CN114179802A - Vehicle cooperation self-adaptive cruise control method - Google Patents
Vehicle cooperation self-adaptive cruise control method Download PDFInfo
- Publication number
- CN114179802A CN114179802A CN202111452366.9A CN202111452366A CN114179802A CN 114179802 A CN114179802 A CN 114179802A CN 202111452366 A CN202111452366 A CN 202111452366A CN 114179802 A CN114179802 A CN 114179802A
- Authority
- CN
- China
- Prior art keywords
- vehicle
- following
- information
- driving
- strategy
- 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
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
- B60W30/14—Adaptive cruise control
- B60W30/16—Control of distance between vehicles, e.g. keeping a distance to preceding vehicle
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
- B60W30/14—Adaptive cruise control
- B60W30/16—Control of distance between vehicles, e.g. keeping a distance to preceding vehicle
- B60W30/165—Automatically following the path of a preceding lead vehicle, e.g. "electronic tow-bar"
Landscapes
- Engineering & Computer Science (AREA)
- Automation & Control Theory (AREA)
- Transportation (AREA)
- Mechanical Engineering (AREA)
- Traffic Control Systems (AREA)
- Control Of Driving Devices And Active Controlling Of Vehicle (AREA)
Abstract
本发明实施例提供了一种车辆协作自适应巡航控制的方法，所述车辆间通过无线网络组成车队，所述方法包括：获取所述车队内首车的动力学信息以及本车的前一辆车的动力学信息；根据车队内首车的动力学信息、本车的前一辆车的动力学信息以及各车辆与首车的动力学的传递函数，确定本车在预设的多种跟车策略下的跟车参考信息，所述跟车参考信息包括每种跟车策略中本车在多种通信时延下的行车控制参数以及关系曲线，所述关系曲线包括多种通信时延下对应的为满足行车稳定性所需的最小行车间距；根据本车的通信时延和跟车参考信息，选择最优的跟车策略，按照对应的行车控制参数计算用于行车控制的控制输出。
An embodiment of the present invention provides a method for vehicle cooperative adaptive cruise control. The vehicles form a fleet through a wireless network, and the method includes: acquiring dynamic information of the first vehicle in the fleet and the preceding vehicle of the vehicle. The dynamic information of the car; according to the dynamic information of the first car in the team, the dynamic information of the previous car of this car, and the transfer function of the dynamics of each vehicle and the first car, determine that the current car is in a variety of preset tracks. vehicle following reference information under the vehicle following strategy, the vehicle following reference information includes the driving control parameters of the vehicle under various communication delays in each vehicle following strategy and the relationship curve, and the relationship curve includes various communication delays. Correspondingly, the minimum driving distance required to meet the driving stability; according to the communication delay of the vehicle and the following reference information, the optimal following strategy is selected, and the control output for driving control is calculated according to the corresponding driving control parameters.
Description
Technical Field
The invention relates to the field of intelligent transportation, in particular to cooperative fleet driving in an intelligent transportation system, which can be applied to the aspect of longitudinal motion control of an outdoor fleet driving system, and more particularly relates to a method for vehicle cooperative adaptive cruise control.
Background
The establishment and the perfection of traffic facilities play an important role in promoting the social development. However, due to factors such as a significant increase in traffic volume and irregular driving by some drivers, traffic congestion and low traffic efficiency may occur.
Some researchers have proposed Adaptive Cruise Control (ACC) which can sense driving environment by means of a vehicle-mounted sensor (such as a radar, a laser radar or a camera sensing system) and adjust the vehicle speed based on the vehicle distance to match the vehicle speed of the vehicle ahead, so as to ensure that the vehicle and the vehicle ahead can keep a certain driving distance. However, the vehicles do not directly exchange information with each other, so that a large safety distance needs to be reserved, and the road is not fully utilized.
As an extension to the ACC, some researchers have subsequently proposed Cooperative Adaptive Cruise Control (CACC), in which, on the basis of the ACC, a fleet of vehicles may be formed by using vehicle wireless communication technology (such as V2X technology), and the vehicles may Control the driving of the vehicle based on the kinematic information of the vehicle ahead. When using the data of the leading vehicle, the CACC system can have a shorter, more accurate time difference control than the ACC system, contributing to an increase in traffic throughput and a reduction in fuel consumption.
CACC systems are widely considered as an effective solution to the traffic problem because of their ability to improve road use efficiency and traffic. The CACC system can realize the longitudinal automatic control of the fleet. The main goal of CACC systems is to maintain uniformity of all behaviors of vehicles in a fleet and to ensure a vehicle spacing that meets stability. Vehicles in the fleet will establish a communication network for periodic sharing of kinematic information. Therefore, the host vehicle can receive the kinematic information of the speed, the acceleration and the position of the front vehicle or the adjacent vehicles thereof according to the predefined network topology. The control strategy based on real-time real information sharing between vehicles is more reasonable, and the driving distance can be reduced.
Some researchers have proposed a CACC controller consisting of a feed-forward parameter and a feedback parameter, taking into account the effect of communication delay on the longitudinal control of the vehicle, given a fixed following distance. The effect of communication delay on the stability of the string was investigated. The results show that if the communication delay exceeds 50 milliseconds, the stability of the string will be destroyed. Some researchers provide a CACC control method based on optimization aiming at single-vehicle forward relay network topology and fixed inter-vehicle distance, and factors such as communication time delay, packet loss rate and the like are considered. The results show that the controller can maintain string stability below 0.293 seconds. Some researchers have focused on the proportional-derivative controller to derive the relationship between communication delay and traffic clearance that meets the stability requirements. The results show that as the communication delay increases from 0.02s to 0.1s, the minimum following distance needs to increase non-linearly to double to maintain chord stability.
In a CACC system fleet, vehicles share information according to a fixed following strategy based on a wireless ad hoc network (a vehicle wireless network, e.g., V2X). The CACC system of a vehicle is typically composed of external inputs, control strategies, driving clearances, a vehicle kinematics module, and a feedback module. The external input module is composed of kinematic information sharing of other vehicles. The control strategy aims to generate a desired kinematic information according to the input kinematic information and the strategy of the driving clearance. The stability of the chord is an index for evaluating the CACC system, and if the CACC system can meet the stability requirement, the CACC system can not be transmitted backwards when the front vehicles in the fleet have speed and other disturbances, so that the traffic jam is reduced. In the existing research, a fixed following strategy is adopted by the CACC, and the design of the CACC is carried out according to the input and feedback information of the design control in the range of the conventional communication time delay so as to realize the minimum driving clearance meeting the stability. If the situation when the communication state is good is considered during design, the CACC designed in the way can realize the optimal driving clearance under the condition of meeting the stability and improve the throughput of the traffic system. However, if the communication conditions are poor, the system is liable to be unstable, and a wave of speed disturbance is generated, and spread to the surroundings, causing traffic congestion and the like. And the communication time delay considered in the design of the CACC is too large, so that the driving clearance which is realized by the system and meets the stability is not optimal, and the throughput of the traffic system is reduced.
In summary, in the prior art, a fixed following strategy is adopted and a minimum following distance meeting the driving stability in a range of conventional communication delay (mainly considering maximum delay) is analyzed, so that each vehicle in a fleet can cruise with the aim of keeping the minimum following distance, but the communication delay is variable, and the road use efficiency cannot be effectively improved according to the specific situation of the communication delay in the prior art. Therefore, there is a need for improvements in the prior art.
Disclosure of Invention
It is therefore an object of the present invention to overcome the above-mentioned drawbacks of the prior art and to provide a method for cooperative adaptive cruise control of a vehicle. The method is used for the aspect of longitudinal motion control in driving control.
The purpose of the invention is realized by the following technical scheme:
according to a first aspect of the present invention, there is provided a method for cooperative adaptive cruise control of vehicles, the vehicles forming a fleet of vehicles via a wireless network, the method comprising: acquiring the dynamics information of the first vehicle in the motorcade and the dynamics information of the previous vehicle of the vehicle; determining vehicle following reference information of the vehicle under multiple preset vehicle following strategies according to the kinetic information of the first vehicle in the vehicle fleet, the kinetic information of the previous vehicle of the vehicle and the transfer function of the dynamics of each vehicle and the first vehicle, wherein the vehicle following reference information comprises driving control parameters and a relation curve of the vehicle under multiple communication time delays in each vehicle following strategy, and the relation curve comprises a corresponding minimum driving distance required by meeting driving stability under multiple communication time delays; and selecting an optimal following strategy according to the communication time delay and the following reference information of the vehicle, and calculating control output for driving control according to corresponding driving control parameters.
In some embodiments of the present invention, the plurality of following strategies are N following strategies, where a following strategy for following N vehicles represents a strategy for a vehicle to travel following N vehicles ahead, and the strategy needs to perform driving control with reference to dynamics information of the N vehicles ahead, where N is greater than or equal to 1 and less than or equal to N, and N are integers.
In some embodiments of the present invention, the relationship curve corresponding to each following strategy is obtained as follows: according to a preset communication delay solving range and a preset step length, gradually increasing the preset step length from the initial communication delay to analyze the driving control parameters under the corresponding communication delay in the communication delay solving range; and calculating the minimum driving distance required by the corresponding communication time delay to meet the driving stability according to the corresponding communication time delay and the corresponding driving control parameters.
In some embodiments of the present invention, the driving control parameter corresponding to the corresponding communication delay of each following strategy is a driving control parameter obtained when an infinite norm of a kinetic transfer function in an algebraic cartesian equation is minimized according to a delay of the current vehicle executing control, the corresponding communication delay, and the transfer function of the dynamics under the following strategy.
In some embodiments of the invention, the transfer function of the corresponding dynamics of the respective vehicle when employing a following strategy for following n vehicles is expressed as:
wherein u isi(s) represents kinetic information of vehicle i, u1(s) represents dynamics information of a first vehicle in the fleet,
Kfb(s) denotes a feedback control parameter, Gi(s) a transfer function representing the kinematics of the vehicle,
qi(s) denotes position information, τiAn internal time delay of the vehicle i is indicated,
indicating time delay of execution control of vehicle i，H-1An inverse transformation function representing the following distance function H, which is expressed in the laplace domain as H(s) ═ hs +1, H representing the reserved safety distance, Kff，i-1Represents thetai-1Corresponding feedforward control parameter, Kff，i-2Represents thetai-2Corresponding feedforward control parameter, Kff，i-nRepresents thetai-nCorresponding feedforward control parameters, D(s) representing the communication delay transfer function, D(s) e-θsE represents the base of the natural logarithm, θ represents the communication delay, the band(s) behind the letter represents the analysis of the corresponding function in the laplace domain, and s represents the laplace operator.
In some embodiments of the present invention, the optimal following strategy is selected in a manner that: and according to the communication time delay of the vehicle, determining a vehicle following strategy corresponding to the minimum inter-vehicle distance at the communication time delay position based on the reference relation of various vehicle following strategies, and taking the vehicle following strategy as an optimal vehicle following strategy.
In some embodiments of the present invention, the controlling the driving of the host vehicle according to the optimal following strategy includes: and when the originally adopted following strategy is different from the optimal following strategy, switching the dynamic information referred by the driving control and the driving distance between the vehicle and the front vehicle according to the optimal following strategy.
In some embodiments of the present invention, the communication delay of the host vehicle is an estimated communication delay, and the information referred to by estimating the communication delay includes transmission power information of a communication unit of an associated vehicle, a signal-to-noise ratio, inter-vehicle distance variation information, or a combination thereof.
According to a second aspect of the present invention, there is provided a vehicle that supports cooperative adaptive cruise control, comprising: the communication unit is used for acquiring the dynamics information of the first vehicle and the dynamics information of the previous vehicle of the vehicle in the fleet and transmitting the dynamics information of the vehicle to the vehicle behind the vehicle in the fleet; the following strategy analysis module is used for determining following reference information of the vehicle under multiple preset following strategies according to the dynamics information of a first vehicle in a vehicle fleet, the dynamics information of a previous vehicle of the vehicle and the transfer function of dynamics of each vehicle and the first vehicle, wherein the following reference information comprises driving control parameters and a relation curve of the vehicle under multiple communication delays in each following strategy, and the relation curve comprises a minimum driving distance required by meeting driving stability corresponding to the multiple communication delays; and the controller selects an optimal following strategy according to the communication time delay of the vehicle and the following reference information, calculates control output for driving control according to driving control parameters corresponding to the communication time delay of the vehicle in the selected optimal following strategy, calculates following error according to the position information of the front vehicle and the position information of the vehicle, and adjusts the control output for driving control.
According to a third aspect of the invention, an electronic device comprises: one or more processors; and a memory, wherein the memory is to store executable instructions; the one or more processors are configured to implement the steps of the method of the first aspect via execution of the executable instructions.
Drawings
Embodiments of the invention are further described below with reference to the accompanying drawings, in which:
FIG. 1 is a schematic flow diagram of a method of vehicle cooperative adaptive cruise control according to an embodiment of the present disclosure;
FIG. 2 is a schematic illustration of a fleet of vehicles in a method of collaborative adaptive cruise control according to an embodiment of the present invention;
FIG. 3 is a graph of exemplary communication delay versus minimum following distance in a method of vehicle cooperative adaptive cruise control according to an embodiment of the present invention;
FIG. 4 is a diagram illustrating results of simulation of following errors for different following strategies in accordance with an embodiment of the present invention;
FIG. 5 is a schematic diagram illustrating a driving control principle when a following strategy of following n vehicles is adopted in the method for vehicle cooperative adaptive cruise control according to the embodiment of the present invention;
fig. 6 is a schematic diagram illustrating a principle of controlling a vehicle after adjusting a following strategy in the vehicle supporting cooperative adaptive cruise control according to the embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail by embodiments with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
As mentioned in the background section, the prior art adopts a fixed following strategy and analyzes the minimum following distance which meets the driving stability in the range of the conventional communication delay (mainly considering the maximum delay), so that each vehicle in a fleet can cruise with the aim of maintaining the minimum following distance, but the communication delay is variable, and the prior art cannot effectively improve the road use efficiency according to the specific situation of the communication delay. The method changes a car following mode of cooperative adaptive cruise control from a fixed car following strategy to support various car following strategies, considers the relation curve of communication time delay and running distance under various different car following strategies, and adaptively selects an optimal car following strategy from the various car following strategies according to the communication time delay of the car, wherein the optimal car following strategy corresponds to the car following strategy for realizing the minimum running distance under the communication time delay of the car; from the CACC system formed by all vehicles in the fleet, the optimal driving distance is integrally realized, and the road utilization rate is improved.
The invention provides a method for cooperative adaptive cruise control, which supports the information sharing in a fleet to cooperatively perform adaptive cruise after the fleet is formed by wireless networks (vehicle wireless communication networks, such as wireless networks based on V2X technology) among vehicles, and supports N switchable vehicle following strategies, wherein the vehicle following strategy of the following N vehicles represents the strategy that the vehicles follow the preceding N vehicles to run, and the strategy needs to perform the running control by referring to the dynamic information of the preceding N vehicles (N is more than or equal to 1 and less than or equal to N, and N is more than 1). When the vehicle runs on the road, other vehicles supporting the method in the road are searched and form a fleet with the other vehicles, when the fleet is formed and after the fleet is formed, the vehicle can analyze the corresponding minimum inter-vehicle distance required by meeting the driving stability under various communication time delays in different inter-vehicle strategies, and the inter-vehicle distance corresponding to the minimum inter-vehicle distance which can meet the driving stability under the communication time delay of the vehicle is preferentially selected according to the communication time delay of the vehicle, so that the inter-vehicle distance can be dynamically adjusted according to the communication time delay, and the influence of severe communication conditions on the driving performance of the fleet can be reduced; therefore, the invention can fully utilize the road space and improve the road utilization rate according to the specific situation of the communication time delay.
Referring now to fig. 1 and 2, a method of cooperative adaptive cruise control according to an embodiment of the present invention is described, including steps S1, S2, S3. Wherein:
step S1: and acquiring the dynamics information of the first vehicle in the motorcade and the dynamics information of the previous vehicle of the vehicle.
According to one embodiment of the invention, the first vehicle in the platoon is the first vehicle in the platoon, such as the vehicle numbered 1 shown in fig. 2. The dynamic information includes, for example, a position, a velocity, an acceleration, or a combination thereof of the vehicle.
Step S2: according to the dynamics information of a first vehicle in a vehicle fleet, the dynamics information of a previous vehicle of the vehicle and the transfer function of dynamics of each vehicle and the first vehicle, vehicle following reference information of the vehicle under multiple preset vehicle following strategies is determined, the vehicle following reference information comprises driving control parameters and a relation curve of the vehicle under multiple communication time delays in each vehicle following strategy, and the relation curve comprises a corresponding minimum driving distance required by driving stability under the multiple communication time delays.
According to a preferred embodiment of the present invention, referring to fig. 2, assuming that the current vehicle i (the own vehicle) is at the end of the fleet, the upper limit of the number of following vehicles in the following strategy is configured to follow n vehicles, and it is necessary to find the driving control parameters and the relationship curves of the following strategies of 1 vehicle, 2 vehicles, … and n vehicles at different communication delays in sequence.
For this reason, the present invention is defined as the following formula 1 for the transfer function of dynamics corresponding to the following strategy of the vehicle following n vehicles:
wherein u isi(s) represents kinetic information of vehicle i, u1(s) represents dynamics information of a first vehicle in the fleet,
Kfb(s) denotes a feedback control parameter, Gi(s) a transfer function representing the kinematics of the vehicle,
qi(s) denotes position information, τiAn internal time delay of the vehicle i is indicated,
time delay representing execution of control of vehicle i, H-1Represents the inverse of the driving distance H, H being represented in the laplace domain as H(s) hs +1, H representing the reserved safety distance, Kff，i-1Represents thetai-1Corresponding feedforward control parameter, Kff，i-2Represents thetai-2Corresponding feedforward control parameter, Kff，i-nRepresents thetai-nCorresponding feedforward control parameters, D(s) representing the communication delay transfer function, D(s) e-θsE represents the base of the natural logarithm, θ represents the communication delay, the band(s) behind the letter represents the analysis of the corresponding function in the laplace domain, and s represents the laplace operator. In one embodiment of the invention, the kinetic information used in calculating the kinetic transfer function is acceleration, i.e. the kinetic transfer function represents the acceleration ratio. It should be understood that in some more complex application scenarios, the implementer may utilize more of the dynamics information, not just the acceleration information.
When the communication delay is solved, the calculation is needed according to a preset communication delay solving range, and the range can be configured in advance by default or adjusted by a user according to needs. Assuming that the communication delay solution range is configured to be (0-0.5) in units of seconds with the step size set to 0.01s, the solution is performed as follows:
and sequentially calculating driving control parameters corresponding to the following strategies of following 1 vehicle, following 2 vehicles, … and following n vehicles from the time delay of communication being 0.01s, wherein:
for a following strategy to follow 1 vehicle, equation 1 may be expressed as
Knowing the currently analyzed communication time delay theta, the internal time delay tau of the vehicle, the time delay of the vehicle performing control
(actuator time delay) and the reserved safety spacing h, and solving the control parameters meeting the requirement when the infinite norm of the transfer function of the corresponding system is minimized by solving an Algebraic Riccati equation (Algebriac Riccati Equations) under the condition that three variables of G(s), D(s) and H(s) are known
Temporal driving control parameter Ki(s)＝(Kfb(s)Kff,i-1(s)); analyzing whether the obtained dynamic transfer function corresponding to the driving control parameter meets the stability requirement or not, namely | | thetai(s)||H∞Less than or equal to 1, if the stability requirement is met, searching the minimum running distance to meet the requirement
For a following strategy to follow 2 vehicles, equation 1 may be expressed as
Driving control parameter K according to following strategy of following 1 vehiclei(s)＝(Kfb(s)Kff,i-1(s)) and G(s), D(s), H(s) to find the transfer function theta of the following strategy of the following 1 vehiclei-1(s). At a known thetai-1In the case of(s), G(s), D(s), H(s), the unknown variables in equation 1 are K(s), thetai(s). Solving the transfer function by solving the algebraic Richi-chi equationThe driving control parameters when the finite norm is minimized meet the requirement
Driving control parameter of, Ki(s)＝(Kfb(s)Kff,i-1(s),Kff,i-2(s)); analyzing whether the obtained dynamic transfer function corresponding to the driving control parameter meets the stability requirement or not, namely | | thetai(s)||H∞Less than or equal to 1, if the stability requirement is met, searching the minimum running distance to meet the requirement
Similarly, the driving control parameters corresponding to the following strategies of more vehicles can be calculated in sequence until the control parameters K corresponding to the following strategies of n vehicles are finishedi(s)＝(Kfb(s)Kff,i-1(s),Kff,i-2(s)…Kff,i-n(s)) calculating; analyzing whether the obtained dynamic transfer function corresponding to the driving control parameter meets the stability requirement or not, namely | | thetai(s)||H∞Less than or equal to 1, if the stability requirement is met, searching the minimum running distance to meet the requirement
And then increasing the analyzed communication delay by 0.01s, and repeating all the steps until the solution of various communication delays in 0.5s set in the communication delay solution range is completed. For example, if only the relationship curves corresponding to the following strategies for 1-3 vehicles are analyzed, the corresponding relationship curves shown in fig. 3 are obtained.
Step S3: and selecting an optimal following strategy according to the communication time delay and the following reference information of the vehicle, and calculating control output for driving control according to the corresponding driving control parameters. Therefore, the vehicle-following distance is dynamically adjusted.
According to one embodiment of the invention, the communication delay of the vehicle is an estimated communication delay, and the information referred to by estimating the communication delay includes transmission power information of a communication unit of the relevant vehicle, a signal-to-noise ratio, inter-vehicle distance variation information, or a combination thereof. For example, after forming a fleet of vehicles, the vehicles in the fleet share information referenced for calculating the communication delay so that the corresponding vehicles can estimate the communication delay.
According to an embodiment of the present invention, step S3 includes: determining a following strategy corresponding to the minimum inter-vehicle distance at the communication delay position of the vehicle based on the reference relation of various following strategies according to the communication delay of the vehicle, and taking the following strategy as an optimal following strategy; and when the originally adopted following strategy is different from the optimal following strategy, switching the dynamic information referred by the driving control and the driving distance between the vehicle and the front vehicle according to the optimal following strategy. Preferably, the following distance may be a time-reserved distance between two vehicles or a space reserved in a location space.
According to an example of the present invention, if the corresponding relation curve shown in fig. 3 is followed, it can be concluded that the minimum following distance corresponds to the case where the following strategy of following 1 vehicle is selected at 0 to 0.24 seconds of communication delay. And when the communication delay is greater than 0.31 second, the following strategy of 3 vehicles corresponds to the minimum distance. Since the minimum following distance required for maintaining the following stability under the corresponding communication delays of the different following strategies is different, the minimum following distance required for maintaining the following stability under the corresponding communication delays of the following strategies is used as the expected following distance when the following strategies are switched.
According to one embodiment of the invention, the influence of time delay on the dynamics information is also taken into account during the driving. Step S3 further includes: and correcting the dynamic information referred by the driving control by using the communication delay transfer function, and calculating the control output for driving control by using the corresponding driving control parameter, the following error and the corrected corresponding dynamic information. Therefore, the influence of communication time delay on driving control is reduced, and the driving safety is guaranteed.
According to one embodiment of the invention, the problem of errors is also taken into account during driving. Preferably, step S3 further includes: and in the process of executing corresponding driving control parameters by the vehicle, calculating a following error according to the position information of the front vehicle and the position information of the vehicle, and adjusting control output for driving control to reduce the following error. The inventor carries out simulation aiming at the following errors of various following strategies under the time-varying communication time delay, and applies the communication time delay varying from 0.02 second to 0.5s in the simulation process to obtain a simulation result as shown in FIG. 4, wherein the abscissa represents time and the ordinate represents the following errors; it can be seen that the scheme of adaptively adjusting the car following number according to the communication delay is better than the scheme of only supporting the fixed car following strategy, and the minimum car following error in the whole process can be realized.
The following describes a process of driving control when a vehicle (hereinafter referred to as a host vehicle) adopts a following strategy of following n vehicles with reference to fig. 5:
the vehicle is based on the dynamic information u of the first vehicle1And corresponding kinetic transfer function Θi-1、Θi-2、…、Θi-nCalculating dynamics information u of the front 1 to n vehicles of the vehicle by multiplying the values of (A) and (B)i-1、ui-2、…、ui-nI.e. ui-n(s)＝u1Θi-n；
Dynamics information u of the first 1 to n vehiclesi-1、ui-2、…、ui-nThe dynamic information u is converted by a communication delay transfer function D (the communication delay transfer function calculates the corresponding communication delay coefficienti-1、ui-2、…、ui-nRespectively multiplied by corresponding communication delay coefficients) to correct the influence of the communication delay on the dynamic information, and the dynamic information is obtained
I.e. in the Laplace domain is
Dynamics information u of the first 1 vehiclei-1Obtained by conversion of the conversion function of the vehicle kinematics in the vehicle kinematics moduleThe position information of the preceding vehicle is based on the position information q of the preceding vehiclei-1Position information q of the vehicleiAnd calculating following error f by using expected following distancei；
When calculating the driving control parameter K according to
And fiCalculating to obtain control output xiiWherein, in the step (A),
inverse transformation function H from the following distance function-1And control output xiiCalculating dynamics information u for controlling the host vehicleiThe calculation method is ui＝ξi*H-1. Preferably, the kinetic information employed includes acceleration; if the following strategy is kept unchanged, the position information q of the front vehicle is calculated by the conversion function G of the vehicle kinematics based on the dynamic information of the vehiclei-1Position information q of the vehicleiAnd obtaining the following error f according to the expected following distance obtained by the following distance function HiAnd the device is used for adjusting the control output for driving control so as to reduce the following error.
According to one embodiment of the present invention, a vehicle supporting cooperative adaptive cruise control is disclosed, the vehicle including: the communication unit is used for acquiring the dynamics information of the first vehicle and the dynamics information of the previous vehicle of the vehicle in the fleet and transmitting the dynamics information of the vehicle to the vehicle behind the vehicle in the fleet; the following strategy analysis module is used for determining following reference information of the vehicle under multiple preset following strategies according to the dynamics information of a first vehicle in a vehicle fleet, the dynamics information of a previous vehicle of the vehicle and the transfer function of dynamics of each vehicle and the first vehicle, wherein the following reference information comprises driving control parameters and a relation curve of the vehicle under multiple communication delays in each following strategy, and the relation curve comprises a minimum driving distance required by meeting driving stability corresponding to the multiple communication delays; and the controller selects an optimal following strategy according to the communication time delay of the vehicle and the following reference information, calculates control output for driving control according to driving control parameters corresponding to the communication time delay of the vehicle in the selected optimal following strategy so as to dynamically adjust the driving distance, calculates following errors according to the position information of the front vehicle and the position information of the vehicle, and adjusts the control output for driving control so as to reduce the following errors.
According to one embodiment of the invention, the controller includes a control module, an inverse following distance transform module, a vehicle kinematics module, and a following error module. Preferably, the control module is used for adjusting the following strategy of the vehicle in real time. And adjusting and selecting a car following strategy in real time according to the input communication time delay. Different car following strategies correspond to different input numbers, and the driving control parameters are correspondingly changed. Preferably, the following distance inverse transformation module is configured to transform the control output based on an inverse transformation function of the following distance function to obtain dynamic information, such as acceleration, for controlling the vehicle. Preferably, the vehicle kinematics module is configured to convert the kinetic information and the position information of the vehicle based on a conversion function of the vehicle kinematics. Preferably, the following error module is configured to calculate the inter-vehicle distance measured between the vehicles and an expected inter-vehicle distance error or deviation (i.e. following error).
According to an embodiment of the present invention, a control process after the following strategy is adjusted is roughly as shown in fig. 6, the kinematic information of the vehicle and the following error required under the following strategy are used as the input of the control module, the control module calculates a control output according to the kinematic information of the required vehicle and the following error, and the control output is converted into the dynamic information for driving control through an inverse transformation function of a driving distance function in an inverse driving distance transformation module and is output for controlling the driving of the vehicle; in addition, the dynamic information is converted into position information through a vehicle kinematics module based on a conversion function of the vehicle kinematics, a following error module calculates a following error according to the expected distance between the vehicles, the position information of the front vehicle and the position information of the vehicle, a control module adjusts driving control parameters according to the following error and outputs an adjusted control output, and the control output is converted into the dynamic information for driving control through an inverse conversion function of a distance between the vehicles in an inverse driving distance conversion module and is output for adjusting the driving of the vehicle.
It should be noted that, although the steps are described in a specific order, the steps are not necessarily performed in the specific order, and in fact, some of the steps may be performed concurrently or even in a changed order as long as the required functions are achieved.
The present invention may be a system, method and/or computer program product. The computer program product may include a computer-readable storage medium having computer-readable program instructions embodied therewith for causing a processor to implement various aspects of the present invention.
The computer readable storage medium may be a tangible device that retains and stores instructions for use by an instruction execution device. The computer readable storage medium may include, for example, but is not limited to, an electronic memory device, a magnetic memory device, an optical memory device, an electromagnetic memory device, a semiconductor memory device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a Static Random Access Memory (SRAM), a portable compact disc read-only memory (CD-ROM), a Digital Versatile Disc (DVD), a memory stick, a floppy disk, a mechanical coding device, such as punch cards or in-groove projection structures having instructions stored thereon, and any suitable combination of the foregoing.
Having described embodiments of the present invention, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen in order to best explain the principles of the embodiments, the practical application, or improvements made to the technology in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.
Claims (10)
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111452366.9A CN114179802B (en) | 2021-12-01 | 2021-12-01 | A method for vehicle cooperative adaptive cruise control |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111452366.9A CN114179802B (en) | 2021-12-01 | 2021-12-01 | A method for vehicle cooperative adaptive cruise control |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114179802A true CN114179802A (en) | 2022-03-15 |
| CN114179802B CN114179802B (en) | 2024-12-10 |
Family
ID=80541075
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111452366.9A Active CN114179802B (en) | 2021-12-01 | 2021-12-01 | A method for vehicle cooperative adaptive cruise control |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114179802B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN119821393A (en) * | 2025-03-10 | 2025-04-15 | 山东科技大学 | Self-adaptive cruise control method, device and medium based on online self-adaptive learning |
Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR100892539B1 (en) * | 2007-12-07 | 2009-04-09 | 현대자동차주식회사 | Vehicle distance control method |
| CN102282598A (en) * | 2009-01-20 | 2011-12-14 | 丰田自动车株式会社 | Row-running control system and vehicle |
| JP2012043199A (en) * | 2010-08-19 | 2012-03-01 | Toyota Motor Corp | Vehicle control system |
| JP2017056805A (en) * | 2015-09-15 | 2017-03-23 | トヨタ自動車株式会社 | Vehicle control device |
| CN109606367A (en) * | 2018-11-06 | 2019-04-12 | 北京工业大学 | Optimal linear control method and device for cruise control system based on Internet of Vehicles |
| CN110816529A (en) * | 2019-10-28 | 2020-02-21 | 西北工业大学 | Vehicle cooperative adaptive cruise control method based on variable time interval strategy |
| CN110888322A (en) * | 2019-11-14 | 2020-03-17 | 中国科学院自动化研究所 | Heterogeneous fleet cooperative adaptive cruise control method based on acceleration feedforward |
| CN111332290A (en) * | 2020-03-24 | 2020-06-26 | 湖南大学 | Vehicle formation method and system based on feedforward-feedback control |
| CN111652345A (en) * | 2020-05-29 | 2020-09-11 | 长安大学 | Fleet braking control method based on joint space-time optimization |
| CN111679668A (en) * | 2020-05-30 | 2020-09-18 | 华南理工大学 | A follow-control method for networked autonomous fleet based on a new time-distance strategy |
| DE102019210559A1 (en) * | 2019-04-15 | 2020-10-15 | Technische Universität Dresden | Method for controlling a convoy by means of vehicle-to-vehicle communication |
| US20210074165A1 (en) * | 2019-09-09 | 2021-03-11 | Volkswagen Aktiengesellschaft | Method, computer program, and apparatus for determining a minimum inter-vehicular distance for a platoon, vehicle, traffic control entity |
| CN113147764A (en) * | 2021-06-01 | 2021-07-23 | 吉林大学 | Vehicle control method based on hybrid potential function of cooperative adaptive cruise system |
| US20210264794A1 (en) * | 2021-05-03 | 2021-08-26 | Intel Corporation | Cooperative adaptive cruise control (cacc) system for control of connected and autonomous vehicle (cav) platoons |
| CN113485329A (en) * | 2021-07-01 | 2021-10-08 | 西北工业大学 | Vehicle multi-queue cooperative control method |
-
2021
- 2021-12-01 CN CN202111452366.9A patent/CN114179802B/en active Active
Patent Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR100892539B1 (en) * | 2007-12-07 | 2009-04-09 | 현대자동차주식회사 | Vehicle distance control method |
| CN102282598A (en) * | 2009-01-20 | 2011-12-14 | 丰田自动车株式会社 | Row-running control system and vehicle |
| JP2012043199A (en) * | 2010-08-19 | 2012-03-01 | Toyota Motor Corp | Vehicle control system |
| JP2017056805A (en) * | 2015-09-15 | 2017-03-23 | トヨタ自動車株式会社 | Vehicle control device |
| CN109606367A (en) * | 2018-11-06 | 2019-04-12 | 北京工业大学 | Optimal linear control method and device for cruise control system based on Internet of Vehicles |
| DE102019210559A1 (en) * | 2019-04-15 | 2020-10-15 | Technische Universität Dresden | Method for controlling a convoy by means of vehicle-to-vehicle communication |
| US20210074165A1 (en) * | 2019-09-09 | 2021-03-11 | Volkswagen Aktiengesellschaft | Method, computer program, and apparatus for determining a minimum inter-vehicular distance for a platoon, vehicle, traffic control entity |
| CN110816529A (en) * | 2019-10-28 | 2020-02-21 | 西北工业大学 | Vehicle cooperative adaptive cruise control method based on variable time interval strategy |
| CN110888322A (en) * | 2019-11-14 | 2020-03-17 | 中国科学院自动化研究所 | Heterogeneous fleet cooperative adaptive cruise control method based on acceleration feedforward |
| CN111332290A (en) * | 2020-03-24 | 2020-06-26 | 湖南大学 | Vehicle formation method and system based on feedforward-feedback control |
| CN111652345A (en) * | 2020-05-29 | 2020-09-11 | 长安大学 | Fleet braking control method based on joint space-time optimization |
| CN111679668A (en) * | 2020-05-30 | 2020-09-18 | 华南理工大学 | A follow-control method for networked autonomous fleet based on a new time-distance strategy |
| US20210264794A1 (en) * | 2021-05-03 | 2021-08-26 | Intel Corporation | Cooperative adaptive cruise control (cacc) system for control of connected and autonomous vehicle (cav) platoons |
| CN113147764A (en) * | 2021-06-01 | 2021-07-23 | 吉林大学 | Vehicle control method based on hybrid potential function of cooperative adaptive cruise system |
| CN113485329A (en) * | 2021-07-01 | 2021-10-08 | 西北工业大学 | Vehicle multi-queue cooperative control method |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN119821393A (en) * | 2025-03-10 | 2025-04-15 | 山东科技大学 | Self-adaptive cruise control method, device and medium based on online self-adaptive learning |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114179802B (en) | 2024-12-10 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106476806B (en) | Cooperating type self-adaption cruise system algorithm based on traffic information | |
| CN110888322B (en) | Heterogeneous fleet cooperative adaptive cruise control method based on acceleration feedforward | |
| Zheng et al. | Development of connected and automated vehicle platoons with combined spacing policy | |
| WO2025044057A1 (en) | Deep reinforcement learning-based vehicle platoon control method and system | |
| CN117218881B (en) | Intelligent vehicle collaborative import decision planning method and system in full network environment | |
| Chen et al. | Traffic signal optimization control method based on adaptive weighted averaged double deep Q network | |
| CN114274957B (en) | A vehicle adaptive cruise control method and system | |
| CN114179802A (en) | Vehicle cooperation self-adaptive cruise control method | |
| CN111679668A (en) | A follow-control method for networked autonomous fleet based on a new time-distance strategy | |
| Moradipari et al. | Benefits of intent sharing in cooperative platooning | |
| CN115782918B (en) | Automatic driving longitudinal control method, device, equipment and storage medium | |
| CN117207966A (en) | An electric fleet formation control and its speed optimization method | |
| CN115963817A (en) | Computer-implemented method and system for determining driving trajectory as training data | |
| CN120602999A (en) | A caching method for Internet of Vehicles task offloading based on latency-energy consumption collaborative optimization | |
| Hu et al. | Distributed control of a vehicular platoon using event-triggered communication strategy based on state estimation | |
| CN119918620A (en) | An adaptive aggregation federated learning method and device based on inter-layer differences | |
| CN114137831B (en) | Longitudinal control method and device in intelligent network automobile queue system | |
| CN115883548B (en) | Cluster-based method, apparatus, and storage medium for unloading onboard tasks | |
| CN118393889A (en) | Heterogeneous vehicle queue control method and system with extended state observer | |
| CN117193313A (en) | A network-connected autonomous driving queuing control strategy considering persistent communication failures | |
| CN117302212A (en) | Vehicle control method, system, electronic equipment, medium and product | |
| Liu et al. | Communication delay-aware network topology adaptation for cooperative control of vehicular platoons | |
| Chen et al. | Adaptive hybrid control strategy for vehicle platoon combining model predictive control and deep reinforcement learning | |
| CN119545431B (en) | Topology link awareness task collaborative offloading method for V2V and V2I joint systems | |
| CN121999632A (en) | An Adaptive V2X Message Transmission Method for Vehicle Platooning Based on Information Urgency |
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 |