CN106097718B - Signalized intersections region transit time method of estimation based on GPS data - Google Patents
Signalized intersections region transit time method of estimation based on GPS data Download PDFInfo
- Publication number
- CN106097718B CN106097718B CN201610708476.XA CN201610708476A CN106097718B CN 106097718 B CN106097718 B CN 106097718B CN 201610708476 A CN201610708476 A CN 201610708476A CN 106097718 B CN106097718 B CN 106097718B
- Authority
- CN
- China
- Prior art keywords
- data
- bicycle
- signalized intersections
- time
- road junction
- 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.)
- Expired - Fee Related
Links
Classifications
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0108—Measuring and analyzing of parameters relative to traffic conditions based on the source of data
- G08G1/0112—Measuring and analyzing of parameters relative to traffic conditions based on the source of data from the vehicle, e.g. floating car data [FCD]
Landscapes
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Position Fixing By Use Of Radio Waves (AREA)
- Navigation (AREA)
Abstract
The signalized intersections region transit time method of estimation based on GPS data that the invention discloses a kind of, includes the following steps：Step 1：The GPS data of all Floating Cars on echo signal intersection is obtained, floating car data collection is built；Step 2：Determine signalized intersections region into road junction biggest impact range Lin；Step 3：Determine that signalized intersections go out road junction biggest impact range Lout；Step 4：Data at the time of bicycle i is obtained by signalized intersections import endpointStep 5：Obtain data at the time of bicycle i is exported by signalized intersections at endpointStep 6：Transit time ts of the calculating bicycle i in signalized intersections regioni.Method provided by the invention consider vehicle signalized intersections operation characteristic, the bicycle transit time in signalized intersections region is effectively estimated, therefore this method is a kind of bicycle transit time method of estimation suitable for signalized intersections and with degree of precision, to lay the foundation with design for the delay of intersection estimation, making rational planning for for intersection.
Description
Technical field
The present invention relates to City ITS technical field, especially a kind of estimation signalized intersections region bicycle is logical
The method of row time, by GPS data establish corresponding model estimate bicycle signalized intersections transit time.
Background technology
Signalized intersections are common one of urban transportation facilities, and link characteristics complex is urban highway traffic
Bottleneck road, the even more emphasis and difficult point of traffic control.The delay time at stop in signalized intersections region is evaluation intersection fortune
One of the efficiency index of line efficiency and service level, and bicycle transit time is the incision for calculating vehicle and being delayed at the intersection
Point.
It is existing mostly to be estimated using place traffic parameter data as model parameter about intersection delay model.So
And fixed detector is not only installed and maintenance cost is high, but also also will produce negative effect to traffic environment.Further, since
The control action of signal lamp causes the periodical stagnation of movement of vehicle, into road junction at often exist vehicle queue waiting phenomenon.Work as wagon flow
Measure larger, when signal lamp region saturation degree is larger, the true impact range of signal lamp is often more than at broadening variation.Obviously,
It only is difficult to accurately estimate with the traffic parameter data in a certain place and obtains the transit time of signalized intersections region vehicle.
As GPS technology is applied to field of traffic, has the advantages that the construction period is shorter, development cost is more low, become
One of most promising traffic information collection means.On the one hand, GPS technology need not install hardware facility on road,
It is easily assembled to and carries out simultaneously system extension and safeguard, it is more practical compared with fixed detector；On the other hand, area coverage
Wide and data acquisition high efficiency, real-time provide a kind of new method for estimation signalized intersections region transit time.
Currently, commonly the bicycle section transit time method of estimation based on GPS data mainly has Velocity-time integration method
With position-temporal interpolation method.Velocity-time integration method, be it is assumed that sample vehicle is at the uniform velocity travelled in each GPS point near zone,
What operating status cannot occur to propose under conditions of larger fluctuation, and in signalized intersections region, due to the presence of signal lamp, warp
It often will appear the case where vehicle queue waits for, vehicle start and stop are more frequent, and instantaneous velocity has larger fluctuation in a short time, adopt
Apparent error is may result in Velocity-time integration method.Position-temporal interpolation method, due to GPS positioning point not necessarily just with
Section starting point is overlapped with terminating point, it is existing research mostly using linear interpolation method obtain vehicle at the endpoint of two, section when
Carve data.Paper " the natural Link Travel Time Estimation method based on GPS Floating Cars " when estimating bicycle Link Travel Time,
The traveling assuming that vehicle remains a constant speed between two adjacent GPS data points calculates vehicle using linear interpolation method and passes through section two
Data at the time of a endpoint.But for signalized intersections region, vehicle repeatedly starting and stopping and acceleration and deceleration, at this time it will again be assumed that vehicle is protected
Large error will obviously be had by holding at the uniform velocity traveling.
Therefore, it is necessary to consider that vehicle in the operation characteristic of signalized intersections, establishes a kind of signalized intersections of being not only suitable for
Bicycle transit time method of estimation with degree of precision again, to lay the foundation for the delay of intersection estimation.
Invention content
The purpose of the present invention is to propose to the signalized intersections region transit time methods of estimation based on GPS data；This method
The bicycle transit time in signalized intersections region is effectively estimated.
The purpose of the present invention is achieved through the following technical solutions：
Signalized intersections region transit time method of estimation provided by the invention based on GPS data, includes the following steps：
Step 1：The GPS data of all Floating Cars on echo signal intersection is obtained, floating car data collection is built；
Step 2：Determine signalized intersections region into road junction biggest impact range Lin；
Step 3：Determine that signalized intersections go out road junction biggest impact range Lout；
Step 4：Data at the time of bicycle i is obtained by signalized intersections import endpoint
Step 5：Obtain data at the time of bicycle i is exported by signalized intersections at endpoint
Step 6：Transit time ts of the calculating bicycle i in signalized intersections regioni。
Further, the GPS data of the Floating Car in the step 1 on echo signal intersection obtains according to the following steps：
S11：The coordinate of signal lamp is calibrated on the electronic map；
S12：Map match is carried out using the vehicle GPS data in a period of time；
S13：All matchings are obtained in the vehicle GPS data where signal lamp on section, build floating car data collection.
Further, in the step 2 vehicle in signalized intersections into road junction coverage LinIt calculates according to the following steps：
S21：Take the GPS data of all Floating Cars on more days target signalized intersections；
S22：Bicycle deceleration point position in this time is calculated using deceleration point method, and calculates deceleration point between stop line
Distance；
S23：Using hierarchical clustering method, the biggest impact range into signal lamp at road junction is sought.
Further, the hierarchical clustering method seeks the biggest impact range into signal lamp at road junction, and concrete operation step is such as
Under：
S231：The deceleration point of more vehicles is subjected to hierarchical clustering to N number of distance between stop line, n classes is obtained, calculates every
The cluster centre of class；
S232：The weight of each data in each cluster section is determined according to following formula：
In formula, mcTo fall into the queuing in C classes apart from quantity, c=1,2 ... n；
S233：It is calculated into signal lamp biggest impact range at road junction according to following formula：
Wherein, LinFor into signal lamp biggest impact range at road junction；fcFor the weight of data in the C of section,For section C's
Average value.
Further, vehicle goes out road junction biggest impact range in signalized intersections and takes at all directions exit ramp in the step 3
It is downstream the biggest impact range of signal lamp at exit ramp at 150-170m.
Further, data at the time of bicycle i is by signalized intersections import endpoint in the step 4According to the following steps
It calculates：
S41：Obtain bicycle i data at the time of into neighbouring two GPS positionings point extraction at the endpoint of road junctionFormula
In, j=0 or 1,0 represents upstream data, and 1 represents downstream data；
S42：Data at the time of using interpolation calculation bicycle i at import endpoint, formula are as follows：
In formula,Indicate data at the time of bicycle i is at crossing inlet endpoint；s1Indicate intersection into road junction and bicycle i
In the range difference of intersection upstream GPS positioning point；s2Indicate bicycle i in intersection downstream GPS positioning point and intersection into road junction
Range difference；Indicate bicycle i data at the time of crossing inlet endpoint upstream；Indicate bicycle i at crossing inlet end
Data at the time of point downstream.
Further, data at the time of bicycle i is exported by signalized intersections at endpoint in the step 5According to the following steps
It calculates：
S51：The floating car data and progress (L for taking the crossing downstream in the bicycle i place periods allO,VO) relation curve
Function V2The least square fitting of=kL+b obtains the parameter of fitting function；
Wherein, Vo indicates that the instantaneous velocity in GPS data, Lo indicate vehicle away from 'STOP' line ahead, and k, b are constant, L>0；
S52：Take the floating car data (l that bicycle i is nearest apart from outlet porto,vo), it is bent using relationship according to following formula
Line function V2The speed vs of=kL+b calculating bicycle i in outletout：
Wherein, loutTo export to the distance of stop line；
S53：Bicycle i is calculated in section S according to following formula3Journey time t3：
S54：At the time of bicycle i being calculated according to following formula by outlet
Wherein,For the floating car data nearest apart from outlet port at the time of data.
Further, transit time ts of the bicycle i in signalized intersections region in the step 6iIt is calculated according to following formula：
Wherein, tiTransit times of the expression bicycle i in signalized intersections region.
By adopting the above-described technical solution, the present invention has the advantage that：
Method provided by the invention consider vehicle signalized intersections operation characteristic, to the list in signalized intersections region
Vehicle transit time is effectively estimated, therefore this method is that a kind of bicycle for being suitable for signalized intersections and having degree of precision is logical
Row Time Estimation Method, to for intersection delay estimation, intersection make rational planning for and design lays the foundation.
Other advantages, target and the feature of the present invention will be illustrated in the following description, and to a certain degree
On, based on will be apparent to those skilled in the art to investigating hereafter, or can be from the present invention's
It is instructed in practice.The target and other advantages of the present invention can be embodied and obtained by following specification.
Description of the drawings
The description of the drawings of the present invention is as follows.
Fig. 1 be present invention determine that signalized intersections into road junction biggest impact range flow chart；
Fig. 2 is signalized intersections schematic diagram；
Fig. 3 is that the present invention is based on the flow charts of the signalized intersections bicycle transit time method of estimation of GPS data.
Specific implementation mode
The invention will be further described with reference to the accompanying drawings and examples.
As shown in Figure 1 to Figure 3, Fig. 3 is that the signalized intersections bicycle provided in an embodiment of the present invention based on GPS data passes through
Time Estimation Method flow chart；Signalized intersections bicycle transit time method of estimation provided in this embodiment based on GPS data,
Include the following steps：
Step 1：Vehicle is obtained in the vehicle GPS data where signalized intersections on section：
(1) coordinate of signal lamp is calibrated on the electronic map；
(2) map match is carried out using the vehicle GPS data in a period of time；
(3) all matchings are obtained in all vehicle GPS data where the signal lamp on section, build floating car data
Collection.
Step 2：Determine signalized intersections region into road junction biggest impact range Lin, signal cross mouth region is passed through according to vehicle
The operation characteristic in domain can generally pass through at the uniform velocity-deceleration-process of parking-acceleration 4 it is found that vehicle passes through signalized intersections, because
The maximum magnitude that the position that this vehicle reduces speed now i.e. vehicle is influenced by signal lamp, Fig. 1 are determination provided in an embodiment of the present invention
Signalized intersections specifically include following steps into road junction biggest impact range flow chart：
(1) take more days all Floating Cars in the GPS data where signalized intersections on section；
(2) bicycle deceleration point position in this time is calculated using deceleration point method, and calculates deceleration point between stop line
Distance；
(3) the distance between the deceleration point of more vehicles to stop line (number N) is subjected to hierarchical clustering, obtains n classes, calculated
Go out the cluster centre of every class.
(4) according to Great possibility there is relatively high confidence level, small probability event to have relatively small confidence level
Principle, determine the weight that each clusters.If the queuing fallen into C classes is m apart from quantityc, c=1,2 ... n, by returning
One changes, the weight of each data in section
(5) then as follows into signal lamp biggest impact range formula at road junction：
Wherein LinFor into signal lamp biggest impact range at road junction；fcFor the weight of data in the C of section,For the flat of section C
Mean value.
Step 3：Determine that signalized intersections straight trip, left-hand rotation, right-hand rotation direction go out road junction biggest impact range, according to level-crossing
The range of mouth planning and design, the present invention take direction outlet thus at downstream 150-170m calculating at all directions exit ramp respectively
The biggest impact range of signal lamp at road.The present embodiment can use 160m.
Step 4：Data at the time of bicycle i is calculated by signalized intersections import endpointIn crossing upstream section, by
It is more in the GPS data of the retardation of signal lamp, single vehicle, therefore, directly utilize linear interpolation method to vehicle in import
The time of running acquisition influence it is little.Fig. 2 is signalized intersections schematic diagram.Specifically, including the following steps：
(1) bicycle i data at the time of into neighbouring two GPS positionings point extraction at the endpoint of road junction are obtained(j=0
Or 1,0 represents upstream data, and 1 represents downstream data)；
(2) data at the time of using interpolation calculation bicycle i at import endpoint, formula are as follows：
Step 5：Calculate data at the time of bicycle i is exported by signalized intersections at endpointIn crossing downstream road section, vehicle
Travel speed it is more stable, variation less and has certain rule, but the GPS data of single vehicle is less, and single vehicle
By various disturbing factors, travel speed is it is possible that unstable phenomenon so that single sample data cannot be true
Reflect the whole scene of wagon flow on section.Therefore, the present invention establishes road using all floating car datas in a hour period
The model of downstream road section Vehicle Speed mouthful nearby, at the time of then calculating vehicle further according to this model and pass through outlet.
Specifically, including the following steps：
(1) floating car data for taking the crossing downstream in the bicycle i place periods all carries out (LO,VO) relation curve letter
Number V2(wherein k, b are constant, L to=kL+b>0) least square fitting obtains the parameter of its fitting function.
(2) floating car data (l that bicycle i is nearest apart from outlet port is takeno,vo), it is known that export to the distance of stop line
lout, utilize relation curve function V2The speed vs of=kL+b calculating bicycle i in outletoutFor：
(3) so, bicycle i is in section s3Journey time t3For：
(4) so, at the time of bicycle i is by outlet in Fig. 2For：
Wherein,For the floating car data nearest apart from outlet port at the time of data.
Step 6：Transit time ts of the calculating bicycle i in signalized intersections regioni, can be calculated by following formula：
Finally illustrate, the above examples are only used to illustrate the technical scheme of the present invention and are not limiting, although with reference to compared with
Good embodiment describes the invention in detail, it will be understood by those of ordinary skill in the art that, it can be to the skill of the present invention
Art scheme is modified or replaced equivalently, and without departing from the objective and range of the technical program, should all be covered in the present invention
Protection domain in.
Claims (6)
1. the signalized intersections region transit time method of estimation based on GPS data, it is characterised in that：Include the following steps：
Step 1：The GPS data of all Floating Cars on echo signal intersection is obtained, floating car data collection is built；
Step 2：Determine signalized intersections region into road junction biggest impact range Lin；
Step 3：Determine that signalized intersections go out road junction biggest impact range Lout；
Step 4：Data at the time of bicycle i is obtained by signalized intersections import endpoint；
Step 5：Obtain data at the time of bicycle i is exported by signalized intersections at endpoint；
Step 6：Transit time ts of the calculating bicycle i in signalized intersections regioni；
In the step 2 vehicle in signalized intersections into road junction coverage LinIt calculates according to the following steps：
S21：Take the GPS data of all Floating Cars on more days target signalized intersections；
S22：Bicycle deceleration point position in more days is calculated using deceleration point method, and calculates deceleration point the distance between to stop line；
S23：Using hierarchical clustering method, the biggest impact range into signal lamp at road junction is sought；
The hierarchical clustering method seeks the biggest impact range into signal lamp at road junction, and concrete operation step is as follows：
S231：The deceleration point of more vehicles is subjected to hierarchical clustering to N number of distance between stop line, n classes is obtained, calculates every class
Cluster centre；
S232：The weight of each data in each cluster section is determined according to following formula：
In formula, mcTo fall into the queuing in C classes apart from quantity, c=1,2 ... n；
S233：It is calculated into signal lamp biggest impact range at road junction according to following formula：
Wherein, LinFor into signal lamp biggest impact range at road junction；fcFor the weight of data in the C of section,For being averaged for section C
Value.
2. the signalized intersections region transit time method of estimation based on GPS data, feature exist as described in claim 1
In：The GPS data of all Floating Cars in the step 1 on echo signal intersection obtains according to the following steps：
S11：The coordinate of signal lamp is calibrated on the electronic map；
S12：Map match is carried out using the vehicle GPS data in a period of time；
S13：All matchings are obtained in the vehicle GPS data where signal lamp on section, build floating car data collection.
3. the signalized intersections region transit time method of estimation based on GPS data, feature exist as described in claim 1
In：Vehicle goes out road junction biggest impact range in signalized intersections and takes at all directions exit ramp downstream 150- in the step 3
It is the biggest impact range of signal lamp at exit ramp at 170m.
4. the signalized intersections region transit time method of estimation based on GPS data, feature exist as described in claim 1
In：Data at the time of bicycle i is by signalized intersections import endpoint in the step 4It calculates according to the following steps：
S41：Obtain bicycle i data at the time of into neighbouring two GPS positionings point extraction at the endpoint of road junctionIn formula, j=
0 or 1,0 represents upstream data, and 1 represents downstream data；
S42：Data at the time of using interpolation calculation bicycle i at import endpoint, formula are as follows：
In formula,Indicate data at the time of bicycle i is at crossing inlet endpoint；s1It indicates：Intersection exists into road junction and bicycle i
The range difference of intersection upstream GPS positioning point；s2It indicates：Bicycle i is in intersection downstream GPS positioning point and intersection into road junction
Range difference；It indicates：Bicycle i data at the time of crossing inlet endpoint upstream；It indicates：Bicycle i is at crossing inlet end
Data at the time of point downstream.
5. the signalized intersections region transit time method of estimation based on GPS data, feature exist as described in claim 1
In：Data at the time of bicycle i is exported by signalized intersections at endpoint in the step 5It calculates according to the following steps：
S51：The floating car data and progress (L in the crossing downstream in the period where taking bicycle iO,VO) relation curve function V2=
The least square fitting of kL+b obtains the parameter of fitting function；
Wherein, Vo indicates that the instantaneous velocity in GPS data, Lo indicate vehicle away from 'STOP' line ahead, and k, b are constant, L>0；
S52：Take the floating car data (l that bicycle i is nearest apart from outlet porto,vo), utilize relation curve letter according to following formula
Number V2The speed vs of=kL+b calculating bicycle i in outletout：
Wherein, loutTo export to the distance of stop line；
S53：Bicycle i is calculated in section S according to following formula3Journey time t3：
S54：At the time of bicycle i being calculated according to following formula by outlet
Wherein,For the floating car data nearest apart from outlet port at the time of data.
6. the signalized intersections region transit time method of estimation based on GPS data, feature exist as described in claim 1
In：Transit time ts of the bicycle i in signalized intersections region in the step 6iIt is calculated according to following formula：
Wherein, tiTransit times of the expression bicycle i in signalized intersections region.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610708476.XA CN106097718B (en) | 2016-08-23 | 2016-08-23 | Signalized intersections region transit time method of estimation based on GPS data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610708476.XA CN106097718B (en) | 2016-08-23 | 2016-08-23 | Signalized intersections region transit time method of estimation based on GPS data |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN106097718A CN106097718A (en) | 2016-11-09 |
| CN106097718B true CN106097718B (en) | 2018-09-11 |
Family
ID=57225662
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610708476.XA Expired - Fee Related CN106097718B (en) | 2016-08-23 | 2016-08-23 | Signalized intersections region transit time method of estimation based on GPS data |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106097718B (en) |
Families Citing this family (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106530698A (en) * | 2016-11-22 | 2017-03-22 | 青岛理工大学 | Estimation method for city road travel time taking exit turning into consideration |
| CN106652454B (en) * | 2016-12-28 | 2019-10-25 | 安徽科力信息产业有限责任公司 | Intersection delay evaluation method based on floating car data |
| CN106875680A (en) * | 2017-03-21 | 2017-06-20 | 杭州电子科技大学 | Crossing average latency computational methods based on big data analysis |
| CN107274672B (en) * | 2017-08-03 | 2020-02-14 | 重庆大学 | Signal intersection single vehicle delay time estimation method based on GPS data |
| CN110782662A (en) * | 2019-09-19 | 2020-02-11 | 重庆交通大学 | Method for estimating vehicle passing time at road signalized intersection |
| CN110766940A (en) * | 2019-09-24 | 2020-02-07 | 重庆交通大学 | Method for evaluating running condition of road signalized intersection |
| CN112967493A (en) * | 2021-01-16 | 2021-06-15 | 北京工业大学 | Neural network-based prediction method for vehicle passing intersection travel time |
Family Cites Families (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2001067594A (en) * | 1999-08-31 | 2001-03-16 | Hitachi Ltd | Broadcast method, broadcast device, traffic information compiling device and traffic information display system |
| JP2006085602A (en) * | 2004-09-17 | 2006-03-30 | Gosei:Kk | Traffic analysis system |
| CN100580734C (en) * | 2007-11-20 | 2010-01-13 | 东南大学 | Automatic detection confirmations method for urban traffic incident |
| CN102034354B (en) * | 2010-11-04 | 2012-09-19 | 东南大学 | Method for determining influence range of urban road traffic accident based on fixed detector |
| CN103593976B (en) * | 2013-11-28 | 2016-01-06 | 青岛海信网络科技股份有限公司 | Based on the method and system of detecting device determination road traffic state |
| CN103680150B (en) * | 2013-12-02 | 2015-10-28 | 同济大学 | Based on traffic events coverage and the duration defining method of Coil Detector |
| CN104615897B (en) * | 2015-02-13 | 2017-07-11 | 北方工业大学 | Road section travel time estimation method based on low-frequency GPS data |
-
2016
- 2016-08-23 CN CN201610708476.XA patent/CN106097718B/en not_active Expired - Fee Related
Also Published As
| Publication number | Publication date |
|---|---|
| CN106097718A (en) | 2016-11-09 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106097718B (en) | Signalized intersections region transit time method of estimation based on GPS data | |
| CN104778845B (en) | Multi-phase-jump and vehicle full-dynamic induction traffic control method | |
| JP5424754B2 (en) | Link travel time calculation device and program | |
| CN106097717B (en) | Signalized intersections based on the fusion of two class floating car datas are averaged transit time method of estimation | |
| CN101783073B (en) | Signalized intersection delayed measuring method based on bisection detector | |
| CN105023428A (en) | Road condition information assessment method and apparatus | |
| CN101739824A (en) | Data fusion technology-based traffic condition estimation method | |
| CN113327419B (en) | Green wave speed determination method and device, electronic equipment and storage medium | |
| CN103186984A (en) | Method for triggering transformation of steering function of variable guidance lanes at urban intersections | |
| CN104750963A (en) | Intersection delay time estimation method and device | |
| CN105786895B (en) | Method and device for measuring and calculating discharge amount of road intersection | |
| CN109559506A (en) | Urban road discrete traffic flow delay time at stop prediction technique under a kind of rainy weather | |
| CN108806258A (en) | Urban road intersection operation evaluation index system based on floating car data | |
| CN107564279A (en) | A kind of traffic index computational methods and system based on floating car data | |
| CN106327881A (en) | Traffic jam time calculation method for transition road segment | |
| CN114283606A (en) | Method, device, equipment and system for vehicle navigation and cloud control platform | |
| CN109583081A (en) | A kind of prediction model of vehicle speed construction method | |
| CN104182633B (en) | Hierarchical traffic operation evaluation method | |
| Gorodokin et al. | Optimization of adaptive traffic light control modes based on machine vision | |
| CN108847019B (en) | Method for calculating travel time of variable-route public transport vehicle to fixed station | |
| CN101976508A (en) | Traffic signal artery phase difference optimization method based on license plate recognition data | |
| JP5857389B2 (en) | Traffic index estimation device and computer program | |
| CN111091714A (en) | Traffic light signal control scheme based on vehicle-road cooperation | |
| CN109712397A (en) | Motorway journeys Time Estimation Method based on GM following-speed model | |
| JP2003203289A (en) | Route search system for presuming distribution of traffic jam |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20180911 Termination date: 20210823 |