CN115880884A - Expressway ramp mixed traffic flow control method based on controllable intelligent network connection - Google Patents
Expressway ramp mixed traffic flow control method based on controllable intelligent network connection Download PDFInfo
- Publication number
- CN115880884A CN115880884A CN202211165614.6A CN202211165614A CN115880884A CN 115880884 A CN115880884 A CN 115880884A CN 202211165614 A CN202211165614 A CN 202211165614A CN 115880884 A CN115880884 A CN 115880884A
- Authority
- CN
- China
- Prior art keywords
- vehicle
- ramp
- formation
- vehicles
- point
- 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
- 238000000034 method Methods 0.000 title claims abstract description 25
- 230000015572 biosynthetic process Effects 0.000 claims abstract description 118
- 238000004364 calculation method Methods 0.000 claims description 8
- 230000001133 acceleration Effects 0.000 claims description 5
- 101150104494 CAV1 gene Proteins 0.000 claims description 3
- 230000035484 reaction time Effects 0.000 claims description 3
- 238000005516 engineering process Methods 0.000 abstract description 4
- 230000008676 import Effects 0.000 description 5
- 238000010586 diagram Methods 0.000 description 4
- 230000006399 behavior Effects 0.000 description 3
- 230000006855 networking Effects 0.000 description 2
- 101150047856 Cav2 gene Proteins 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 238000011217 control strategy Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000011144 upstream manufacturing Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
-
- 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
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Traffic Control Systems (AREA)
Abstract
The invention relates to the field of intelligent transportation, in particular to a highway ramp mixed traffic flow control method based on controllable intelligent internet connection, which comprises the following steps of: s1, dividing a ramp section of a highway into a normal driving section, a formation section and an accelerated convergence section; s2, forming a vehicle formation in a road section formed by the intelligent internet connection vehicle and the human-driven following vehicle in the formation; s3, calculating a time interval [ t ] of the vehicle formation to completely reach the merging point S min ,t max ](ii) a S4, cooperatively controlling the intelligent network connection vehicle on the main road and the intelligent network connection vehicle on the ramp road section, and reserving a gathering gap for formation vehicles on the ramp on the main road; and S5, the vehicles are assembled into the main road. The invention obtains the traffic conditions of the highway main road and the downstream confluence area in advance by means of the Internet of vehicles technology, guides the vehicles on the ramp to safely converge into the highway main road by controlling the speed of the intelligent Internet vehicles, and avoids the situation that a driver only needs to collect the vehicles on the ramp into the highway main roadAnd searching the time of converging into the main road according to the driving experience of the driver and the surrounding driving environment.
Description
Technical Field
The invention relates to the field of intelligent transportation, in particular to a highway ramp mixed traffic flow control method based on controllable intelligent internet connection.
Background
With the development of 5G communication technology, car networking technology, intelligent automobiles and roadside equipment, the products of intelligent networking gradually move towards the field of vision of people. The intelligent networked vehicle can improve the precision and the effect of a management and control strategy by means of the accurate sensing, passing and controlling capacity of the intelligent networked vehicle, and meanwhile, the negative influence on the running of a traffic system caused by the randomness and uncertainty of the driving behavior of a driver of a traditional person driving and following vehicle can be avoided.
The ramp confluence area is used as a confluence node of the highway, and due to the randomness of frequent lane change and driving behaviors, the ramp confluence area is often a serious disaster area of traffic jam of the highway, and traffic safety problems also occur occasionally. When the traffic flow of the main road of the expressway is large, if the vehicles on the ramp can not find a proper merging gap, the forced lane changing behavior of the vehicles on the main road can be caused, and the traffic jam in the merging area can be further aggravated.
Most of the existing methods for controlling the ramp traffic flow of the expressway are traditional signal lamp control, but for a complex traffic scene such as a ramp confluence point of the expressway, single signal timing control is difficult to deal with the complex traffic flow running in a ramp confluence area. In addition, the control of the intelligent network connection vehicle is also a difficult point of managing and controlling the mixed traffic flow of the ramp, and the unreasonable speed control of the intelligent network connection vehicle can aggravate the traffic jam of the downstream road section of the expressway.
Disclosure of Invention
Aiming at the problem of management and control of congestion of junction points of ramps of a highway in the prior art, the invention provides a method for managing and controlling a mixed traffic flow of ramps of the highway based on a controllable intelligent internet.
The invention is realized by the following technical scheme:
a highway ramp mixed traffic flow control method based on controllable intelligent internet connection comprises the following steps:
s1, dividing a ramp road section into a normal driving road section, a formation forming road section and an accelerated merging road section, and marking a head vehicle determining point A, a formation finishing point B and a merging point S on the ramp road section;
s2, forming a vehicle formation taking the intelligent network connection vehicle as a head vehicle on a formation road section by the intelligent network connection vehicle and the human-driven following vehicles;
s3, calculating a time interval [ t ] of the vehicle formation to completely reach the merging point S min ,t max ]；
S4, cooperatively controlling the intelligent network connection vehicle on the main road and the intelligent network connection vehicle on the ramp road section, and reserving an exit and entry gap for formation vehicles on the ramp on the main road;
and S5, the vehicles are assembled into the main road.
Preferably, in S2, when formation is completed, the formula is satisfied between the intelligent networked vehicle and the following vehicle driven by people:
in the formula ,LA For the first vehicleThe position of the fixed point A on the ramp;
v head_cav (t) is the running speed of the head car forming the formation at the time t;
v follower (t) the running speed of the person driving the following vehicles forming the formation at the moment t;
L H and forming the vehicle distance when the head vehicle and the human drive follow the vehicles to form a formation.
Preferably, in S3, the specific step of calculating the time interval when the vehicle formation completely reaches the merge point S is: the method comprises the steps of firstly calculating the lowest speed of the intelligent internet vehicle running on a ramp, then respectively calculating the time of the intelligent internet vehicle and the time of the human driving following vehicle reaching the convergence point S, and finally calculating the time interval of the vehicle formation completely reaching the convergence point S.
Preferably, the speed of the intelligent internet vehicle running on the ramp meets the formula:
L A +v min t＝v max t+L H
v min t＝L B -L A
in the formula ,vmin The lowest speed of the vehicle running on the ramp;
v max the highest speed of the vehicle running on the ramp;
L B the position of a formation completion point B on the ramp is shown;
and t is the running time of the vehicle on the ramp.
Preferably, the time for the intelligent internet vehicle to reach the joining point S is calculated according to the vehicle formation completion point:
the first condition is as follows: when the formation completion point of the vehicle formation is coincident with the formation completion point B marked on the ramp, the time t when the intelligent networked vehicle reaches the convergence point S cav_to_S Satisfies the formula:
case two: when the formation completion point of the vehicle formation is positioned between the first vehicle determination point A and the formation completion point B on the ramp, the intelligent network connection vehicle arrivesTime t of joining point S cav_to_S Satisfies the formula:
in the formula ,LB The position of a formation completion point B on the ramp is determined;
L S the position of an afflux point S on the ramp;
a cav1 the acceleration of the intelligent networked vehicle is obtained;
L Current_HeadCav_Pos the position of the intelligent internet vehicle on the ramp is determined when the formation is successful.
Preferably, the time for the human-driven following vehicle to reach the convergence point S is calculated based on a Newell following model, and the formula is satisfied:
in the formula ,τn Following the vehicle for human driving reaction time;
d n the minimum following distance of the following vehicles is set for the person to drive;
n is the nth vehicle in the formation, and n is not equal to 1.
Preferably, the time interval for the formation of vehicles to completely reach the joining point S is [ t ] min ,t max ]Wherein the shortest time t min The calculation formula of (c) is:
maximum time t max The calculation formula of (c) is:
in the formula ,LB The position of a formation completion point B on the ramp is shown;
L S for merging points S on rampsA location;
n is the number of vehicles in the ramp vehicle formation;
L H the distance between vehicles in the queue in the following state;
l is the body length of the vehicle.
Preferably, in S4, when the location of the intelligent internet vehicle on the main road is located in the section [ M [ ] S -v mainlane_max t max ,M S -v mainlane_max t min ]And adjusting the speed of the intelligent network connection vehicle on the main road to reserve a safe convergence gap for the ramp vehicle formation, wherein v mainlane_max The highest speed limit of the main road of the highway, M S Is the distance from the beginning of the main road to the joining point S.
Preferably, in S4, the speed v of the intelligent internet vehicle on the main road mainlane_cav Satisfies the formula:
wherein ,Lmainlane_cav When vehicles in the ramp are successfully formed, the position of the intelligent network connection vehicle is cooperatively controlled on the main road;
t N the time required for the last vehicle in the vehicle formation to travel to the merge point S;
v mainlane_cav and (t) controlling the running speed of the intelligent internet vehicle on the main road in a coordinated manner at the moment t.
Preferably, in S4, on the main road, the inter-vehicle distance L between the intelligent internet vehicle and the vehicle in front of the intelligent internet vehicle mainlane_cav_followdist Satisfies the formula:
L mainlane_cav_followdist >(N-1)L H +N·l
in the formula, N is the number of vehicles in the ramp vehicle formation;
L H the distance between vehicles in the queue in the following state;
l is the automobile body length of vehicle, and the automobile body length of the intelligent internet vehicle and the automobile driven by the person is assumed to be the same in this embodiment, and is l.
Compared with the prior art, the invention has the following beneficial effects:
the invention relates to a highway ramp mixed traffic flow control method based on controllable intelligent internet connection vehicles, which starts from a highway ramp control scene, combines a traffic flow model and a vehicle kinematics model, aims at the controllability of safe import of ramp mixed traffic flow, and firstly carries out sectional processing on ramp road sections based on the idea that the intelligent internet connection vehicles guide ramp vehicle formation and import, analyzes the formation conditions of ramp vehicle formation on the premise that the intelligent internet connection vehicles are controllable, and reserves an import gap for the ramp vehicle formation by predicting the time required for the vehicle formation to reach a ramp import point through the cooperative control of the intelligent internet connection vehicles on a highway trunk road so as to ensure the safe import of ramp vehicles.
When the intelligent networked vehicles and the rear vehicles in the queue are successfully formed into a queue, whether the intelligent networked vehicles which can be cooperatively controlled exist in the corresponding position interval at the upstream of the main road of the expressway at the moment is judged according to the time interval when the vehicle formation reaches the merging point S, and if the intelligent networked vehicles exist, the speed control can be performed on the corresponding intelligent networked vehicles on the main road to ensure the safety clearance when the vehicles are formed into the queue. The safety controllability of vehicles on the ramps when vehicles converge is realized by utilizing the intelligent internet connection vehicles on the main road and the intelligent internet connection vehicles on the ramps and the cooperative control of the two vehicles.
The method is suitable for different types of expressway ramps. Under the condition of balanced and unbalanced ramp traffic flow, the safety and controllability of the ramp vehicle convergence can be effectively ensured.
Drawings
FIG. 1 is a schematic view of a highway traffic scenario in an embodiment of the present invention.
Fig. 2 is a schematic diagram illustrating analysis of formation conditions in a ramp according to an embodiment of the present invention.
Fig. 3 is a schematic diagram of the case one when the formation is completed in the embodiment of the present invention.
FIG. 4 is a diagram illustrating a second case when the formation is completed according to the embodiment of the present invention.
Fig. 5 is a schematic diagram of the cooperative control of the intelligent internet vehicle of the main road in the embodiment of the invention.
Detailed Description
The present invention will now be described in further detail with reference to specific examples, which are intended to be illustrative, but not limiting, of the invention.
The invention discloses a highway ramp mixed traffic flow control method based on controllable intelligent internet connection, which comprises the following steps of:
s1, referring to FIGS. 1 and 2, dividing a ramp road section into a normal driving road section, a formation forming road section and an accelerated merging road section, and marking a head-car determining point A, a formation finishing point B and a merging point S on the ramp road section; the position of the head car determining point A on the ramp is L A The position of the formation completion point B is L B The position of the merging point S on the ramp is L S At a position M on the trunk road S 。
S2, forming a vehicle formation taking the intelligent network connection vehicle as a head vehicle on a formation road section by the intelligent network connection vehicle and the human-driven following vehicles;
in the extreme case, it is assumed that when the intelligent internet vehicle just reaches the head vehicle determination point a, a person just drives into the ramp entrance to drive the following vehicle, and no other vehicle exists between the two vehicles. When formation is completed, the intelligent network connection vehicle and the following person drive following vehicles meet the formula:
in the formula ,LA Determining the position of a point A on a ramp for a head car;
v head_cav (t) is the running speed of the head car forming the formation at the time t;
v follower (t) the running speed of the person driving the following vehicles forming the formation at the time t;
L H and forming the vehicle distance when the head vehicle and the human drive follow the vehicles to form a formation.
When the formation completion point of the vehicle formation is coincident with the formation completion point B marked on the ramp, the intelligent internet vehicle and the human-driven following vehicle meet the formula:
in the formula ,vA_cav Determining the speed of the head vehicle when the head vehicle reaches the point A;
a cav2 the deceleration of the intelligent networked vehicle is determined;
a hdv1 acceleration of a vehicle being followed for a human drive;
a hdv2 deceleration of the vehicle for human driving;
t 1 and t2 The constant-speed running time of the intelligent internet vehicle and the driving following vehicle is respectively.
S3, calculating a time interval [ t ] of the vehicle formation to completely reach the merging point S min ,t max ]The time of completely reaching the merge point S is an interval value because the driving speeds of the vehicles in the vehicle formation are different, and the specific calculation steps are as follows:
s31, firstly, calculating the lowest speed of the intelligent internet vehicle running on the ramp:
when the acceleration and deceleration processes of the first vehicle and the following vehicles driven by people are not considered, the running speed of the intelligent internet vehicle on the ramp meets the formula:
L A +v min t＝v max t+L H
v min t＝L B -L A
in the formula ,vmin The lowest speed of the vehicle running on the ramp;
v max the highest speed of the vehicle running on the ramp is that the vehicle is connected with the intelligent network and follows the vehicle by people;
L B the position of a formation completion point B on the ramp is determined;
and t is the running time of the vehicle on the ramp.
And S32, respectively calculating the time of the intelligent internet connection vehicle and the time of the human driving following vehicle reaching the convergence point S:
(1) Calculating the time of the intelligent internet vehicle reaching the convergence point S according to the vehicle formation completion point:
the first condition is as follows: referring to fig. 3, when the formation completion point of the vehicle formation coincides with the formation completion point B marked on the ramp, the time t when the intelligent internet vehicle arrives at the joining point S cav_to_S Satisfies the formula:
case two: referring to fig. 4, when a formation completion point of a vehicle formation is located between a head car determination point a and a formation completion point B on a ramp, a time t when an intelligent internet connection car arrives at a convergence point S cav_to_S Satisfies the formula:
in the formula ,LB The position of a formation completion point B on the ramp is determined;
L S the position of an afflux point S on the ramp;
a cav1 the acceleration of the intelligent networked vehicle is obtained;
L Current_HeadCav_Pos the position of the intelligent internet vehicle on the ramp is determined when the formation is successful.
(2) Calculating the time for the human driving following vehicle to completely reach the convergence point S based on a Newell following model, and satisfying the formula:
in the formula ,τn Following the vehicle for human driving reaction time;
d n the minimum following distance of the following vehicles is set for the person to drive;
n is the nth vehicle in the formation, and n is not equal to 1.
S33, finally calculating the time interval of the vehicle formation to completely reach the merging point S:
the time interval for the formation of vehicles to completely reach the convergence point S is t min ,t max ]WhereinAssuming that the distances between two adjacent vehicles in the formation of vehicles are the same, the shortest time t min The calculation formula of (c) is:
maximum time t max The calculation formula of (2) is as follows:
in the formula ,LB The position of a formation completion point B on the ramp is shown;
L S the position of an afflux point S on the ramp is shown;
n is the number of vehicles in the ramp vehicle formation;
L H the distance between vehicles in the queue in the following state;
l is the automobile body length of vehicle, and the automobile body length of the intelligent internet vehicle and the automobile driven by the person is assumed to be the same in this embodiment, and is l.
The number N of vehicles in the formation can be obtained by utilizing the cooperative calculation of the intelligent network connection vehicle and the road side equipment, and the specific algorithm steps are as follows:
step (1), as shown in fig. 2, when the vehicle runs to the head car determination point a, the roadside device first judges the vehicle type thereof, and if the vehicle is an intelligent internet vehicle, determines it as the head car and executes step (2). And (4) if the vehicle is driven by a traditional person, executing the step (3).
Step (2), judging whether other head vehicles exist in the formation road section at the moment, if so, automatically forming the head vehicles in the formation road section and the vehicles behind the head vehicles, wherein the number N = Count of the vehicles in the formation, the value of the Count is determined by a vehicle counter at the point A in the formation period, after the number N of the vehicles in the last formation is obtained, the Count is re-assigned, the Count =1 is made, and the step (1) is returned to be continuously executed; if not, assigning value to Count, making Count =1, returning to step (1) to continue execution, and executing step (4) circularly.
Step (3), judging whether a head vehicle waits for formation of a formation in the formation forming road section, if so, making the value Count = Count +1 of the vehicle counter at the point A, and sequentially executing step (4); if not, returning to the step (1) to continue the execution.
And (4) judging whether the head vehicle which does not form the formation in the formation road section runs to a formation completion point B, if so, communicating the head vehicle with roadside equipment at the point B, stopping counting by the vehicle counter, and returning to the step (1) to continue executing, wherein the value of the vehicle counter is the number N of the vehicles in the queue.
S4, cooperatively controlling the intelligent network connection vehicle on the main road and the intelligent network connection vehicle on the ramp road section, and when the position of the intelligent network connection vehicle on the main road is positioned in an interval [ M ] S -v mainlane_max t max ,M S -v mainlane_max t min ]And adjusting the speed of the intelligent network connection vehicle on the main road to reserve a safe convergence gap for the ramp vehicle formation, wherein v mainlane_max The highest speed limit of a main road of the highway, M S Is the distance from the beginning of the main road to the junction point S.
For the cooperatively controlled intelligent networked vehicles determined in the interval, to ensure enough clearance for merging of the ramp vehicle formation, as shown in fig. 4 and 5, the intelligent networked vehicle on the main road must arrive at the merging point S later than the last vehicle of the vehicle formation, i.e. the speed v of the intelligent networked vehicle on the main road mainlane_cav Satisfies the formula:
wherein ,Lmainlane_cav When vehicles in the ramp are successfully formed, the position of the intelligent network connection vehicle is cooperatively controlled on the main road;
t N the time required for the last vehicle in the vehicle formation to travel to the merge point S;
v mainlane_cav and (t) cooperatively controlling the running speed of the intelligent networked vehicle at the moment t by the main road.
On the main road, the inter-vehicle distance L between the intelligent network connection vehicle and the front vehicle mainlane_cav_followdist Satisfies the formula:
L mainlane_cav_followdist >(N-1)L H +N·l
in the formula, N is the number of vehicles in the ramp vehicle formation;
L H the distance between vehicles in the queue in the following state;
l is the automobile body length of vehicle, and the automobile body length of the intelligent internet vehicle and the automobile driven by the person is assumed to be the same in this embodiment, and is l.
And S5, the vehicles are assembled into the main road.
The invention relates to a highway ramp mixed traffic flow control method based on a controllable intelligent internet vehicle, which acquires traffic conditions of a highway trunk road and a downstream confluence area in advance by means of an internet of vehicles technology, and completes guiding ramp vehicles to safely merge into the highway trunk road by controlling the speed of the intelligent internet vehicle by utilizing the controllability of the intelligent internet vehicle, thereby avoiding the situation that a driver only searches for the time of merging into the trunk road according to own driving experience and surrounding driving environment.
The above description is only a preferred embodiment of the present invention, and it should be understood by those skilled in the art that the present invention is not limited to the above embodiments, but also includes various modifications and substitutions without departing from the spirit and principle of the present invention.
Claims (10)
1. A highway ramp mixed traffic flow control method based on controllable intelligent internet connection is characterized by comprising the following steps:
s1, dividing a ramp road section into a normal driving road section, a formation forming road section and an accelerated merging road section, and marking a head vehicle determining point A, a formation finishing point B and a merging point S on the ramp road section;
s2, forming a vehicle formation with the intelligent internet connection vehicle as a head vehicle on a formation road section by the intelligent internet connection vehicle and the human-driven following vehicle;
s3, calculating a time interval [ t ] of the vehicle formation to completely reach the merging point S min ,t max ]；
S4, cooperatively controlling the intelligent network connection vehicle on the main road and the intelligent network connection vehicle on the ramp road section, and reserving an exit and entry gap for formation vehicles on the ramp on the main road;
and S5, the vehicles are assembled into the main road.
2. The method for managing and controlling the mixed traffic flow of the ramp of the expressway based on the controllable intelligent network connection vehicle as claimed in claim 1, wherein in S2, when formation is completed, a formula is satisfied between the intelligent network connection vehicle and the following vehicles driven by people:
in the formula ,LA Determining the position of a point A on a ramp for a head car;
v head_cav (t) is the running speed of the head car forming the formation at the time t;
v follower (t) the running speed of the person driving the following vehicles forming the formation at the moment t;
L H and forming the vehicle distance when the head vehicle and the human drive follow the vehicles to form a formation.
3. The method for managing and controlling the mixed traffic flow of the ramps of the expressway based on the controllable intelligent internet vehicle as claimed in claim 2, wherein in the step S3, the specific step of calculating the time interval when the formation of the vehicles completely reaches the convergence point S is as follows: the method comprises the steps of firstly calculating the lowest speed of the intelligent internet vehicle running on a ramp, then respectively calculating the time of the intelligent internet vehicle and the time of the human driving following vehicle completely reaching the convergence point S, and finally calculating the time interval of the vehicle formation completely reaching the convergence point S.
4. The method for managing and controlling the mixed traffic flow on the ramp of the expressway based on the controllable intelligent internet vehicle according to claim 3, wherein the speed of the intelligent internet vehicle running on the ramp meets the formula:
L A +v min t＝v max t+L H
v min t＝L B -L A
in the formula ,vmin The lowest speed of the vehicle running on the ramp;
v max the highest speed of the vehicle running on the ramp;
L B the position of a formation completion point B on the ramp is determined;
and t is the running time of the vehicle on the ramp.
5. The method for managing and controlling the mixed traffic flow of the ramp on the expressway based on the controllable intelligent internet connection vehicle as claimed in claim 3, wherein the time for the intelligent internet connection vehicle to reach the convergence point S is calculated according to the vehicle formation completion point:
the first condition is as follows: when the formation completion point of the vehicle formation is coincident with the formation completion point B marked on the ramp, the time t when the intelligent internet connection vehicle reaches the convergence point S cav_to_S Satisfies the formula:
case two: when the formation completion point of the vehicle formation is positioned between the first vehicle determination point A and the formation completion point B on the ramp, the time t when the intelligent internet vehicle arrives at the convergence point S cav_to_S Satisfies the formula:
in the formula ,LB The position of a formation completion point B on the ramp is shown;
L S the position of an afflux point S on the ramp;
a cav1 the acceleration of the intelligent networked vehicle is obtained;
L Current_HeadCav_Pos the position of the intelligent internet vehicle on the ramp is determined when the formation is successful.
6. The method for managing and controlling the mixed traffic flow on the ramp of the expressway based on the controllable intelligent internet vehicle as claimed in claim 5, wherein the time for the human-driven following vehicle to reach the junction point S is calculated based on a Newell following model, and the formula is satisfied:
in the formula ,τn Following the vehicle for human driving reaction time;
d n the minimum following distance of the following vehicles is set for the person to drive;
n is the nth vehicle in the formation, and n is not equal to 1.
7. The method for managing and controlling the mixed traffic flow of the ramp on the expressway based on the controllable intelligent internet vehicle as claimed in claim 6, wherein the time interval for the formation of vehicles to completely reach the convergence point S is [ t [ ] min ,t max ]Wherein the shortest time t min The calculation formula of (2) is as follows:
maximum time t max The calculation formula of (2) is as follows:
in the formula, N is the number of vehicles in the ramp vehicle formation;
L H the distance between vehicles in the queue in the following state;
l is the body length of the vehicle.
8. The method according to claim 3The highway ramp mixed traffic flow control method of the controllable intelligent network connection vehicle is characterized in that in S4, when the position of the intelligent network connection vehicle on the main road is located in an interval [ M [ ] S -v mainlane_max t max ,M S -v mainlane_max t min ]And adjusting the speed of the intelligent network connection vehicle on the main road to reserve a safe convergence gap for the ramp vehicle formation, wherein v mainlane_max The highest speed limit of a main road of the highway, M S Is the distance from the beginning of the main road to the joining point S.
9. The method for managing and controlling the mixed traffic flow of the ramps of the expressway based on the controllable intelligent internet connection vehicle according to claim 8, wherein in S4, the speed v of the intelligent internet connection vehicle on the main road mainlane_cav Satisfies the formula:
wherein ,Lmainlane_cav When vehicles in the ramp are successfully formed, the position of the intelligent network connection vehicle is cooperatively controlled on the main road;
t N the time required for the last vehicle in the vehicle formation to travel to the merge point S;
v mainlane_cav and (t) controlling the running speed of the intelligent internet vehicle on the main road in a coordinated manner at the moment t.
10. The method for managing and controlling the mixed traffic flow of the ramps of the expressway based on the controllable intelligent internet connection vehicle according to claim 8, wherein in S4, the inter-vehicle distance L between the intelligent internet connection vehicle and the vehicle in front of the intelligent internet connection vehicle on the main road mainlane_cav_followdist Satisfies the formula:
L mainlane_cav_followdist >(N-1)L H +N·l
in the formula, N is the number of vehicles in the ramp vehicle formation;
L H the distance between vehicles in the queue in the following state;
l is the automobile body length of vehicle, and the automobile body length of the intelligent internet vehicle and the automobile driven by the person is assumed to be the same in this embodiment, and is l.
Priority Applications (3)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211165614.6A CN115880884B (en) | 2022-09-23 | 2022-09-23 | Expressway ramp mixed traffic flow control method based on controllable intelligent network vehicle connection |
| PCT/CN2023/074797 WO2024060486A1 (en) | 2022-09-23 | 2023-02-07 | Expressway ramp hybrid-traffic-flow management and control method based on controllable connected and automated vehicles |
| US18/461,285 US20230415745A1 (en) | 2022-09-23 | 2023-09-05 | CONTROL METHOD OF MIXED TRAFFIC FLOW ON FREEWAY RAMP BASED ON CONTROLLABLE CONNECTED AND AUTONOMOUS VEHICLES (CAVs) |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211165614.6A CN115880884B (en) | 2022-09-23 | 2022-09-23 | Expressway ramp mixed traffic flow control method based on controllable intelligent network vehicle connection |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115880884A true CN115880884A (en) | 2023-03-31 |
| CN115880884B CN115880884B (en) | 2023-10-27 |
Family
ID=85769996
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211165614.6A Active CN115880884B (en) | 2022-09-23 | 2022-09-23 | Expressway ramp mixed traffic flow control method based on controllable intelligent network vehicle connection |
Country Status (2)
| Country | Link |
|---|---|
| CN (1) | CN115880884B (en) |
| WO (1) | WO2024060486A1 (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116665459A (en) * | 2023-08-02 | 2023-08-29 | 武汉御风智行科技有限公司 | Confluence area multi-vehicle cooperation method and device based on mixed traffic flow |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118553115B (en) * | 2024-07-30 | 2024-11-08 | 中汽数据(天津)有限公司 | Vehicle ramp collaborative import method, device and storage medium |
Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| GB1223443A (en) * | 1967-04-14 | 1971-02-24 | Lab For Electronics Inc | Expressway ramp traffic control system |
| WO1996040545A1 (en) * | 1995-06-07 | 1996-12-19 | Autran Corp. | System for automated transport of automobile platforms, passenger cabins and other loads |
| EP1699033A2 (en) * | 2005-03-03 | 2006-09-06 | Aisin Aw Co., Ltd. | A method of driving support and a driving support apparatus |
| CN102314769A (en) * | 2010-07-07 | 2012-01-11 | 交通运输部公路科学研究所 | Intelligent safety early-warning control method for merging area of entrance ramp of expressway |
| CN106601002A (en) * | 2016-11-23 | 2017-04-26 | 苏州大学 | Urban expressway entrance ramp vehicle traffic guiding system and guiding method thereof in Internet of vehicles environment |
| US20200294394A1 (en) * | 2019-03-13 | 2020-09-17 | Mitsubishi Electric Research Laboratories, Inc. | Joint Control of Vehicles Traveling on Different Intersecting Roads |
| CN112116822A (en) * | 2020-09-21 | 2020-12-22 | 长沙理工大学 | Expressway traffic capacity cooperative regulation and control method based on CAVs mixed traffic flow lane dynamic allocation |
| CN113313949A (en) * | 2021-05-31 | 2021-08-27 | 长安大学 | Method, device and equipment for cooperative control of passenger cars and trucks on expressways and ramp ways |
| CN113345268A (en) * | 2021-07-16 | 2021-09-03 | 长沙理工大学 | CAV lane change decision-making method for expressway down-ramp diversion area based on automatic driving special lane deployment scene |
| CN113409594A (en) * | 2021-07-29 | 2021-09-17 | 苏州大学 | Ramp signal control optimization method and system based on reinforcement learning |
| CN113781788A (en) * | 2021-11-15 | 2021-12-10 | 长沙理工大学 | Automatic driving vehicle management method based on stability and safety |
| CN113808436A (en) * | 2021-08-31 | 2021-12-17 | 东南大学 | Motorcade control method for off-ramp vehicles to leave intelligent internet dedicated lane |
| CN216211540U (en) * | 2021-10-25 | 2022-04-05 | 天津新展高速公路有限公司 | Intelligent high-speed safe intelligent guidance system of wisdom |
| CN114639246A (en) * | 2022-05-18 | 2022-06-17 | 哈尔滨工业大学 | Expressway ramp confluence area vehicle-road cooperative control method and system |
Family Cites Families (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2010103504A1 (en) * | 2009-03-08 | 2010-09-16 | Yehuda Gore | System and method for controlling traffic by coordination of intersection approaching flows |
| CN104464317B (en) * | 2014-12-03 | 2016-05-11 | 武汉理工大学 | On-Ramp on Freeway interflow district's guiding control system and method |
| JP7272530B2 (en) * | 2018-05-09 | 2023-05-12 | シーエーブイエイチ エルエルシー | Systems and methods for allocation of driving intelligence between vehicles and highways |
| CN108538069B (en) * | 2018-05-24 | 2020-10-16 | 长安大学 | System and method for controlling vehicle speed in ramp merging area |
| CN108986471B (en) * | 2018-06-22 | 2020-08-21 | 长安大学 | Intersection vehicle guiding method under mixed traffic condition |
| CN110930697B (en) * | 2019-11-12 | 2021-05-25 | 南京航空航天大学 | Rule-based intelligent networked vehicle cooperative convergence control method |
| CN111369813B (en) * | 2020-03-23 | 2021-10-08 | 江苏大学 | Ramp division and confluence cooperative control method and system for intelligent network-connected automobile |
| CN111599194B (en) * | 2020-05-27 | 2024-06-18 | 中汽研汽车检验中心（天津）有限公司 | Highway entrance ramp heterogeneous traffic flow speed guiding system and guiding method |
| CN112614340B (en) * | 2020-12-11 | 2022-03-08 | 国汽(北京)智能网联汽车研究院有限公司 | Method and device for enabling branch vehicles to converge into main road, electronic equipment and storage medium |
| CN114067559B (en) * | 2021-09-27 | 2022-11-15 | 北京交通大学 | Confluence optimization control method for merging special lane for automatic vehicle into common lane |
| CN114664078B (en) * | 2022-03-18 | 2023-01-17 | 河北工业大学 | Road confluence area cooperation convergence control method based on automatic driving vehicle queue |
| CN114708734B (en) * | 2022-05-07 | 2023-01-10 | 合肥工业大学 | Entrance ramp network connection manual driving vehicle main line converging cooperative control method |
| CN114973666A (en) * | 2022-05-18 | 2022-08-30 | 江苏科创车联网产业研究院有限公司 | Vehicle-road cooperation-based internet vehicle speed induction method, device and medium |
| CN114999152B (en) * | 2022-05-25 | 2024-04-30 | 清华大学 | Ramp converging edge cloud control method for mixed traffic flow |
-
2022
- 2022-09-23 CN CN202211165614.6A patent/CN115880884B/en active Active
-
2023
- 2023-02-07 WO PCT/CN2023/074797 patent/WO2024060486A1/en unknown
Patent Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| GB1223443A (en) * | 1967-04-14 | 1971-02-24 | Lab For Electronics Inc | Expressway ramp traffic control system |
| WO1996040545A1 (en) * | 1995-06-07 | 1996-12-19 | Autran Corp. | System for automated transport of automobile platforms, passenger cabins and other loads |
| EP1699033A2 (en) * | 2005-03-03 | 2006-09-06 | Aisin Aw Co., Ltd. | A method of driving support and a driving support apparatus |
| CN102314769A (en) * | 2010-07-07 | 2012-01-11 | 交通运输部公路科学研究所 | Intelligent safety early-warning control method for merging area of entrance ramp of expressway |
| CN106601002A (en) * | 2016-11-23 | 2017-04-26 | 苏州大学 | Urban expressway entrance ramp vehicle traffic guiding system and guiding method thereof in Internet of vehicles environment |
| US20200294394A1 (en) * | 2019-03-13 | 2020-09-17 | Mitsubishi Electric Research Laboratories, Inc. | Joint Control of Vehicles Traveling on Different Intersecting Roads |
| CN112116822A (en) * | 2020-09-21 | 2020-12-22 | 长沙理工大学 | Expressway traffic capacity cooperative regulation and control method based on CAVs mixed traffic flow lane dynamic allocation |
| CN113313949A (en) * | 2021-05-31 | 2021-08-27 | 长安大学 | Method, device and equipment for cooperative control of passenger cars and trucks on expressways and ramp ways |
| CN113345268A (en) * | 2021-07-16 | 2021-09-03 | 长沙理工大学 | CAV lane change decision-making method for expressway down-ramp diversion area based on automatic driving special lane deployment scene |
| CN113409594A (en) * | 2021-07-29 | 2021-09-17 | 苏州大学 | Ramp signal control optimization method and system based on reinforcement learning |
| CN113808436A (en) * | 2021-08-31 | 2021-12-17 | 东南大学 | Motorcade control method for off-ramp vehicles to leave intelligent internet dedicated lane |
| CN216211540U (en) * | 2021-10-25 | 2022-04-05 | 天津新展高速公路有限公司 | Intelligent high-speed safe intelligent guidance system of wisdom |
| CN113781788A (en) * | 2021-11-15 | 2021-12-10 | 长沙理工大学 | Automatic driving vehicle management method based on stability and safety |
| CN114639246A (en) * | 2022-05-18 | 2022-06-17 | 哈尔滨工业大学 | Expressway ramp confluence area vehicle-road cooperative control method and system |
Non-Patent Citations (1)
| Title |
|---|
| 史昕;纪艺;赵祥模;惠飞;: "基于多前车最优速度与加速度的网联车跟驰模型", 现代电子技术, no. 09 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116665459A (en) * | 2023-08-02 | 2023-08-29 | 武汉御风智行科技有限公司 | Confluence area multi-vehicle cooperation method and device based on mixed traffic flow |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115880884B (en) | 2023-10-27 |
| WO2024060486A1 (en) | 2024-03-28 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN114664078B (en) | Road confluence area cooperation convergence control method based on automatic driving vehicle queue | |
| WO2021227502A1 (en) | Method for traffic light and vehicle track control at signalized intersection | |
| CN114613179B (en) | Gathering and passing method for internet-connected automatic-driving mixed-driving vehicle intersection and control system thereof | |
| CN108986488B (en) | Method and equipment for determining ramp merging cooperative track in vehicle-vehicle communication environment | |
| CN115880884A (en) | Expressway ramp mixed traffic flow control method based on controllable intelligent network connection | |
| CN113327441B (en) | Network-connection automatic vehicle speed control and track optimization method based on highway confluence area | |
| CN112373472A (en) | Method for controlling vehicle entering time and running track at automatic driving intersection | |
| CN110533946B (en) | Single-point intersection vehicle speed optimization method under mixed-traveling environment based on edge calculation | |
| CN110444015B (en) | Intelligent network-connected automobile speed decision method based on no-signal intersection partition | |
| CN113345240A (en) | Highway vehicle importing method and system based on intelligent networking environment | |
| CN111243296B (en) | Ramp confluence cooperative control method and system based on confluence time optimization | |
| CN113470407B (en) | Vehicle speed guiding method for multi-intersection passing, server and readable storage medium | |
| CN110910646A (en) | Cooperative control method for unmanned buses at intersection | |
| CN112233413A (en) | Multilane space-time trajectory optimization method for intelligent networked vehicle | |
| CN113257007B (en) | Signal control method and system for intersection to share automatic driving lane | |
| CN117315955B (en) | Intelligent network-connected vehicle ramp on-ramp cooperative control method based on deep reinforcement learning | |
| CN115376346A (en) | Multi-mode driving vehicle collaborative intersection method for expressway confluence area under mixed-driving condition | |
| CN116189462B (en) | Mixed traffic flow-oriented vehicle track and traffic signal cooperative control method | |
| CN112258864A (en) | Automatic driving vehicle intersection scheduling method and system based on sequence selection | |
| CN110364003B (en) | Intersection double-line tramcar signal priority control method based on Internet of vehicles | |
| CN116129627B (en) | Collaborative lane changing strategy in front of intelligent network connected vehicle under ramp | |
| CN115116245B (en) | Intersection dynamic induction signal control method and system in vehicle mixed traffic environment | |
| CN117133119A (en) | Time prediction-based priority driving control method for bus without special lane | |
| CN118053306A (en) | Vehicle control method and system for signalless intersection in Internet of vehicles environment | |
| CN111341123B (en) | Intersection queue-waiting estimation method based on vehicle kinematics model |
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 |