CN108305484A - A kind of vehicle control syetem and path and method for determining speed - Google Patents
A kind of vehicle control syetem and path and method for determining speed Download PDFInfo
- Publication number
- CN108305484A CN108305484A CN201711479608.7A CN201711479608A CN108305484A CN 108305484 A CN108305484 A CN 108305484A CN 201711479608 A CN201711479608 A CN 201711479608A CN 108305484 A CN108305484 A CN 108305484A
- Authority
- CN
- China
- Prior art keywords
- section
- path
- road
- time
- speed
- 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
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/0968—Systems involving transmission of navigation instructions to the vehicle
-
- 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
- G01C21/34—Route searching; Route guidance
- G01C21/3453—Special cost functions, i.e. other than distance or default speed limit of road segments
- G01C21/3492—Special cost functions, i.e. other than distance or default speed limit of road segments employing speed data or traffic data, e.g. real-time or historical
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
- G06Q10/047—Optimisation of routes or paths, e.g. travelling salesman problem
Abstract
For the present invention based on the normal distribution model of each section congestion, the traffic data of the previous short time period of digging utilization estimates the transit time in each section with statistical method, and then obtain the time driven by departure place to destination by taken path.A degree of automatic Pilot may be implemented in vehicle.The data that the present invention takes are few, so the acquisition communication and processing of data are all very fast, data processing method is simple and efficient, and result feedback is exceedingly fast, and may be implemented instantaneously to handle, cost is extremely low, is easy to promote in vehicle control syetem.
Description
Technical field
The present invention relates to the control strategy technical fields for considering routing information, more particularly to a kind of vehicle control syetem and
Path and method for determining speed.
Background technology
Currently, requirement of the people to trip is higher and higher, it is desirable to arrive at as early as possible, it is desirable to which vehicle being capable of automatic Pilot
Or " foolproof " driving, and city especially megapolis such as Shanghai, Beijing is increasing, road is more and more, central city
Area is various stifled, and road conditions become increasingly complex.
For the Path selection of vehicle control syetem, existing technology basic flow is in static treatment or the letter of various navigation
As a result single real-time selection usually differs too many with practical, data processing is extremely rough, and accuracy rate is very low, can not be very
The good previous traffic data of excavation, can not arrive in the shortest time.I application No. is 2017111930629
Application proposes a solution, and the present invention continues optimization to the program and promotes.
Many chance phenomena can be described with normal distribution or approximate description, when observation is enough, great Liang Sui
Machine phenomenon with normal distribution describes that reliable prediction can be made.
Normal distribution（Normal distribution）Also known as Gaussian Profile（Gaussian distribution）, it is one
It is a in all very important probability distribution in the fields such as mathematics, physics and engineering, have great shadow at statistical many aspects
Ring power.If stochastic variable X one mathematic expectaion of obedience is μ, variance σ2Gaussian Profile, be denoted as
X∼N(μ,σ2),
Its probability density function is
The desired value μ of normal distribution determines that its position, standard deviation sigma determine the amplitude of distribution.Because its curve is bell-like, because
This people is often referred to as bell curve again.
The a bit fabulous statistical property of normal distribution:
（1）Its density function is symmetrical about mean value,
（2）Its data high concentration is near mean μ, P（-σ<x-μ<σ）=68%, namely nearly 70% data distribution is in section（μ-
σ, μ+σ）.
Invention content
The object of the present invention is to provide a kind of vehicle control syetem and path and method for determining speed, discover and use previous friendship
Logical data, provide the different road speed of different sections of highway, find out the shortest path of used time from origin to destination and
Speed ensures that user arrives within the shortest time.
To achieve the above object, the present invention uses following technical scheme：
A kind of path and method for determining speed, including step：
（1）Geographical location information and temporal information are obtained, that is, obtains departure place, the geographical location information of destination and when setting out
Between temporal information；
（2）Obtain all possible paths, i.e., according to geographical data bank, departure place and the geographical location information of destination, find out by
Departure place is to the be possible to pass in destination:Path 1, path 2 ..., path n；
（4）It determines the specific section in each path, that is, determines the specific section in path 1, the specific section ... in path 2, path n
Specific section；
（5）Determine each time on road tij, that is, the normal distribution model of section congestion is utilized, be possible to pass is calculated
Every a road section used in the time, tijTime used in the jth section of expression path i, i value ranges are 1 ..., n, and j value ranges are
1,…,m；
（6）Determine each path used time T1, T2..., Tn, i.e., it is by the sum of time calculating used in each section of each path i：Ti=
ti1+ti2+…+tim；
（7）Take T1, T2..., TnMinimum value TaIt is final roadway to choose the paths a to get the paths destination path a namely vehicle
Diameter, and it is running speed to choose corresponding speed.
The normal distribution model of the section congestion, to certain a road section, method for building up is:
S01 determines time information：D points, a, b, c, d when e a month b day c, e is determined；
S02 obtains the road section length s by geographical data bank；
The motor vehicle average speed in d points of sections when c from being obtained first 50 days in highway traffic data library S03, obtains one group 50
A speed data；
The time required to S04 is obtained the complete section of motor line by t=s/v；
S05 takes μ=(t1+t2+t3+…+t50)/50;σ2=(t1 2 +t2 2+t3 2+…+t50 2)/ 50-μ2, remember the time X by section,
X obey a mathematic expectaion be μ, standard variance σ2Normal distribution, be denoted as：
X∼N(μ,σ2),
μ, σ are substituted into the formula of probability density function by S06;
S07 determines t, specially：T is found out by normal distribution database or normal distribution computing module0So that P（x<=t0）=
0.9；t0As in c d points, the required time that the complete section of motor line is estimated.
The geographical location information can be obtained from geographical data bank, and geographical data bank includes road latitude and longitude coordinates
Information, road name, link length, building latitude and longitude coordinates, building title etc., the geographical data bank is according to existing geography
Information is established.
Each section of the pass is established rules then really, and the road name per a road section is single, and includes starting point,
Do not include terminal, the last item section includes starting and terminal point.
The highway traffic data library, including the long road of link name, road, each moment is in the flat of two-way various vehicles
Equal speed.
Really the timing carves rule information and is, the initial time of subsequent section is before the initial time of preceding a road section adds
The transit time of a road section.
50 speed datas are respectively first 1 day, 2 days first, above-mentioned c on the preceding 3rd, 4,5 ... 50 when d points in the section
Motor vehicle average overall travel speed v1, v2..., v50。
The motor vehicle average speed in section, the moment that the section can be obtained by the speed camera in the section are several
Then vehicle running speed takes its average value.
A kind of vehicle control syetem, including vehicle command system, vehicle control system, highway traffic data library, geographical number
According to library, normal distribution computing module, normal distribution database；Vehicle control system can call each database, normal distribution meter
Module is calculated, is communicated with vehicle command system, data are handled；Wherein normal distribution database can by above-mentioned probability density function with
And parameter μ, σ2, Probability p provides above-mentioned t0。
The vehicle command system, including input/output module, wherein input module can include departure place, mesh with typing
Ground information, output module can show vehicle control system processing data as a result, including suggest path, velocity correlation letter
Breath.
Advantages of the present invention：
The present invention is based on the normal distribution model of each section congestion, the traffic number of the previous short time period of digging utilization
According to specific to particular moment, specific road section estimates each section according to 50 days previous traffic datas with statistical method
Transit time, and then the time driven by departure place to destination by taken path is obtained, vehicle may be implemented a degree of
Automatic Pilot.
The present invention, which can concede vehicle, more Model choices, and the suggestion speed per a road section can all provide, driver
It is travelled by this speed, vehicle can pass through all the way, because the present invention has counted crossing when calculating the time.
The present invention especially pays attention to selecting at the time of section using the newest transit time data of the preceding a road section calculated in time
Taking realizes Dynamic Programming.
Present invention determine that path be by the most short determination of vehicle line haul hour, rather than it is previous simply with passive distance most it is short in advance
It determines, ensure that the used time is most short, increase feasibility.
In addition, the data that the present invention takes are few, so the acquisition communication and all very fast, the data processing of processing of data
Mode is simple and efficient, and result feedback is exceedingly fast, and may be implemented instantaneously to handle and provide as a result, cost is extremely low, be easy to vehicle-mounted
It is promoted in control system.
Specific implementation mode
Embodiment 1：
For example vehicle command system is connected to instruction for 23 seconds 6 minutes at 5 points in afternoon on March 4th, 2017 from Zhongshan Road 8 to Yan'an road 7
Number.
So vehicle control system will be done as follows：
（1）The entitled the Yellow River mansion of building on Yan'an road 7 is transferred according to geographical data bank, latitude and longitude coordinates are（8 ° of east longitude, north
9 ° of latitude）, transfer the entitled Zhongshan Hotel of building of Zhongshan Road 8, latitude and longitude coordinates are（10 ° of east longitude, 11 ° of north latitude）It is set out
Ground, destination geographical location information；
（2）Zhongshan Hotel is easy to get by geographical data bank（10 ° of east longitude, 11 ° of north latitude）To the Yellow River mansion（8 ° of east longitude, 9 ° of north latitude）
7 different predominating paths, specially path 1, path 2, path 3, path 4, path 5；Path 6, path 7；
(3) we illustrate how to determine the section in path by taking path 1 as an example：Path 1 is made of 3 sections：Yan'an 1
Road, 2 tunnel of Yan'an, 3 tunnel of Yan'an；1 section of Yan'an, 2 section of Yan'an include starting point crossing, and 3 section of Yan'an includes starting point crossing and end
Point crossing, crossings all so all by calculation to and only let it pass primary；
Using the normal distribution model of section congestion, time t used in every a road section in path 1 is calculated1,1, t1,2, t1,3;
(4) with the changed time t in 1 tunnel of the 1st section Yan'an1,1For illustrate how to establish the normal distribution mould of certain a road section congestion
Type, specific method are：
S01 was by 6 minutes when 5 points of 23 seconds 6 minutes determining time information 4 days 17 March in 2017 of afternoon 4 day March 2017 departure time；
Also 6 points are rounded up for 23 seconds to obtain 6 points；
S02 obtains 1 tunnel length s=2 kilometer of section Yan'an by geographical data bank；
S03 is according to highway traffic data library, 66 machine for being segmented 1 tunnels of Yan'an when dividing i.e. September in 2017 3 days 17 when obtaining preceding 1 day 17
Motor-car average speed:6 divide four kinds of vehicle running speeds when obtaining September in 2017 3 days 17 by the speed camera on 1 tunnel of Yan'an,
Respectively：30,22,18,26, take its average value（30+22+18+26）/ 4=24, so v1=24 kilometers/hour；It obtains first 2 days
The motor vehicle average overall travel speed V on 66 pavement branch sections Yan'an, 1 tunnels when dividing i.e. September in 2017 2 days 17 when 172=25 kilometers/hour ...
The motor vehicle average overall travel speed V on 6 pavement branch sections Yan'an, 1 tunnel when obtaining the preceding same day 17 on the 50th50=25 kilometers/hour
The first n days（1=<n<=50）6 divide v kilometers/hour of average overall travel speed when motor vehicle 17
Preceding V on the 1st1=24
Preceding V on the 2nd2=25
. .
. .
Preceding V on the 30th30=24
. .
. .
Preceding V on the 50th50=20.7
S04 obtains t by t=s/v1The driving of 6 extension set motor-cars has been gone 1 road of Yan'an and has been taken at=2/24 hour=5 minutes, i.e., first 1 day 17
Between, 6 divide t the time required to the complete 1 tunnel section of Yan'an of motor line at first 2 days 172=4.8 minutes, in this way, obtaining preceding 3,4,5 ..., 50
6 divide t the time required to complete 1 tunnel of Yan'an of motor line when day 173,t4,…,t50;
ti t1, t2, t3, t4, t5, … , t30, …, t 50
Time/minute 5,4.8,4.9,5.2,5.1 ..., 5 ..., 5.8
S05 is by μ=(t1+t2+t3+…+t50)/50=(5+4.8+4.9+ ...+5.8)/50=5,
σ2=(t1 2 +t2 2+t3 2+…+t50 2)/50-μ2=(52+4.82 +4.92+ …+5.82)/50-52=8.41,
It is X the time required to remembering complete 1 tunnel of Yan'an of motor line, it is μ=5, variance σ that X, which obeys a mathematic expectaion,2=8.41 normal state
Distribution, i.e. X~N (5,8.41)；
S06 substitutes into μ=5, σ=2.9
=, obtain specific the formula of probability density function;
S07 is by P（x<= t0）=0.9 seeks t0, specially
Make P（x<= t0）=0.9=
T is calculated by normal distribution computing module0=9 minutes, t0As 6 complete 1 road of Yan'an of motor line is divided to estimate at 17
Time, t1,1The accuracy rate of=9 minute estimated time is 90%, that is, motor vehicle is in the probability on complete 1 tunnel of Yan'an of 9 minutes experts
It is 90%, or says that certainty is 90%.
t1,2,t1,3The same t of algorithm1,1, do not exist together and be only that the moment：
t1,1 6 divide when September in 2017 4 days 17,
T again1,1=9 minutes, so：
t1,215 divide when September in 2017 4 days 17
T is calculated using the normal distribution model of above-mentioned section congestion1,2When, 15 divide when time information takes September in 2017 4 days 17,
And then calculate t1,2=10 minutes, then similar
t1,325 divide when September in 2017 4 days 17
T is calculated using the normal distribution model of above-mentioned section congestion1,3When, 16 divide when time information takes September in 2017 4 days 17,
And then calculate t1,3=20 minutes；
(7) by the changed time t in 1 tunnel of the 1st section Yan'an1,1=9 minutes, the changed time t in 2 tunnel of the 2nd section of Yan'an1,2=10 minutes, the 3rd section
The changed time t in 3 tunnel of Yan'an1,3=20 minutes;
So transit time T of route 11=t1,1+t1,2+t1,3=9+10+20=39 minute.
Because route 1 is made of 3 sections, and the used time that the probability per a road section is 0.9 is respectively within 9 minutes 10
Within minute, within 20 minutes, so probability of the used time of whole route no more than 39 minutes is 0.9*0.9*0.9;
Similar, we can calculate path 2 ..., the transit time in path 7, T1, T2..., T7, as shown in the table：
Ti T1 , T2 , T3 , T4 , T5, T6, T7,
Unit/minute 39,59,47,60,57,44,54,
(8) T1=39 is minimum, therefore it be destination path namely path selection 1 for final planning driving path, corresponding each road to take path 1
Section be 1 tunnel of Yan'an, 2 kilometers/5 minutes=24 kilometers/hour, vd=2/9 minute=13.3 kilometers/hour QUOTE 13 is public
In/hour, vdFor speed lower bound namely vehicle, speed is not less than 13 kilometers/hour under steam, the average speed in entire section
Degree is 24 kilometers/hour；
And the average speed on 2 tunnel of Yan'an is respectively 25 kilometers/hour, speed is not less than 13 kilometers/hour to vehicle under steam,
And the average speed on 3 tunnel of Yan'an is respectively 30 kilometers/hour, speed is not less than 21 kilometers/hour to vehicle under steam；Vehicle
These paths and velocity information are submitted vehicle command system and are shown to driver by control system.
Path that driver prompts according to vehicle command system and speed were from Zhongshan Hotel, you can at about 39 minutes
Interior arrival the Yellow River mansion.In fact, if technical feasibility, vehicle can only be converted in turning and section with automatic Pilot
When need the participation of driver.
Claims (10)
1. a kind of path and method for determining speed, which is characterized in that including step：
（1）Geographical location information and temporal information are obtained, that is, obtains departure place, the geographical location information of destination and when setting out
Between temporal information；
（2）Obtain all possible paths, i.e., according to geographical data bank, departure place and the geographical location information of destination, find out by
Departure place is to the be possible to pass in destination:Path 1, path 2 ..., path n；
（4）It determines the specific section in each path, that is, determines the specific section in path 1, the specific section ... in path 2, path n
Specific section；
（5）Determine each time on road tij, that is, the normal distribution model of section congestion is utilized, be possible to pass is calculated
Time used in per a road section, tijTime used in the jth section of expression path i, i value ranges are 1 ..., n, and j value ranges are
1,…,m；
（6）Determine each path used time T1, T2..., Tn, i.e., it is by the sum of time calculating used in each section of each path i：Ti=
ti1+ti2+…+tim；
（7）Take T1, T2..., TnMinimum value TaIt is final planning driving path to choose the paths a to get the paths destination path a namely vehicle,
And it is running speed to choose corresponding speed.
2. the normal distribution model of section congestion according to claim 1, to certain a road section, which is characterized in that congestion
Normal distribution model method for building up is:
S01 determines time information：D points, a, b, c, d when e a month b day c, e is determined；
S02 obtains the road section length s by geographical data bank；
The motor vehicle average speed in d points of sections when c from being obtained first 50 days in highway traffic data library S03, obtains one group 50
A speed data；
The time required to S04 is obtained the complete section of motor line by t=s/v；
S05 takes μ=(t1+t2+t3+…+t50)/50;σ2=(t1 2 +t2 2+t3 2+…+t50 2)/ 50-μ2, remember the time X by section,
X obey a mathematic expectaion be μ, standard variance σ2Normal distribution, be denoted as：
X∼N(μ,σ2),
μ, σ are substituted into the formula of probability density function by S06;
S07 determines t, specially：T is found out by normal distribution database or normal distribution computing module0So that P（x<=t0）=
0.9；t0As in c d points, the required time that the complete section of motor line is estimated.
3. geographical location information according to claim 1, which is characterized in that can be obtained from geographical data bank, geographical number
Include road latitude and longitude coordinates information, road name, link length, building latitude and longitude coordinates, building title etc. according to library, describedly
Managing database is established according to existing geography information.
4. each section of pass according to claim 1 is established rules then really, it is characterised in that：Road per a road section
Title is single, and includes starting point, does not include terminal, the last item section includes starting and terminal point.
5. highway traffic data library according to claim 2, it is characterised in that：Including link name, the long road of road, per for the moment
It is engraved in the average speed of two-way various vehicles.
6. determining time information rule according to claim 2 is, the initial time of subsequent section is rising for preceding a road section
Moment beginning adds the transit time of preceding a road section.
7. 50 speed datas according to claim 2, which is characterized in that 50 speed datas are respectively first 1 day, preceding 2
The d points of motor vehicle average overall travel speed v in section when day, above-mentioned c on the preceding 3rd, 4,5 ... 501, v2..., v50。
8. the motor vehicle average speed in the section according to claim 2, which is characterized in that can be by the speed in the section
Camera obtains the moment several vehicle running speeds in the section, then takes its average value.
9. a kind of vehicle control syetem, which is characterized in that including vehicle command system, vehicle control system, highway traffic data
Library, geographical data bank, normal distribution computing module, normal distribution database；Vehicle control system can call each database, just
State distribution calculation module is communicated with vehicle command system, handles data；Wherein normal distribution database can be close by above-mentioned probability
Spend function and parameter μ, σ2, Probability p provides above-mentioned t0。
10. the vehicle command system described in claim 9, which is characterized in that including input/output module, wherein input module can
Include departure place, destination information with typing, output module can show vehicle control system processing data as a result, including building
Discuss path, velocity correlation information.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711479608.7A CN108305484A (en) | 2017-12-29 | 2017-12-29 | A kind of vehicle control syetem and path and method for determining speed |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711479608.7A CN108305484A (en) | 2017-12-29 | 2017-12-29 | A kind of vehicle control syetem and path and method for determining speed |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN108305484A true CN108305484A (en) | 2018-07-20 |
Family
ID=62868257
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201711479608.7A Pending CN108305484A (en) | 2017-12-29 | 2017-12-29 | A kind of vehicle control syetem and path and method for determining speed |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108305484A (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20040023902A (en) * | 2002-09-12 | 2004-03-20 | 에스케이 주식회사 | Apparatus for producing traffic information and method thereof, and traffic information providing system |
| CN102353381A (en) * | 2011-07-06 | 2012-02-15 | 广东威创视讯科技股份有限公司 | Method and device for obtaining optimal path to hurry to scene of traffic accident |
| CN102393206A (en) * | 2011-10-19 | 2012-03-28 | 北京世纪高通科技有限公司 | Path planning method and device |
| CN103077610A (en) * | 2012-12-31 | 2013-05-01 | 清华大学 | Road trip time estimating method and system |
| CN103134505A (en) * | 2011-11-25 | 2013-06-05 | 天眼卫星科技有限公司 | Route planning system and method thereof |
-
2017
- 2017-12-29 CN CN201711479608.7A patent/CN108305484A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20040023902A (en) * | 2002-09-12 | 2004-03-20 | 에스케이 주식회사 | Apparatus for producing traffic information and method thereof, and traffic information providing system |
| CN102353381A (en) * | 2011-07-06 | 2012-02-15 | 广东威创视讯科技股份有限公司 | Method and device for obtaining optimal path to hurry to scene of traffic accident |
| CN102393206A (en) * | 2011-10-19 | 2012-03-28 | 北京世纪高通科技有限公司 | Path planning method and device |
| CN103134505A (en) * | 2011-11-25 | 2013-06-05 | 天眼卫星科技有限公司 | Route planning system and method thereof |
| CN103077610A (en) * | 2012-12-31 | 2013-05-01 | 清华大学 | Road trip time estimating method and system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106297357B (en) | Real-time route planning and POI information searching system and method based on car networking | |
| CN100583182C (en) | Vehicle navigation method based on multi-information sources dynamic traffic information | |
| CN104658297B (en) | A kind of center type dynamic route guidance method based on Sarsa study | |
| CN106548646A (en) | Road information service system and method when being blocked up based on the city that mist is calculated | |
| CN105702073B (en) | A kind of dynamic steering air navigation aid based on road network decision point journey time index value | |
| WO2015151034A1 (en) | Storing and accessing traffic data images in a limited bandwidth environment | |
| CN108303110A (en) | A kind of vehicle control syetem and path velocity determine method | |
| WO2022166239A1 (en) | Vehicle travel scheme planning method and apparatus, and storage medium | |
| CN102708698A (en) | Vehicle optimal-path navigation method based on vehicle internet | |
| CN108303978A (en) | A kind of dynamic route and method for determining speed of Vehicular automatic driving | |
| Li et al. | Traffic signal timing optimization in connected vehicles environment | |
| CN105489000A (en) | Night-shift bus stop and path selection method | |
| CN104680829B (en) | Bus arrival time prediction system and method based on multi-user cooperation | |
| CN107490384A (en) | A kind of optimal static path system of selection based on city road network | |
| CN108305489A (en) | A kind of vehicle control syetem and dynamic route speed planning method | |
| CN105806355A (en) | Green vehicle path navigation system and method | |
| CN105260551B (en) | Car networking interior joint distribution character analysis method | |
| CN107883972A (en) | Running time dynamic pushing method and device | |
| CN108303109A (en) | A kind of safety-protection system alert processing route planning system and normal state method | |
| CN107610498A (en) | A kind of automobile trip of city traffic peak period automatically selects route methods | |
| CN108305484A (en) | A kind of vehicle control syetem and path and method for determining speed | |
| CN108305487A (en) | A kind of vehicle control syetem and path and speed planning method | |
| CN108303977A (en) | A kind of path of Vehicular automatic driving and method for determining speed | |
| CN108303973A (en) | A kind of monthly control strategy of the dynamic route of vehicle | |
| CN108305486A (en) | A kind of state of an illness processing path planing method of first-aid system |
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 | ||
| WD01 | Invention patent application deemed withdrawn after publication | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20180720 |