CN110379182B - Ramp confluence area cooperative control system based on generalized dynamics of vehicle and road - Google Patents
Ramp confluence area cooperative control system based on generalized dynamics of vehicle and road Download PDFInfo
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Abstract
The invention relates to a ramp confluence area cooperative control system based on generalized dynamics of a vehicle and a road, which comprises: the general dynamics module of the bus road in the confluence area: establishing a generalized dynamic model of the vehicle road and determining ramp merging cooperative control indexes based on the model; the ramp afflux vehicle safety boundary determining module: determining a safety boundary of the vehicle entering the ramp on the basis of the running information of the vehicle entering the ramp and the vehicle information of the main lane; determining a main lane safety boundary based on the own vehicle running information and the surrounding main lane vehicle information; a collaborative planning control module: and taking the ramp afflux cooperative control index as a target, taking a ramp afflux vehicle safety boundary and a main lane vehicle safety boundary as constraints, performing ramp afflux vehicle movement planning and main lane group vehicle movement planning, and controlling ramp afflux vehicles and main lane group vehicles to run by using the ramp afflux vehicle movement planning and the main lane group vehicle movement planning. Compared with the prior art, the method and the system have the advantages that the effective cooperative control is carried out on the ramp merging area, and the traffic safety and the traffic efficiency are improved.
Description
Technical Field
The invention relates to the technical field of vehicle networking, in particular to a ramp confluence area cooperative control system based on generalized dynamics of a vehicle road.
Background
The ramp convergence is a comprehensive traffic behavior that the group of vehicles need to be controlled laterally and longitudinally, drivers of all related vehicles often cannot make correct judgment and drive correctly, and the traffic jam condition is aggravated or even serious safety accidents are caused by the error of any vehicle due to the uncoordinated speed of the vehicle.
Most studies now treat the main lane as a ramp merging of a single lane and simplify the merging vehicle as a fixed merging point. At the moment, the main lane cooperates with the vehicle to only execute longitudinal acceleration and deceleration cooperation action on the ramp merging vehicle so as to ensure the safety of the ramp merging process. In practical situations, the main lane is multi-lane, and if the main lane is limited to the longitudinal cooperative control of a single main lane, the generalized force excitation of the imported vehicle will certainly have a serious influence on the traffic balance of the single main lane. Therefore, based on the intelligent networking automobile technology, deep research and development are carried out on longitudinal and transverse cooperative control of multi-main lane group vehicles in the traffic environment of ramp confluence, generalized force excitation of vehicles converged is dispersed on a plurality of main lanes, and the multi-vehicle cooperative control optimized by taking global traffic safety and traffic efficiency as targets is a path.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a ramp confluence area cooperative control system based on the generalized dynamics of a vehicle road.
The purpose of the invention can be realized by the following technical scheme:
a ramp confluence area cooperative control system based on generalized dynamics of a vehicle road comprises:
the general dynamics module of the bus road in the confluence area: the module establishes a generalized dynamic model of the vehicle road and determines ramp merging cooperative control indexes based on the model;
the ramp afflux vehicle safety boundary determining module: the module determines a safety boundary of the ramp vehicle-entering based on the running information of the ramp vehicle-entering and the vehicle information of the main lane;
a main lane safety boundary determination module: the module determines a main lane vehicle safety boundary based on the own vehicle driving information and the main lane surrounding vehicle information;
a collaborative planning control module: the module takes the ramp afflux cooperative control index as a target and takes a ramp afflux vehicle safety boundary and a main lane vehicle safety boundary as constraints to carry out ramp afflux vehicle movement planning and main lane group vehicle movement planning and control ramp afflux vehicles and main lane group vehicles to run.
The generalized dynamic model of the vehicle road comprises a ramp-merging vehicle generalized excitation submodel;
the ramp afflux vehicle generalized excitation submodel is based on the Daronbel dynamics principle, and the mathematical model is as follows:
wherein the generalized active excitation of the model
Generalized response of model for inbound excitation of ramp vehicles
Transient and steady state responses of the overall traffic flow, including speed fluctuations, acceleration fluctuations and comfort transient and steady state responses,
the method is characterized in that the generalized constraint force of model elements is the generalized constraint force of all vehicles in a lane change model, and the generalized constraint force comprises longitudinal following constraint and lateral lane change constraint.
The ramp afflux cooperative control indexes comprise traffic efficiency, safety, traffic flow stability and driving comfort.
The main lane vehicle information comprises the motion state, the position, the speed, the acceleration, the course angle and the lane information of the main lane vehicle.
The ramp afflux vehicle information comprises position, speed and acceleration information of the ramp vehicle.
The safety boundary comprises a longitudinal safety boundary and a lateral safety boundary.
The ramp merging vehicle movement planning specifically comprises the following steps:
the first step is as follows: the ramp merging vehicle runs at a constant speed in the ramp according to the speed limit of traffic regulations and drives into an acceleration lane at the tail end of the ramp;
the second step is that: when the ramp merges into a vehicle and runs to an acceleration lane, performing acceleration linear motion by a set acceleration value, and performing forced lane change at a merging point;
the third step: in the lane changing process, the ramp merging vehicle acquires the position and the posture of the vehicle at the current moment, and automatic lane changing dynamic real-time trajectory planning is carried out under the restriction of the safety boundary of the ramp merging vehicle, specifically: and when the vehicle of the main lane has a state mutation to cause the actual track of the vehicle merging into the ramp to exceed the real-time safety boundary of the vehicle merging into the ramp, replanning the optimal lane changing track to finish the automatic lane changing dynamic real-time track planning.
The main lane group vehicle motion planning specifically comprises the following steps:
the first step is as follows: the main lane vehicles entering the ramp merging area establish communication with a traffic control center through vehicle-mounted communication equipment;
the second step is that: the control center predicts the relative position and the relative speed of the current main lane vehicle and the ramp vehicle, determines the corresponding main lane rear vehicle as a cooperative vehicle when the ramp vehicle changes lanes, receives a control instruction of the traffic control center by the main lane vehicle determined as the cooperative vehicle, and the cooperative motion mode comprises a longitudinal deceleration avoidance mode and a lateral lane change avoidance mode;
the third step: the traffic control center judges the performance indexes of the two cooperative motion modes and sends a final motion instruction to the corresponding cooperative vehicle;
the fourth step: the method comprises the following steps of executing a traffic control center instruction by a cooperative vehicle to finish a cooperative motion process, specifically: the method comprises the steps that surrounding vehicle information is obtained through a vehicle-mounted sensor, a main lane safety boundary determining module calculates a real-time main lane safety boundary, when the state of surrounding vehicles changes suddenly and the actual track of a main lane vehicle exceeds the real-time main lane safety boundary, the running rule of the main lane vehicle is re-planned, and the cooperative motion of the main lane vehicle is completed.
Compared with the prior art, the invention has the following advantages:
(1) the invention researches and develops longitudinal and transverse cooperative control of multi-main lane group vehicles in the ramp afflux traffic environment, disperses generalized force excitation of afflux vehicles on a plurality of main lanes, and is multi-vehicle cooperative control taking global traffic safety and traffic efficiency as optimization targets.
(2) In lane change trajectory planning, most researches do not consider the change of the motion state of the vehicles around the lane change vehicle, and only once planning of the safety boundary of single vehicle system dynamics is carried out.
(3) The safety judgment of the invention comprises longitudinal collision safety restraint and lateral stability safety restraint.
(4) According to the ramp confluence control based on the generalized dynamics of the vehicle and the road, the control objects comprise the main lane and the ramp vehicles, the overall traffic efficiency can be optimized to the greatest extent, and the control of a single object is avoided.
Drawings
FIG. 1 is a block diagram of a ramp confluence area cooperative control system based on generalized dynamics of a vehicle road;
FIG. 2 is a generalized dynamic system of a vehicle-road in a junction area of a ramp;
FIG. 3 is a schematic diagram of a decision stage based on the Internet of vehicles before an incoming vehicle enters an acceleration lane;
fig. 4 is a schematic diagram of a lane change track real-time planning stage based on environmental perception after an influx vehicle enters an acceleration lane.
In the figure, SV is the merging vehicle, VMi is the main lane group vehicle, Δ Sij is the longitudinal safe vehicle distance, and Fsv is the ramp merging generalized force excitation.
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments. Note that the following description of the embodiments is merely a substantial example, and the present invention is not intended to be limited to the application or the use thereof, and is not limited to the following embodiments.
Examples
As shown in fig. 1, a ramp confluence area cooperative control system based on generalized dynamics of a vehicle road includes:
the general dynamics module of the bus road in the confluence area: the module establishes a generalized dynamic model of the vehicle road and determines ramp merging cooperative control indexes based on the model;
the ramp afflux vehicle safety boundary determining module: the module determines a safety boundary of the ramp vehicle-entering based on the running information of the ramp vehicle-entering and the vehicle information of the main lane;
the trunk road safety boundary determining module: the module determines a main lane vehicle safety boundary based on main lane self-driving information and ramp incoming vehicle information;
a collaborative planning control module: the module takes the ramp afflux cooperative control index as a target and takes a ramp afflux vehicle safety boundary and a main lane vehicle safety boundary as constraints to carry out ramp afflux vehicle movement planning and main lane group vehicle movement planning and control ramp afflux vehicles and main lane group vehicles to run.
The generalized dynamic model of the vehicle road comprises a ramp-in vehicle generalized excitation submodel, the ramp-in vehicle generalized excitation submodel is a ramp-in generalized excitation submodel based on the Dalang Bell dynamic principle, and the mathematical model is as follows:
wherein the generalized active excitation of the model
Generalized response of model for inbound excitation of ramp vehicles
Transient and steady state responses of the overall traffic flow, including speed fluctuations, acceleration fluctuations and comfort transient and steady state responses,
the method is characterized in that the generalized constraint force of model elements is the generalized constraint force of all vehicles in a lane change model, and the generalized constraint force comprises longitudinal following constraint and lateral lane change constraint.
The ramp afflux cooperative control indexes comprise traffic efficiency, safety, traffic flow stability and driving comfort.
The host lane vehicle information includes a motion state, a position, a speed, an acceleration, a heading angle, and lane information of the host lane vehicle. The ramp import vehicle information includes position, speed and acceleration information of the ramp vehicles. The security border includes a longitudinal security border and a lateral security border.
The ramp inward-entering vehicle movement planning specifically comprises the following steps:
the first step is as follows: the ramp merging vehicle runs at a constant speed in the ramp according to the speed limit of traffic regulations and drives into an acceleration lane at the tail end of the ramp;
the second step is that: when the ramp merges into a vehicle and runs to an acceleration lane, performing acceleration linear motion by a set acceleration value, and performing forced lane change at a merging point;
the third step: in the lane changing process, the ramp merging vehicle acquires the position and the posture of the vehicle at the current moment, and automatic lane changing dynamic real-time trajectory planning is carried out under the restriction of the safety boundary of the ramp merging vehicle, specifically: and when the vehicle of the main lane has a state mutation to cause the actual track of the vehicle merging into the ramp to exceed the real-time safety boundary of the vehicle merging into the ramp, replanning the optimal lane changing track to finish the automatic lane changing dynamic real-time track planning.
The main lane group vehicle movement planning specifically comprises the following steps:
the first step is as follows: the main lane vehicles entering the ramp merging area establish communication with a traffic control center through vehicle-mounted communication equipment;
the second step is that: the control center predicts the relative position and the relative speed of the current main lane vehicle and the ramp vehicle, determines the corresponding main lane rear vehicle as a cooperative vehicle when the ramp vehicle changes lanes, receives a control instruction of the traffic control center by the main lane vehicle determined as the cooperative vehicle, and the cooperative motion mode comprises a longitudinal deceleration avoidance mode and a lateral lane change avoidance mode;
the third step: the traffic control center judges the performance indexes of the two cooperative motion modes and sends a final motion instruction to the corresponding cooperative vehicle;
the fourth step: the method comprises the following steps of executing a traffic control center instruction by a cooperative vehicle to finish a cooperative motion process, specifically: the method comprises the steps that surrounding vehicle information is obtained through a vehicle-mounted sensor, a main lane safety boundary determining module calculates a real-time main lane safety boundary, when the state of surrounding vehicles changes suddenly and the actual track of a main lane vehicle exceeds the real-time main lane safety boundary, the running rule of the main lane vehicle is re-planned, and the cooperative motion of the main lane vehicle is completed.
Comprehensively, firstly, a generalized dynamic model of a vehicle road is established in an intelligent internet traffic environment, and a ramp is converged into a vehicle to be used as a generalized force for excitation. And designing ramp afflux cooperative control indexes in consideration of traffic efficiency, safety and driving comfort, inputting the indexes into a decision model in a traffic efficiency optimal cooperative decision planning module, and respectively planning the movement of ramp afflux vehicles and main lane group vehicles by a ramp afflux group vehicle cooperative control strategy. After the position, the speed, the acceleration, the course angle and the relevant information of the main lane vehicle of the ramp merging vehicle are obtained through the environment perception sensor, the safety boundary of the ramp merging vehicle is calculated, and the ramp-changing merging point of the ramp merging acceleration section is planned. And the main lane group vehicles also know the position, the speed, the acceleration section, the course angle, the information of vehicles entering from the ramp and other environmental information through an environmental perception sensor, analyze and calculate the longitudinal and transverse safety boundaries of the main lane, and decide to adopt a cooperative longitudinal following decision or a cooperative lateral lane change decision according to the situation.
Fig. 2 shows a dynamic system model describing a traffic scene of a ramp merging area. The vehicles on the main lane travel at respective safe distances in the longitudinal direction, and the merging vehicle SV travels from the ramp. The SV travels at a low vehicle speed before entering the acceleration lane, and starts accelerating and prepares to merge into the main lane after entering the acceleration lane.
Fig. 3 is a schematic diagram of a decision phase based on internet of vehicles technology before an oncoming vehicle SV enters an acceleration lane. At this stage, all vehicles establish communication links with a Traffic Control Center (TCC) in a medium-short range communication mode, are directly controlled by the TCC, establish an internet of vehicles system and upload various state parameters of the vehicles in real time. At this stage, after obtaining the state information of all vehicles, the TCC calculates an optimal main lane group vehicle cooperation scheme for the vehicles merging into the ramp through algorithm analysis, and transmits the scheme to all vehicles in the vehicle networking system.
Fig. 4 is a schematic diagram of a lane change track real-time planning stage based on environment perception after an influx vehicle SV enters an accelerating lane. At this stage, the lane-changing vehicle (shown as an incoming vehicle SV in the figure, but not limited to SV) detects the relative distance and speed between the lane-changing vehicle and the surrounding vehicles through sensors such as millimeter wave radar and cameras, senses the surrounding traffic environment, and performs automatic lane-changing dynamic real-time trajectory planning based on a quintic polynomial. Safety constraints for real-time trajectory planning include longitudinal crash safety constraints and lateral stability constraints.
The above embodiments are merely examples and do not limit the scope of the present invention. These embodiments may be implemented in other various manners, and various omissions, substitutions, and changes may be made without departing from the technical spirit of the present invention.
Claims (4)
1. A ramp confluence area cooperative control system based on generalized dynamics of a vehicle road is characterized by comprising:
the general dynamics module of the bus road in the confluence area: the module establishes a generalized dynamic model of the vehicle road and determines ramp merging cooperative control indexes based on the model;
the ramp afflux vehicle safety boundary determining module: the module determines a safety boundary of the ramp vehicle-entering based on the running information of the ramp vehicle-entering and the vehicle information of the main lane;
a main lane safety boundary determination module: the module determines a main lane vehicle safety boundary based on the own vehicle driving information and the main lane surrounding vehicle information;
a collaborative planning control module: the module takes the ramp afflux cooperative control index as a target and takes a ramp afflux vehicle safety boundary and a main lane vehicle safety boundary as constraints to carry out ramp afflux vehicle movement planning and main lane group vehicle movement planning and control ramp afflux vehicles and main lane group vehicles to run by the ramp afflux vehicle movement planning and the main lane group vehicle movement planning;
the generalized dynamic model of the vehicle road comprises a ramp-merging vehicle generalized excitation submodel;
the ramp afflux vehicle generalized excitation submodel is based on the Daronbel dynamics principle, and the mathematical model is as follows:
wherein the generalized active excitation of the model
Generalized response of model for inbound excitation of ramp vehicles
Transient and steady state responses of the overall traffic flow, including speed fluctuations, acceleration fluctuations and comfort transient and steady state responses,
the method comprises the following steps of (1) obtaining generalized constraint force of model elements, wherein the model elements are all vehicles in a lane change model, and the generalized constraint force comprises longitudinal following constraint and lateral lane change constraint;
the ramp afflux cooperative control indexes comprise traffic efficiency, safety, traffic flow stability and driving comfort;
the main lane vehicle information comprises the motion state, position, speed, acceleration, course angle and lane information of the main lane vehicle;
the ramp afflux vehicle information comprises position, speed and acceleration information of the ramp vehicle.
2. The system of claim 1, wherein the safety boundaries comprise a longitudinal safety boundary and a lateral safety boundary.
3. The system of claim 1, wherein the ramp confluence area cooperative control system based on generalized dynamics of a vehicle and a road is characterized in that the ramp confluence vehicle motion planning specifically comprises:
the first step is as follows: the ramp merging vehicle runs at a constant speed in the ramp according to the speed limit of traffic regulations and drives into an acceleration lane at the tail end of the ramp;
the second step is that: when the ramp merges into a vehicle and runs to an acceleration lane, performing acceleration linear motion by a set acceleration value, and performing forced lane change at a merging point;
the third step: in the lane changing process, the ramp merging vehicle acquires the position and the posture of the vehicle at the current moment, and automatic lane changing dynamic real-time trajectory planning is carried out under the restriction of the safety boundary of the ramp merging vehicle, specifically: and when the vehicle of the main lane has a state mutation to cause the actual track of the vehicle merging into the ramp to exceed the real-time safety boundary of the vehicle merging into the ramp, replanning the optimal lane changing track to finish the automatic lane changing dynamic real-time track planning.
4. The ramp confluence area cooperative control system based on the generalized dynamics of the vehicle and the road as claimed in claim 1, wherein the main lane group vehicle movement planning specifically comprises:
the first step is as follows: the main lane vehicles entering the ramp merging area establish communication with a traffic control center through vehicle-mounted communication equipment;
the second step is that: the control center predicts the relative position and the relative speed of the current main lane vehicle and the ramp vehicle, determines the corresponding main lane rear vehicle as a cooperative vehicle when the ramp vehicle changes lanes, receives a control instruction of the traffic control center by the main lane vehicle determined as the cooperative vehicle, and the cooperative motion mode comprises a longitudinal deceleration avoidance mode and a lateral lane change avoidance mode;
the third step: the traffic control center judges the performance indexes of the two cooperative motion modes and sends a final motion instruction to the corresponding cooperative vehicle;
the fourth step: the method comprises the following steps of executing a traffic control center instruction by a cooperative vehicle to finish a cooperative motion process, specifically: the method comprises the steps that surrounding vehicle information is obtained through a vehicle-mounted sensor, a main lane safety boundary determining module calculates a real-time main lane safety boundary, when the state of surrounding vehicles changes suddenly and the actual track of a main lane vehicle exceeds the real-time main lane safety boundary, the running rule of the main lane vehicle is re-planned, and the cooperative motion of the main lane vehicle is completed.
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| CN110782704B (en) * | 2019-11-01 | 2021-02-02 | 北京星云互联科技有限公司 | Traffic guidance method, device and system based on vehicle-road cooperation and storage medium |
| CN111091721A (en) * | 2019-12-23 | 2020-05-01 | 清华大学 | Ramp confluence control method and system for intelligent train traffic system |
| CN113002544B (en) * | 2021-04-13 | 2022-04-22 | 知行汽车科技（苏州）有限公司 | Ramp afflux point track planning method |
| CN113324556B (en) * | 2021-06-04 | 2024-03-26 | 苏州智加科技有限公司 | Path planning method and device based on vehicle-road collaborative reinforcement learning and application system |
| CN113781770B (en) * | 2021-08-13 | 2023-03-31 | 同济大学 | Simulation double-clutch type confluence area vehicle-road cooperative control system |
| CN114655214B (en) * | 2022-04-24 | 2024-04-26 | 重庆长安汽车股份有限公司 | Sectional control method and system for driving through converging port |
| CN114707364B (en) * | 2022-06-02 | 2022-09-02 | 西南交通大学 | Ramp vehicle convergence simulation method, device, equipment and readable storage medium |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101694742A (en) * | 2009-06-16 | 2010-04-14 | 同济大学 | Operation safety control method of major highway traffic infrastructure |
| CN101944148A (en) * | 2010-09-10 | 2011-01-12 | 天津市市政工程设计研究院 | Cellular automata based design method of circular curve elements of bends of harbor roads |
| CN102157072A (en) * | 2011-03-29 | 2011-08-17 | 北京航空航天大学 | Inducing device and inducing method of vehicle confluence at intersection based on vehicle and road collaboration |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| 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 |
| CN106601002B (en) * | 2016-11-23 | 2019-06-07 | 苏州大学 | Entrance ramp vehicle pass-through guidance system and its bootstrap technique under car networking environment |
| CN106991828A (en) * | 2017-05-10 | 2017-07-28 | 重庆大学 | A kind of real-time multivariable bridge up train speed limit control system and its control method |
| DE102017221104A1 (en) * | 2017-11-24 | 2019-05-29 | Robert Bosch Gmbh | Method for coordinating distances within a vehicle association |
| CN109859500B (en) * | 2018-12-17 | 2021-02-02 | 浙江海康智联科技有限公司 | High-speed confluence area safety early warning method based on vehicle-road cooperation |
-
2019
- 2019-07-12 CN CN201910629757.XA patent/CN110379182B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101694742A (en) * | 2009-06-16 | 2010-04-14 | 同济大学 | Operation safety control method of major highway traffic infrastructure |
| CN101944148A (en) * | 2010-09-10 | 2011-01-12 | 天津市市政工程设计研究院 | Cellular automata based design method of circular curve elements of bends of harbor roads |
| CN102157072A (en) * | 2011-03-29 | 2011-08-17 | 北京航空航天大学 | Inducing device and inducing method of vehicle confluence at intersection based on vehicle and road collaboration |
Non-Patent Citations (3)
| Title |
|---|
| Development and evaluation of enhanced intellidrive enabled lane changing advisory algorithm to address freeway merge conflict;Park H;《Transportation Research Record Journal of the Transportation Research Board》;20111231;全文 * |
| 引入缓冲区的入口匝道系统交通流特性研究;朱昶胜等;《计算机仿真》;20141231;全文 * |
| 快速路匝道与主线合流区交通参数关系模型;曹廷等;《交通运输研究》;20170531;全文 * |
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