CN106840153A - A kind of high in the clouds calculates the method by speed in tunnel - Google Patents
A kind of high in the clouds calculates the method by speed in tunnel Download PDFInfo
- Publication number
- CN106840153A CN106840153A CN201710151680.0A CN201710151680A CN106840153A CN 106840153 A CN106840153 A CN 106840153A CN 201710151680 A CN201710151680 A CN 201710151680A CN 106840153 A CN106840153 A CN 106840153A
- Authority
- CN
- China
- Prior art keywords
- tunnel
- vehicle
- speed
- cloud server
- inertial navigation
- 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.)
- Pending
Links
Classifications
-
- 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
- G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
- G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
- G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
- G01C21/165—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments
-
- 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
- G01S19/49—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 inertial position system, e.g. loosely-coupled
Landscapes
- Engineering & Computer Science (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Computer Networks & Wireless Communication (AREA)
- Automation & Control Theory (AREA)
- Navigation (AREA)
Abstract
The method in tunnel by speed is calculated the present invention relates to a kind of high in the clouds, is comprised the following steps：When vehicle is reached near tunnel, inertial navigation set end uploads the information such as the current GPS location point longitude and latitude of vehicle to cloud server；Search index tunnel described point collection；Matching distance recently and maximum probability tunnel portal, combining information draws probability travel speed of the vehicle in tunnel；Issue probability travel speed and give inertial navigation set end；Dead reckoning is carried out with the probability travel speed for receiving；Vehicle is rolled away from after tunnel regains gps signal and reports the time passed through in tunnel, feeds back to cloud server.Extra electronic equipment is not needed, the forward speed of vehicle diverse location in tunnel is extrapolated with reference to means such as road network, weather, traffic, vehicle historical information, machine learning by being gathered to tunnel information, help the upper algorithm of inertial navigation set and end to suppress forward error diverging, improve positioning precision.
Description
Technical field
Calculated in tunnel the present invention relates to a kind of method calculated in vehicle tunnel by speed, more particularly to a kind of high in the clouds
By the method for speed.
Background technology
VDR (Vehicle Dead Reckoning, vehicle-mounted dead reckoning) technology can be in GPS (Global
Positioning System, global positioning system) in the case of dropout (as under overhead, tunnel, underground garage etc.)
Continue to position by dead reckoning, being merged with GPS positioning technology can lift location efficiency.Due to inertial navigation device, precision is asked in itself
Topic and Algorithm Error, positioning precision increases over time, simultaneously because inertial navigation device cannot draw before vehicle to speed in itself
, it is necessary to by odometer, image auxiliary, the mode such as magnetometer is obtained degree indirectly, and these modes are required for extra electronic equipment
Auxiliary is completed.
The content of the invention
Regarding to the issue above, the present invention proposes that a kind of high in the clouds calculates the method by speed in tunnel, comprises the following steps：
S1：When vehicle is reached near tunnel, inertial navigation set end uploads information of vehicles to cloud server, packet
Include：Current GPS location point longitude and latitude, (Recommended Minimum Specific GPS/TRANSIT Data, push away GPRMC
Recommend location information) in the information such as velocity amplitude, current time；
S2：Cloud server searches index tunnel described point collection；
S3：Cloud server judges whether vehicle reaches tunnel face, if in tunnel face, then matching distance is recently and probability
Maximum tunnel portal, if not then jumping to step S1 in tunnel face；
S4：Historical speed of the cloud server search vehicle in the same period, with reference to weather and Real-time Traffic Information to tunnel
The feedback of road jam situation, and have run out the tunnel that the vehicle in tunnel reports and show that gps signal is lost by temporal information
Probability travel speed of the rear vehicle in tunnel；If vehicle is for the first time by the tunnel, logical in the period using other vehicles
The speed average in tunnel is crossed as probability travel speed；
S5：Cloud server issues probability travel speed and gives inertial navigation set end by network；
S6：Inertial navigation set end carries out dead reckoning with the probability travel speed for receiving, and calculates the longitude and latitude of the vehicle；
S7：Inertial navigation set end is spaced uploads the longitude and latitude for calculating to cloud server according to set time, and high in the clouds takes
Business device judges position and place tunnel branch of the vehicle in tunnel, judges whether to update downloading speed, if desired re-issues,
Then issue the speed after updating；
S8：Vehicle rolls inertial navigation set end after tunnel regains gps signal away from and reports what vehicle passed through in tunnel
Time, speed calculation data source of the cloud server as other vehicles is fed back to, update all vehicle periods by tunnel
Probability travel speed, update the vehicle period by the probability travel speed in tunnel.
Tunneling data is gathered by offline mode, fixed range is spaced in tunnel and is gathered a positioning described point, for many
Entrance, multiple exit tunnel gather all tunnel branches described point；Tunnel plot is taken out by the connectedness between described point again, is led to
Cross coded system code index tunnel plot and form tunnel described point collection.
The beneficial effect that technical solution of the present invention is realized：
The present invention does not need extra electronic equipment, indexes by being gathered to tunnel information and beyond the clouds, with reference to road network, day
The means such as gas, traffic, vehicle historical information, machine learning extrapolate the forward speed of vehicle diverse location in tunnel, high in the clouds
Server is issued in inertial navigation set by network, helps the upper algorithm of inertial navigation set and end to suppress forward error hair
Dissipate, improve positioning precision.
Brief description of the drawings
Fig. 1 is the schematic diagram that a kind of high in the clouds of the invention calculates the method in tunnel by speed.
Specific embodiment
Below in conjunction with the accompanying drawings and specific embodiment, the present invention is expanded on further, the embodiment of the present invention is only used to illustrate this hair
The protection domain that bright technical scheme is not intended to limit the present invention.
As shown in figure 1, the present invention proposes that a kind of high in the clouds calculates the method by speed in tunnel, comprise the following steps：
S1：When vehicle is reached near tunnel, the current GPS location point longitude and latitude of inertial navigation set end upload vehicle,
The information such as velocity amplitude, current time in GPRMC are to cloud server；
S2：Cloud server searches index tunnel described point collection；
S3：Cloud server judges whether vehicle reaches tunnel face, if in tunnel face, then matching distance is recently and probability
Maximum tunnel portal (according to the distance apart from tunnel face, user's history driving habits and traffic conditions comprehensive descision, for example away from
From certain tunnel face more close to, and the user's history by the tunnel number of times more at most probability it is bigger), if not then being redirected in tunnel face
To step S1；
S4：(historical speed is recorded historical speed of the cloud server search vehicle in the same period by different periods, different
Period speed confidence level is different, wall scroll record weighted), with reference to weather and Real-time Traffic Information to the anti-of tunnel jam situation
Feedback, and tunnel that the vehicle (regaining GPS location information after rolling tunnel away from) in tunnel reports is had run out by time etc.
Information is (by running time t in length of tunnel L and tunnel, you can obtain average speed in tunnel：S=L/t), by mathematical modulo
Type show that gps signal loses probability travel speed of the rear vehicle in tunnel；If vehicle is for the first time by the tunnel, using it
His vehicle is used as probability travel speed in the period by the speed average in tunnel, and (simultaneously non-present is truly fast for probability travel speed
Degree, but in the case of maximum probability and the approximate speed of current true velocity)；
S5：Cloud server issues probability travel speed and gives inertial navigation set end by network；
S6：Inertial navigation set end carries out dead reckoning with the probability travel speed for receiving, and calculates the longitude and latitude of the vehicle；
S7：Inertial navigation set end is spaced uploads the longitude and latitude for calculating to cloud server according to set time, and high in the clouds takes
Business device judges position and place tunnel branch of the vehicle in tunnel, judges whether to update downloading speed, if desired re-issues,
Then issue the speed after updating；
S8：Vehicle rolls inertial navigation set end after tunnel regains gps signal away from and reports what vehicle passed through in tunnel
Time, speed calculation data source of the cloud server as other vehicles is fed back to, update all vehicle periods by tunnel
Probability travel speed, update the vehicle period by the probability travel speed in tunnel.
Tunneling data is gathered by offline mode, one positioning of fixed range (50m or so) collection is spaced in tunnel and is retouched
Point (true longitude and latitude point), all tunnel branches described point is gathered for complicated tunnel (multiple entry, multiple exit)；Again by described point it
Between connectedness take out tunnel plot, it is all by coded system code index by GeoHash or other coded systems
Tunnel plot forms tunnel described point collection.
In the case where being helped without auxiliary equipment, index by being gathered to tunnel information and beyond the clouds, with reference to road network, day
The means such as gas, traffic, vehicle historical information, machine learning extrapolate the forward speed of vehicle diverse location in tunnel, high in the clouds
Server is issued in inertial navigation set by network, helps the upper algorithm of inertial navigation set and end to suppress forward error hair
Dissipate, through actual verification, the forward direction in inertial navigation tunnel effectively calculates that distance can be promoted to more than 70% by length of tunnel 20-30%,
Substantially increase positioning precision.
It is to be noted that probability travel speed in the present invention and non-present true velocity, but in the case of maximum probability and
The approximate speed of current true velocity.
Claims (2)
1. a kind of high in the clouds calculates the method by speed in tunnel, it is characterised in that comprise the following steps：
S1：When vehicle is reached near tunnel, inertial navigation set end uploads the information of the vehicle to cloud server, described
Information include current GPS location point longitude and latitude, GPRMC in velocity amplitude and current time；
S2：The cloud server searches index tunnel described point collection；
S3：The cloud server judges whether the vehicle reaches tunnel face, if in tunnel face, then matching distance recently and
The tunnel portal of maximum probability, if not then jumping to the step S1 in tunnel face；
S4：The cloud server searches for historical speed of the vehicle in the same period, with reference to weather and Real-time Traffic Information
To the feedback of tunnel jam situation, and have run out the tunnel that the vehicle in tunnel reports gps signal is drawn by temporal information
Probability travel speed of the vehicle in tunnel after loss；If the vehicle by the tunnel, uses other cars for the first time
Probability travel speed is used as by the speed average in tunnel in the period；
S5：The cloud server issues the probability travel speed to the inertial navigation set end by network；
S6：The inertial navigation set end carries out dead reckoning with the probability travel speed for receiving, and calculates the vehicle
Longitude and latitude；
S7：The inertial navigation set end is spaced uploads the longitude and latitude for calculating to the cloud server, institute according to set time
State cloud server and judge position and place tunnel branch of the vehicle in tunnel, judge whether to update downloading speed, if
Needs are re-issued, then issue the speed after updating；
S8：The vehicle rolls the inertial navigation set end after tunnel regains gps signal away from and reports the vehicle in tunnel
The time for inside passing through, speed calculation data source of the cloud server as other vehicles is fed back to, updating all vehicles should
The probability travel speed that period passes through tunnel, updates probability travel speed of the described vehicle period by tunnel.
2. high in the clouds according to claim 1 calculates the method by speed in tunnel, it is characterised in that by offline mode
Collection tunneling data, fixed range is spaced in tunnel and gathers a positioning described point, for multiple entry, multiple exit tunnel collection institute
There is tunnel branch described point；Tunnel plot is taken out by the connectedness between the described point again, rope is encoded by coded system
Draw the tunnel plot and form the tunnel described point collection.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710151680.0A CN106840153A (en) | 2017-03-14 | 2017-03-14 | A kind of high in the clouds calculates the method by speed in tunnel |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710151680.0A CN106840153A (en) | 2017-03-14 | 2017-03-14 | A kind of high in the clouds calculates the method by speed in tunnel |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN106840153A true CN106840153A (en) | 2017-06-13 |
Family
ID=59144643
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710151680.0A Pending CN106840153A (en) | 2017-03-14 | 2017-03-14 | A kind of high in the clouds calculates the method by speed in tunnel |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106840153A (en) |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108663700A (en) * | 2018-08-10 | 2018-10-16 | 吉利汽车研究院（宁波）有限公司 | A kind of GPS signal loses processing system and method |
| CN108709553A (en) * | 2018-05-21 | 2018-10-26 | 千寻位置网络有限公司 | The method and apparatus that arbitrary point passes through rate pattern in the estimation tunnel of high in the clouds |
| CN109660318A (en) * | 2018-12-28 | 2019-04-19 | 成都路行通信息技术有限公司 | A kind of speed noise-reduction method based on car networking |
| CN109841078A (en) * | 2017-11-27 | 2019-06-04 | 腾讯科技（深圳）有限公司 | Navigation data processing method and its device, storage medium |
| JP2019132717A (en) * | 2018-01-31 | 2019-08-08 | パイオニア株式会社 | Velocity computation device, velocity computation method, and program |
| CN110967006A (en) * | 2018-09-28 | 2020-04-07 | 巴拿拿科技(香港)有限公司 | Navigation positioning method and device based on tunnel map, storage medium and terminal equipment |
| CN114724298A (en) * | 2022-04-02 | 2022-07-08 | 福建智康云医疗科技有限公司 | Hospital queuing number calling method and system based on artificial intelligence and storage medium |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101201255A (en) * | 2007-12-21 | 2008-06-18 | 四川川大智胜软件股份有限公司 | Vehicle combined navigation system based on intelligent navigation algorithm |
| US20090216439A1 (en) * | 2005-12-27 | 2009-08-27 | Niko Haatainen | Intelligent vehicle tracking |
| CN102741656A (en) * | 2010-02-24 | 2012-10-17 | 歌乐株式会社 | Navigation device with function of estimating position within tunnel |
| CN103499350A (en) * | 2013-09-28 | 2014-01-08 | 长安大学 | High-precision vehicle positioning method for fusing multi-source information under GPS (global positioning system) blind area and device |
| CN104677375A (en) * | 2015-03-18 | 2015-06-03 | 沈阳美行科技有限公司 | System for guiding tunnel road in advance |
-
2017
- 2017-03-14 CN CN201710151680.0A patent/CN106840153A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090216439A1 (en) * | 2005-12-27 | 2009-08-27 | Niko Haatainen | Intelligent vehicle tracking |
| CN101201255A (en) * | 2007-12-21 | 2008-06-18 | 四川川大智胜软件股份有限公司 | Vehicle combined navigation system based on intelligent navigation algorithm |
| CN102741656A (en) * | 2010-02-24 | 2012-10-17 | 歌乐株式会社 | Navigation device with function of estimating position within tunnel |
| CN103499350A (en) * | 2013-09-28 | 2014-01-08 | 长安大学 | High-precision vehicle positioning method for fusing multi-source information under GPS (global positioning system) blind area and device |
| CN104677375A (en) * | 2015-03-18 | 2015-06-03 | 沈阳美行科技有限公司 | System for guiding tunnel road in advance |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109841078A (en) * | 2017-11-27 | 2019-06-04 | 腾讯科技（深圳）有限公司 | Navigation data processing method and its device, storage medium |
| CN109841078B (en) * | 2017-11-27 | 2022-03-04 | 腾讯科技（深圳）有限公司 | Navigation data processing method and device and storage medium |
| JP2019132717A (en) * | 2018-01-31 | 2019-08-08 | パイオニア株式会社 | Velocity computation device, velocity computation method, and program |
| CN108709553A (en) * | 2018-05-21 | 2018-10-26 | 千寻位置网络有限公司 | The method and apparatus that arbitrary point passes through rate pattern in the estimation tunnel of high in the clouds |
| CN108709553B (en) * | 2018-05-21 | 2022-07-08 | 千寻位置网络有限公司 | Method and device for cloud estimation of passing speed model of any point in tunnel |
| CN108663700A (en) * | 2018-08-10 | 2018-10-16 | 吉利汽车研究院（宁波）有限公司 | A kind of GPS signal loses processing system and method |
| CN110967006A (en) * | 2018-09-28 | 2020-04-07 | 巴拿拿科技(香港)有限公司 | Navigation positioning method and device based on tunnel map, storage medium and terminal equipment |
| CN109660318A (en) * | 2018-12-28 | 2019-04-19 | 成都路行通信息技术有限公司 | A kind of speed noise-reduction method based on car networking |
| CN114724298A (en) * | 2022-04-02 | 2022-07-08 | 福建智康云医疗科技有限公司 | Hospital queuing number calling method and system based on artificial intelligence and storage medium |
| CN114724298B (en) * | 2022-04-02 | 2023-12-12 | 福建智康云医疗科技有限公司 | Hospital queuing and calling method and system based on artificial intelligence and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106840153A (en) | A kind of high in the clouds calculates the method by speed in tunnel | |
| US11340091B2 (en) | Storing and accessing traffic data images in a limited bandwidth environment | |
| US10704920B2 (en) | Traffic lane guidance system for vehicle and traffic lane guidance method for vehicle | |
| US11188575B2 (en) | Map updates from a connected vehicle fleet | |
| US10366612B2 (en) | Optimal warning distance | |
| US10145698B2 (en) | Route search system, route search method, and computer program | |
| US20130332402A1 (en) | On-demand suggestion for vehicle driving | |
| CN110849382A (en) | Driving duration prediction method and device | |
| CN106574842B (en) | Navigation system | |
| US20210326699A1 (en) | Travel speed prediction | |
| CN103115626A (en) | Method, device and equipment for calculating congestion information and navigating based on congestion information | |
| Abdelrahman et al. | Crowdsensing-based personalized dynamic route planning for smart vehicles | |
| CN104515530A (en) | Method for optimizing navigation line of long-distance freight vehicle | |
| CN111982145A (en) | Travel path recommendation method, device, equipment and storage medium | |
| US20220219699A1 (en) | On-board apparatus, driving assistance method, and driving assistance system | |
| CN112785072B (en) | Route planning and model training method, device, equipment and storage medium | |
| CN114639263B (en) | Vehicle parking position identification method and device | |
| JP2023005015A (en) | Traffic condition forecasting device and traffic condition forecasting method | |
| CN103900588A (en) | Emergency navigation method and device under traffic jam conditions | |
| Kyaw et al. | Estimating travel speed of yangon road network using gps data and machine learning techniques | |
| KR20220072125A (en) | Method for generating a driving route of an autonomous vehicle in case of an emergency and a server using the same | |
| JP2016217820A (en) | Route guide device | |
| US20230386324A1 (en) | Method for generating traffic flow statistical data by using wiper operation information of vehicle, method for calculating estimated time of arrival of vehicle by using traffic flow statistical data generated using wiper operation information of vehicle, and management server used therefor | |
| CN114435347B (en) | Method, device, equipment and storage medium for determining parking track | |
| JP2017194809A (en) | Traffic jam prediction method and traffic jam prediction device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20170613 |
|
| RJ01 | Rejection of invention patent application after publication |