 1, creation dynamic space data
Using the vertical point of lane center where main vehicle position location point to main vehicle as coordinate origin, main vehicle driving direction is in the same direction
Lane center direction be X-axis construct dynamic coordinate system.In this dynamic coordinate system, pass through the vehicle around sensor perception
With moving object position data, and the position data of acquisition is matched in the level-one, second level and three-level dynamic space of main vehicle.
The lane data in Static-state Space subregion are obtained, and the lane data in Static-state Space subregion are mapped into main vehicle
In dynamic space coordinate system.
By in V2X message in Static-state Space vehicle and mobile object information also map to the dynamic space coordinate system of main vehicle
It is interior.
Step 2, data fusion and data processing
Repetition and conflicting information redundancy for vehicle or mobile object in subregion select the data of high confidence level or incite somebody to action
The data in multiple sources are modified by algorithm.The data of the high confidence level be according to sensor or V2X data when
Between error and space error assessment, the relatively small data of space-time error.
If precision is not much different, while knowing vehicle or mobile object form parameter, foundation by V2X or other approach
Form parameter, sensor observation angle and location data calculate position and the posture of vehicle or mobile object, to correct vehicle
Or moving object position information.A general anchor point of picking up the car is dynamic space coordinate origin with the vertical point of place lane center.Vehicle
Or the position of mobile object can be scaled the coordinate in space, the distance and visual angle that can also use origin indicate.
Operating condition determines and effect determines mainly to analyze and determine the optional of Driving Decision-making according to current road traffic state
The implementation effect of movement and driver behavior provides judgment basis for execution, amendment or change Driving Decision-making.
Driving Decision-making includes long path decision and short path decision.In addition to path decision, driving intention can pass through driving
The combination of movement is completed.Driver behavior contains the control of throttle, brake, steering wheel.In space-time partition model, long road
Diameter decision is made a policy in three-level or level Four space-time subregion, and short path decision is made in second level or three-level space-time subregion
Decision, and driver behavior is made a policy in level-one space-time subregion.
Step 3, V2X information exchange
V2X information exchange includes the V2X information exchange of roadside device and the V2X information exchange of vehicle intelligent control loop.
The V2X information exchange of roadside device includes Static-state Space partition data more new demand servicing.The V2X information of roadside device is handed over
What is changed further includes that the vehicle position information that will be received is converted to information of vehicles in Static-state Space subregion and according to time subregion
Summarize together, then issues out to road vehicle.The V2X information exchange of roadside device also includes traffic control or limitation
The early warning such as information and accident, failure and information of road surface or warning message.
The V2X information exchange of vehicle intelligent control loop is mainly to issue position, the speed, vehicle condition, vehicle shape of main vehicle
The position for the mobile object in first order dynamic space-time subregion that parameter and main vehicle sensor perceive, velocity information.Main vehicle
Information is issued with Static-state Space position, and sensor information then uses the position of dynamic space to issue.
The information issued when the V2X information exchange of roadside device is with the publication of Static-state Space position.So roadside device
The sensor information of the vehicle intelligent control loop received when V2X information exchange needs to carry out coordinate when carrying out data fusion
Conversion.Conversely, the V2X information that vehicle intelligent control loop receives roadside device is also required to carry out coordinate conversion.
Claims (2)
1. a kind of space-time partition model construction method, which comprises the following steps:
Step 1, building time subregion
It is time-consuming according to the behavior of intelligent driving, the behavior time-consuming of intelligent driving is divided into five grades, forms time subregion；Tool
Body is one level temporal subregion, i.e. movement decision level time subregion: 1-200 milliseconds of behavior time-consuming；Second level time subregion, that is, act
Controlled stage time subregion: behavior time-consuming 0.1-2 seconds；Three-level time subregion, i.e. short path decision level time subregion: behavior time-consuming 1-
30 seconds；Level Four time subregion, i.e., long path decision grade time subregion: behavior time-consuming 0.5-30 minutes；Pyatyi time subregion, i.e., entirely
Domain activity time, subregion time: behavior time-consuming 0.5 hour or more；
Step 2, building dynamic space subregion
Step 2.1 establishes dynamic space subregion coordinate system
Using the vertical point of lane center where main vehicle position location point to main vehicle as coordinate origin, main vehicle driving direction vehicle in the same direction
Road centerline direction is that X-axis constructs dynamic coordinate system；
Step 2.2 establishes first-stage dynamic space partition zone
The minimum space region perceived required for main vehicle driver behavior decision is obtained, which constitutes first-stage dynamic
Space partition zone；
Step 2.3 establishes the two-stage dynamic space partition zone
The first-stage dynamic space for obtaining all vehicles on the boundary of main vehicle first-stage dynamic space partition zone, by the one of vehicles all on boundary
Grade dynamic space seeks union, and the first-stage dynamic area of space of main vehicle is removed from the result for asking union to obtain, and it is dynamic to form second level
State space subregion；
Step 2.4 establishes three-level dynamic space subregion
Obtaining all intelligent driving behaviors in the three-level time subregion of main vehicle makes the spatial dimension of main vehicle movement covering, from the space
Firsts and seconds dynamic space subregion is removed in range, forms three-level dynamic space subregion；
Step 3, building Static-state Space subregion
High-precision road-map-data is split into the section as 50 to 100 meters long, each section is arranged unique identification code, deposits
The lane grade map datum for storing up each section, forms Static-state Space subregion；The lane grade map datum in each section includes as follows
Content: latitude and longitude coordinates, lane information hand over rule information, information of road surface, road shoulder and trackside facility；Number in Static-state Space subregion
According to according to recorded renewal time and the requirement of road Up-to-date state, data real-time update is provided by V2X trackside communication equipment；
Complete the building of space-time partition model.
2. a kind of method for carrying out data fusion and processing using space-time partition model described in claim 1, which is characterized in that tool
Body the following steps are included:
Step 1, creation dynamic space data
Using the vertical point of lane center where main vehicle position location point to main vehicle as coordinate origin, main vehicle driving direction vehicle in the same direction
Road centerline direction is that X-axis constructs dynamic coordinate system；In this dynamic coordinate system, by sensor perception around vehicle and
Moving object position data, and the position data of acquisition is matched in the level-one, second level and three-level dynamic space of main vehicle；
The lane data in Static-state Space subregion are obtained, and the lane data in Static-state Space subregion are mapped to the dynamic of main vehicle
In space coordinates；
By in V2X message in Static-state Space vehicle and mobile object information also map in the dynamic space coordinate system of main vehicle；
Step 2, data fusion and data processing
Repetition and conflicting information redundancy for vehicle or mobile object in subregion, select high confidence level data or will be multiple
The data in source are modified by algorithm；The data of the high confidence level are to be missed according to the time to sensor or V2X data
The assessment of difference and space error, the relatively small data of space-time error；
If precision is not much different, while knowing vehicle or mobile object form parameter by V2X or other approach, according to shape
Parameter, sensor observation angle and location data calculate position and the posture of vehicle or mobile object, to correct vehicle or shifting
Animal body location information；
Step 3, V2X information exchange
V2X information exchange includes the V2X information exchange of roadside device and the V2X information exchange of vehicle intelligent control loop；
The V2X information exchange of roadside device includes Static-state Space partition data more new demand servicing；The V2X information exchange of roadside device
It further include that the vehicle position information that will be received is converted to the information of vehicles in Static-state Space subregion and summarizes according to time subregion
Together, then to road vehicle it issues out；The V2X information exchange of roadside device also includes traffic control or limitation letter
Breath and early warning or warning message；
The V2X information exchange of vehicle intelligent control loop includes the position for issuing main vehicle, speed, vehicle condition, vehicle shape parameter, with
And position, the velocity information of the mobile object in the first order dynamic space-time subregion that perceives of main vehicle sensor；Main vehicle information is used
The publication of Static-state Space position, and sensor information then uses the position of dynamic space to issue.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110006440A (en) * | 2019-04-12 | 2019-07-12 | 北京百度网讯科技有限公司 | A kind of expression, device, electronic equipment and the storage medium of map relationship |
| CN112053592A (en) * | 2020-04-28 | 2020-12-08 | 上海波若智能科技有限公司 | Road network dynamic data acquisition method and road network dynamic data acquisition system |
| CN113012429A (en) * | 2021-02-23 | 2021-06-22 | 启迪云控(上海)汽车科技有限公司 | Vehicle road multi-sensor data fusion method and system |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20030084175A1 (en) * | 2001-11-01 | 2003-05-01 | Microsoft Corporation | Method and framework for processing network communication protocol timers |
| CN102710796A (en) * | 2012-06-20 | 2012-10-03 | 张�林 | Area data downloading method and device based on multi-level partition network |
| CN103544065A (en) * | 2013-11-05 | 2014-01-29 | 中国航空工业集团公司西安飞机设计研究所 | Avionics system partition window scheduling method under ARINC653 standard |
| CN104112363A (en) * | 2014-07-04 | 2014-10-22 | 西安交通大学 | Multi-sensing-data space-time synchronization method and road multi-sensing-data vehicle-mounted acquisition system |
| CN106885601A (en) * | 2017-01-09 | 2017-06-23 | 北京理工大学 | Unmanned vehicle multi-sensor data synchronous |
-
2017
- 2017-06-30 CN CN201710521991.1A patent/CN109211247B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20030084175A1 (en) * | 2001-11-01 | 2003-05-01 | Microsoft Corporation | Method and framework for processing network communication protocol timers |
| CN102710796A (en) * | 2012-06-20 | 2012-10-03 | 张�林 | Area data downloading method and device based on multi-level partition network |
| CN103544065A (en) * | 2013-11-05 | 2014-01-29 | 中国航空工业集团公司西安飞机设计研究所 | Avionics system partition window scheduling method under ARINC653 standard |
| CN104112363A (en) * | 2014-07-04 | 2014-10-22 | 西安交通大学 | Multi-sensing-data space-time synchronization method and road multi-sensing-data vehicle-mounted acquisition system |
| CN106885601A (en) * | 2017-01-09 | 2017-06-23 | 北京理工大学 | Unmanned vehicle multi-sensor data synchronous |
Non-Patent Citations (1)
| Title |
|---|
| 莫元富: "车联网环境下交通信息分发与处理关键技术研究", 《中国博士学位论文全文数据库·工程科技Ⅱ辑》 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110006440A (en) * | 2019-04-12 | 2019-07-12 | 北京百度网讯科技有限公司 | A kind of expression, device, electronic equipment and the storage medium of map relationship |
| CN112053592A (en) * | 2020-04-28 | 2020-12-08 | 上海波若智能科技有限公司 | Road network dynamic data acquisition method and road network dynamic data acquisition system |
| CN114783214A (en) * | 2020-04-28 | 2022-07-22 | 上海波若智能科技有限公司 | Road network dynamic data acquisition method and road network dynamic data acquisition system |
| CN113012429A (en) * | 2021-02-23 | 2021-06-22 | 启迪云控(上海)汽车科技有限公司 | Vehicle road multi-sensor data fusion method and system |
| CN113012429B (en) * | 2021-02-23 | 2022-07-15 | 云控智行(上海)汽车科技有限公司 | Vehicle road multi-sensor data fusion method and system |
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