CN113971888A - Ramp merging traffic control method and system based on traffic accident number estimation - Google Patents
Ramp merging traffic control method and system based on traffic accident number estimation Download PDFInfo
- Publication number
- CN113971888A CN113971888A CN202111174617.1A CN202111174617A CN113971888A CN 113971888 A CN113971888 A CN 113971888A CN 202111174617 A CN202111174617 A CN 202111174617A CN 113971888 A CN113971888 A CN 113971888A
- Authority
- CN
- China
- Prior art keywords
- ramp
- traffic
- road
- time
- optimal
- 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.)
- Granted
Links
Images
Classifications
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/07—Controlling traffic signals
- G08G1/075—Ramp control
-
- 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
- G08G1/0125—Traffic data processing
- G08G1/0129—Traffic data processing for creating historical data or processing based on historical data
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/07—Controlling traffic signals
- G08G1/08—Controlling traffic signals according to detected number or speed of vehicles
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Traffic Control Systems (AREA)
Abstract
The invention discloses a ramp merging traffic control method and system based on traffic accident number estimation, which comprises the following steps: acquiring the state quantity at the current moment; building a ramp merging traffic model; estimating the total possible accident number; calculating the total time consumption; establishing a ramp merging traffic control problem as a nonlinear optimal control problem; and solving the optimal control problem to obtain the optimal entry rate of the vehicles on the ramps of each road section. According to the method, the estimated total possible accident quantity and total time consumption are introduced into the objective function, the optimal ramp vehicle entering rate of each road section is solved, the traffic accident risk is reduced, and the traffic efficiency of the ramp merging area is improved.
Description
Technical Field
The invention belongs to the technical field of intelligent traffic systems, and particularly relates to a ramp merging traffic control method and system based on traffic accident number estimation.
Background
The ramp convergence area is always an area with frequent traffic accidents and congestion. The merging of vehicles on the ramp causes the section traffic flow of the main line road to increase rapidly, and often causes large-scale congestion in the merging area. In addition, because the density of vehicles in the area is too high, the interaction between the vehicles is too tight, and traffic accidents are easily caused. At present, the technology of an intelligent traffic system is rapidly developed, and the main development trend is to adopt intelligent road side equipment to construct the intelligent traffic system to regulate and control the traffic state.
Some studies have proposed some effective solutions to the ramp afflux problem. The invention discloses a ramp entrance traffic control method based on radar in Chinese patent application No. CN202010500454.0, which is named as a ramp entrance traffic control system and method based on radar. The invention discloses a Chinese patent application number CN201810907648.5, which is named as an urban expressway entrance ramp control method based on queuing length, and provides an urban expressway entrance ramp control method based on queuing length. However, although the existing method can improve the congestion problem caused by the ramp merging, the traffic accident risk possibly occurring in the ramp merging area is not considered, and further improvement is needed in the aspect of reducing the traffic safety risk.
Disclosure of Invention
In view of the above-mentioned deficiencies of the prior art, the present invention provides a method and a system for controlling ramp-in traffic based on traffic accident number estimation, which are used for analyzing the relationship between traffic density and traffic accident number and establishing a traffic accident number estimation model; the estimated total possible accident quantity and total time consumption are introduced into an objective function, the optimal ramp vehicle entering rate of each road section is solved, the traffic accident risk is reduced, and the traffic efficiency of the ramp merging area is improved.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows:
the invention discloses a ramp afflux traffic control method based on traffic accident number estimation, which comprises the following steps:
1) dividing the road into N sections along the road direction, wherein the length of each section is L, and the number of lanes of the ith section of main line road is lambdai(ii) a Dividing a control time domain into K time steps, wherein each time step is T, i is 1,2, …, N;
2) building a ramp merging traffic model DM; solving traffic density rho of each road section at current momenti(0) Average traffic speed vi(0) Queuing length l of rampi(0) Upstream traffic flow d of rampi(0) Substituting the traffic state quantity obtained by the solving into a ramp and importing the ramp into a traffic model to initialize the ramp and importing the ramp into the traffic model;
3) establishing a ramp merging traffic control problem as a discrete-time nonlinear optimal control problem:
s.t.DM
in the formula, ζs、ζtAnd
is a weight; TATS is the total possible accident number of a road with 1 kilometer of unit time; TATSncIs a constant used to regularize TATS; TTS is the total time consumption; TTSncIs a constant for regularizing the TTS; mu is the optimal entering rate of the ramp vehicles of each road section in the control time domain, and mu is { mu ═ mu1,μ2,...,μN}；μi(k) The optimal entering rate of the ramp vehicles of the ith road at the kT moment is, if the ith road has no ramp, mui(k)＝0；
Is the minimum entry rate;
4) solving the optimal control problem in the step 3) to obtain the optimal entry rate of the ramp vehicles of each road section at each moment in the control time domain; and controlling traffic light equipment at the ramp junction of each road section according to the optimal entry rate of the ramp vehicles of each road section in the first time step in the control time domain, so that the ratio of the green light starting time to the whole traffic light period is equal to the optimal entry rate.
Further, the ramp merging traffic model in the step 2) is as follows:
li(k+1)＝li(k)+T[di(k)-ri(k)]
qi(k)＝ρi(k)λivi(k)
in the formula, ρi(k) Is the traffic density of the ith road segment at the moment of kT; q. q.si(k) Is at a time interval [ kT, (k +1) T]The exit traffic flow of the ith road; v. ofi(k) Is the average traffic speed of the ith road segment at the moment of kT; li(k) Is the queuing length of waiting vehicles on the ramp of the ith road section at the moment of kT; r isi(k) Is at a time interval [ kT, (k +1) T]The traffic flow of the main line road driven by the vehicles on the ramp of the ith road; di(k) Is the upstream traffic flow of the ramp of the ith road segment at the moment of kT;
is the critical traffic density;
is the density of traffic causing congestion;
is the free traffic flow velocity;
the maximum driving traffic flow of the ramp is obtained; tau, chi, delta, chicAnd m and l are model parameters and are adjusted through traffic data fitting.
Further, the traffic density of each road segment at the current moment is as follows:
in the formula, Mi(0) For the ith road section at the current momentThe number of vehicles;
the average traffic speed of each road section at the current moment is as follows:
in the formula, vi,j(0) Is the speed of vehicle j in the ith road segment;
the queuing length l of each road section ramp at the current momenti(0) Upstream traffic flow d of the on-rampi(0) Directly obtained by road side equipment on the ramp.
Further, the total possible accident number in the step 3) is:
TATS＝MTAT+RTAT
in the formula, MTAT is the number of possible accidents of a road of 1 km per unit time of a main line road, and is solved by the following formula:
in the formula, sm,i(ρi(k) Number of accidents per million kilometers of vehicles in the main road; alpha is alphai、σ0,i、σ1,i、σ2,i、σ3,i、κiIs a constant parameter which is a constant value,
the traffic density threshold value is obtained by fitting according to actual traffic data; RTAT is the number of possible accidents per unit time of 1 km of road on the ramp, which is solved by the following formula:
in the formula (I), the compound is shown in the specification,
the traffic average speed of the ramp of the ith road section; sr,i(di(k) Number of accidents per million vehicle kilometers of ramp.
Further, the total time consumed in the step 3) is as follows:
the invention also provides a ramp afflux traffic control system based on traffic accident number estimation, which comprises:
a road division module for dividing the road into N sections along the road direction, each section having a length of L, the number of lanes of the i-th section of the mainline road being lambdai(ii) a Dividing a control time domain into K time steps, wherein each time step is T, i is 1,2, …, N;
the model building module is used for building a ramp merging traffic model DM;
a calculation module for solving the traffic density rho of each road section at the current momenti(0) Average traffic speed vi(0) Queuing length l of rampi(0) Upstream traffic flow d of rampi(0) Substituting the traffic state quantity obtained by the solving into a ramp and importing the ramp into a traffic model to initialize the ramp and importing the ramp into the traffic model;
the problem establishing module is used for establishing a discrete-time nonlinear optimal control problem of the traffic control problem of the ramp convergence;
the optimization solving module is used for solving an optimal control problem to obtain the optimal entry rate of the ramp vehicles of each road section at each moment in the control time domain;
and the control module is used for controlling traffic light equipment at the ramp junction of each road section according to the optimal entry rate of the ramp vehicle of each road section in the first time step in the control time domain, so that the ratio of the green light lighting time to the whole traffic light period is equal to the optimal entry rate.
The invention has the beneficial effects that:
the method analyzes the relation between the traffic density and the number of the traffic accidents, establishes a traffic accident number estimation model, and introduces the estimated total possible accident number and total time into an optimal control objective function, so that the ramp merging traffic control is safer and more efficient, the traffic accident risk is reduced, and the traffic efficiency of the ramp merging area is improved.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
Fig. 2 is a traffic diagram of ramp merging.
Detailed Description
In order to facilitate understanding of those skilled in the art, the present invention will be further described with reference to the following examples and drawings, which are not intended to limit the present invention.
Referring to fig. 1, the ramp merging traffic control method based on traffic accident number estimation according to the present invention includes the following steps:
1) dividing the road into N sections along the road direction, wherein the length of each section is L, and the number of lanes of the ith section of main line road is lambdai(ii) a Dividing a control time domain into K time steps, wherein each time step is T, i is 1,2, …, N;
2) building a ramp merging traffic model DM; solving traffic density rho of each road section at current momenti(0) Average traffic speed vi(0) Queuing length l of rampi(0) Upstream traffic flow d of rampi(0) Substituting the traffic state quantity obtained by the solving into a ramp and importing the ramp into a traffic model to initialize the ramp and importing the ramp into the traffic model;
referring to fig. 2, the ramp merging traffic model in step 2) is:
li(k+1)＝li(k)+T[di(k)-ri(k)]
qi(k)＝ρi(k)λivi(k)
in the formula, ρi(k) Is the traffic density of the ith road segment at the moment of kT; q. q.si(k) Is at a time interval [ kT, (k +1) T]The exit traffic flow of the ith road; v. ofi(k) Is the average traffic speed of the ith road segment at the moment of kT; li(k) Is the queuing length of waiting vehicles on the ramp of the ith road section at the moment of kT; r isi(k) Is at a time interval [ kT, (k +1) T]The traffic flow of the main line road driven by the vehicles on the ramp of the ith road; di(k) Is the upstream traffic flow of the ramp of the ith road segment at the moment of kT;
is the critical traffic density;
is the density of traffic causing congestion;
is the free traffic flow velocity;
the maximum driving traffic flow of the ramp is obtained; tau, chi, delta, chicAnd m and l are model parameters and are adjusted through traffic data fitting.
Wherein the traffic density of each road section at the current moment is as follows:
in the formula, Mi(0) The number of vehicles in the ith road at the current moment is the number of the vehicles in the ith road;
the average traffic speed of each road section at the current moment is as follows:
in the formula, vi,j(0) Is the speed of vehicle j in the ith road segment;
the queuing length l of each road section ramp at the current momenti(0) Upstream traffic flow d of the on-rampi(0) Directly obtained by road side equipment on the ramp.
3) Establishing a ramp merging traffic control problem as a discrete-time nonlinear optimal control problem:
s.t.DM
in the formula, ζs、ζtAnd
is a weight; TATS is the total possible accident number of a road with 1 kilometer of unit time; TATSncIs a constant used to regularize TATS; TTS is the total time consumption; TTSncIs a constant for regularizing the TTS; mu is the optimal entering rate of the ramp vehicles of each road section in the control time domain, and mu is { mu ═ mu1,μ2,...,μN}；μi(k) The optimal entering rate of the ramp vehicles of the ith road at the kT moment is, if the ith road has no ramp, mui(k)＝0；
Is the minimum entry rate;
wherein, the total possible accident number is:
TATS＝MTAT+RTAT
in the formula, MTAT is the number of possible accidents of a road of 1 km per unit time of a main line road, and is solved by the following formula:
in the formula, sm,i(ρi(k) Number of accidents per million kilometers of vehicles in the main road; alpha is alphai、σ0,i、σ1,i、σ2,i、σ3,i、κiIs a constant parameter which is a constant value,
the traffic density threshold value is obtained by fitting according to actual traffic data; RTAT is the number of possible accidents per unit time of 1 km of road on the ramp, which is solved by the following formula:
in the formula (I), the compound is shown in the specification,
ramp for i-th roadAverage speed of traffic of; sr,i(di(k) Number of accidents per million vehicle kilometers of ramp.
The total time spent was:
4) solving the optimal control problem in the step 3) to obtain the optimal entry rate of the ramp vehicles of each road section at each moment in the control time domain; and the road testing equipment controls traffic light equipment at the ramp junction of each road section according to the optimal entry rate of ramp vehicles of each road section in the first time step in the control time domain, so that the ratio of the green light lighting time to the whole traffic light period is equal to the optimal entry rate.
The invention also provides a ramp afflux traffic control system based on traffic accident number estimation, which comprises:
a road division module for dividing the road into N sections along the road direction, each section having a length of L, the number of lanes of the i-th section of the mainline road being lambdai(ii) a Dividing a control time domain into K time steps, wherein each time step is T, i is 1,2, …, N;
the model building module is used for building a ramp merging traffic model DM;
a calculation module for solving the traffic density rho of each road section at the current momenti(0) Average traffic speed vi(0) Queuing length l of rampi(0) Upstream traffic flow d of rampi(0) Substituting the traffic state quantity obtained by the solving into a ramp and importing the ramp into a traffic model to initialize the ramp and importing the ramp into the traffic model;
the problem establishing module is used for establishing a discrete-time nonlinear optimal control problem of the traffic control problem of the ramp convergence;
the optimization solving module is used for solving an optimal control problem to obtain the optimal entry rate of the ramp vehicles of each road section at each moment in the control time domain;
and the control module is used for controlling traffic light equipment at the ramp junction of each road section according to the optimal entry rate of the ramp vehicle of each road section in the first time step in the control time domain, so that the ratio of the green light lighting time to the whole traffic light period is equal to the optimal entry rate.
While the invention has been described in terms of its preferred embodiments, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention.
Claims (6)
1. A ramp afflux traffic control method based on traffic accident number estimation is characterized by comprising the following steps:
1) dividing the road into N sections along the road direction, wherein the length of each section is L, and the number of lanes of the ith section of main line road is lambdai(ii) a Dividing a control time domain into K time steps, wherein each time step is T, i is 1,2, …, N;
2) building a ramp merging traffic model DM; solving traffic density rho of each road section at current momenti(0) Average traffic speed vi(0) Queuing length l of rampi(0) Upstream traffic flow d of rampi(0) Substituting the traffic state quantity obtained by the solving into a ramp and importing the ramp into a traffic model to initialize the ramp and importing the ramp into the traffic model;
3) establishing a ramp merging traffic control problem as a discrete-time nonlinear optimal control problem:
s.t.DM
in the formula, ζs、ζtAnd
is a weight; TATS is the total possible accident number of a road with 1 kilometer of unit time; TATSncIs a constant used to regularize TATS; TTS is the total time consumption; TTSncIs a constant for regularizing the TTS; mu is the optimal entering rate of the ramp vehicles of each road section in the control time domain, and mu is { mu ═ mu1,μ2,...,μN}；μi(k) The optimal entering rate of the ramp vehicles of the ith road at the kT moment is, if the ith road has no ramp, mui(k)＝0；
Is the minimum entry rate;
4) solving the optimal control problem in the step 3) to obtain the optimal entry rate of the ramp vehicles of each road section at each moment in the control time domain; and controlling traffic light equipment at the ramp junction of each road section according to the optimal entry rate of the ramp vehicles of each road section in the first time step in the control time domain, so that the ratio of the green light starting time to the whole traffic light period is equal to the optimal entry rate.
2. The ramp-merging traffic control method based on the traffic accident number estimation according to claim 1, wherein the ramp-merging traffic model in the step 2) is:
li(k+1)＝li(k)+T[di(k)-ri(k)]
qi(k)＝ρi(k)λivi(k)
in the formula, ρi(k) Is the traffic density of the ith road segment at the moment of kT; q. q.si(k) Is at a time interval [ kT, (k +1) T]The exit traffic flow of the ith road; v. ofi(k) Is the average traffic speed of the ith road segment at the moment of kT; li(k) Is the queuing length of waiting vehicles on the ramp of the ith road section at the moment of kT; r isi(k) Is at a time interval [ kT, (k +1) T]The traffic flow of the main line road driven by the vehicles on the ramp of the ith road; di(k) Is the upstream traffic flow of the ramp of the ith road segment at the moment of kT;
is the critical traffic density;
is the density of traffic causing congestion;
is the free traffic flow velocity;
the maximum driving traffic flow of the ramp is obtained; tau, chi, delta, chicAnd m and l are model parameters and are adjusted through traffic data fitting.
3. The ramp afflux traffic control method according to claim 2, wherein the traffic density of each road segment at the current time is:
in the formula, Mi(0) The number of vehicles in the ith road at the current moment is the number of the vehicles in the ith road;
the average traffic speed of each road section at the current moment is as follows:
in the formula, vi,j(0) Is the speed of vehicle j in the ith road segment;
the queuing length l of each road section ramp at the current momenti(0) Upstream traffic flow d of the on-rampi(0) Directly obtained by road side equipment on the ramp.
4. The method for controlling the merging of the ramp based on the traffic accident number estimation according to claim 2, wherein the total number of possible accidents in the step 3) is as follows:
TATS＝MTAT+RTAT
in the formula, MTAT is the number of possible accidents of a road of 1 km per unit time of a main line road, and is solved by the following formula:
in the formula, sm,i(ρi(k) Number of accidents per million kilometers of vehicles in the main road; alpha is alphai、σ0,i、σ1,i、σ2,i、σ3,i、κiIs a constant parameter which is a constant value,
the traffic density threshold value is obtained by fitting according to actual traffic data; RTAT is the number of possible accidents per unit time of 1 km of road on the ramp, which is limited bySolving the formula:
in the formula (I), the compound is shown in the specification,
the traffic average speed of the ramp of the ith road section; sr,i(di(k) Number of accidents per million vehicle kilometers of ramp.
5. The method for controlling the merging of the ramps into the traffic according to the estimation of the number of the traffic accidents according to the claim 2, wherein the total time consumption in the step 3) is as follows:
6. a ramp-merging traffic control system based on traffic accident number estimation, comprising:
a road division module for dividing the road into N sections along the road direction, each section having a length of L, the number of lanes of the i-th section of the mainline road being lambdai(ii) a Dividing a control time domain into K time steps, wherein each time step is T, i is 1,2, …, N;
the model building module is used for building a ramp merging traffic model DM;
the calculation module is used for solving the traffic density, the average traffic speed, the ramp queuing length and the upstream traffic flow of the ramp of each road section at the current moment, and substituting the traffic state quantity obtained by the solution into the ramp and importing the traffic model to initialize the ramp and importing the traffic model;
the problem establishing module is used for establishing a discrete-time nonlinear optimal control problem of the traffic control problem of the ramp convergence;
the optimization solving module is used for solving an optimal control problem to obtain the optimal entry rate of the ramp vehicles of each road section at each moment in the control time domain;
and the control module is used for controlling traffic light equipment at the ramp junction of each road section according to the optimal entry rate of the ramp vehicle of each road section in the first time step in the control time domain, so that the ratio of the green light lighting time to the whole traffic light period is equal to the optimal entry rate.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111174617.1A CN113971888B (en) | 2021-10-09 | 2021-10-09 | Ramp merging traffic control method and system based on traffic accident number estimation |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111174617.1A CN113971888B (en) | 2021-10-09 | 2021-10-09 | Ramp merging traffic control method and system based on traffic accident number estimation |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113971888A true CN113971888A (en) | 2022-01-25 |
| CN113971888B CN113971888B (en) | 2022-09-30 |
Family
ID=79587223
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111174617.1A Active CN113971888B (en) | 2021-10-09 | 2021-10-09 | Ramp merging traffic control method and system based on traffic accident number estimation |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113971888B (en) |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102360522A (en) * | 2011-09-27 | 2012-02-22 | 浙江交通职业技术学院 | Highway optimization control method |
| CN107633692A (en) * | 2017-09-29 | 2018-01-26 | 河南理工大学 | A kind of city expressway Entrance ramp MFA control method |
| JP2019175004A (en) * | 2018-03-27 | 2019-10-10 | Ｎｅｃプラットフォームズ株式会社 | Vehicle guide control device, vehicle guide system, vehicle guide control method, and program |
| CN111091721A (en) * | 2019-12-23 | 2020-05-01 | 清华大学 | Ramp confluence control method and system for intelligent train traffic system |
| CN112614337A (en) * | 2020-12-03 | 2021-04-06 | 浙江浙大中控信息技术有限公司 | Multi-source data-driven intelligent control method for expressway entrance ramp |
| CN112927503A (en) * | 2021-01-25 | 2021-06-08 | 河北上元智能科技股份有限公司 | Method for coordinating and controlling main line speed limitation and ramp fusion of expressway in rainy days |
| CN113345234A (en) * | 2021-06-07 | 2021-09-03 | 哈尔滨工业大学（深圳） | Expressway entrance ramp cooperative control method and device for emergency evacuation scene |
-
2021
- 2021-10-09 CN CN202111174617.1A patent/CN113971888B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102360522A (en) * | 2011-09-27 | 2012-02-22 | 浙江交通职业技术学院 | Highway optimization control method |
| CN107633692A (en) * | 2017-09-29 | 2018-01-26 | 河南理工大学 | A kind of city expressway Entrance ramp MFA control method |
| JP2019175004A (en) * | 2018-03-27 | 2019-10-10 | Ｎｅｃプラットフォームズ株式会社 | Vehicle guide control device, vehicle guide system, vehicle guide control method, and program |
| CN111091721A (en) * | 2019-12-23 | 2020-05-01 | 清华大学 | Ramp confluence control method and system for intelligent train traffic system |
| CN112614337A (en) * | 2020-12-03 | 2021-04-06 | 浙江浙大中控信息技术有限公司 | Multi-source data-driven intelligent control method for expressway entrance ramp |
| CN112927503A (en) * | 2021-01-25 | 2021-06-08 | 河北上元智能科技股份有限公司 | Method for coordinating and controlling main line speed limitation and ramp fusion of expressway in rainy days |
| CN113345234A (en) * | 2021-06-07 | 2021-09-03 | 哈尔滨工业大学（深圳） | Expressway entrance ramp cooperative control method and device for emergency evacuation scene |
Non-Patent Citations (3)
| Title |
|---|
| 曾繁荣等: "城市快速路匝道的最优控制", 《电子科技》 * |
| 胡灵龙: "基于MPC的快速路入口匝道协调控制策略研究", 《中国优秀博硕士学位论文全文数据库(硕士) 工程科技Ⅱ辑》 * |
| 马明辉等: "高速公路主线与匝道合流区协调控制方法", 《哈尔滨工程大学学报》 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113971888B (en) | 2022-09-30 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN114627647B (en) | Mixed traffic flow optimal control method based on combination of variable speed limit and lane change | |
| CN113593258B (en) | Signal timing and vehicle speed dynamic coordination control optimization method based on vehicle-road cooperation | |
| CN110930697B (en) | Rule-based intelligent networked vehicle cooperative convergence control method | |
| CN108665707B (en) | Expressway entrance diversion and flow cooperative control method for preventing local traffic jam | |
| CN113689692B (en) | Intelligent network connection mixed traffic flow signal intersection vehicle arrival prediction correction method | |
| CN108806252A (en) | A kind of Mixed Freeway Traffic Flows collaboration optimal control method | |
| CN113160582B (en) | Highway flow management and control method and system | |
| CN103383817B (en) | Crossroad traffic signal control method based on utility | |
| CN104966402A (en) | Supersaturated traffic flow intersection queue overflow prevention and control method | |
| CN115273500B (en) | Signal intersection network-connected vehicle track optimization guiding method and system | |
| CN114419903B (en) | Intelligent network connection automobile queue intersection traffic control method and device and vehicle | |
| CN110444015B (en) | Intelligent network-connected automobile speed decision method based on no-signal intersection partition | |
| CN111243296B (en) | Ramp confluence cooperative control method and system based on confluence time optimization | |
| CN115206115A (en) | Road network congestion area control method based on multi-source data edge calculation in intelligent networking environment | |
| CN111932916A (en) | Control method and control system for dynamic emergency lane of urban road | |
| CN113506438B (en) | Dynamic control method, system, device and medium for network connection automatic driving hybrid vehicle | |
| CN115273499B (en) | Traffic flow-based signal lamp dynamic timing method and system | |
| CN111477021B (en) | Vehicle priority guidance method and priority guidance system | |
| CN113971888B (en) | Ramp merging traffic control method and system based on traffic accident number estimation | |
| CN114999187B (en) | Ramp entry signal coordination control method based on inductive feedback | |
| CN113110043B (en) | Vehicle convergence control method considering workshop interaction | |
| CN116534018A (en) | CAV lane change speed regulation and control method for expressway diversion area in networking environment | |
| CN115662170A (en) | Expressway intelligent network vehicle ramp cooperation confluence control method and system under intelligent network connection mixed-running condition | |
| CN115424432A (en) | Upstream shunting method under highway abnormal event based on multi-source data | |
| CN114937360B (en) | Intelligent internet automobile queue signalized intersection traffic guiding method |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |