1. A cloud support-based wide-area energy-saving optimization automatic driving control method in an internet environment is characterized by comprising the following steps:

the vehicle end and the cloud end confirm whether to enter an automatic driving cruise mode or not based on the cruise mode of a vehicle cloud communication mechanism;

when the automatic driving cruise mode is entered, the vehicle end T-Box uploads the vehicle state information;

the cloud end obtains the recommended speeds of different waypoints based on the dynamic programming wide-area vehicle speed optimization according to the vehicle state information and issues the recommended speeds to the vehicle end;

matching the vehicle end with the waypoints corresponding to the recommended speed according to a T-Box vehicle map matching speed analysis algorithm and by combining the actual position of the vehicle;

and the vehicle end T-Box issues a control command and transmits the control command to an electronic control unit of the vehicle, and the electronic control unit is used for controlling the vehicle to run at the matched corresponding road point according to the recommended speed.

2. A wide-area energy-saving optimization automatic driving control method based on cloud support in a network environment is applied to a cloud end and is characterized by comprising the following steps:

receiving vehicle state information sent by a vehicle, wherein the vehicle state information comprises: vehicle position information, vehicle self-state information and vehicle target cruising speed;

according to the vehicle state information, speed planning is carried out on the vehicle to obtain recommended speeds of different road points;

and sending the recommended speeds of the different road points to the vehicle, so that the vehicle runs at different road sections according to the recommended speeds in a cruising mode.

3. The method of claim 2, wherein the speed planning the vehicle according to the vehicle state information to obtain the recommended speeds of different waypoints comprises:

dividing the road in the position target range of the vehicle according to the vehicle position information to obtain a plurality of waypoints;

and obtaining the planned speeds of the vehicle at the plurality of road points according to the vehicle position information, the vehicle state information, the vehicle target cruising speed and the target constraint condition.

4. The method of claim 3, wherein obtaining the planned speeds of the vehicle at the plurality of waypoints based on the vehicle position information, the vehicle own state information, the vehicle target cruising speed, and target constraints comprises:

obtaining the running cost of the vehicle in a road point range corresponding to the current position according to the vehicle position information, the vehicle state information and the vehicle target cruising speed;

obtaining the total running cost of the vehicle at the multiple waypoints according to the running cost of the vehicle in the waypoint range corresponding to the current position;

and obtaining the planned speeds of the vehicle at the multiple waypoints according to the total driving cost of the multiple waypoints and the target constraint condition.

5. The method according to claim 4, wherein the obtaining of the driving cost of the vehicle in the road point range corresponding to the current position according to the vehicle position information, the vehicle self-state information and the vehicle target cruising speed comprises:

wherein, J_K ^*For the running cost, T, in the waypoint K in which the vehicle is located_eAs vehicle engine torque, ω_cAs the vehicle engine speed, F_C(T_e，ω_c) For fuel consumption in a waypoint K at which the vehicle is located, Δ S is the displacement of the vehicle in the waypoint K, V_kIs the driving speed, omega, of the vehicle in the waypoint k₁、ω₂、ω₃、ω₄Are respectively a weight coefficient, V_ccFor a target cruising speed of the vehicle, th_ccIs the throttle opening th at which the vehicle is traveling at the target cruising speed_pccFor vehicles in waypoints k with V_KSpeed of (V) throttle opening degree during driving_k-1Is the driving speed of the vehicle in waypoint k-1.

6. The method according to claim 4, wherein the obtaining of the total driving cost of the vehicle at the plurality of waypoints according to the driving cost of the vehicle in the waypoint range corresponding to the current position comprises:

wherein, J_NFor a total driving cost in the range of N waypoints,for vehicles on the Nth roadDriving cost in the range of points, T_ieVehicle engine torque, ω, at ith waypoint_icVehicle engine speed, F, for the ith waypoint_iC(T_ie，ω_ic) For fuel consumption, Δ S, in a waypoint i in which the vehicle is located_iFor the displacement of the vehicle in the waypoint i, V_iIs the driving speed, ω, of the vehicle in the waypoint i₁、ω₂、ω₃、ω₄Are respectively a weight coefficient, V_ccFor a target cruising speed of the vehicle, th_ccIs the throttle opening th at which the vehicle is traveling at the target cruising speed_pccFor vehicles at waypoints i with V_iSpeed of (V) throttle opening degree during driving_i-1Is the driving speed of the vehicle within waypoint i-1.

7. The method according to any of claims 4-6, wherein the target constraints are:

wherein, minJ_NIs the minimum value of the total running cost of the vehicle at N waypoints, a_minRepresents the minimum acceleration limit, a_naxIndicates the maximum limit of acceleration, v_k+1Represents the planning velocity, v, of waypoint K +1_kIndicates the planning speed, v, of the waypoint K_ccA vehicle target cruising speed;where r is the effective tire radius, CD is the air resistance coefficient, A is the windward area, ρ is the air density, m is the overall vehicle mass, f is the rolling resistance coefficient, θ is the road grade, i_gMain reducer transmission ratio, i₀Is the transmission ratio of the gearbox, eta_tFor transmission efficiency.

8. A cloud support-based wide-area energy-saving optimization automatic driving control method in a network environment is characterized by being applied to a vehicle end and comprising the following steps:

when a cruise mode entry instruction is received, vehicle state information is sent, wherein the vehicle state information comprises: vehicle position information, vehicle self-state information and vehicle target cruising speed;

and when the recommended speeds of different road points are received, controlling the vehicle to run at different road sections according to the recommended speeds in the cruise mode.

9. The method of claim 8, prior to said transmitting vehicle status information, comprising:

when an instruction for entering the cruise mode is received, judging whether the current vehicle driving condition meets the target condition for entering the automatic driving cruise mode;

and entering the automatic driving cruise mode when the vehicle driving condition meets the target condition for entering the automatic driving cruise mode.

10. The method according to claim 8, wherein the controlling the vehicle to travel at the recommended speed in a cruise mode on different road segments when the recommended speed for different road points is received comprises:

receiving the recommended speeds of different waypoints, and matching the waypoint position corresponding to the recommended speed with the current position of the vehicle to obtain the planning speed of the current position of the vehicle;

and controlling the vehicle to run according to the planned speed of the current position of the vehicle.

Background

With the development of vehicle driving technology, the driving burden of a driver is reduced. In the related art, a cruise system, that is, a speed control system, is generally installed in a vehicle, and functions to automatically maintain a vehicle speed at a speed requested by a driver without the driver stepping on an accelerator pedal, so that the vehicle can travel at a fixed speed. However, in the cruise mode, even when the vehicle is under a complicated road condition, the vehicle still requires constant speed driving according to the vehicle speed of the driver, so that the driving control of the vehicle is inflexible and the intelligence is low.

Disclosure of Invention

In view of this, the embodiment of the invention provides a wide-area energy-saving optimization automatic driving control method based on cloud support in an internet environment, so as to overcome the defects that in the prior art, vehicle driving control is inflexible and the intelligence degree is low.

According to a first aspect, an embodiment of the present invention provides a cloud-support-based wide-area energy-saving optimization automatic driving control method in an internet environment, including: the vehicle end and the cloud end confirm whether to enter an automatic driving cruise mode or not based on the cruise mode of a vehicle cloud communication mechanism; when the automatic driving cruise mode is entered, the vehicle end T-Box uploads the vehicle state information; the cloud end obtains the recommended speeds of different waypoints based on the dynamic programming wide-area vehicle speed optimization according to the vehicle state information and issues the recommended speeds to the vehicle end; matching the vehicle end with the waypoints corresponding to the recommended speed according to a T-Box vehicle map matching speed analysis algorithm and by combining the actual position of the vehicle; and the vehicle end T-Box issues a control command and transmits the control command to an electronic control unit of the vehicle, and the electronic control unit is used for controlling the vehicle to run at the matched corresponding road point according to the recommended speed.

According to a second aspect, an embodiment of the present invention provides a wide area energy saving optimization automatic driving control method based on cloud support in an internet environment, which is applied to a cloud, and includes: receiving vehicle state information sent by a vehicle, wherein the vehicle state information comprises: vehicle position information, vehicle self-state information and vehicle target cruising speed; according to the vehicle state information, speed planning is carried out on the vehicle to obtain recommended speeds of different road points; and sending the recommended speeds of the different road points to the vehicle, so that the vehicle runs at different road sections according to the recommended speeds in a cruising mode.

Optionally, the speed planning the vehicle according to the vehicle state information to obtain recommended speeds of different waypoints includes: dividing the road in the position target range of the vehicle according to the vehicle position information to obtain a plurality of waypoints; and obtaining the planned speeds of the vehicle at the plurality of road points according to the vehicle position information, the vehicle state information, the vehicle target cruising speed and the target constraint condition.

Optionally, the obtaining the planned speeds of the vehicle at the multiple waypoints according to the vehicle position information, the vehicle state information, the vehicle target cruising speed, and the target constraint condition includes: obtaining the running cost of the vehicle in a road point range corresponding to the current position according to the vehicle position information, the vehicle state information and the vehicle target cruising speed; obtaining the total running cost of the vehicle at the multiple waypoints according to the running cost of the vehicle in the waypoint range corresponding to the current position; and obtaining the planned speeds of the vehicle at the multiple waypoints according to the total driving cost of the multiple waypoints and the target constraint condition.

Optionally, the obtaining, according to the vehicle position information, the vehicle state information, and the vehicle target cruising speed, a driving cost of the vehicle in a waypoint range corresponding to the current position includes:

wherein, J_K ^*For the running cost in the road point K where the vehicle is located, Te is the vehicle engine torque, omega_cAs the vehicle engine speed, F_C(T_e，ω_c) For fuel consumption in a waypoint K at which the vehicle is located, Δ S is the displacement of the vehicle in the waypoint K, V_kIs the driving speed, omega, of the vehicle in the waypoint k₁、ω₂、ω₃、ω₄Are respectively a weight coefficient, V_ccFor a target cruising speed of the vehicle, th_ccIs the throttle opening th at which the vehicle is traveling at the target cruising speed_pccFor vehicles in waypoints k with V_KSpeed of (V) throttle opening degree during driving_k-1Is the driving speed of the vehicle in waypoint k-1.

Optionally, the obtaining, according to the running cost of the vehicle in the waypoint range corresponding to the current location, the total running cost of the vehicle at the plurality of waypoints includes:

wherein, J_NFor a total driving cost in the range of N waypoints,for the running cost of the vehicle in the Nth waypoint range, T_ieVehicle engine torque, ω, at ith waypoint_icVehicle engine speed, F, for the ith waypoint_ic(T_ie，ω_ic) For fuel consumption, Δ S, in a waypoint i in which the vehicle is located_iFor the displacement of the vehicle in the waypoint i, V_iIs the driving speed, ω, of the vehicle in the waypoint i₁、ω₂、ω₃、ω₄Are respectively a weight coefficient, V_ccFor a target cruising speed of the vehicle, th_ccIs the throttle opening th at which the vehicle is traveling at the target cruising speed_pccFor vehicles at waypoints i with V_iSpeed of (V) throttle opening degree during driving_i-1Is the driving speed of the vehicle within waypoint i-1.

Optionally, the target constraint condition is:

wherein, minJ_NIs the minimum value of the total running cost of the vehicle at N waypoints, a_minRepresents the minimum acceleration limit, a_maxIndicates the maximum limit of acceleration, v_k+1Represents the planning velocity, v, of waypoint K +1_kIndicates the planning speed, v, of the waypoint K_ccA vehicle target cruising speed;where r is the effective tire radius, CD is the air resistance coefficient, A is the windward area, ρ is the air density, m is the overall vehicle mass, f is the rolling resistance coefficient, θ is the road grade, i_gMain reducer transmission ratio, i₀Is the transmission ratio of the gearbox, eta_tFor transmission efficiency.

According to a third aspect, an embodiment of the present invention provides a cloud support-based wide-area energy-saving optimization automatic driving control method in an internet environment, which is applied to a vehicle end, and includes the following steps: when a cruise mode entry instruction is received, vehicle state information is sent, wherein the vehicle state information comprises: vehicle position information, vehicle self-state information and vehicle target cruising speed; and when the recommended speeds of different road points are received, controlling the vehicle to run at different road sections according to the recommended speeds in the cruise mode.

Optionally, before the sending the vehicle state information, the method further comprises: when an instruction for entering the cruise mode is received, judging whether the current vehicle driving condition meets the target condition for entering the automatic driving cruise mode; and entering the automatic driving cruise mode when the vehicle driving condition meets the target condition for entering the automatic driving cruise mode.

Optionally, the controlling the vehicle to travel at the recommended speed in different road sections in the cruise mode when the recommended speed of different road points is received includes: receiving the recommended speeds of different waypoints, and matching the waypoint position corresponding to the recommended speed with the current position of the vehicle to obtain the planning speed of the current position of the vehicle; and controlling the vehicle to run according to the planned speed of the current position of the vehicle.

The technical scheme of the invention has the following advantages:

according to the wide-area energy-saving optimization automatic driving control method based on cloud support in the internet environment, under the condition that the target cruising speed of a driver is received, dynamic planning of the vehicle running speed is achieved according to the vehicle position and the vehicle state information, compared with cruising at a constant speed, the flexibility and the intelligent degree of vehicle driving control are improved, the optimal economic vehicle speed rule can be given according to the gradient information of a cloud map, dynamic adjustment of the working interval of an engine is further achieved, the probability that the engine works in a more efficient interval is increased, compared with the CC cruising control technology of an original vehicle, the working state and the working environment of the engine are more efficient and friendly, therefore, the running environment of the engine is improved, the service life of the engine is prolonged, and the maintenance period of the engine is prolonged.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.

Fig. 1 is a flowchart of a specific example of a wide-area energy-saving optimization automatic driving control method based on cloud support in an internet environment according to an embodiment of the present invention;

fig. 2 is a flowchart of a specific example of a wide-area energy-saving optimization automatic driving control method based on cloud support in an internet environment according to an embodiment of the present invention;

fig. 3 is a flowchart of a specific example of a wide-area energy-saving optimization automatic driving control method based on cloud support in an internet environment according to an embodiment of the present invention;

fig. 4 is an interaction diagram of a specific example of a wide-area energy-saving optimization automatic driving control method based on cloud support in an internet environment in the embodiment of the present invention.

Detailed Description

The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it should be understood that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience of description and simplicity of description, but do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.

In the description of the present invention, it should be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; the two elements may be directly connected or indirectly connected through an intermediate medium, or may be communicated with each other inside the two elements, or may be wirelessly connected or wired connected. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.

In addition, the technical features involved in the different embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.

The embodiment provides a wide-area energy-saving optimization automatic driving control method based on cloud support in a network environment, which is applied to a cloud, and as shown in fig. 1, the method includes the following steps:

s101, receiving vehicle state information sent by a vehicle, wherein the vehicle state information comprises: vehicle position information, vehicle self-state information and vehicle target cruising speed;

for example, the vehicle position information may include information indicating the current longitude and latitude, elevation, etc. of the vehicle, the vehicle own state information may include the current vehicle speed, the current torque and rotation speed of the vehicle engine, and the opening degree information of the throttle valve, etc., and the vehicle target cruise speed represents a target speed set by the user when the vehicle enters the cruise mode. The manner of receiving the vehicle position information, the vehicle self-state information and the vehicle target cruising speed sent by the vehicle may be to receive information sent by a T-box which is connected with the cloud end through 4G or 5G technology communication on the vehicle. The embodiment does not limit the communication interaction mode between the vehicle and the cloud, and the technical personnel in the field can determine the communication interaction mode according to the needs.

S102, according to the vehicle state information, speed planning is carried out on the vehicle, and speed planning information of different waypoints is obtained;

for example, the waypoint may be positions obtained by dividing the target driving path according to a target rule, the target rule may be equal division, or may be divided according to traffic signs on the driving path, for example, a turning point is used as a waypoint, and a starting point and an end point of the speed reduction road section are respectively used as waypoints, the determination method of the waypoint is not limited in this embodiment, and a person skilled in the art may determine the waypoint as needed.

According to the vehicle position information, the vehicle state information and the vehicle target cruising speed, the vehicle is subjected to speed planning, and the speed planning information can be obtained in a mode that firstly, the vehicle position information is matched with a map prestored in a cloud end to obtain road information near the vehicle position, such as gradient, curvature, limit information and the like. Secondly, planning is carried out according to the vehicle position information and the vehicle self state information, the planning target can be that under the constraint of the target cruising speed, the vehicle abrasion degree is minimum, the vehicle oil consumption is minimum or the energy is minimum, the constraint of the target cruising speed can be the target cruising speed with the highest driving speed being 1.1 times and the target cruising speed with the lowest driving speed being 0.9 times, and the vehicle driving speed is dynamically planned at different road points in the range of the highest driving speed and the lowest driving speed by combining the vehicle self state information and the road information.

S103, sending the recommended speeds of different road points to the vehicle, so that the vehicle can run at different road sections according to the recommended speeds in the cruise mode.

For example, the speed planning information may be sent to the vehicle by connecting a T-box at the vehicle end through 4G or 5G technology communication, and sending the speed planning information of each waypoint to the vehicle, so that the vehicle travels at different road sections according to the corresponding recommended speed.

According to the wide-area energy-saving optimization automatic driving control method based on cloud support in the internet environment, dynamic planning of the vehicle running speed is achieved according to the vehicle position and the vehicle state information under the condition that the target cruising speed of a driver is received, and compared with cruising at a constant speed, the flexibility and the intelligent degree of vehicle driving control are improved.

As an optional implementation manner of this embodiment, speed planning is performed on the vehicle according to the vehicle state information, so as to obtain recommended speeds of different waypoints, including:

firstly, dividing roads in a position target range of a vehicle according to vehicle position information to obtain a plurality of waypoints;

for example, the target range of the position of the vehicle may be within 2 kilometers of the position of the vehicle as a starting point in the traveling direction of the vehicle. The method for dividing the road in the target range of the position of the vehicle according to the position information of the vehicle to obtain a plurality of waypoints may be that, firstly, the position information of the vehicle is matched with the map information stored in the cloud end to obtain the road condition in the target range of the position of the vehicle. Secondly, the roads are divided according to the road conditions in the target range, the dividing mode can be that the roads are divided according to distances, for example, the roads are divided every 20 meters, the range of 2 kilometers is divided into 100 waypoints, it can be understood that when a bifurcation occurs in the target range, all the roads in the target range can be divided, the dividing result is recorded, a plurality of waypoints are obtained, for example, a bifurcation intersection occurs in one position in the target range, two roads in the target range can be divided, the longitude and the latitude of each 20 meters are recorded, and the information of the longitude and the latitude are stored in a cloud end as the dividing result. When roads with different levels or speed-limiting roads appear in the position range of the vehicle, the roads can be divided according to the road levels or speed-limiting requirements, for example, a high-speed entrance, a high-speed exit and the like are used as waypoints. The embodiment does not limit the way of dividing the road in the target range of the position of the vehicle, and a person skilled in the art can determine the way as required.

In order to avoid the problem that all the branched roads in the target range need to be subjected to road point division due to the fact that road branching occurs in the target range, the vehicle end can send the target location where the vehicle needs to arrive or the road information where the vehicle is going to run, so that the cloud end can carry out road point division on the road in a targeted mode, and the calculation amount of the cloud end is reduced.

And secondly, obtaining the planned speeds of the vehicle at a plurality of road points according to the vehicle position information, the vehicle self state information, the vehicle target cruising speed and the target constraint condition.

For example, the target constraint condition may be a driving cost optimal constraint condition, that is, a planning speed of each road point is obtained when the vehicle driving cost is minimum, and the driving cost may include oil consumption, a vehicle wear degree, and the like; the target constraint condition may also be determined by road requirements in the waypoint, for example, after entering the highway at the high-speed entrance section, that is, after entering the highway, the target constraint condition may be to obtain the planned speed of each waypoint under the condition of ensuring the speed-limiting requirement of the highway section, so that the vehicle running cost is the minimum. The target constraint condition is not limited in this embodiment, and can be determined by those skilled in the art as needed. The resulting speed planning information may be characterized by:

P₁(X₁，Y₁，V₁)，P₂(X₂，Y₂，V₂)，P₃(X₃，Y₃，V₃)，…，P_n(X_n，Y_n，V_n)

wherein, P_n(X_n，Y_n，V_n) Characterizing a longitude at waypoint n as X_nLatitude of Y_nWith a programming speed V_n。

According to the wide-area energy-saving optimization automatic driving control method based on cloud support in the internet environment, roads in the target range of the position of the vehicle are divided, the speed of the vehicle is planned according to each road point without real-time planning, the calculated amount of the cloud is reduced, the requirement for real-time performance is lowered, and meanwhile, the speed of the road in the target range is planned, so that the problem that the vehicle cannot receive speed planning information due to network jitter or delay when the vehicle runs in the target range can be solved.

As an optional implementation manner of this embodiment, obtaining the planned speeds of the vehicle at the multiple waypoints according to the vehicle position information, the vehicle state information, the vehicle target cruising speed, and the target constraint condition includes:

firstly, obtaining the running cost of the vehicle in a waypoint range corresponding to the current position according to the vehicle position information, the vehicle state information and the vehicle target cruising speed;

for example, the driving cost of the vehicle in the road point range corresponding to the current position can be obtained by the following formula according to the vehicle position information, the vehicle self-state information and the vehicle target cruising speed:

wherein, J_K ^*For the running cost, T, in the waypoint K in which the vehicle is located_eAs vehicle engine torque, ω_cAs the vehicle engine speed, F_C(T_e，ω_c) For fuel consumption in a waypoint K at which the vehicle is located, Δ S is the displacement of the vehicle in the waypoint K, V_kIs the driving speed, omega, of the vehicle in the waypoint k₁、ω₂、ω₃、ω₄Are respectively a weight coefficient, V_ccFor a target cruising speed of the vehicle, th_ccIs the throttle opening th at which the vehicle is traveling at the target cruising speed_pccFor vehicles in waypoints k with V_KSpeed of (V) throttle opening degree during driving_k-1Is the driving speed of the vehicle in waypoint k-1.

Secondly, obtaining the total driving cost of the vehicle at a plurality of waypoints according to the driving cost of the vehicle in the waypoint range corresponding to the current position;

for example, the total driving cost of the vehicle at a plurality of waypoints can be obtained by the following formula according to the driving cost of the vehicle in the waypoint range corresponding to the current position:

wherein, J_NFor a total driving cost in the range of N waypoints,for the running cost of the vehicle in the Nth waypoint range, T_ieVehicle engine torque, ω, at ith waypoint_icVehicle engine speed, F, for the ith waypoint_iC(T_ie，ω_ic) For fuel consumption, Δ S, in a waypoint i in which the vehicle is located_iFor the displacement of the vehicle in the waypoint i, V_iIs the driving speed, ω, of the vehicle in the waypoint i₁、ω₂、ω₃、ω₄Are respectively a weight coefficient, V_ccFor a target cruising speed of the vehicle, th_ccTarget patrol for vehicleThrottle opening th at cruise speed_pccFor vehicles at waypoints i with V_iSpeed of (V) throttle opening degree during driving_i-1Is the driving speed of the vehicle within waypoint i-1. And then, obtaining the planned speeds of the vehicle at the plurality of waypoints according to the total driving cost of the plurality of waypoints and the target constraint condition.

Illustratively, obtaining the planned speeds of the vehicle at the multiple waypoints according to the total driving cost of the multiple waypoints and the target constraint condition comprises:

solving the speed value when the total running cost of the multiple road points is the lowest under the following target constraint conditions, wherein the specific mathematical description is as follows:

wherein, minJ_NIs the minimum value of the total running cost of the vehicle at N waypoints, a_minRepresents the minimum acceleration limit, a_maxIndicates the maximum limit of acceleration, v_k+1Represents the planning velocity, v, of waypoint K +1_kIndicates the planning speed, v, of the waypoint K_ccA vehicle target cruising speed;where r is the effective tire radius, CD is the air resistance coefficient, A is the windward area, ρ is the air density, m is the overall vehicle mass, f is the rolling resistance coefficient, θ is the road grade, i_gMain reduction gear ratio, /)₀Is the transmission ratio of the gearbox, eta_tFor transmission efficiency.

Wherein, minJ_NThe minimum value of the total running cost of the vehicle at the N road points,for the running cost of the vehicle in the Nth waypoint range, T_ieVehicle engine torque, ω, at ith waypoint_icVehicle engine speed, F, for the ith waypoint_iC(T_ie，ω_ic) For fuel consumption, Δ S, in a waypoint i in which the vehicle is located_iFor the displacement of the vehicle in the waypoint i, V_iIs the driving speed, ω, of the vehicle in the waypoint i₁、ω₂、ω₃、ω₄Are respectively a weight coefficient, V_ccFor a target cruising speed of the vehicle, th_ccIs the throttle opening th at which the vehicle is traveling at the target cruising speed_pccFor vehicles at waypoints i with V_iSpeed of (V) throttle opening degree during driving_i-1Is the driving speed of the vehicle within waypoint i-1.

The wide-area energy-saving optimization automatic driving control method based on cloud support in the internet environment provided by the embodiment considers the vehicle running cost, so that the vehicle obtains the lowest planned speed of the running cost under the condition of meeting the requirement of the target cruising speed, the vehicle running cost is reduced, the optimal economic vehicle speed rule can be given according to the gradient information of the cloud map, the dynamic adjustment of the working interval of the engine is further realized, the probability that the engine works in a more efficient interval is increased, compared with the CC cruising control technology of the original vehicle, the working state and the working environment of the engine are more efficient and friendly, therefore, the running environment of the engine is improved, the working life of the engine is prolonged, and the maintenance period of the engine is prolonged.

The embodiment provides a cloud support-based wide-area energy-saving optimization automatic driving control method in an internet environment, as shown in fig. 2, applied to a vehicle end, and including the following steps:

s201, when a cruise mode entering instruction is received, vehicle state information is sent, and the vehicle state information comprises: vehicle position information, vehicle self-state information and vehicle target cruising speed;

for example, the mode of receiving the cruise mode entry instruction may be to receive pressure information or knob information of a user on a button representing that the cruise mode is entered, or to receive voice information of the user entering the cruise mode. The vehicle position information may include information on the current longitude and latitude, elevation, and other characteristic positions of the vehicle, the vehicle own state information may include the current vehicle speed, the current torque and rotation speed of the vehicle engine, and the opening degree information of the throttle valve, and the like, and the vehicle target cruise speed represents a target speed set by a user when the vehicle enters the cruise mode. The vehicle position information may be obtained by a GPS system installed in the vehicle, and the vehicle own state information may be obtained by various sensors installed in the vehicle. The manner of sending the vehicle position information, the vehicle own state information, and the vehicle target cruising speed may be that the T-BOX of the vehicle transmits the information to the cloud through 4G or 5G technology.

And S202, when the recommended speeds of different road points are received, controlling the vehicle to run at the different road points according to the recommended speeds in the cruise mode.

Illustratively, the received recommended speeds of the different waypoints may be characterized by the following form:

P₁(X₁，Y₁，V₁)，P₂(X₂，Y₂，V₂)，P₃(X₃，Y₃，V₃)，…，P_n(X_n，Y_n，V_n)

wherein, P_n(X_n，Y_n，V_n) Characterised by a longitude of X_nLatitude of Y_nThe planning speed of the characterized waypoint is V_n。

And the vehicle T-BOX receives the speed planning information, matches the speed planning information with the current position, and sends the planned speed of the current vehicle position to the vehicle electronic control unit so as to control the vehicle to run according to the speed planning information.

According to the cloud-support-based wide-area energy-saving optimization automatic driving control method in the internet environment, the vehicle receives speed planning information and controls the vehicle to drive according to the speed planning information, dynamic planning of the vehicle running speed can be achieved in the cruise mode, and compared with cruise at a constant speed, the flexibility and the intelligent degree of vehicle driving control are improved.

As an optional implementation manner of this embodiment, before sending the vehicle state information, the method includes:

when an instruction for entering the cruise mode is received, judging whether the current vehicle driving condition meets the target condition for entering the automatic driving cruise mode; and entering the automatic driving cruise mode when the vehicle driving condition meets the target condition for entering the automatic driving cruise mode.

For example, after receiving the instruction to enter the cruise mode, before the vehicle enters the cruise mode, the driving condition of the current vehicle needs to be determined, and whether the driving condition meets the condition of entering the cruise mode is determined, where the target condition may include that the vehicle network connection is normal, the cloud data is received normally, the format of the received cloud data is correct, the GPS is calculated normally, the vehicle speed of the current vehicle is within the vehicle speed threshold range, the vehicle position is in the cloud map cache, and the like. Whether the network connection is normal or not can be determined by judging whether the network parameters are consistent with the standard network parameters or not, for example, whether the network speed is 0kb/s or not, and when the network speed is 0kb/s, the network connection is determined to be abnormal, and when the network speed is more than 0kb/s, the network connection is determined to be normal. Whether the data format is normal or not can be determined by judging the comparison of the received data format and a preset format.

As an optional implementation manner of this embodiment, when receiving the recommended speeds of different waypoints, controlling the vehicle to travel at different road sections according to the recommended speeds in the cruise mode includes:

receiving the recommended speeds of different waypoints, and matching the waypoint position corresponding to the recommended speed with the current position of the vehicle to obtain the planning speed of the current position of the vehicle; and controlling the vehicle to run according to the planned speed of the current position of the vehicle.

For example, the method of receiving the recommended speeds of different waypoints and matching the waypoint position in the speed planning information with the current position of the vehicle to obtain the planned speed of the current position of the vehicle may be: firstly, the current position of the vehicle is obtained according to the positioning system (such as GPS system) of the vehicleInformation, assuming the current position of the vehicle is P₀(X₀，Y₀). Secondly, the position of the road point in the speed planning information is matched with the current position of the vehicle, and the matching mode can be as follows: the received speed planning information is stored and called in a stack mode, and the coordinate of the first waypoint of the stack S is assumed to be P₁(X₁，Y₁) The coordinate of the second waypoint is assumed to be P₂(X₂，Y₂) Then, the straight line formed by the first waypoint and the second waypoint in the stack S is ax + by + c, which is 0.

P₀(X₀，Y₀) To ax + by + c is 0 drop point

If (m, n) is in P₁，P₂In between, perform P₂Corresponding vehicle speed V₂Eject P from stack S₁Storing the recommended speed corresponding to the new road point into a stack;

if (m, n) is not in P₁，P₂In the above-mentioned formula, (m, n) to P₁A distance of D₁To P₂A distance of D₂；

If D is₁＞D₂Popping P from stack S₁Storing the recommended speed corresponding to the new road point into a stack;

if D is₁＜D₂Executing P₁Corresponding vehicle speed V₁Eject P from stack S₁Storing the recommended speed corresponding to the new road point into a stack;

and if the length of the stack S is less than 2, finishing the judgment and waiting for the new data of the cloud end to be issued.

According to the vehicle driving control provided by the embodiment, the road point position in the speed planning information is matched with the current position of the vehicle, so that the planning speed of the current position of the vehicle is determined, and the accuracy of the planning speed of the current position determined by the vehicle is ensured.

The embodiment provides a cloud support-based wide-area energy-saving optimization automatic driving control method in an internet environment, as shown in fig. 3 and 4, the method includes the following steps:

s01, confirming whether the vehicle end and the cloud end enter an automatic driving cruise mode or not based on the cruise mode of a vehicle cloud communication mechanism;

illustratively, the cruise modes include a normal cruise mode, an auto-drive cruise mode, and the auto-drive cruise mode includes a wide-area optimized auto-drive ready mode, a wide-area optimized auto-drive operational mode, a wide-area optimized auto-drive failure mode, and the like. The method for determining whether to enter the automatic driving cruise mode or not can be based on the cruise mode of the vehicle cloud communication mechanism and can be used for judging whether an instruction of a user for entering the automatic driving cruise mode is received or not and judging whether the driving condition of the current vehicle meets the condition for entering the automatic driving cruise mode or not, and the target conditions can include normal vehicle network connection, normal cloud data receiving, correct cloud data receiving format and normal GPS resolving. When an instruction of a user is received and the driving condition satisfies a condition, it is determined to enter the auto-driving cruise mode.

S02, when the vehicle enters the automatic driving cruise mode, the vehicle end T-Box uploads the vehicle state information;

illustratively, the vehicle state information includes vehicle position information, vehicle own state information, and a vehicle target cruising speed, and the like. The vehicle position information may include information on the current longitude and latitude, elevation, and other characteristic positions of the vehicle, the vehicle own state information may include the current vehicle speed, the current torque and rotation speed of the vehicle engine, and the opening degree information of the throttle valve, and the like, and the vehicle target cruise speed represents a target speed set by a user when the vehicle enters the cruise mode. The vehicle end T-Box can achieve uploading of vehicle state information to the cloud end through 4G or 5G technical communication.

S03, the cloud end obtains the recommended speeds of different waypoints based on the dynamic programming wide-area vehicle speed optimization according to the vehicle state information and issues the recommended speeds to the vehicle end;

for an exemplary specific content, refer to the above embodiment of the method applied to the cloud, which is not described herein again.

S04, matching the vehicle end with a waypoint corresponding to the recommended speed according to a T-Box vehicle map matching speed analysis algorithm and by combining the actual position of the vehicle;

for an exemplary vehicle map matching speed analysis algorithm, refer to the partial description of "matching the position of the road point corresponding to the recommended speed with the current position of the vehicle to obtain the planned speed of the current position of the vehicle" in the above embodiment, which is not described herein again.

And S05, the vehicle end T-Box issues a control instruction and transmits the control instruction to the electronic control unit of the vehicle, and the electronic control unit is used for controlling the vehicle to run at the matched corresponding waypoint according to the recommended speed.

It should be understood that the above examples are only for clarity of illustration and are not intended to limit the embodiments. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. And obvious variations or modifications therefrom are within the scope of the invention.