CN117227727A - Vehicle control method and device and vehicle - Google Patents

Vehicle control method and device and vehicle Download PDF

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Publication number
CN117227727A
CN117227727A CN202311244835.7A CN202311244835A CN117227727A CN 117227727 A CN117227727 A CN 117227727A CN 202311244835 A CN202311244835 A CN 202311244835A CN 117227727 A CN117227727 A CN 117227727A
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target
vehicle
target vehicle
state information
lane
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CN202311244835.7A
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张新会
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Great Wall Motor Co Ltd
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Great Wall Motor Co Ltd
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Priority to CN202311244835.7A priority Critical patent/CN117227727A/en
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Abstract

The application provides a vehicle control method, a device and a vehicle, wherein the method is applied to the technical field of intelligent control of vehicles and comprises the following steps: responding to a lane changing request of a target vehicle, and acquiring first state information of the target vehicle at a first moment, and second state information and second control information of a plurality of reference vehicles at the first moment; determining a plurality of third state information of each reference vehicle at a plurality of subsequent second moments according to the second state information and the second control information of the plurality of reference vehicles; and determining target control information of the target vehicle according to the first state information and the cost function of the target vehicle and a plurality of third state information of a plurality of reference vehicles at a plurality of subsequent second moments. The method can accurately evaluate the third state information of a plurality of reference vehicles around the target vehicle at a plurality of subsequent second moments, efficiently and accurately obtain the target control information of the target vehicle in the lane change process, adapt to complex traffic conditions and improve the safety of a traffic system.

Description

Vehicle control method and device and vehicle
Technical Field
The present application relates to the field of intelligent vehicle control technologies, and more particularly, to a vehicle control method and apparatus, and a vehicle in the field of intelligent vehicle control technologies.
Background
During driving of a car, trailing and lane changing are two main driving actions. Lane changing is more complicated than trailing, because lane changing needs to consider the lateral movement of the automobile and the traffic condition of the target lane, and conflicts with other drivers easily occur in the process of executing lane changing, so that the traffic environment is greatly influenced. It is shown that about 15% to 20% of traffic accidents occur during lane changes of vehicles, and that lane change-induced traffic congestion problems account for about 25% of the total.
The existing intelligent network-connected automobile technology has advanced to a certain extent, so that the safety and the traffic smoothness of channel changing can be improved to a certain extent; however, it is still impossible to accurately evaluate the traffic environment and determine the best opportunity for lane change, and it is not possible to adapt to complex traffic conditions.
Disclosure of Invention
The application provides a vehicle control method, a vehicle control device and a vehicle.
In a first aspect, a vehicle control method is provided, applied to a cloud platform, and the method includes: responding to a lane change request of a target vehicle, and acquiring first state information of the target vehicle at a first moment, and second state information and second control information of a plurality of reference vehicles at the first moment; the second control information is information for changing the state of the reference vehicle, the lane change request is used for requesting to change from a current lane to a target lane, and the reference vehicle is a vehicle in a preset range around the target vehicle;
Determining a plurality of third state information of each reference vehicle at a plurality of subsequent second moments according to the second state information and the second control information of the plurality of reference vehicles;
determining target control information of the target vehicle according to the first state information and the cost function of the target vehicle and a plurality of third state information of the plurality of reference vehicles at a plurality of subsequent second moments; the cost function is used for indicating the advantages and disadvantages of the target control information, and the target control information is used for indicating whether to switch to the target lane and the target state information of the target vehicle at a plurality of subsequent second moments.
In the technical scheme, firstly, the cloud platform responds to a lane changing request of a target vehicle, and obtains first state information of the target vehicle at a first moment and second state information and second control information of a plurality of reference vehicles at the first moment through road side sensing equipment so as to obtain detailed information about the target vehicle and the reference vehicles at the first moment; secondly, predicting a plurality of third state information of each reference vehicle at a plurality of subsequent second moments according to the second state information and the second control information of the plurality of reference vehicles so as to provide reference for the target control information of the target vehicle; finally, determining target control information of the target vehicle according to the first state information and the cost function of the target vehicle and a plurality of third state information of a plurality of reference vehicles at a plurality of subsequent second moments, wherein the target control information is used for indicating whether to change to a target lane or not and the target state information of the target vehicle at the plurality of subsequent second moments; the method and the system can accurately evaluate the third state information of the plurality of reference vehicles around the target vehicle at the subsequent plurality of second moments, efficiently and accurately obtain the target control information of the target vehicle in the lane change process based on the third state information of the plurality of reference vehicles at the subsequent plurality of second moments, and the target control information provides the target vehicle with the target state information of each second moment in the subsequent plurality of second moments in the lane change process, thereby being beneficial to realizing intelligent and efficient target vehicle control and improving the efficiency and safety of a traffic system.
With reference to the first aspect, in some possible implementations, the determining, according to the second state information and the second control information of the plurality of reference vehicles, a plurality of third state information of each of the reference vehicles at a plurality of subsequent second moments includes:
for any one of the plurality of reference vehicles, determining a time compensation value of the reference vehicle according to the time interval of two adjacent second moments in the subsequent plurality of second moments;
for any one of the subsequent second moments, determining a first coefficient and a second coefficient of the reference vehicle according to the time compensation value; the first coefficient is used for adjusting the weight of fourth state information in the third state information, the second coefficient is used for adjusting the weight of fourth control information in the third state information, the fourth state information is state information of the reference vehicle at the moment which is the moment before the second moment, and the fourth control information is control information of the reference vehicle at the moment which is the moment before the second moment;
and determining third state information of the reference vehicle at the second moment according to the fourth state information, the fourth control information, the first coefficient and the second coefficient.
In the above technical solution, when determining the third status information of any one of the plurality of reference vehicles at any one second moment, firstly, determining a time compensation value of the reference vehicle according to the time interval between two adjacent second moments in the plurality of subsequent second moments; next, determining a first coefficient for adjusting the weight of the fourth state information in the third state information to be determined and a second coefficient for adjusting the weight of the second control system in the third state information to be determined according to the time compensation value, the fourth state information is the state information of the reference vehicle at the moment which is the moment before the second moment, and the fourth control information is the control information of the reference vehicle at the moment which is the moment before the second moment; and finally, determining third state information to be determined of the reference vehicle at the second moment according to the fourth state information, the fourth control information, the first coefficient and the second coefficient. By combining the state information, the control information and the weight coefficient of the reference vehicle at the last moment of the second moment corresponding to the third state information to be determined, accurate prediction and adjustment of the third state information to be determined of the reference vehicle at the second moment in the future are realized, the prediction precision is high, and the target state information of the target vehicle can be determined conveniently according to the plurality of third state information of each reference vehicle obtained by prediction at the plurality of second moments in the future
With reference to the first aspect and the foregoing implementation manner, in some possible implementation manners, before determining the target control information of the target vehicle according to the first state information and the cost function of the target vehicle, and a plurality of third state information of the plurality of reference vehicles at the subsequent plurality of second moments, the method further includes:
for any one of the subsequent second moments, determining a running efficiency cost, a following safety cost and a lane changing safety cost of the target vehicle according to the state information and the expected running speed of the target vehicle and the third state information of the reference vehicle; the driving efficiency cost is used for measuring the energy consumption cost of the target vehicle in the driving process, the following safety cost is used for measuring the safety distance and the safety behavior between the target vehicle and a reference vehicle positioned in front of the target vehicle, and the lane change safety cost is used for measuring the influence of the lane change behavior of the target vehicle on traffic safety;
determining a driving comfort cost of the target vehicle according to the expected acceleration of the target vehicle; the driving comfort cost is used for measuring the riding comfort degree of the target vehicle in the driving process;
Determining the cost of the target vehicle deviating from a target lane according to the state information of the target vehicle; the target lane departure cost is used for measuring the departure degree of the target vehicle and the target lane;
determining a cost function of the target vehicle according to the driving efficiency cost, the following safety cost, the lane changing safety cost, the driving comfort cost and the target lane departure cost;
and establishing constraint conditions for the cost function, wherein the constraint conditions comprise speed constraint conditions and acceleration constraint conditions of the target vehicle.
According to the technical scheme, a cost function of the target vehicle at the second moment is constructed according to the driving efficiency cost, the following safety cost, the lane changing safety cost, the driving comfort cost and the lane departure target cost of the target vehicle at each second moment, constraint conditions are built for the cost function, the driving efficiency cost, the following safety cost, the lane changing safety cost, the driving comfort cost and the lane departure target cost reflect the cost and the cost of the target vehicle at different aspects, the cost function obtained through the cost can comprehensively evaluate the cost and the cost of the target vehicle at different aspects at the second moment, and the comprehensive advantages and the disadvantages of the target vehicle under specific conditions can be judged, so that more effective and reliable vehicle control can be realized.
With reference to the first aspect and the foregoing implementation manner, in some possible implementation manners, the determining, according to the first state information and the cost function of the target vehicle, and a plurality of third state information of the plurality of reference vehicles at the subsequent plurality of second moments, target control information of the target vehicle includes:
for any one of the subsequent second moments, determining a plurality of cost function values of the target vehicle under different acceleration conditions according to fifth state information and the cost function and a plurality of third state information of the reference vehicles at the second moment; wherein the fifth state information is state information of the target vehicle at a time immediately before the second time;
selecting the acceleration corresponding to the minimum cost function value in the plurality of cost function values as the target acceleration at the second moment;
and determining target state information of the target vehicle at the second moment according to the target acceleration and the fifth state information.
In the above technical solution, when determining the target control information of the target vehicle at any one of a plurality of subsequent second moments, firstly, determining a plurality of cost function values of the target vehicle under different acceleration conditions and different target lane departure cost conditions according to fifth state information of the target vehicle at a moment previous to the second moment, a cost function of the target vehicle at the second moment, and a plurality of third state information of a plurality of reference vehicles at the second moment; secondly, selecting the acceleration corresponding to the minimum cost function value in a plurality of cost function values under the condition of different departure target lane cost as the target acceleration of the different departure target lane cost of the target vehicle at the second moment; and finally, determining target control information of the target vehicle at the second moment according to the target acceleration of the target vehicle and the fifth state information, wherein the target control information at the second moment comprises a first target longitudinal speed of the target vehicle when the track is not changed at the second moment and a second target longitudinal speed of the target vehicle when the track is changed. By considering a plurality of cost function values under the condition of the same departure target lane cost, the performance and effect of the target vehicle under the condition of different acceleration of the same departure target lane cost can be evaluated, and the acceleration corresponding to the minimum cost function value is selected as the target acceleration, so that the target vehicle can reach the optimal state at the second moment, the instability of the target vehicle in the running process can be reduced, and the stability and reliability of the target vehicle in the running process can be improved.
In a second aspect, there is provided a vehicle control method performed by an in-vehicle terminal of a target vehicle, the method including: responding to a lane changing request of the target vehicle, and acquiring target control information of the target vehicle issued by a cloud platform; the target control information is used for indicating whether to shift to the target lane and target state information of the target vehicle at a plurality of subsequent second moments;
and controlling the target vehicle based on the target control information.
According to the technical scheme, the target vehicle sends a lane changing request to the cloud platform, the cloud platform generates target control information of the target vehicle according to factors such as current road conditions and traffic flow conditions after receiving the request of the target vehicle, the target vehicle responds to the lane changing request of the target vehicle, acquires the target control information generated by the cloud platform, and controls the target vehicle according to the target control information; through the information interaction between the target vehicle and the cloud platform, more accurate and intelligent vehicle control is realized, and the efficiency and the safety of lane changing operation are effectively improved.
With reference to the second aspect and the foregoing implementation manner, in some possible implementation manners, the controlling the target vehicle based on the target control information includes:
Judging whether the target control information meets a safe channel changing condition or not;
under the condition that the target control information meets the safe channel changing condition, planning a target channel changing path;
and controlling the target vehicle to change from the current lane to the target lane according to the target lane changing path and the target control information, and driving at the plurality of subsequent second moments by the target state information corresponding to each second moment.
In the above technical solution, first, it is determined whether a plurality of target state information in the target control information satisfies a safe channel change condition; secondly, under the condition that the plurality of target state information meets the safe lane change condition, planning a target lane change path of the target vehicle; and finally, according to the target lane changing path and the target control information, the target vehicle is controlled to change from the current lane to the target lane, and the target vehicle runs at a plurality of subsequent second moments by the target state information corresponding to each second moment, so that the automatic lane changing operation of the target vehicle is realized, the running efficiency and the comfort of the target vehicle are improved, the operation burden of a driver can be reduced, the risk and the occurrence probability of traffic accidents are reduced, and the safety and the reliability of road traffic are improved.
With reference to the second aspect and the foregoing implementation manner, in some possible implementation manners, after the determining whether the target control information meets the safe lane change condition, the method further includes:
under the condition that the target control information does not meet the safe lane change condition, planning a target straight path;
and controlling the target vehicle to run at the plurality of subsequent second moments according to the target straight-going path and the target control information and the target state information corresponding to each second moment.
In the above technical solution, in the embodiment of the present application, when the plurality of pieces of target state information of the target control information do not satisfy the safe lane change condition, the target lane change path of the target vehicle is planned, and the target straight-going path is planned, so that it is ensured that the target vehicle can travel on the target straight-going path according to the target state information and the path point of the target straight-going path at each of a plurality of subsequent second moments when the target vehicle cannot make a safe lane change.
In a third aspect, there is provided a vehicle control apparatus including:
The system comprises a first acquisition module, a second acquisition module and a control module, wherein the first acquisition module is used for responding to a lane change request of a target vehicle and acquiring first state information of the target vehicle at a first moment, and second state information and second control information of a plurality of reference vehicles at the first moment; the second control information is information for changing the state of the reference vehicle, the lane change request is used for requesting to change from a current lane to a target lane, and the reference vehicle is a vehicle in a preset range around the target vehicle;
a first determining module, configured to determine a plurality of third state information of each of the reference vehicles at a plurality of subsequent second moments according to the second state information and the second control information of the plurality of reference vehicles;
the second determining module is used for determining target control information of the target vehicle according to the first state information and the cost function of the target vehicle and a plurality of third state information of the plurality of reference vehicles at a plurality of subsequent second moments; the cost function is used for indicating the advantages and disadvantages of the target control information, and the target control information is used for indicating whether to switch to the target lane and the target state information of the target vehicle at a plurality of subsequent second moments.
With reference to the first aspect, in some possible implementations, the first determining module is specifically configured to:
for any one of the plurality of reference vehicles, determining a time compensation value of the reference vehicle according to the time interval of two adjacent second moments in the subsequent plurality of second moments;
for any one of the subsequent second moments, determining a first coefficient and a second coefficient of the reference vehicle according to the time compensation value; the first coefficient is used for adjusting the weight of fourth state information in the third state information, the second coefficient is used for adjusting the weight of fourth control information in the third state information, the fourth state information is state information of the reference vehicle at the moment which is the moment before the second moment, and the fourth control information is control information of the reference vehicle at the moment which is the moment before the second moment;
and determining third state information of the reference vehicle at the second moment according to the fourth state information, the fourth control information, the first coefficient and the second coefficient.
With reference to the first aspect and the foregoing implementation manner, in some possible implementation manners, the apparatus further includes:
A third determining module, configured to determine, for any one of the subsequent second moments, a running efficiency cost, a following safety cost, and a lane change safety cost of the target vehicle according to the state information and the expected running speed of the target vehicle, and third state information of the reference vehicle; the driving efficiency cost is used for measuring the energy consumption cost of the target vehicle in the driving process, the following safety cost is used for measuring the safety distance and the safety behavior between the target vehicle and a reference vehicle positioned in front of the target vehicle, and the lane change safety cost is used for measuring the influence of the lane change behavior of the target vehicle on traffic safety;
a fourth determining module, configured to determine a driving comfort cost of the target vehicle according to a desired acceleration of the target vehicle; the driving comfort cost is used for measuring the riding comfort degree of the target vehicle in the driving process;
a fifth determining module, configured to determine a target lane departure cost of the target vehicle according to the state information of the target vehicle; the target lane departure cost is used for measuring the departure degree of the target vehicle and the target lane;
A sixth determining module, configured to determine a cost function of the target vehicle according to the driving efficiency cost, the following safety cost, the lane changing safety cost, the driving comfort cost, and the target lane departure cost;
the establishing module is used for establishing constraint conditions for the cost function, wherein the constraint conditions comprise speed constraint conditions and acceleration constraint conditions of the target vehicle.
With reference to the first aspect and the foregoing implementation manner, in some possible implementation manners, the second determining module is specifically configured to:
for any one of the subsequent second moments, determining a plurality of cost function values of the target vehicle under different acceleration conditions according to fifth state information and the cost function and a plurality of third state information of the reference vehicles at the second moment; wherein the fifth state information is state information of the target vehicle at a time immediately before the second time;
selecting the acceleration corresponding to the minimum cost function value in the plurality of cost function values as the target acceleration at the second moment;
and determining target state information of the target vehicle at the second moment according to the target acceleration and the fifth state information.
In a fourth aspect, there is provided a vehicle control apparatus including:
the second acquisition module is used for responding to a lane change request of a target vehicle and acquiring target control information of the target vehicle; the target control information is used for indicating whether to shift to the target lane and target state information of the target vehicle at a plurality of subsequent second moments;
and the control module is used for controlling the target vehicle based on the target control information.
With reference to the second aspect and the foregoing implementation manner, in some possible implementation manners, the control module is specifically configured to:
judging whether the target control information meets a safe channel changing condition or not;
under the condition that the target control information meets the safe channel changing condition, planning a target channel changing path;
and controlling the target vehicle to change from the current lane to the target lane according to the target lane changing path and the target control information, and driving at the plurality of subsequent second moments by the target state information corresponding to each second moment.
With reference to the second aspect and the foregoing implementation manner, in some possible implementation manners, the control module is specifically configured to:
Under the condition that the target control information does not meet the safe lane change condition, planning a target straight path;
and controlling the target vehicle to run at the plurality of subsequent second moments according to the target straight-going path and the target control information and the target state information corresponding to each second moment.
In a fifth aspect, a vehicle is provided that includes a memory and a processor. The memory is for storing executable program code and the processor is for calling and running the executable program code from the memory such that the vehicle performs the method of the second aspect or any one of the possible implementations of the second aspect.
In a sixth aspect, there is provided a computer program product comprising: computer program code which, when run on a computer, causes the computer to perform the method of the first aspect or any one of the possible implementation manners of the first aspect or causes the computer to perform the method of the second aspect or any one of the possible implementation manners of the second aspect.
In a seventh aspect, a computer readable storage medium is provided, the computer readable storage medium storing computer program code which, when run on a computer, causes the computer to perform the method of the first aspect or any one of the possible implementations of the first aspect, or causes the computer to perform the method of the second aspect or any one of the possible implementations of the second aspect.
Drawings
FIG. 1 is a schematic view of an environment in which a vehicle control method according to an embodiment of the present application is implemented;
FIG. 2 is a schematic flow chart of a vehicle control method provided by an embodiment of the application;
FIG. 3 is a schematic flow chart of another vehicle control method provided by an embodiment of the present application;
fig. 4 is a schematic structural view of a vehicle control apparatus according to an embodiment of the present application;
fig. 5 is a schematic structural view of another vehicle control apparatus according to an embodiment of the present application;
fig. 6 is a schematic structural diagram of a vehicle according to an embodiment of the present application.
Detailed Description
The technical scheme of the application will be clearly and thoroughly described below with reference to the accompanying drawings. Wherein, in the description of the embodiments of the present application, unless otherwise indicated, "/" means or, for example, a/B may represent a or B: the text "and/or" is merely an association relation describing the associated object, and indicates that three relations may exist, for example, a and/or B may indicate: the three cases where a exists alone, a and B exist together, and B exists alone, and furthermore, in the description of the embodiments of the present application, "plural" means two or more than two.
The terms "first," "second," and the like, are used below for descriptive purposes only and are not to be construed as implying or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more such feature.
First, terms related to one or more embodiments of the present specification will be explained.
Status information: including the position, longitudinal speed and lane information of the vehicle, status information has an important role for intelligent transportation systems and vehicle driving assistance systems. The intelligent traffic system can know the surrounding traffic environment, including road congestion, the running track of other vehicles, the state of intersection signals and the like, by acquiring the positions of the vehicles and the lanes in real time according to the positions of the vehicles and the lane information, and is very important for the intelligent traffic system to make decisions and plan according to actual conditions, such as reasonably arranging lane changing of the vehicles, selecting an optimal path and the like; the intelligent traffic system can calculate a more proper running path according to the current position and the next target position of the vehicle, dynamically adjust according to the speed information of the vehicle, help a driver to select an optimal running route, provide guiding information and enable the driving process to be more efficient and convenient; the state information can be used for evaluating traffic safety risks, for example, the longitudinal speed of the vehicle can be used for detecting whether the vehicle is overspeed or the distance between the vehicle and the front vehicle is too close, so that a driver is reminded of taking corresponding measures to reduce accident risks, and meanwhile, the position and lane information of the vehicle can also be used for detecting whether illegal behaviors exist or not, such as driving without a specified lane, and the like, and corresponding warning and correction are carried out; the state information can also be used for real-time optimization of traffic flow, and the intelligent traffic system can monitor and predict traffic flow and distribution thereof in real time by collecting the position and longitudinal speed of the vehicle, so that strategies such as signal lamp timing, lane flow distribution adjustment and the like are optimized, congestion is reduced, and overall traffic efficiency is improved.
Control information: including acceleration information and lane change information of the vehicle, which is critical to controlling the longitudinal speed and acceleration of the vehicle. The intelligent traffic system can formulate proper acceleration and deceleration strategies according to acceleration information of vehicles and combining traffic environment and road conditions so as to realize stable, safe and energy-saving running; the acceleration information of the vehicle can also be used for detecting a front obstacle or other vehicles and predicting possible collision risks, and by monitoring the acceleration change of the vehicle in real time, the intelligent traffic system can send out corresponding alarms or automatically take measures, such as deceleration, braking or emergency avoidance, so as to avoid collision accidents; lane change information of vehicles is critical to the coordination and safety of traffic flows. Through the lane change information of the vehicles, the intelligent traffic system can perform cooperation and coordination among the vehicles, adjust the traffic distribution of the lanes and optimize the speed of the vehicles so as to improve the overall traffic efficiency, and in addition, the intelligent traffic system can also be used for detecting and warning the illegal lane change behavior and ensuring traffic safety.
Time Headway (THW): refers to the time interval between the front and rear vehicles during the following of the vehicle, which represents the time required for the rear vehicle to reach a certain fixed point after the front vehicle passes the point. The headway is an index for measuring the distance between vehicles, and is generally used for evaluating the safety distance and the following behavior between vehicles, and a larger headway means a longer time difference between a rear vehicle and a front vehicle, namely, the distance between vehicles is longer, which reflects a conservative following strategy and can provide more reaction time and space to cope with emergency. The calculation of the headway is typically based on the time difference between vehicles and the longitudinal speed.
Time To Collision (TTC): refers to the time required for a collision between two objects (e.g., a vehicle, a pedestrian, etc.) during the running of a vehicle, and is an index for evaluating collision risk and safety. The collision time can be calculated by measuring the distance between two objects and their relative velocity. The shorter the collision time, meaning the higher the collision risk, the more urgent reaction and avoidance actions are required; conversely, a longer collision time indicates a lower risk of collision, giving more time and space to take appropriate action to avoid a collision.
The following describes an implementation environment of the technical solution provided by the embodiment of the present application. Fig. 1 is a schematic diagram of an implementation environment of a vehicle control method according to an embodiment of the present application, and referring to fig. 1, the implementation environment includes a road side sensing device 110, a vehicle terminal 120, and a cloud platform 130.
The road side sensing device 110 is connected to the cloud platform 130 through a wireless network, the road side sensing device 110 includes a plurality of types of sensors including, but not limited to, a visual sensor, a sound sensor, a position sensor and an inertial sensor, through which various information around the vehicle can be obtained, including information of a position, a longitudinal speed, a direction, an acceleration, a distance of surrounding obstacles, and the like of the vehicle, and correspondingly, the road side sensing device 110 further includes a processor and a memory, the memory stores information collected by the sensors, and the processor is used for processing the information stored in the memory. The roadside sensing device 110 is installed and operated with an application program supporting acquisition of various information around the vehicle.
The vehicle-mounted terminal 120 is integrated in the target vehicle, the vehicle-mounted terminal 120 is respectively connected with the cloud platform 130 and the road side sensing device 110 through a wireless network, the vehicle-mounted terminal 120 can acquire user instructions, the vehicle-mounted terminal 120 further comprises a plurality of types of sensors (such as a camera and a radar) through which surrounding environment data can be sensed, and correspondingly, the vehicle-mounted terminal 120 further comprises a processor and a memory, the memory is used for storing information acquired by the sensors, and the processor is used for processing the information stored in the memory. The in-vehicle terminal 110 is installed and operated with an application program supporting acquisition of user instructions and surrounding environment data.
Cloud platform 130 is a stand-alone entity that may include a server cluster of multiple physical servers. The cloud platform 130 receives various information around the vehicle acquired by the road side sensing device 110 and user instructions acquired by the vehicle-mounted terminal 120, and provides target control information corresponding to the user instructions for the vehicle-mounted terminal 120.
After the implementation environment of the embodiment of the present application is described, an application scenario of the embodiment of the present application will be described below with reference to the implementation environment, where in the following description process, the road side sensing device is the road side sensing device 110 in the implementation environment, the vehicle-mounted terminal is the vehicle-mounted terminal 120 in the implementation environment, and the cloud platform is the cloud platform 130 in the implementation environment.
The technical scheme provided by the embodiment of the application can be applied to the scene of automatic lane changing control of the vehicle, and under the condition that the target vehicle sends a lane changing request to the cloud platform, firstly, the cloud platform acquires first state information of the target vehicle at a first moment and second state information and second control information of a plurality of reference vehicles at the first moment through the road side sensing equipment so as to acquire detailed information about the target vehicle and the reference vehicles at the first moment; secondly, predicting a plurality of third state information of each reference vehicle at a plurality of subsequent second moments according to the second state information and the second control information of the plurality of reference vehicles so as to provide reference for the target control information of the target vehicle; finally, determining target control information of the target vehicle according to the first state information and the cost function of the target vehicle and a plurality of third state information of a plurality of reference vehicles at a plurality of subsequent second moments, wherein the target control information is used for indicating whether to change to a target lane or not and the target state information of the target vehicle at the plurality of subsequent second moments; the method and the system can accurately evaluate the third state information of the plurality of reference vehicles around the target vehicle at the subsequent plurality of second moments, efficiently and accurately obtain the target control information of the target vehicle in the lane change process based on the third state information of the plurality of reference vehicles at the subsequent plurality of second moments, and the target control information provides the target vehicle with the target state information of each second moment in the subsequent plurality of second moments in the lane change process, thereby being beneficial to realizing intelligent and efficient target vehicle control and improving the efficiency and safety of a traffic system.
After the target vehicle sends a lane changing request to the cloud platform and the cloud platform receives the request of the target vehicle, target control information of the target vehicle is generated according to factors such as current road conditions, traffic flow conditions and the like, the target vehicle responds to the lane changing request of the target vehicle, the target control information generated by the cloud platform is obtained, and the target vehicle is controlled according to the target control information; through the information interaction between the target vehicle and the cloud platform, more accurate and intelligent vehicle control is realized, and the efficiency and the safety of lane changing operation are effectively improved.
After the implementation environment and the application scenario of the embodiment of the present application are introduced, a vehicle control method provided by the embodiment of the present application is described below. Referring to fig. 2, fig. 2 is a schematic flowchart of a vehicle control method according to an embodiment of the present application, taking an execution subject as a cloud platform as an example, the vehicle control method 200 includes steps 202 to 206.
In step 202, the cloud platform responds to a lane change request of the target vehicle to acquire first state information of the target vehicle at a first moment, and second state information and second control information of a plurality of reference vehicles at the first moment.
The lane change request of the target vehicle is used for requesting the target vehicle to change from the current lane to the target lane, and the lane change request can be manually triggered by a driver, can be automatically triggered by the target vehicle, can be triggered by a traffic management system, and can be triggered by communication among vehicles.
Specifically, the driver can actively send a lane changing request to the cloud platform through a control panel, a button or a man-machine interaction interface in the target vehicle, the lane changing mode allows the driver to change lanes according to own will and judgment, and the control right of the driver on the operation of the target vehicle is well reserved; the automatic driving system of the target vehicle can automatically judge whether lane changing is needed according to preset traffic rules and strategies, and send a lane changing request to the cloud platform, and the lane changing decision can be automatically carried out according to environmental change, road conditions and other information without manual intervention of a driver; the urban traffic management system can send a channel changing request to the target vehicle according to the information of road conditions, traffic demands, traffic flow and the like, and the mode can realize traffic jam dredging and cruising road scheduling so as to improve the overall traffic efficiency; the vehicles can communicate through the internet of vehicles technology, and the triggering of the lane changing request of the target vehicle is realized by mutually exchanging information and achieving consensus.
The cloud platform acquires first state information of a target vehicle, second state information of a reference vehicle and second control information of the reference vehicle through the road side sensing equipment, wherein the first state information comprises a position of the target vehicle at a first moment, a longitudinal speed of the target vehicle and lane information of the target vehicle, the second state information comprises a position of the reference vehicle at the first moment, a longitudinal speed of the reference vehicle and lane information of the reference vehicle, and the second control information of the reference vehicle comprises acceleration information of the reference vehicle and lane change information of the reference vehicle at the first moment.
Specifically, at a first moment, the road side sensing device can acquire first state information of the target vehicle, second state information and second control information of each of the plurality of reference vehicles, and upload the acquired first state information of the target vehicle, the acquired second state information and the acquired second control information of each of the plurality of reference vehicles to the cloud platform.
The reference vehicle is a vehicle in a preset range around the target vehicle, a range with a specific distance is set around the target vehicle, the vehicles in the range are all reference vehicles, and the reference vehicle can be vehicles in front of, behind or on adjacent lanes of the target vehicle. By taking vehicles in a preset range around the target vehicle as reference vehicles, finer traffic coordination and optimization can be realized, and by acquiring the state information and the control information of the reference vehicles, a more proper lane change strategy can be formulated according to the position and the traffic environment of the target vehicle, so that collision or interference with other vehicles is avoided.
It should be noted that, the preset range may be set according to a specific traffic environment and a channel changing situation, and the size and shape of the range may be determined according to an actual requirement and an algorithm design, which is not specifically limited in this embodiment.
For example, the areas of 30 meters in front of the target vehicle, 30 meters in rear, 6 meters on the left side, and 6 meters on the right side may be set as the preset range of the reference vehicle.
In step 204, the cloud platform determines a plurality of third state information of each reference vehicle at a plurality of subsequent second moments according to the second state information and the second control information of the plurality of reference vehicles.
Wherein the number of the reference vehicles is p, and the p reference vehicles are C respectively 1 ，C 2 ，C 3 ，……，C p P is a positive integer, and p is more than or equal to 1; the first time is the current time and is marked as T 1 The subsequent second times represent future times after the current time, and are in turn T 2 ，T 3 ，……，T n N is a positive integer, and n is not less than 2.
In the embodiment of the application, the method for determining the third state information and the third control information of p reference vehicles at a plurality of subsequent second moments by the cloud platform according to the second state information and the second control information of the p reference vehicles at the first moments is the same, and the cloud platform is used for determining the third state information and the third control information of the p reference vehicles at the subsequent second moments according to the reference vehicle C in the p reference vehicles q Fourth state information and fourth control information of (C) to determine a reference vehicle C q A second time T among a plurality of subsequent second times i+1 Step 204 is described as an example of the third state information, q and i are positive integers, and q is 1-p, i is 1-n-1, and step 204 specifically includes steps 2041-2043.
Step 2041, determining a time compensation value of the reference vehicle according to time intervals of two adjacent second moments in the plurality of second moments.
Wherein T is 1 ，T 2 ，T 3 ，……，T n An arithmetic series is formed, and the tolerance of the arithmetic series is delta T, delta T is the reference vehicle C q Is used for the time compensation value of (a).
It should be noted that the time compensation values Δt of the plurality of reference vehicles at the plurality of subsequent second moments are all the same.
In step 2042, a first coefficient and a second coefficient of the reference vehicle are determined based on the time compensation value.
Wherein the first coefficient A is used for adjusting the reference vehicle C q At a second time T i Fourth state information of (C) is in reference vehicle C q At a second time T i+1 The matrix form of the first coefficient is expressed asSecond time T i For the second time T i+1 Is the last moment in time.
The second coefficient B is used for adjusting the reference vehicle C q At a second time T i Fourth control information of (C) is in reference vehicle C q At a second time T i+1 The matrix form of the second coefficient is expressed as
It should be noted that the fourth state information may be the second state information or the third state information; in the case of i=1, the second time T i+1 For the 1 st second time of the subsequent second times, the fourth state information is the first time T 1 Corresponding second state information; in case i > 1, the second instant T i+1 For the second time except the 1 st second time in the subsequent plurality of second times, the fourth state information is the second time T i+1 Third state information corresponding to the last second time of the table.
In the embodiment of the application, the first coefficients and the second coefficients of the plurality of reference vehicles at the subsequent second moments are the same, and the first coefficients and the second coefficients of the reference vehicles are adjusted to enable the third state information of the reference vehicles at the second moments to be more accurate and more suitable for the current environment, so that the state information of the reference vehicles in the future can be predicted and determined better, and intelligent decision and planning can be performed.
In step 2043, the cloud platform determines third state information of the reference vehicle at the second moment according to the fourth state information, the fourth control information, the first coefficient and the second coefficient.
Wherein reference will be made to vehicle C q At a second time T i Is denoted as Z q (T i ) Reference vehicle C q At a second time T i Is denoted as U q (T i )。
Wherein Z is q (T i )＝{x q (T i ),v q (T i ),lane q (T i )}，x q (T i ) For reference vehicle C q At a second time T i Is arranged at the longitudinal position of the frame; v q (T i ) For reference vehicle C q At a second time T i Is a longitudinal speed of (2); lane q (T i ) For reference vehicle C q At a second time T i Number of lane, lane q (T i )＝{1,2,……, l }, l is the reference vehicle C q Total number of lanes on the road, reference vehicle C q The number of the lanes of the road is sequentially 1,2, … …, l and l are positive integers from right to left, and l is more than or equal to 1.
Wherein,a q (T i ) For reference vehicle C q At a second time T i Acceleration of (2); />For reference vehicle C q At a second time T i Is to change track left request, is to add> Indicating that the channel is not changed,indicating a lane change to the left; />For reference vehicle C q At two moments T i Is to change track right request,/-> Indicating that the channel is not changed and the user is assy>Indicating a lane change to the right.
In an embodiment of the present application, according to formula Z q (T i+1 )＝A*Z q (T i )+B*U q (T i ) Determining a reference vehicle C q At a second time T i+1 Third state information Z of (2) q (T i+1 ) Fourth control information U q (T i ) A of (a) q (T i ) Is based on reference vehicle C q Is determined by the cost function of reference vehicle C q The cost function determining method of the target vehicle is the same as the cost function determining method of the target vehicle, and specific details refer to steps 2051-2055; at the same time according to reference vehicle C q Cost function determination a of (2) q (T i ) The method of determining the target acceleration according to the cost function of the target vehicle is the same as the following method, and the details of steps 2061 to 2063 are omitted in this embodiment.
In the embodiment of the application, under the condition that the third state information of any one of a plurality of reference vehicles at any one second moment is determined, firstly, determining a time compensation value of the reference vehicle according to the time interval of two adjacent second moments in a plurality of subsequent second moments; next, determining a first coefficient for adjusting the weight of the fourth state information in the third state information to be determined and a second coefficient for adjusting the weight of the second control system in the third state information to be determined according to the time compensation value, the fourth state information is the state information of the reference vehicle at the moment which is the moment before the second moment, and the fourth control information is the control information of the reference vehicle at the moment which is the moment before the second moment; and finally, determining third state information to be determined of the reference vehicle at the second moment according to the fourth state information, the fourth control information, the first coefficient and the second coefficient. By combining the state information, the control information and the weight coefficient of the reference vehicle at the last moment of the second moment corresponding to the third state information to be determined, accurate prediction and adjustment of the third state information to be determined of the reference vehicle at the second moment in the future are realized, the prediction precision is high, and the target state information of the target vehicle can be determined conveniently according to a plurality of third state information of each reference vehicle obtained through prediction at a plurality of subsequent second moments.
Step 206, the cloud platform determines target control information of the target vehicle according to the first state information and the cost function of the target vehicle and a plurality of third state information of a plurality of reference vehicles at a plurality of subsequent second moments; the cost function is used for indicating the advantages and disadvantages of target control information, and the target control information is used for indicating whether the target vehicle is converted to a target lane or not and target state information of the target vehicle at a plurality of subsequent second moments.
It should be noted that the lane change function and meaning of the vehicle is that a proper lane can be selected, so that the running of the vehicle more accords with the expectations of a driver; in determining the target control information of the target vehicle, it is necessary to optimize the driving efficiency, the following safety, the lane changing safety and the driving comfort of the target vehicle, so as to improve the driving quality and the riding experience of the target vehicle and ensure the driving safety.
The driving efficiency refers to that the target vehicle can complete tasks with the shortest time or the lowest energy consumption under the given road condition, for example, proper longitudinal speed and acceleration are selected to ensure that the target vehicle can quickly and effectively reach the destination.
Following safety refers to maintaining a safe vehicle distance between the target vehicle and the lead vehicle to ensure adequate time and space to react in the event of an emergency or emergency braking.
Lane change safety refers to the interaction of a target vehicle with other vehicles during lane change, and it is necessary to ensure that no danger is caused or travel of other vehicles is disturbed during lane change.
The driving comfort refers to the stability and comfort of the target vehicle during driving, such as reducing sudden braking or turning, etc., and provides a good driving experience for the occupant.
In the embodiment of the application, the methods for determining the plurality of target state information of the target vehicle at the plurality of subsequent second moments are the same, and the cloud platform is used for determining the second moment T in the plurality of subsequent second moments i+1 For example, step 206 is described, and step 206 specifically includes steps 2061 to 2063.
Step 2061, determining a plurality of cost function values of the target vehicle under different acceleration conditions according to the fifth state information and the cost function and a plurality of third state information of the plurality of reference vehicles at the second moment.
Wherein, the firstThe five-state information is that the target vehicle is at the second moment T i+1 Is the last time (i.e. the second time T i ) The fifth state information may be the first state information or the target state information; in the case of i=1, the second time T i+1 For the 1 st second time of the subsequent second times, the fifth status information is the first time T of the target vehicle 1 Corresponding first state information; in case i > 1, the second instant T i+1 For the second time except the 1 st second time in the subsequent plurality of second times, the fifth state information is the second time T i+1 Target state information corresponding to the last second moment.
The target vehicle C g At a second time T i+1 Is Z g (T i+1 )，Z g (T i+1 )＝{x g (T i+1 ),v g (T i+1 ),lane g (T i+1 )}，x g (T i+1 ) For the target vehicle C g At a second time T i+1 Is arranged at the longitudinal position of the frame; v g (T i+1 ) For the target vehicle C g At a second time T i+1 Is a longitudinal speed of (2); lane g (T i+1 ) For the target vehicle C g At a second time T i+1 Number of lane, lane g (T i+1 )＝{1,2,……,l}。
In the embodiment of the application, the target vehicle is at the second time T i+1 The specific determination steps of the cost function of (a) include steps 2051 to 2055.
Step 2051, according to the target vehicle at the second time T i+1 State information and desired travel speed of the reference vehicle at a second time T i+1 Determining the third state information of the target vehicle at the second time T i+1 Driving efficiency cost, following safety cost and lane changing safety cost.
The travel efficiency cost J 1 For measuring the energy consumption of the target vehicle during driving, according to the second moment T of the target vehicle i+1 In the fifth state information of (2)And the longitudinal speed of the target vehicle at a second instant T i+1 Is set to the desired longitudinal velocity v g (e) And the reference vehicle is at a second time T i+1 Longitudinal speed in the third state information of (2), determining the running efficiency cost J 1 。
Wherein the driving efficiency cost J 1 The formula of (2) is:w v cost of travel efficiency J 1 Weight coefficient, v fv (T i+1 ) For the second time T i+1 Located in the target vehicle C g Front side, and with the target vehicle C g Longitudinal speed of a reference vehicle located in the same lane.
Note that, the following safety cost J 3 For measuring the safety distance and safety behavior between a target vehicle and a reference vehicle located in front of and in the same lane as the target vehicle, in dependence on the target vehicle at a second moment T i+1 Longitudinal position and driving position in the fifth state information of (c), and reference vehicle at the second time T i+1 Longitudinal position and driving position in the third state information of (2) to determine the following safety cost J 3 。
Wherein, the following safety cost J 3 The formula of (2) is:w f to keep pace with the security cost J 3 Weight coefficient f of (1) g (T i+1 ) At a second time T for the target vehicle i+1 Is a safety penalty.
In the embodiment of the application, the target vehicle is at the second time T i+1 The following safety cost f g (T i+1 ) Calculating by using the headway (TimeHeadway, THW) and the Collision Time (TTC) as indexes,x fv (T i+1 ) For the second time T i+1 Is positioned atTarget vehicle C g Front side, and with the target vehicle C g Longitudinal position of reference vehicles located in the same lane. />
In the case where a reference vehicle is present in front of the target vehicle in the same lane as the target vehicle and the longitudinal speed of the reference vehicle is not lower than the longitudinal speed of the target vehicle, it is necessary to not only maintain a safe following distance but also consider the relative speed between the vehicles, and therefore, the following safety cost in this case needs to consider both THW and TTC indexes; in the case where there is a reference vehicle in front of the target vehicle that is in the same lane as the target vehicle and the longitudinal speed of the reference vehicle is higher than the longitudinal speed of the target vehicle, there is no tendency of relative proximity between the target vehicle and the reference vehicle, and therefore, in this case, it is sufficient to maintain the safe following distance without considering the TTC index, only considering the THW index.
Thus, the target vehicle is at the second time T i+1 The following safety cost f g (T i+1 ) The calculation formula of (2) is as follows:a is the following safety cost f g (T i+1 ) Weight coefficient of the middle THW index, b is the following safety cost f g (T i+1 ) The weight coefficient of the TTC index in the middle, THWr is the second moment T i+1 TTCr is the second time T i+1 Is used for the collision time.
It should be noted that the lane change security cost J 4 For measuring the effect of the lane change behavior of the target vehicle on the traffic safety, according to the second time T of the target vehicle i+1 Longitudinal position in the fifth status information of (2) and reference vehicle at the second time T i+1 Longitudinal position in the third state information of (2) determining a following safety cost J 3 。
Wherein, the lane change safety cost J 4 The formula of (2) is:w lc for the lane change safety cost J 4 Weight coefficient, lc g (T i+1 ) At a second time T for the target vehicle i+1 Is a trade-off security cost.
In the embodiment of the application, the target vehicle is at the second time T i+1 Lane change security cost lc g (T i+1 ) The calculation formula of (2) is as follows:D real at a second moment T for the target vehicle and a reference vehicle behind the target vehicle and in the same lane as the target vehicle i+1 D is the actual distance of e At a second moment T for the target vehicle and a reference vehicle behind the target vehicle and in the same lane as the target vehicle i+1 Is a desired distance from the first end of the first link; in order to avoid frequent lane changing of the target vehicle, under the condition that the reference vehicle does not exist behind the lane where the target vehicle is located, a part of lane changing safety cost still can be generated, and at the moment, the lane changing safety cost lc is set g (T i+1 ) Taking 0.03.
In step 2052, the cloud platform determines a driving comfort cost of the target vehicle according to the desired acceleration of the target vehicle.
The driving comfort cost J 2 For measuring the riding comfort degree of the target vehicle in the running process, and the running comfort cost J 2 The formula of (2) is:w a to keep pace with the security cost J 2 Is used for the weight coefficient of the (c),at a second time T for the target vehicle i+1 Is used to determine the desired acceleration of the vehicle.
In step 2053, the cloud platform determines a cost of the target vehicle deviating from the target lane according to the state information of the target vehicle.
Note that, the departure target lane cost J 5 For measuring the degree of deviation of the target vehicle from the target laneCost J 5 The formula of (2) is:w l to deviate from the target lane cost J 5 Weight coefficient, p g (T i+1 ) At a second time T for the target vehicle i+1 Is set to the target lane cost.
Wherein the target vehicle is at a second time T i+1 Is the departure target lane cost p g (T i+1 ) The calculation formula of (2) is as follows: lane g (T i+1 ) =0 indicates that the target vehicle is at the second time T i+1 The lane is the target lane, lane g (T i+1 ) Not equal to 0 indicates that the target vehicle is at the second time T i+1 The lane is other lanes than the target lane.
In the embodiment of the application, the target lane is determined based on a lane change request sent by the target vehicle to the cloud platform.
In step 2054, the cloud platform determines a cost function of the target vehicle according to the driving efficiency cost, the following safety cost, the lane changing safety cost, the driving comfort cost, and the target lane departure cost.
Wherein the cost function J of the target vehicle is the running efficiency cost J of the target vehicle 1 Safety cost of following 3 Lane change security cost J 4 Cost of comfort in driving J 2 And departure target lane cost J 5 And, the cost function J of the target vehicle is given by: j=j 1 +J 2 +J 3 +J 4 +J 5 The method comprises the following steps:
in step 2055, the cloud platform establishes constraints for the cost function, where the constraints include a speed constraint and an acceleration constraint of the target vehicle.
When the cost function optimization solution is performed, the to-be-solved variables of the target vehicle are constrained based on the actual conditions, and the to-be-solved variables are the longitudinal speed and the acceleration of the target vehicle.
Considering road speed limit and self-dynamics performance of a target vehicle, longitudinal speed constraint conditions of the target vehicle are as follows: maximum driving speed limited for the road on which the target vehicle is located,/->A maximum travel speed that can be achieved for the target vehicle.
Considering the road environment and the limitation of the power system of the target vehicle, the acceleration constraint conditions of the target vehicle are as follows:and jerk min ≤jerk g (T i+1 )≤jerk max ，/>A is the maximum braking deceleration of the target vehicle max (g) For maximum acceleration of the target vehicle, jerk g (T i+1 ) At a second time T for the target vehicle i+1 Rate of change of acceleration of jerk min (g) At a second time T for the target vehicle i+1 Is the minimum of the acceleration rate of change of (1), jerk max (g) At a second time T for the target vehicle i+1 Acceleration rate of change maximum of (c).
In the embodiment of the application, a cost function of the target vehicle at each second moment is constructed according to the driving efficiency cost, the following safety cost, the lane changing safety cost, the driving comfort cost and the lane departure target cost of the target vehicle at each second moment, constraint conditions are established for the cost function, the driving efficiency cost, the following safety cost, the lane changing safety cost, the driving comfort cost and the lane departure target cost reflect the cost and the cost of the target vehicle at different aspects, and the cost function obtained by the costs can comprehensively evaluate the cost and the cost of the target vehicle at different aspects at the second moment, so that the comprehensive advantages and disadvantages of the target vehicle under specific conditions can be judged, and more effective and reliable vehicle control can be realized.
At the second moment T when the target vehicle is obtained i+1 After the cost function and the constraint condition, the target vehicle in the cost function is at the second moment T i+1 Is set to the desired acceleration a of Ti+1 As an independent variable, calculate at p g (T i+1 ) In the case of =0, a plurality of different desired accelerations a Ti+1 A corresponding plurality of first price function values and calculated at p g (T i+1 ) In the case of =1, a plurality of different desired accelerationsA corresponding plurality of second cost function values.
In step 2062, the cloud platform selects an acceleration corresponding to the minimum cost function value of the plurality of cost function values as the target acceleration at the second moment.
Wherein the expected acceleration corresponding to the minimum first cost function value of the plurality of first cost function valuesAs the second time T i+1 A first target acceleration of the target vehicle at a second time T i+1 Acceleration when the vehicle does not need to be changed to a target lane; the expected acceleration corresponding to the smallest second cost function value in the plurality of second cost function valuesAs the second time T i+1 A second target acceleration of the target vehicle at a second time T i+1 Acceleration when changing to the target lane.
In the embodiment of the application, the acceleration corresponding to the minimum first cost function value in the plurality of first cost function values is taken as the second moment T i+1 And takes the acceleration corresponding to the smallest second cost function value in the plurality of second cost function values as a second moment T i+1 Can accurately predict the acceleration information of the target vehicle no matter whether the target vehicle is changed to the target lane, and can make the target vehicle at the second moment T i+1 Is closer to the desired state, and at the same time, enables the target vehicle to be at the second time T i+1 And the device operates with higher energy efficiency, and reduces unnecessary energy consumption.
In step 2063, the cloud platform determines target control information of the target vehicle according to the target acceleration and the fifth state information.
Wherein according to formula V goal1 (T i+1 )＝a goal1 (T i+1 )*ΔT+V goal1 (T i ) Calculating the second time T of the target vehicle i+1 Is set to a first target longitudinal velocity V goal1 (T i+1 )，a goal1 (T i+1 ) At a second time T for the target vehicle i+1 V of the first target longitudinal velocity of (2) goal1 (T i ) At a second time T for the target vehicle i Is set at a first target longitudinal speed; according to formula V goal2 (T i+1 )＝a goal2 (T i+1 )*ΔT+V goal2 (T i ) Calculating the second time T of the target vehicle i+1 Is a second target longitudinal velocity V of (2) goal2 (T i+1 )，a goal2 (T i+1 ) At a second time T for the target vehicle i+1 V of the second target longitudinal velocity of (2) goal2 (T i ) At a second time T for the target vehicle i Is set at the first target longitudinal speed.
The target vehicle is at the second time T i+1 The target control information of (1) includes the target vehicle at the second time T i+1 First target longitudinal speed V without lane change goal1 (T i+1 ) And the target vehicle is at a second time T i+1 Second at lane changeTarget longitudinal velocity V goal2 (T i+1 )。
In the embodiment of the application, under the condition of determining target control information of a target vehicle at any one of a plurality of subsequent second moments, firstly, determining a plurality of cost function values of the target vehicle under different acceleration conditions and different target lane departure cost conditions according to fifth state information of the target vehicle at a moment which is the last of the second moments, cost functions of the target vehicle at the second moments and a plurality of third state information of a plurality of reference vehicles at the second moments; secondly, selecting the acceleration corresponding to the minimum cost function value in a plurality of cost function values under the condition of different departure target lane cost as the target acceleration of the different departure target lane cost of the target vehicle at the second moment; and finally, determining target control information of the target vehicle at the second moment according to the target acceleration of the target vehicle and the fifth state information, wherein the target control information at the second moment comprises a first target longitudinal speed of the target vehicle when the track is not changed at the second moment and a second target longitudinal speed of the target vehicle when the track is changed. By considering a plurality of cost function values under the condition of the same departure target lane cost, the performance and effect of the target vehicle under the condition of different acceleration of the same departure target lane cost can be evaluated, and the acceleration corresponding to the minimum cost function value is selected as the target acceleration, so that the target vehicle can reach the optimal state at the second moment, the instability of the target vehicle in the running process can be reduced, and the stability and reliability of the target vehicle in the running process can be improved.
In the embodiment of the application, firstly, a cloud platform responds to a lane changing request of a target vehicle, and obtains first state information of the target vehicle at a first moment and second state information and second control information of a plurality of reference vehicles at the first moment through a road side sensing device so as to obtain detailed information about the target vehicle and the reference vehicles at the first moment; secondly, predicting a plurality of third state information of each reference vehicle at a plurality of subsequent second moments according to the second state information and the second control information of the plurality of reference vehicles so as to provide reference for the target control information of the target vehicle; finally, determining target control information of the target vehicle according to the first state information and the cost function of the target vehicle and a plurality of third state information of a plurality of reference vehicles at a plurality of subsequent second moments, wherein the target control information is used for indicating whether to change to a target lane or not and the target state information of the target vehicle at the plurality of subsequent second moments; the method and the system can accurately evaluate the third state information of the plurality of reference vehicles around the target vehicle at the subsequent plurality of second moments, efficiently and accurately obtain the target control information of the target vehicle in the lane change process based on the third state information of the plurality of reference vehicles at the subsequent plurality of second moments, and the target control information provides the target vehicle with the target state information of each second moment in the subsequent plurality of second moments in the lane change process, thereby being beneficial to realizing intelligent and efficient target vehicle control and improving the efficiency and safety of a traffic system.
Another technical solution provided by the embodiments of the present application is described below. Referring to fig. 3, fig. 3 is a schematic flowchart of another vehicle control method according to an embodiment of the present application, taking an execution subject as an example of a target vehicle, the vehicle control method 300 includes steps 302 and 304.
Step 302, a target vehicle responds to a lane change request of the target vehicle to acquire target control information of the target vehicle; the target control information is used for indicating whether to switch to a target lane and target state information of a target vehicle at a plurality of subsequent second moments.
The cloud platform responds to the lane changing request of the target vehicle to obtain target control information of the target vehicle, and the target vehicle responds to the lane changing request of the target vehicle to obtain the target control information obtained by the cloud platform.
It should be noted that, the target control information includes a lane change instruction and target control information at each of a plurality of subsequent second moments, the lane change instruction indicates whether the target vehicle performs a lane change operation, and the target control information at each of the second moments includes a first target longitudinal speed and a second target longitudinal speed, where the first target longitudinal speed is a longitudinal speed of the target vehicle when the lane change instruction indicates that the lane change is not performed, and the second target longitudinal speed is a longitudinal speed of the target vehicle when the lane change instruction indicates that the lane change is performed.
For example, in the case where the lane change instruction in the target control information is "yes", the target vehicle is changed from the current lane to the target lane at a second target longitudinal speed in the target state information at a plurality of subsequent second moments; in the case where the lane change instruction in the target control information is no, the target vehicle travels in the current lane at the first target longitudinal speed in the target state information at a plurality of subsequent second times.
In the embodiment of the application, a target vehicle sends a channel changing request to a cloud platform, and the cloud platform generates target control information of the target vehicle according to factors such as current road conditions, traffic flow conditions and the like after receiving the request of the target vehicle and sends the target control information back to the target vehicle; after receiving the target control information returned by the cloud platform, the target vehicle can perform corresponding lane changing operation according to the target control information. Through the information interaction between the target vehicle and the cloud platform, more accurate and intelligent vehicle control is realized, and the efficiency and the safety of lane changing operation are improved. Meanwhile, the cloud platform can analyze and optimize the traffic condition of the whole road through information sharing and summarizing of multiple vehicles, and further improves the efficiency and safety of road traffic.
The target vehicle controls the target vehicle based on the target control information, step 304.
The step 304 is to control the target vehicle based on the target control information, and specifically includes steps 3041 to 3045.
In step 3041, the target vehicle determines whether the target control information satisfies a safe lane change condition.
After the target vehicle acquires the target control information of the target vehicle, the target vehicle judges whether second target longitudinal speeds of a plurality of target state information of the target control information meet the safe lane change condition through the lane change safety judging model again.
The method for determining whether the second target longitudinal speed of the plurality of target state information satisfies the safe lane change condition by the lane change safety determination model is the same, and step 3041 is described by taking as an example whether the second target longitudinal speed of any one of the plurality of target state information satisfies the safe lane change condition by the lane change safety determination model, where step 3041 specifically includes steps 30111 to 30116.
In step 30411, the target vehicle obtains a plurality of dynamic information of a plurality of reference vehicles at a second time corresponding to the target state information.
The target vehicle can acquire a plurality of dynamic information of a plurality of reference vehicles at the current moment through the road side sensing equipment, one reference vehicle corresponds to one dynamic information, and the dynamic information of each reference vehicle comprises the longitudinal position and the longitudinal speed of the reference vehicle.
Step 30212, for each of the plurality of reference vehicles, determining a relative speed between the reference vehicle and the target vehicle based on the longitudinal speed of the reference vehicle and the longitudinal speed of the target vehicle.
Wherein at a second time corresponding to the target state information, the relative speed V between the reference vehicle and the target vehicle xd The calculation formula of (2) is as follows: v (V) xd ＝|V 1 -V 2 |，V 1 For the longitudinal speed of the reference vehicle at the second moment, V 2 Is a second target longitudinal speed of the target vehicle.
Step 3043, determining a vehicle distance between the reference vehicle and the target vehicle based on the longitudinal position of the reference vehicle and the longitudinal position of the target vehicle.
At a second moment corresponding to the target state information, a calculation formula of a vehicle distance L between the reference vehicle and the target vehicle is as follows: l= |p 1 -P 2 |，P 1 For the longitudinal position of the reference vehicle at the second moment, P 2 Is the longitudinal position of the target vehicle at the second moment.
Step 30414, determining a collision value of the reference vehicle at the second moment according to the relative speed and the vehicle distance corresponding to the reference vehicle.
Wherein the collision value TTC of the reference vehicle at the second moment xd The calculation formula of (2) is as follows:
in step 30414, under the condition that the collision values of the plurality of reference vehicles at the second moment are all larger than the preset collision value, it is determined that the target state information meets the safe lane change condition.
When the collision values of the plurality of reference vehicles are all larger than the preset collision value, the fact that a sufficient time interval exists between the target vehicle and surrounding reference vehicles at the second moment corresponding to the control information in the lane change process, namely, the direct risk of collision with other reference vehicles does not exist.
It should be noted that, the preset collision value may be set with reference to a road traffic rule and a safety standard; reasonable collision values can also be estimated based on abundant experiences accumulated in the traffic safety field by a large number of practitioners such as traffic engineers, driver trainers, automobile manufacturers, and the like, and as preset collision values, the embodiment is not particularly limited thereto.
Step 30416, determining that the target state information does not satisfy the safe lane change condition when there is at least one reference vehicle having a collision value less than or equal to a preset collision value at the second time among the plurality of reference vehicles.
If the collision value of the reference vehicle is smaller than or equal to the preset collision value at the second moment, the risk of collision exists between the target vehicle and surrounding reference vehicles in the lane change process, and therefore, if at least one of the plurality of reference vehicles has the collision value smaller than or equal to the preset collision value, the target state information is considered to not meet the safe lane change condition.
In the embodiment of the application, under the condition that a plurality of pieces of target state information of target control information meet the safety channel switching condition, determining whether the target control information meets the safety channel switching condition; otherwise, the target control information is considered to not meet the safe channel change condition.
It should be noted that the lane change security judgment model may be a TTC model, or may be a Mazda model, a Honda model, a Berkeley model, a SeungwukMoon model, or the like, which is not specifically limited in this embodiment.
In step 3042, the target vehicle plans the target lane change path when the target control information satisfies the safe lane change condition.
Under the condition that the target control information meets the safe lane change condition, the target vehicle plans the target lane change path of the target vehicle through the lane change path planning model.
In the embodiment of the application, the method for planning the target road changing path of the target vehicle through the road changing path planning model specifically comprises the steps 30321 to 30427.
In step 30421, the lane change start position and the lane change end position of the target vehicle are acquired.
The lane change starting position is the current position of the target vehicle, and the lane change ending position is the position where lane change is expected to reach the target position.
Step 30422, calculating the distance between the channel changing start position and the channel changing end position according to the channel changing start position and the channel changing end position.
The distance between the channel changing starting position and the channel changing ending position is the reference and limiting condition of the channel changing operation.
In step 30423, the speed of the target vehicle at the lane change start position, the speed of the target vehicle at the lane change end position, the acceleration of the target vehicle at the lane change start position, and the speed of the target vehicle at the lane change end position are set.
And step 30416, determining a fitting path by using a five-degree polynomial function according to the lane change starting position, the lane change ending position, the speed of the target vehicle at the lane change starting position, the speed of the target vehicle at the lane change ending position, the acceleration of the target vehicle at the lane change starting position and the speed of the target vehicle at the lane change ending position.
The five-degree polynomial function can describe a complex curve shape, can have one or more turning points and has rich characteristics, and the shape and the position of the function can be changed by adjusting the values of the coefficients so as to adapt to different application requirements.
And step 30525, calculating the lane change path point coordinates of each time step by using the fitted penta-order polynomial function, the lane change starting position, the lane change ending position, the speed of the target vehicle at the lane change starting position, the speed of the target vehicle at the lane change ending position, the acceleration of the target vehicle at the lane change starting position and the speed of the target vehicle at the lane change ending position.
The method for calculating the coordinates of the road changing path points of each time step is that the time is gradually increased from the first moment to the last second moment in a plurality of subsequent second moments, and a plurality of road changing path points are calculated according to the fitted quintic polynomial function, wherein the road changing path points comprise the abscissa of the road changing path points and the ordinate of the road changing path points.
And step 30426, performing interpolation processing on the plurality of lane change path points calculated in step 30125 to obtain a plurality of lane change path points after interpolation processing.
The interpolation processing method can be a plurality of interpolation modes such as linear interpolation and spline interpolation, and the channel changing path points calculated in the step 30525 are subjected to interpolation processing to obtain a plurality of channel changing path points after interpolation processing, so that the transition between the channel changing path points corresponding to a plurality of subsequent second moments is more natural, and abrupt change is avoided.
And 30427, sorting the plurality of interpolation-processed road-changing path points according to the time sequence to form a road-changing path point sequence.
The number of the road changing path points after interpolation processing in the road changing path point sequence is equal to and corresponds to the number of the following second moments one by one, and the road changing path point sequence is the target road changing path of the target vehicle.
In step 3043, the target vehicle is controlled to change from the current lane to the target lane according to the target lane change path and the target control information, and is driven at a plurality of second moments in sequence with the target state information corresponding to each second moment.
According to the plurality of interpolation-processed road changing path points in the target road changing path and the second target longitudinal speed in the plurality of target state information of the target control information, the target vehicle is driven to the interpolation-processed road changing path points corresponding to the second moment at each second moment by the longitudinal controller and the transverse controller of the target vehicle at the second target longitudinal speed corresponding to the second moment, so that the target vehicle is changed from the current lane to the target lane.
The longitudinal controller of the target vehicle adopts the PID controller to control the longitudinal direction of the target vehicle, and the specific process of the longitudinal controller to control the longitudinal direction of the target vehicle comprises the following steps: firstly, defining state quantity and input signals in a longitudinal controller, wherein the state quantity can comprise speed, acceleration and the like of a target vehicle, the input signals can comprise expected speed, expected acceleration and the like of the target vehicle, and a PID controller is designed to control driving or braking moment of the target vehicle; secondly, a longitudinal inverse dynamics model of the target vehicle is established, the model converts an input signal into a desired driving or braking torque, and a desired throttle opening and a desired braking wheel cylinder pressure are calculated according to the longitudinal inverse dynamics model and by combining an engine map and a braking pressure relation curve of the target vehicle; finally, during the running of the target vehicle, the state quantity and the input signal of the target vehicle are acquired in real time, and corresponding control instructions are calculated through the PID controller and the longitudinal inverse dynamics model, and the control instructions are transmitted to the actuating mechanism of the vehicle, such as a throttle actuator and a brake system, as inputs so as to realize the control of the throttle opening and the brake cylinder pressure.
The transverse controller of the target vehicle adopts the LQR controller with feedforward control compensation to carry out transverse control on the target vehicle, and the specific process of the transverse controller for carrying out transverse control on the target vehicle comprises the following steps: firstly, defining state quantities in a transverse controller, wherein the state quantities comprise transverse position errors (transverse deviation), course angle errors, transverse speed errors and the like of a target vehicle; secondly, tracking the target lane change path by adopting an LQR (Linear quadratic regulator) controller according to the target lane change path; meanwhile, on the basis of the LQR controller, a feedforward control compensation item is introduced and used for further improving the tracking performance of the LQR controller, and the feedforward control compensation item can be used for obtaining a final control instruction by converting curvature information of a target lane change path into a desired front wheel corner and adding the desired front wheel corner with output of the LQR controller; finally, in the running process of the target vehicle, the state quantity of the target vehicle is obtained in real time, a control instruction corresponding to each state quantity is calculated through the LQR controller and feedforward control compensation, and the control instruction is transmitted to an actuating mechanism of the target vehicle, such as a steering system, as input, so that the control of the front wheel rotation angle is realized.
In the embodiment of the application, firstly, judging whether a plurality of target state information in target control information meets a safe channel changing condition or not; secondly, under the condition that the plurality of target state information meets the safe lane change condition, planning a target lane change path of the target vehicle; and finally, according to the target lane changing path and the target control information, the target vehicle is controlled to change from the current lane to the target lane, and the target vehicle runs at a plurality of subsequent second moments by the target state information corresponding to each second moment, so that the automatic lane changing operation of the target vehicle is realized, the running efficiency and the comfort of the target vehicle are improved, the operation burden of a driver can be reduced, the risk and the occurrence probability of traffic accidents are reduced, and the safety and the reliability of road traffic are improved.
In step 3044, the target vehicle plans the target straight path if the target control information does not satisfy the safe lane change condition.
Under the condition that the target control information does not meet the safe lane changing condition, the target vehicle plans a target straight-going path of the target vehicle through the straight-going path planning model.
In the embodiment of the application, the method for planning the target diameter path of the target vehicle through the straight path planning model specifically comprises steps 30441 to 30446.
In step 30441, the network of roads where the target vehicle is located is represented as a directed weighted graph, where each road is represented as an edge, the intersection or crossing is represented as a node, and each edge has a weight, which may be represented as a distance, travel time, or other suitable cost.
In step 3042, the node where the target vehicle is located at the first moment is taken as the starting node, the cost value g of the starting node is set to 0, and the heuristic value rhs is initialized to the estimated cost from the target vehicle to the target node.
The target node is a node where the position of the target vehicle at the last second moment in the plurality of second moments is located.
And step 3043, updating the cost value g and the heuristic value rhs of the neighbor node according to the neighbor node of the current node, and taking the neighbor node with the minimum cost value g as the next node to be accessed.
Step 30444, using the next node to be accessed as the current node, repeating steps 3042 and 3043 multiple times until the target node is reached.
In step 30445, after reaching the target node, the path from the target node to the start node is traced back, and each node on the path is converted into a coordinate point of the corresponding road center line.
In step 30446, the coordinate points of the plurality of road centerlines are ordered in time sequence to form a straight-going path point sequence.
The number of coordinate points of the central line of the road in the straight-going path point sequence is equal to and corresponds to the number of the subsequent second moments one by one, and the straight-going path point sequence is the target straight-going path of the target vehicle.
In the embodiment of the present application, the straight-path planning model may use Dijkstra algorithm, a-x algorithm or D-x lite algorithm, which is not limited in this embodiment.
Step 3045, controlling the target vehicle to travel at a plurality of subsequent second moments according to the target straight-going path and the target control information and the target state information corresponding to each second moment.
According to the plurality of straight-going path points in the target diameter path and the first target longitudinal speed in the plurality of target state information of the target control information, the target vehicle is controlled to travel to the straight-going path points corresponding to the second moment at each second moment by the longitudinal controller and the transverse controller of the target vehicle, so that the target vehicle is driven in the current lane at the corresponding target state information of each second moment.
The method for controlling the target vehicle to travel to the straight-going path point corresponding to the second time at the first target longitudinal speed corresponding to the second time by the longitudinal controller and the transverse controller of the target vehicle at each second time is the same as the method for controlling the target vehicle to travel to the interpolated lane-changing path point corresponding to the second time at each second time by the longitudinal controller and the transverse controller of the target vehicle at each second time at the second target longitudinal speed corresponding to the second time in step 3043, and the embodiment is not repeated.
In the embodiment of the application, when the plurality of target state information of the target control information does not meet the safe lane change condition, the target lane change path of the target vehicle is planned, and the target straight-through path is planned, so that the target vehicle can be ensured to run on the target straight-through path according to the target state information at the second moment and the path point of the target straight-through path at each second moment in the subsequent plurality of second moments under the condition that the target vehicle cannot safely change lanes.
In the embodiment of the application, a target vehicle sends a lane changing request to a cloud platform, the cloud platform generates target control information of the target vehicle according to factors such as current road conditions, traffic flow conditions and the like after receiving the request of the target vehicle, the target vehicle responds to the lane changing request of the target vehicle, acquires the target control information generated by the cloud platform, and controls the target vehicle according to the target control information; through the information interaction between the target vehicle and the cloud platform, more accurate and intelligent vehicle control is realized, and the efficiency and the safety of lane changing operation are effectively improved.
Fig. 4 is a schematic structural diagram of a vehicle control device according to an embodiment of the present application. Illustratively, as shown in FIG. 4, the apparatus 400 includes a first acquisition module 401, a first determination module 402, and a second determination module 403.
A first obtaining module 401, configured to obtain, in response to a lane change request of a target vehicle, first state information of the target vehicle at a first moment, and second state information and second control information of a plurality of reference vehicles at the first moment; the second control information is information for changing the state of the reference vehicle, and the lane change request is used for requesting to change from the current lane to the target lane, wherein the reference vehicle is a vehicle in a preset range around the target vehicle;
a first determining module 402, configured to determine a plurality of third state information of each reference vehicle at a plurality of subsequent second moments according to the second state information and the second control information of the plurality of reference vehicles;
a second determining module 403, configured to determine target control information of the target vehicle according to the first state information and the cost function of the target vehicle, and a plurality of third state information of a plurality of reference vehicles at a plurality of subsequent second moments; the cost function is used for indicating the advantages and disadvantages of target control information, and the target control information is used for indicating whether the target vehicle is converted to a target lane or not and target state information of the target vehicle at a plurality of subsequent second moments.
In one possible implementation manner, the first determining module 402 is specifically configured to: for any one of the plurality of reference vehicles, determining a time compensation value of the reference vehicle according to the time interval between two adjacent second moments in the subsequent plurality of second moments; for any one of a plurality of subsequent second moments, determining a first coefficient and a second coefficient of the reference vehicle according to the time compensation value; the first coefficient is used for adjusting the weight of fourth state information in third state information, the second coefficient is used for adjusting the weight of fourth control information in third state information, the fourth state information is state information of a reference vehicle at the last moment of the second moment, and the fourth control information is control information of the reference vehicle at the last moment of the second moment; and determining third state information of the reference vehicle at the second moment according to the fourth state information, the fourth control information, the first coefficient and the second coefficient.
In one possible implementation manner, the apparatus 400 further includes a third determining module, a fourth determining module, a fifth determining module, a sixth determining module, and an establishing module.
The third determining module is used for determining the running efficiency cost, the following safety cost and the lane changing safety cost of the target vehicle according to the state information and the expected running speed of the target vehicle and the third state information of the reference vehicle at any one of a plurality of subsequent second moments; the driving efficiency cost is used for measuring the energy consumption cost of the target vehicle in the driving process, the following safety cost is used for measuring the safety distance and the safety behavior between the target vehicle and the reference vehicle positioned in front of the target vehicle, and the lane change safety cost is used for measuring the influence of the lane change behavior of the target vehicle on traffic safety.
A fourth determining module, configured to determine a driving comfort cost of the target vehicle according to the expected acceleration of the target vehicle; the driving comfort cost is used for measuring the riding comfort degree of the target vehicle in the driving process.
A fifth determining module, configured to determine a cost of the target vehicle deviating from the target lane according to the state information of the target vehicle; the cost of deviating from the target lane is used for measuring the deviation degree of the target vehicle from the target lane.
And the sixth determining module is used for determining a cost function of the target vehicle according to the driving efficiency cost, the following safety cost, the lane changing safety cost, the driving comfort cost and the target lane departure cost.
The establishing module is used for establishing constraint conditions for the cost function, wherein the constraint conditions comprise speed constraint conditions and acceleration constraint conditions of the target vehicle.
In a possible implementation manner, the second determining module 403 is specifically configured to: for any one of a plurality of subsequent second moments, determining a plurality of cost function values of the target vehicle under different acceleration conditions according to the fifth state information and the cost function and a plurality of third state information of the plurality of reference vehicles at the second moment; the fifth state information is the state information of the target vehicle at the moment immediately before the second moment; selecting the acceleration corresponding to the minimum cost function value in the plurality of cost function values as the target acceleration at the second moment; and determining target state information of the target vehicle at the second moment according to the target acceleration and the fifth state information.
It should be noted that: in the vehicle control device provided in the above embodiment, when the vehicle is controlled, only the division of the above functional modules is used as an example, and in practical application, the above functional allocation may be performed by different functional modules according to needs, that is, the internal structure of the computer device is divided into different functional modules, so as to perform all or part of the functions described above. In addition, the vehicle control device and the vehicle control method embodiment provided in the foregoing embodiments belong to the same concept, and specific implementation processes of the vehicle control device and the vehicle control method embodiment are detailed in the method embodiment, and are not repeated herein.
According to the technical scheme provided by the embodiment of the application, firstly, the cloud platform responds to a lane changing request of a target vehicle, and obtains first state information of the target vehicle at a first moment and second state information and second control information of a plurality of reference vehicles at the first moment through road side sensing equipment so as to obtain detailed information about the target vehicle and the reference vehicles at the first moment; secondly, predicting a plurality of third state information of each reference vehicle at a plurality of subsequent second moments according to the second state information and the second control information of the plurality of reference vehicles so as to provide reference for the target control information of the target vehicle; finally, determining target control information of the target vehicle according to the first state information and the cost function of the target vehicle and a plurality of third state information of a plurality of reference vehicles at a plurality of subsequent second moments, wherein the target control information is used for indicating whether to change to a target lane or not and the target state information of the target vehicle at the plurality of subsequent second moments; the method and the system can accurately evaluate the third state information of the plurality of reference vehicles around the target vehicle at the subsequent plurality of second moments, efficiently and accurately obtain the target control information of the target vehicle in the lane change process based on the third state information of the plurality of reference vehicles at the subsequent plurality of second moments, and the target control information provides the target vehicle with the target state information of each second moment in the subsequent plurality of second moments in the lane change process, thereby being beneficial to realizing intelligent and efficient target vehicle control and improving the efficiency and safety of a traffic system.
Fig. 5 is a schematic structural view of another vehicle control apparatus according to an embodiment of the present application. Illustratively, as shown in FIG. 5, the apparatus 500 includes a second acquisition module 501 and a control module 502.
A second obtaining module 501, configured to obtain target control information of a target vehicle in response to a lane change request of the target vehicle; the target control information is used for indicating whether to shift to a target lane and target state information of a target vehicle at a plurality of subsequent second moments;
the control module 502 is configured to control the target vehicle based on the target control information.
In one possible implementation, the control module 502 is specifically configured to: judging whether the target control information meets the safe channel changing condition or not; under the condition that the target control information meets the safe channel changing condition, planning a target channel changing path; and according to the target lane change path and the target control information, controlling the target vehicle to change from the current lane to the target lane, and driving at a plurality of subsequent second moments by the target state information corresponding to each second moment.
In one possible implementation, the control module 502 is specifically configured to: under the condition that the target control information does not meet the safe channel changing condition, planning a target straight path; and controlling the target vehicle to run at a plurality of subsequent second moments according to the target straight-going path and the target control information and the target state information corresponding to each second moment.
It should be noted that: in the vehicle control device provided in the above embodiment, when the vehicle is controlled, only the division of the above functional modules is used as an example, and in practical application, the above functional allocation may be performed by different functional modules according to needs, that is, the internal structure of the computer device is divided into different functional modules, so as to perform all or part of the functions described above. In addition, the vehicle control device and the vehicle control method embodiment provided in the foregoing embodiments belong to the same concept, and specific implementation processes of the vehicle control device and the vehicle control method embodiment are detailed in the method embodiment, and are not repeated herein.
In the embodiment of the application, a target vehicle sends a lane changing request to a cloud platform, the cloud platform generates target control information of the target vehicle according to factors such as current road conditions, traffic flow conditions and the like after receiving the request of the target vehicle, the target vehicle responds to the lane changing request of the target vehicle, acquires the target control information generated by the cloud platform, and controls the target vehicle according to the target control information; through the information interaction between the target vehicle and the cloud platform, more accurate and intelligent vehicle control is realized, and the efficiency and the safety of lane changing operation are effectively improved.
Fig. 6 is a schematic structural diagram of a vehicle according to an embodiment of the present application.
Illustratively, as shown in FIG. 6, the vehicle 600 includes: a memory 601 and a processor 602, wherein the memory 601 stores therein executable program code 6011, and the processor 602 is configured to call and execute the executable program code 6011 to perform a vehicle control method.
In addition, the embodiment of the application also protects a device, which can comprise a memory and a processor, wherein executable program codes are stored in the memory, and the processor is used for calling and executing the executable program codes to execute the vehicle control method provided by the embodiment of the application.
In this embodiment, the functional modules of the apparatus may be divided according to the above method example, for example, each functional module may be corresponding to one processing module, or two or more functions may be integrated into one processing module, where the integrated modules may be implemented in a hardware form. It should be noted that, in this embodiment, the division of the modules is schematic, only one logic function is divided, and another division manner may be implemented in actual implementation.
In the case of dividing the respective function modules by the respective functions, the apparatus may further include a second acquisition module, a control module, and the like. It should be noted that, all relevant contents of each step related to the above method embodiment may be cited to the functional description of the corresponding functional module, which is not described herein.
It should be understood that the apparatus provided in the present embodiment is used to perform one of the vehicle control methods described above, and thus the same effects as those of the implementation method described above can be achieved.
In case of an integrated unit, the apparatus may comprise a processing module, a memory module. Wherein, when the device is applied to a vehicle, the processing module can be used for controlling and managing the action of the vehicle. The memory module may be used to support the vehicle in executing mutual program code, etc.
Wherein a processing module may be a processor or controller that may implement or execute the various illustrative logical blocks, modules, and circuits described in connection with the present disclosure. A processor may also be a combination of computing functions, e.g., including one or more microprocessors, digital signal processing (digital signal processing, DSP) and microprocessor combinations, etc., and a memory module may be a memory.
In addition, the device provided by the embodiment of the application can be a chip, a component or a module, wherein the chip can comprise a processor and a memory which are connected; the memory is used for storing instructions, and when the processor calls and executes the instructions, the chip can be caused to execute the vehicle control method provided by the embodiment.
The present embodiment also provides a computer-readable storage medium having stored therein computer program code which, when run on a computer, causes the computer to execute the above-described related method steps to implement a vehicle control method provided by the above-described embodiments.
The present embodiment also provides a computer program product which, when run on a computer, causes the computer to perform the above-described related steps to implement a vehicle control method provided by the above-described embodiments.
The apparatus, the computer readable storage medium, the computer program product, or the chip provided in this embodiment are used to execute the corresponding method provided above, and therefore, the advantages achieved by the apparatus, the computer readable storage medium, the computer program product, or the chip can refer to the advantages of the corresponding method provided above, which are not described herein.
It will be appreciated by those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional modules is illustrated, and in practical application, the above-described functional allocation may be performed by different functional modules according to needs, i.e. the internal structure of the apparatus is divided into different functional modules to perform all or part of the functions described above.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of modules or units is merely a logical function division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another apparatus, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.
The foregoing is merely illustrative of the present application, and the present application is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present application. Therefore, the protection scope of the application is subject to the protection scope of the claims.

Claims (10)

1. A vehicle control method, characterized by being applied to a cloud platform, the method comprising:
Responding to a lane change request of a target vehicle, and acquiring first state information of the target vehicle at a first moment, and second state information and second control information of a plurality of reference vehicles at the first moment; the second control information is information for changing the state of the reference vehicle, the lane change request is used for requesting to change from a current lane to a target lane, and the reference vehicle is a vehicle in a preset range around the target vehicle;
determining a plurality of third state information of each reference vehicle at a plurality of subsequent second moments according to the second state information and the second control information of the plurality of reference vehicles;
determining target control information of the target vehicle according to the first state information and the cost function of the target vehicle and a plurality of third state information of the plurality of reference vehicles at a plurality of subsequent second moments; the cost function is used for indicating the advantages and disadvantages of the target control information, and the target control information is used for indicating whether to switch to the target lane and the target state information of the target vehicle at a plurality of subsequent second moments.
2. The method of claim 1, wherein said determining a plurality of third status information of each of said reference vehicles at a subsequent plurality of second moments in time based on said second status information and said second control information of said plurality of reference vehicles comprises:
For any one of the plurality of reference vehicles, determining a time compensation value of the reference vehicle according to the time interval of two adjacent second moments in the subsequent plurality of second moments;
for any one of the subsequent second moments, determining a first coefficient and a second coefficient of the reference vehicle according to the time compensation value; the first coefficient is used for adjusting the weight of fourth state information in the third state information, the second coefficient is used for adjusting the weight of fourth control information in the third state information, the fourth state information is state information of the reference vehicle at the moment which is the moment before the second moment, and the fourth control information is control information of the reference vehicle at the moment which is the moment before the second moment;
and determining third state information of the reference vehicle at the second moment according to the fourth state information, the fourth control information, the first coefficient and the second coefficient.
3. The method of claim 1, wherein prior to determining the target control information for the target vehicle based on the first state information and the cost function for the target vehicle and the plurality of third state information for the plurality of reference vehicles at the subsequent plurality of second moments, the method further comprises:
For any one of the subsequent second moments, determining a running efficiency cost, a following safety cost and a lane changing safety cost of the target vehicle according to the state information and the expected running speed of the target vehicle and the third state information of the reference vehicle; the driving efficiency cost is used for measuring the energy consumption cost of the target vehicle in the driving process, the following safety cost is used for measuring the safety distance and the safety behavior between the target vehicle and a reference vehicle positioned in front of the target vehicle, and the lane change safety cost is used for measuring the influence of the lane change behavior of the target vehicle on traffic safety;
determining a driving comfort cost of the target vehicle according to the expected acceleration of the target vehicle; the driving comfort cost is used for measuring the riding comfort degree of the target vehicle in the driving process;
determining the cost of the target vehicle deviating from a target lane according to the state information of the target vehicle; the target lane departure cost is used for measuring the departure degree of the target vehicle and the target lane;
determining a cost function of the target vehicle according to the driving efficiency cost, the following safety cost, the lane changing safety cost, the driving comfort cost and the target lane departure cost;
And establishing constraint conditions for the cost function, wherein the constraint conditions comprise speed constraint conditions and acceleration constraint conditions of the target vehicle.
4. The method of claim 3, wherein the determining the target control information for the target vehicle based on the first state information and the cost function for the target vehicle and a plurality of third state information for the plurality of reference vehicles at the subsequent plurality of second moments comprises:
for any one of the subsequent second moments, determining a plurality of cost function values of the target vehicle under different acceleration conditions according to fifth state information and the cost function and a plurality of third state information of the reference vehicles at the second moment; wherein the fifth state information is state information of the target vehicle at a time immediately before the second time;
selecting the acceleration corresponding to the minimum cost function value in the plurality of cost function values as the target acceleration at the second moment;
and determining target state information of the target vehicle at the second moment according to the target acceleration and the fifth state information.
5. A vehicle control method, characterized by being executed by an in-vehicle terminal of a target vehicle, comprising:
responding to a lane changing request of the target vehicle, and acquiring target control information of the target vehicle issued by a cloud platform; the target control information is used for indicating whether to shift to the target lane and target state information of the target vehicle at a plurality of subsequent second moments; the target control information is determined based on the vehicle control method according to any one of claims 1 to 4;
and controlling the target vehicle based on the target control information.
6. The method according to claim 5, wherein the controlling the target vehicle based on the target control information includes:
judging whether the target control information meets a safe channel changing condition or not;
under the condition that the target control information meets the safe channel changing condition, planning a target channel changing path;
and controlling the target vehicle to change from the current lane to the target lane according to the target lane changing path and the target control information, and driving at the plurality of subsequent second moments by the target state information corresponding to each second moment.
7. The method of claim 6, wherein after the determining whether the target control information satisfies the safe lane change condition, the method further comprises:
under the condition that the target control information does not meet the safe lane change condition, planning a target straight path;
and controlling the target vehicle to run at the plurality of subsequent second moments according to the target straight-going path and the target control information and the target state information corresponding to each second moment.
8. A vehicle control apparatus, characterized in that the apparatus comprises:
the system comprises a first acquisition module, a second acquisition module and a control module, wherein the first acquisition module is used for responding to a lane change request of a target vehicle and acquiring first state information of the target vehicle at a first moment, and second state information and second control information of a plurality of reference vehicles at the first moment; the second control information is information for changing the state of the reference vehicle, the lane change request is used for requesting to change from a current lane to a target lane, and the reference vehicle is a vehicle in a preset range around the target vehicle;
a first determining module, configured to determine a plurality of third state information of each of the reference vehicles at a plurality of subsequent second moments according to the second state information and the second control information of the plurality of reference vehicles;
The second determining module is used for determining target control information of the target vehicle according to the first state information and the cost function of the target vehicle and a plurality of third state information of the plurality of reference vehicles at a plurality of subsequent second moments; the cost function is used for indicating the advantages and disadvantages of the target control information, and the target control information is used for indicating whether to switch to the target lane and the target state information of the target vehicle at a plurality of subsequent second moments.
9. A vehicle control apparatus, characterized in that the apparatus comprises:
the second acquisition module is used for responding to a lane change request of a target vehicle and acquiring target control information of the target vehicle; the target control information is used for indicating whether to shift to the target lane and target state information of the target vehicle at a plurality of subsequent second moments;
and the control module is used for controlling the target vehicle based on the target control information.
10. A vehicle, characterized in that the vehicle comprises:
a memory for storing executable program code;
a processor for calling and running the executable program code from the memory, causing the vehicle to perform the method of any one of claims 5 to 7.
CN202311244835.7A 2023-09-25 2023-09-25 Vehicle control method and device and vehicle Pending CN117227727A (en)

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