Commercial vehicle cruise method and device for cloud control

Abstract

The application relates to the technical field of intelligent networked vehicles, in particular to a commercial vehicle cruising method and device for cloud control, wherein the method comprises the following steps: acquiring front road information, an actual vehicle network state and current traffic information, and matching a best cruising mode; when the best cruising mode is a predictive cruising mode, performing a first cruising action at an economic vehicle speed of a target commercial vehicle; when the best cruising mode is a self-adaptive cruising mode, performing a second cruising action based on a preset self-adaptive cruising strategy; and when the best cruising mode is a constant-speed cruising mode, performing a third cruising action at a preset cruising vehicle speed. According to the application, the interaction between the target commercial vehicle and the cloud can be used to judge the network state, the road information and the traffic information, so that the switching between different cruising modes can be realized, the response capability of the commercial vehicle to sudden situations is improved while the predictive cruising function is fully exerted, the economy of vehicle cruising is improved, and the vehicle driving is safer and more intelligent.

Description

Technical Field

[0001] This application relates to the field of intelligent connected vehicle technology, and in particular to a cloud-controlled commercial vehicle cruise method and device. Background Technology

[0002] With the development of technology, vehicle driver assistance functions have gradually matured, and the types of vehicle cruise control functions have become increasingly diverse.

[0003] Among related technologies, predictive cruise technology is implemented by acquiring information about the slope of the road ahead of the vehicle and calculating the vehicle's economical speed with the goal of economical driving. It can be divided into two categories: predictive cruise systems based on on-board computing platforms and predictive cruise systems based on cloud control.

[0004] However, the relevant technologies do not fully consider the actual driving scenarios of commercial vehicles. They cannot respond in a timely manner when there are obstructing vehicles in front, and the method for judging the switching of cruise modes is simple and difficult to handle unexpected situations during actual cruise. This results in insufficient safety for commercial vehicles during cruise and affects the functionality of predictive cruise technology, which urgently needs to be addressed. Summary of the Invention

[0005] This application provides a cloud-controlled commercial vehicle cruise method and device to address the problems in related technologies, such as insufficient consideration of actual driving scenarios for commercial vehicles, inability to respond promptly when there are obstructing vehicles ahead, and simple judgment methods for switching cruise modes, which make it difficult to handle unexpected situations during actual cruise, resulting in insufficient safety of commercial vehicles during cruise and affecting the functionality of predictive cruise technology.

[0006] The first aspect of this application provides a cloud-controlled commercial vehicle cruise method applied to a server, comprising the following steps: acquiring forward road information, actual vehicle network status, and current traffic information of a target commercial vehicle; matching the optimal cruise mode of the target commercial vehicle based on the forward road information, the actual vehicle network status, and the current traffic information; when the optimal cruise mode is a predictive cruise mode, performing a first cruise action at the economic speed of the target commercial vehicle; when the optimal cruise mode is an adaptive cruise mode, performing a second cruise action based on a preset adaptive cruise strategy; and when the optimal cruise mode is a constant speed cruise mode, performing a third cruise action at a preset cruise speed.

[0007] Optionally, in one embodiment of this application, the step of performing the first cruise action at the economic speed of the target commercial vehicle includes: an economic driving strategy based on the principle of traversal optimization, and in combination with the slope of the road ahead, establishing a slope state transition equation by limiting the traversal range; obtaining the fuel consumption cost and time cost of the speed change according to the slope state transition equation, so as to establish an optimal search strategy and search for the economic speed.

[0008] Specifically, in one embodiment of this application, the formula for calculating the fuel consumption cost is as follows:

[0009]

[0010] Among them, U k Let n be the fuel consumption cost of the vehicle in stage k. k T is the vehicle's rotational speed in stage k. k Let v be the torque of the vehicle in stage k, ΔS be the minimum distance discretized by the road gradient S km ahead, and v be the torque of the vehicle in stage k. k Let be the vehicle's speed in stage k; and the formula for calculating the time cost is:

[0011]

[0012] Among them, T k Let v be the time cost of the vehicle in stage k, ΔS be the minimum distance discretized from the road gradient S km ahead, and v be the time cost of the vehicle in stage k. k Let be the speed of the vehicle in stage k.

[0013] Optionally, in one embodiment of this application, the search for the economical vehicle speed includes: generating four containers for storing speed strategies according to a preset priority search order; classifying the speed strategies for the road at a preset distance ahead stored within the traversal range, filtering strategies with fuel consumption costs less than the fuel consumption cost of the cruise control mode and average vehicle speed greater than or equal to the preset cruise speed into the containers, and then filtering them into other containers according to different levels of average vehicle speed; performing a second round of filtering on the speed strategies in different containers, wherein if the maximum throttle opening of the speed strategy in each container is greater than or equal to the throttle opening of the cruise control mode or the average throttle opening is greater than or equal to the average throttle opening of the cruise control mode, then removing the corresponding container; determining whether there is still a speed strategy in each container, if there is no speed strategy in all containers, then outputting the preset cruise speed, otherwise performing the next round of filtering; searching different containers from top to bottom, if the speed strategy exists, then selecting the speed strategy with the lowest fuel consumption cost for output, otherwise filtering the next container.

[0014] Optionally, in one embodiment of this application, matching the optimal cruise mode of the target commercial vehicle based on the road information ahead, the actual vehicle network status, and the current traffic information includes: if the actual vehicle network status meets a preset smooth traffic condition and the road information ahead exists, then the optimal cruise mode is the predictive cruise mode; if the actual vehicle network status does not meet the preset smooth traffic condition or the road information ahead does not exist, then the optimal cruise mode is the constant speed cruise mode; if the actual vehicle network status meets a preset adaptive cruise condition, then the optimal cruise mode is the adaptive cruise mode.

[0015] A second aspect of this application provides a cloud-controlled commercial vehicle cruise control device applied to a server. The device includes: an acquisition module for acquiring forward road information, actual vehicle network status, and current traffic information of a target commercial vehicle; a matching module for matching the optimal cruise mode of the target commercial vehicle based on the forward road information, the actual vehicle network status, and the current traffic information; and a control module for performing a first cruise action at the economical speed of the target commercial vehicle when the optimal cruise mode is a predictive cruise mode, performing a second cruise action based on a preset adaptive cruise strategy when the optimal cruise mode is an adaptive cruise mode, and performing a third cruise action at a preset cruise speed when the optimal cruise mode is a constant speed cruise mode.

[0016] Optionally, in one embodiment of this application, the control module includes: an establishment unit, used to establish an economic driving strategy based on the principle of traversal optimization, and in combination with the slope of the road ahead, by limiting the traversal range to establish a slope state transition equation; and a search unit, used to obtain the fuel consumption cost and time cost of the vehicle speed change according to the slope state transition equation, so as to establish an optimal search strategy and search for the economic vehicle speed.

[0017] Specifically, in one embodiment of this application, the formula for calculating the fuel consumption cost is as follows:

[0018]

[0019] Among them, U k Let n be the fuel consumption cost of the vehicle in stage k. k T is the vehicle's rotational speed in stage k. k Let v be the torque of the vehicle in stage k, ΔS be the minimum distance discretized by the road gradient S km ahead, and v be the torque of the vehicle in stage k. k Let be the vehicle's speed in stage k; and the formula for calculating the time cost is:

[0020]

[0021] Among them, Tk Let v be the time cost of the vehicle in stage k, ΔS be the minimum distance discretized from the road gradient S km ahead, and v be the time cost of the vehicle in stage k. k Let be the speed of the vehicle in stage k.

[0022] Optionally, in one embodiment of this application, the control module further includes: a generation unit, configured to generate four containers for storing speed strategies according to a preset priority search order when searching for the economic speed; a first filtering unit, configured to classify the speed strategies for the road at a preset distance ahead stored within the traversal range, filtering strategies whose fuel consumption cost is less than the fuel consumption cost of the cruise control mode and whose average speed is greater than or equal to the preset cruise speed into the containers, and then filtering them into other containers according to different levels of average speed; and a second filtering unit, configured to perform a second round of filtering on the speed strategies in different containers. The process involves several steps: First, if the maximum throttle opening of a speed strategy within each container is greater than or equal to the throttle opening of the cruise control mode, or the average throttle opening is greater than or equal to the average throttle opening of the cruise control mode, then the corresponding container is removed. Second, a judgment unit determines whether a speed strategy still exists in each container. If no speed strategy exists in any container, the preset cruise speed is output; otherwise, the next round of filtering is performed. Third, a third filtering unit searches different containers from top to bottom. If the speed strategy exists, the speed strategy with the lowest fuel consumption is selected and output; otherwise, the next container is filtered.

[0023] Optionally, in one embodiment of this application, the matching module includes: a first matching unit, configured to, when the actual vehicle network status meets a preset smooth traffic condition and the road information ahead exists, select the predictive cruise mode as the optimal cruise mode; a second matching unit, configured to, when the actual vehicle network status does not meet the preset smooth traffic condition or the road information ahead does not exist, select the constant speed cruise mode as the optimal cruise mode; and a third matching unit, configured to, when the actual vehicle network status meets a preset adaptive cruise condition, select the adaptive cruise mode as the optimal cruise mode.

[0024] A third aspect of this application provides a server, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the cloud-controlled commercial vehicle cruise method as described in the above embodiments.

[0025] A fourth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described cloud-controlled commercial vehicle cruise method.

[0026] This application's embodiments can switch between different cruise modes based on the interaction between the target commercial vehicle and the cloud, according to network status, road information, and traffic information. This ensures the full utilization of predictive cruise functionality while improving the commercial vehicle's ability to respond to emergencies, thereby increasing the economic efficiency of vehicle cruise and making driving safer and more intelligent. This solves the problems in related technologies, such as insufficient consideration of actual driving scenarios for commercial vehicles, inability to respond promptly to obstacles ahead, and simplistic methods for determining cruise mode switching that are difficult to handle unexpected situations during actual cruise, leading to insufficient safety for commercial vehicles during cruise and affecting the functionality of predictive cruise technology.

[0027] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0028] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0029] Figure 1 This is a flowchart illustrating a cloud-controlled commercial vehicle cruise method according to an embodiment of this application;

[0030] Figure 2 This is a schematic diagram illustrating the cruise mode switching process according to one embodiment of this application;

[0031] Figure 3 This is a schematic diagram illustrating the process of selecting the economic speed according to an embodiment of this application;

[0032] Figure 4 This is a schematic diagram of a cloud-controlled commercial vehicle cruise process according to one embodiment of this application;

[0033] Figure 5 This is a schematic diagram of the structure of a cloud-controlled commercial vehicle cruise device according to an embodiment of this application;

[0034] Figure 6 This is a schematic diagram of the server structure according to an embodiment of this application. Detailed Implementation

[0035] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0036] The following description, with reference to the accompanying drawings, describes a cloud-controlled commercial vehicle cruise method and apparatus according to embodiments of this application. Addressing the issues raised in the background section regarding the related technologies that fail to adequately consider actual driving scenarios for commercial vehicles, cannot respond promptly to obstacles ahead, and employ simplistic methods for determining cruise mode switching, making it difficult to handle unexpected situations during actual cruise. This results in insufficient safety for commercial vehicles during cruise and hinders the functionality of predictive cruise technology. This application provides a cloud-controlled commercial vehicle cruise method that, based on the interaction between the target commercial vehicle and the cloud, makes judgments based on network status, road information, and traffic information to achieve switching between different cruise modes. While ensuring the full functionality of predictive cruise, it enhances the commercial vehicle's responsiveness to unexpected situations, thereby improving the economy of vehicle cruise and making driving safer and more intelligent. This solves the problems of related technologies that fail to adequately consider actual driving scenarios for commercial vehicles, cannot respond promptly to obstacles ahead, and employ simplistic methods for determining cruise mode switching, making it difficult to handle unexpected situations during actual cruise, resulting in insufficient safety for commercial vehicles during cruise and hindering the functionality of predictive cruise technology.

[0037] Specifically, Figure 1 This is a schematic flowchart of a cloud-controlled commercial vehicle cruise method provided in an embodiment of this application.

[0038] like Figure 1 As shown, the commercial vehicle cruise control method for cloud-based systems includes the following steps:

[0039] In step S101, the road information ahead of the target commercial vehicle, the actual vehicle network status, and the current traffic information are obtained.

[0040] It is understood that the road information ahead of the target commercial vehicle in this application embodiment may include map information, the actual vehicle network status may include vehicle GPS positioning information, T-BOX network status and vehicle uploaded data format, and the current traffic information may include cruising speed, speed of the vehicle in front and the relative distance between the vehicles in front and behind. The target commercial vehicle may be various types of vehicles used to transport people and goods, such as passenger cars, light trucks and heavy trucks.

[0041] This application embodiment can obtain the road information ahead of the target commercial vehicle, the actual vehicle network status and the current traffic information, thereby obtaining the relevant information of the target vehicle and providing the necessary data basis for matching the optimal cruise mode in the following steps.

[0042] In step S102, the optimal cruise mode for the target commercial vehicle is matched based on the road information ahead, the actual vehicle network status, and the current traffic information.

[0043] It is understood that in this embodiment, the vehicle's communication quality can be obtained through the actual network status, the map information of the current destination can be obtained through the road information ahead, and the specific road type of the road ahead can be obtained. The relevant data of the obstacle vehicle and the target vehicle ahead can be obtained through the current traffic information, so as to integrate the information and obtain the best cruise mode that can adapt to the current actual driving status of the vehicle.

[0044] This application embodiment can match the optimal cruise mode of the target commercial vehicle based on the road information ahead, the actual vehicle network status, and the current traffic information. Thus, based on the actual situation, it uses the various data information obtained in the above steps to select the required cruise mode and obtain the optimal driving plan required by the current vehicle, thereby improving the level of intelligence in vehicle information processing.

[0045] Optionally, in one embodiment of this application, matching the optimal cruise mode of the target commercial vehicle based on the road information ahead, the actual vehicle network status, and the current traffic information includes: if the actual vehicle network status meets the preset smooth traffic conditions and there is road information ahead, the optimal cruise mode is a predictive cruise mode; if the actual vehicle network status does not meet the preset smooth traffic conditions or there is no road information ahead, the optimal cruise mode is a constant speed cruise mode; if the actual vehicle network status meets the preset adaptive cruise conditions, the optimal cruise mode is an adaptive cruise mode.

[0046] It is understood that the preset smooth communication condition in this application embodiment can refer to the vehicle's good communication status, enabling smooth communication transmission between the cloud control system and the vehicle. The preset adaptive cruise control condition can refer to the distance between the two vehicles being too small and the speed of the vehicle in front being less than the vehicle's cruise speed, while the vehicle's network communication status is good.

[0047] It should be noted that the preset smooth traffic conditions and preset adaptive cruise control conditions are set by those skilled in the art according to the actual situation, and are not specifically limited here.

[0048] In actual operation, when a vehicle switches from cruise control to predictive cruise control, a stable network connection and availability of road information are required. If the network connection or map information is unavailable, the vehicle switches back to cruise control. Adaptive cruise control requires a distance of less than 'd' between the two vehicles and the speed of the vehicle in front to be less than the vehicle's cruise speed. When the network connection is normal and the conditions for entering adaptive cruise control are met, the vehicle switches from either predictive or cruise control to adaptive cruise control. When the network connection and map information are good and the conditions for exiting adaptive cruise control are met, the vehicle switches back to predictive cruise control. When the network connection is abnormal or there is no road information ahead and the conditions for exiting adaptive cruise control are met, the vehicle switches back to cruise control.

[0049] As shown Figure 2 in the figure, it is a schematic diagram of the switching process of the cruise mode according to an embodiment of the present application, and the specific conditions are shown in Table 1 below.

[0050] Table 1 Switching Conditions for Cruise Mode

[0051]

[0052]

[0053] Among them, 1 represents affirmation and 0 represents negation. When condition 1 is met, that is, when the network status is unobstructed and map information exists, the vehicle switches from the constant speed cruise mode to the predictive cruise mode.

[0054] When condition 2 is met, that is, when the network status is abnormal or map information does not exist, the vehicle switches from the predictive cruise mode to the constant speed cruise mode.

[0055] When condition 3 is met, that is, when the network status is unobstructed, the relative distance between the vehicle and the vehicle in front is <d, and the speed of the vehicle in front is <the cruise speed, the vehicle switches from the predictive cruise mode to the adaptive cruise mode.

[0056] When condition 4 is met, that is, when the network status is unobstructed and map information exists, and the relative distance between the vehicle and the vehicle in front is ≥d or the speed of the vehicle in front is ≥the cruise speed, the vehicle switches from the adaptive cruise mode to the predictive cruise mode.

[0057] When condition 5 is met, that is, when the network status is unobstructed, the relative distance between the vehicle and the vehicle in front is <d, and the speed of the vehicle in front is <the cruise speed, the vehicle switches from the constant speed cruise mode to the adaptive cruise mode.

[0058] When condition 6 is met, that is, when the network status is abnormal, or map information does not exist, and either the relative distance between the vehicle and the vehicle in front is ≥d or the speed of the vehicle in front is ≥the cruise speed, the vehicle switches from the adaptive cruise mode to the constant speed cruise mode.

[0059] The embodiment of the present application can switch the vehicle into the predictive cruise mode, constant speed cruise mode or adaptive cruise mode according to whether the actual vehicle network status meets the preset unobstructed condition, whether it meets the preset adaptive cruise condition, and whether there is information about the road ahead, so as to flexibly switch the cruise mode according to the current actual state of the vehicle, improve the vehicle's ability to respond to emergencies, and enhance the safety of the vehicle.

[0060] In step S103, when the optimal cruise mode is predictive cruise mode, the first cruise action is performed at the economic speed of the target commercial vehicle; when the optimal cruise mode is adaptive cruise mode, the second cruise action is performed based on a preset adaptive cruise strategy; and when the optimal cruise mode is constant speed cruise mode, the third cruise action is performed at a preset cruise speed.

[0061] It is understood that, in the embodiments of this application, the first cruise action may include the vehicle driving at an economical speed in predictive cruise mode, the second cruise action may include the vehicle driving under adaptive cruise strategy in adaptive cruise mode, and the third cruise action may include the vehicle driving at a constant speed according to a preset cruise speed in constant speed cruise mode.

[0062] It should be noted that the preset adaptive cruise control strategy and preset cruise speed are set by those skilled in the art based on actual conditions, and are not specifically limited here.

[0063] The embodiments of this application can execute the first cruise action, the second cruise action, or the third cruise action of the vehicle when the optimal cruise mode is predictive cruise mode, adaptive cruise mode, or constant speed cruise mode, respectively. This allows the vehicle to execute different driving schemes according to different cruise modes, enriching the vehicle's cruise mode selection and making vehicle driving more intelligent and reliable.

[0064] Optionally, in one embodiment of this application, the first cruise action is performed at the economic speed of the target commercial vehicle, including: an economic driving strategy based on the principle of traversal optimization, and in combination with the slope of the road ahead, establishing a slope state transition equation by limiting the traversal range; obtaining the fuel consumption cost and time cost of the speed change according to the slope state transition equation, so as to establish an optimal search strategy and search for the economic speed.

[0065] In actual implementation, predictive cruise algorithms can be used to reconstruct the gradient of the road ahead (S km) and calculate the economic speed based on the reconstructed gradient, thus achieving economical driving.

[0066] First, by reading the road slope of S km ahead, the road slope is discretized with ΔS as the reference, resulting in N reconstructed road slope segments.

[0067]

[0068]

[0069] Where θ is the road angle, Δh is the relative height between the two waypoints, and ΔS is the minimum distance discretized from the road gradient S km ahead. The curvature of the road.

[0070] Secondly, using the vehicle's current speed as the starting speed, boundary conditions such as speed limits and torque limits are set, and the traversal range is determined based on these boundary conditions.

[0071]

[0072] Among them, v min Let v(k+i) be the minimum speed allowed for the vehicle, and v(k+i) be the vehicle speed on road segment k+i. max T is the maximum permissible speed for the vehicle. min T(k+i) represents the minimum allowable torque for the vehicle, and T(k+i) represents the engine torque of the vehicle on road segment k+i. max The maximum allowable torque for the vehicle is given, with speed measured in km / h and torque measured in Nm.

[0073] Specifically, let the current time be k, and the vehicle's speed be v. h (k), where the location is ΔS(k), and the speed traversal range of waypoint ΔS(k+1) is defined as v. h (k)+Δv,v h (k)-Δv remains unchanged, meaning there exists a range set{k+1} that satisfies this condition.

[0074]

[0075] The traversal range of waypoint ΔS(k+2) is the sum of the possible values ​​of the previous waypoint plus or minus Δv, with Δv remaining unchanged. That is, there exists a traversal range set{k+2} that satisfies...

[0076]

[0077] Until there exists a waypoint ΔS(k+N) and its traversal range set{k+N} satisfies

[0078]

[0079] Here, Δv is the traversal factor, whose value is determined by the change in road slope within two adjacent ΔS. All traversal ranges are within the maximum and minimum allowable fluctuations in vehicle speed.

[0080] Next, the driving cost at different driving speeds is calculated based on the state transition equation of the vehicle from stage k to stage k+N, and the driving cost of cruise control is also calculated.

[0081] Specifically, based on the analysis of the vehicle's longitudinal dynamics model, the expansion of the vehicle's driving equation can be further obtained as follows:

[0082]

[0083] The expansion of the vehicle's equation of motion is transformed from the time domain to the space domain, resulting in...

[0084]

[0085] Right now

[0086]

[0087] Integral result

[0088]

[0089] Where ΔS is the minimum distance discretized from the road gradient S km ahead, δ is the vehicle rotational mass conversion factor, satisfying δ>1, m is the vehicle mass in kg, and T tq For engine torque, i g The transmission ratio is i0, which is the transmission ratio of the main reducer, or the main drive ratio. η is the transmission ratio of the gearbox. t For the mechanical efficiency of the transmission system, r w C is the radius of the wheel. D Where A is the air resistance coefficient, ρ is the frontal area, v is the air density, and v is the vehicle speed. k Let S be the vehicle speed at stage k, and S be the distance of the preceding road gradient. Let be the road curvature. Let 'a' be the acceleration 'a' from stage k to the next stage. k for

[0090]

[0091] Among them, a k Let v be the acceleration of the vehicle from stage k to the next stage. k Let be the vehicle speed at stage k, and ΔS be the minimum distance discretized from the road gradient S km ahead.

[0092] This application embodiment can establish an economic driving strategy based on the principle of traversal optimization, and combine the slope of the road ahead to establish a slope state transition equation by limiting the traversal range. The fuel consumption cost and time cost of vehicle speed change are obtained from the slope state transition equation to establish an optimal search strategy and search for an economical vehicle speed, thereby improving the economy of the cruise control strategy. Furthermore, the boundary conditions are limited to ensure the driving comfort, stability and driver acceptance of the vehicle, and reduce the amount of computation during the execution process.

[0093] Specifically, in one embodiment of this application, the formula for calculating fuel consumption cost is as follows:

[0094]

[0095] Among them, U k Let n be the fuel consumption cost of the vehicle in stage k. k T is the vehicle's rotational speed in stage k.k Let v be the torque of the vehicle in stage k, ΔS be the minimum distance discretized by the road gradient S km ahead, and v be the torque of the vehicle in stage k. k Let be the vehicle's speed in stage k; and the formula for calculating the time cost is:

[0096]

[0097] Among them, T k Let v be the time cost of the vehicle in stage k, ΔS be the minimum distance discretized from the road gradient S km ahead, and v be the time cost of the vehicle in stage k. k Let be the speed of the vehicle in stage k.

[0098] As can be seen from the above formula, in actual execution, the vehicle's rotational speed n in stage k can be obtained. k Torque T k By searching for a fuel consumption model, the fuel consumption cost U can be obtained. k Time cost T k Then, based on the fuel consumption cost and time cost corresponding to different speed curves between each waypoint, the overall fuel consumption cost and time cost of different speed strategies on the road ahead of skm are obtained. By comparing the costs, the speed curve that meets the optimal search requirements is selected, thereby achieving economical driving on slopes.

[0099] The embodiments of this application can calculate the fuel consumption cost and time cost of a vehicle at different stages, obtain the overall cost of the vehicle at different speeds, and then compare and select the optimal speed to achieve economical driving and improve the practicality of the vehicle.

[0100] Optionally, in one embodiment of this application, searching for an economical vehicle speed includes: generating four containers for storing speed strategies according to a preset priority search order; classifying the speed strategies for the road at a preset distance ahead stored within the traversal range, filtering strategies with fuel consumption costs less than the fuel consumption cost of the cruise control mode and average vehicle speed greater than or equal to the preset cruise speed into the containers, and then filtering them into other containers according to different levels of average vehicle speed; performing a second round of filtering on the speed strategies in different containers, wherein if the maximum throttle opening of a speed strategy in each container is greater than or equal to the throttle opening of the cruise control mode or the average throttle opening is greater than or equal to the average throttle opening of the cruise control mode, then removing the corresponding container; determining whether there is still a speed strategy in each container, and if there is no speed strategy in all containers, then outputting the preset cruise speed, otherwise performing the next round of filtering; searching different containers from top to bottom, and if a speed strategy exists, selecting the speed strategy with the lowest fuel consumption cost for output, otherwise filtering the next container.

[0101] In some embodiments, such as Figure 3The diagram illustrates the process of selecting economical vehicle speeds according to an embodiment of this application. First, four containers are generated according to a top-down priority search order to store speed strategies, classifying the speed strategies for the preceding Skm of road within the traversal range. The strategy with fuel consumption cost FC (Fuel Consumption) less than cruise control fuel consumption cost FC_CC (Fuel Consumption_Cruise Control), and with an average vehicle speed Aver... Speed Vehicles with average speeds greater than or equal to the cruise speed (Vcc) are filtered into one container, and then further filtered into other containers according to different levels of average speed, based on the criteria of being greater than or equal to 99%, 98%, and 95% of the cruise speed, respectively.

[0102] Secondly, a second round of screening is performed on the vehicle speed strategies within different containers, retaining those whose maximum throttle opening (Max_throttle) is less than the cruise control throttle opening (Max_throttle_CC) and whose average throttle opening (Aver) is greater than the speed strategy within each container. throttle Less than the average throttle opening during cruise control. throttle_CC The speed strategy is set, and speed strategies that do not meet the conditions are removed from the container.

[0103] Finally, it is determined whether a speed strategy still exists within the containers. If no speed strategy exists in any container, the cruise speed Vcc is output; otherwise, a third round of filtering is performed, searching different containers from top to bottom. If a speed strategy exists within a container, the speed strategy with the lowest fuel consumption, MIN_FC, is selected and output; otherwise, the next container is selected. Furthermore, when the vehicle reaches road segment k+1, the predicted speed for the road ahead Skm is recalculated.

[0104] It should be noted that the preset priority search order and preset cruise speed are set by those skilled in the art according to the actual situation, and are not specifically limited here.

[0105] This application embodiment can filter the speed strategy of the obtained vehicle on the road ahead to obtain the optimal speed strategy that meets the lowest fuel consumption cost. In this way, the vehicle cruises on the road ahead while ensuring maximum fuel saving, which improves the practicality and intelligence of the vehicle and makes it more energy-efficient.

[0106] The following detailed description of the working content of the embodiments of this application is based on a specific example. Figure 4 The diagram shown is a schematic representation of a cloud-controlled commercial vehicle cruise process according to an embodiment of this application.

[0107] First, the vehicle-side platform, based on the cloud-based digital twin platform, determines the cruise mode and executes the mode switching strategy based on the vehicle's GPS positioning information, T-BOX network status, vehicle uploaded data format, map information, cruise speed, speed of the vehicle in front, and network status, road information, and traffic information obtained from the relative distance between the vehicles in front and behind.

[0108] Furthermore, when the mode switching strategy controls the vehicle to enter the predictive cruise mode, the economic driving strategy based on the principle of traversal optimization considers the road slope ahead for road preprocessing, establishes the traversal range, establishes the state transition equation, and obtains the fuel consumption cost and time cost of the vehicle speed change.

[0109] Finally, an optimal search strategy is established to determine whether an optimal economic speed exists. If so, the economic speed is output to achieve economical driving; otherwise, the system switches to cruise control mode.

[0110] The cloud-controlled commercial vehicle cruise method proposed in this application can switch between different cruise modes based on the interaction between the target commercial vehicle and the cloud, according to network status, road information, and traffic information. This ensures the full utilization of predictive cruise functionality while improving the commercial vehicle's ability to respond to emergencies, thereby increasing the economic efficiency of vehicle cruise and making driving safer and more intelligent. This solves the problems in related technologies, such as insufficient consideration of actual driving scenarios for commercial vehicles, inability to respond promptly to obstacles ahead, and simplistic cruise mode switching methods that are difficult to handle emergencies during actual cruise, leading to insufficient safety for commercial vehicles during cruise and affecting the functionality of predictive cruise technology.

[0111] Next, referring to the accompanying drawings, a cloud-controlled commercial vehicle cruise device is described according to an embodiment of this application.

[0112] Figure 5 This is a schematic diagram of the structure of a cloud-controlled commercial vehicle cruise device according to an embodiment of this application.

[0113] like Figure 5 As shown, the commercial vehicle cruise control device 10 for cloud control includes: an acquisition module 100, a matching module 200, and a control module 300.

[0114] The acquisition module 100 is used to acquire information about the road ahead, the actual vehicle network status, and the current traffic information of the target commercial vehicle.

[0115] The matching module 200 is used to match the optimal cruise mode for the target commercial vehicle based on the road information ahead, the actual vehicle network status, and the current traffic information.

[0116] The control module 300 is used to perform a first cruise action at the economic speed of the target commercial vehicle when the optimal cruise mode is predictive cruise mode, and to perform a second cruise action based on a preset adaptive cruise strategy when the optimal cruise mode is adaptive cruise mode, and to perform a third cruise action at a preset cruise speed when the optimal cruise mode is constant speed cruise mode.

[0117] Optionally, in one embodiment of this application, the control module 300 includes: a setup unit and a search unit.

[0118] Among them, the establishment unit is used for an economic driving strategy based on the principle of traversal optimization, and combined with the slope of the road ahead, the slope state transition equation is established by limiting the traversal range.

[0119] The search unit is used to obtain the fuel consumption cost and time cost of vehicle speed change based on the slope state transition equation, so as to establish the optimal search strategy and search for the economical vehicle speed.

[0120] Specifically, in one embodiment of this application, the formula for calculating fuel consumption cost is as follows:

[0121]

[0122] Among them, U k Let n be the fuel consumption cost of the vehicle in stage k. k T is the vehicle's rotational speed in stage k. k Let v be the torque of the vehicle in stage k, ΔS be the minimum distance discretized by the road gradient S km ahead, and v be the torque of the vehicle in stage k. k Let be the vehicle's speed in stage k. Furthermore, the formula for calculating the time cost is:

[0123]

[0124] Among them, T l Let v be the time cost of the vehicle in stage k, ΔS be the minimum distance discretized from the road gradient S km ahead, and v be the time cost of the vehicle in stage k. k Let be the speed of the vehicle in stage k.

[0125] Optionally, in one embodiment of this application, the control module 300 further includes: a generation unit, a first filtering unit, a second filtering unit, a judgment unit, and a third filtering unit.

[0126] The generation unit is used to generate four containers for storing speed strategies according to a preset priority search order when searching for economical vehicle speed.

[0127] The first filtering unit is used to classify the road speed strategies stored within the traversal range that are at a preset distance ahead. Strategies with fuel consumption costs less than those of the cruise control mode and average vehicle speed greater than or equal to the preset cruise speed are filtered into containers. Then, they are filtered into other containers according to different levels of average vehicle speed.

[0128] The second filtering unit is used to perform a second round of filtering on the vehicle speed strategies in different containers. If the maximum throttle opening of the speed strategy in each container is greater than or equal to the throttle opening of the cruise control mode or the average throttle opening is greater than or equal to the average throttle opening of the cruise control mode, then the corresponding container is removed.

[0129] The judgment unit is used to determine whether a speed strategy still exists in each container. If no speed strategy exists in any container, the preset cruising speed is output; otherwise, the next round of filtering is performed.

[0130] The third filtering unit is used to search different containers from top to bottom. If a speed strategy exists, the speed strategy with the lowest fuel consumption cost is selected and output; otherwise, the next container is filtered.

[0131] Optionally, in one embodiment of this application, the matching module includes: a first matching unit, a second matching unit, and a third matching unit.

[0132] The first matching unit is configured to use a predictive cruise mode as the optimal cruise mode when the actual vehicle network condition meets the preset smooth conditions and there is road information ahead.

[0133] The second matching unit is used to select cruise control as the optimal cruise mode when the actual vehicle network status does not meet the preset smooth conditions or there is no information about the road ahead.

[0134] The third matching unit is used to determine the optimal cruise mode as the adaptive cruise mode when the actual vehicle network conditions meet the preset adaptive cruise conditions.

[0135] It should be noted that the foregoing explanation of the embodiment of the cloud-controlled commercial vehicle cruise method also applies to the cloud-controlled commercial vehicle cruise device of this embodiment, and will not be repeated here.

[0136] The cloud-controlled commercial vehicle cruise control device proposed in this application can switch between different cruise modes based on the interaction between the target commercial vehicle and the cloud, according to network status, road information, and traffic information. This ensures the full utilization of predictive cruise functionality while improving the commercial vehicle's ability to respond to emergencies, thereby increasing the economic efficiency of vehicle cruise and making driving safer and more intelligent. This solves the problems in related technologies, such as insufficient consideration of actual driving scenarios for commercial vehicles, inability to respond promptly to obstacles ahead, and simplistic methods for determining cruise mode switching that are difficult to handle emergencies during actual cruise, leading to insufficient safety for commercial vehicles during cruise and affecting the functionality of predictive cruise technology.

[0137] Figure 6 A schematic diagram of the structure of a server provided in an embodiment of this application. The server may include:

[0138] The memory 601, the processor 602, and the computer program stored on the memory 601 and capable of running on the processor 602.

[0139] When the processor 602 executes the program, it implements the cloud-controlled commercial vehicle cruise method provided in the above embodiments.

[0140] Furthermore, the server also includes:

[0141] Communication interface 603 is used for communication between memory 601 and processor 602.

[0142] The memory 601 is used to store computer programs that can run on the processor 602.

[0143] The memory 601 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0144] If the memory 601, processor 602, and communication interface 603 are implemented independently, then the communication interface 603, memory 601, and processor 602 can be interconnected via a bus to complete communication between them. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of representation, Figure 6The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0145] Optionally, in a specific implementation, if the memory 601, processor 602, and communication interface 603 are integrated on a single chip, then the memory 601, processor 602, and communication interface 603 can communicate with each other through an internal interface.

[0146] The processor 602 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application.

[0147] This embodiment also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described cloud-controlled commercial vehicle cruise method.

[0148] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0149] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0150] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0151] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0152] It should be understood that the various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0153] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0154] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0155] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A method for cloud-controlled commercial vehicle cruise control, characterized in that, Applied to a server, the method includes the following steps: Obtain information about the road ahead, the actual vehicle network status, and the current traffic information for the target commercial vehicle; Based on the road information ahead, the actual vehicle network status, and the current traffic information, the optimal cruise mode for the target commercial vehicle is matched; and When the optimal cruise mode is predictive cruise mode, a first cruise maneuver is performed at the economical speed of the target commercial vehicle; when the optimal cruise mode is adaptive cruise mode, a second cruise maneuver is performed based on a preset adaptive cruise strategy; and when the optimal cruise mode is constant speed cruise mode, a third cruise maneuver is performed at a preset cruise speed. The first cruise maneuver, performed at the economical speed of the target commercial vehicle, includes: An economical driving strategy based on the principle of traversal optimization, combined with the slope of the road ahead, establishes a slope state transition equation by limiting the traversal range; The fuel consumption cost and time cost of vehicle speed change are obtained based on the slope state transition equation to establish an optimal search strategy and search for the economic speed. The search for the economical vehicle speed includes: Four containers for storing speed strategies are generated according to a preset priority search order; Classify the road speed strategies stored within the traversal range that are at a preset distance ahead. Filter strategies with fuel consumption costs less than the fuel consumption cost of the cruise control mode and average vehicle speed greater than or equal to the preset cruise speed into a container. Then, filter them into other containers according to different levels of average vehicle speed. A second round of screening is performed on the vehicle speed strategies in different containers. If the maximum throttle opening of the speed strategy in each container is greater than or equal to the throttle opening of the cruise control mode or the average throttle opening is greater than or equal to the average throttle opening of the cruise control mode, then the corresponding container is removed. Determine whether a speed strategy still exists in each container. If the speed strategy does not exist in any container, output the preset cruising speed; otherwise, proceed to the next round of filtering. The search proceeds from top to bottom across different containers. If the speed strategy described above exists, the speed strategy with the lowest fuel consumption is selected and output; otherwise, the next container is selected.

2. The method according to claim 1, characterized in that, The formula for calculating the fuel consumption cost is as follows: in, For vehicles in The cost of fuel consumption during the phase For vehicles in Rotation speed of the stage, For vehicles in Stage torque, For the front Minimum distance for discretizing km road slope For vehicles in The speed of the stage; Furthermore, the formula for calculating the time cost is as follows: in, For vehicles in The time cost of each stage For the front Minimum distance for discretizing km road slope For vehicles in The speed of the stage.

3. The method according to claim 1, characterized in that, The step of matching the optimal cruising mode for the target commercial vehicle based on the road information ahead, the actual vehicle network status, and the current traffic information includes: If the actual vehicle network status meets the preset smooth conditions and the road information ahead exists, then the optimal cruise mode is the predictive cruise mode. If the actual vehicle network status does not meet the preset smooth traffic conditions or there is no information about the road ahead, then the optimal cruise mode is the cruise control mode. If the actual vehicle network status meets the preset adaptive cruise conditions, then the optimal cruise mode is the adaptive cruise mode.

4. A cloud-controlled commercial vehicle cruise control device, characterized in that, Applied to a server, wherein the device includes: The acquisition module is used to acquire information about the road ahead, the actual vehicle network status, and the current traffic information of the target commercial vehicle. The matching module is used to match the optimal cruising mode of the target commercial vehicle based on the road information ahead, the actual vehicle network status, and the current traffic information; and A control module is configured to perform a first cruise maneuver at the economic speed of the target commercial vehicle when the optimal cruise mode is predictive cruise mode, perform a second cruise maneuver based on a preset adaptive cruise strategy when the optimal cruise mode is adaptive cruise mode, and perform a third cruise maneuver at a preset cruise speed when the optimal cruise mode is constant speed cruise mode. The control module includes: Establish a unit for an economical driving strategy based on the principle of traversal optimization, and combine it with the slope of the road ahead to establish the slope state transition equation by limiting the traversal range; The search unit is used to obtain the fuel consumption cost and time cost of the vehicle speed change according to the slope state transition equation, so as to establish the optimal search strategy and search for the economic speed. The control module further includes: The generation unit is used to generate four containers for storing speed strategies according to a preset priority search order when searching for the economic vehicle speed. The first filtering unit is used to classify the road speed strategies stored within the traversal range that are at a preset distance ahead. Strategies with fuel consumption costs less than the fuel consumption cost of the cruise control mode and average vehicle speed greater than or equal to the preset cruise speed are filtered into containers. Then, they are filtered into other containers according to different levels of average vehicle speed. The second screening unit is used to perform a second round of screening on the vehicle speed strategies in different containers. If the maximum throttle opening of the speed strategy in each container is greater than or equal to the throttle opening of the cruise control mode or the average throttle opening is greater than or equal to the average throttle opening of the cruise control mode, then the corresponding container is removed. The judgment unit is used to determine whether a speed strategy still exists in each container. If the speed strategy does not exist in any container, the preset cruising speed is output; otherwise, the next round of filtering is performed. The third filtering unit is used to search different containers from top to bottom. If the speed strategy exists, the speed strategy with the lowest fuel consumption cost is selected and output; otherwise, the next container is filtered.

5. The apparatus according to claim 4, characterized in that, The formula for calculating the fuel consumption cost is as follows: in, For vehicles in The cost of fuel consumption during the phase For vehicles in Rotation speed of the stage, For vehicles in Stage torque, For the front Minimum distance for discretizing km road slope For vehicles in The speed of the stage; Furthermore, the formula for calculating the time cost is as follows: in, For vehicles in The time cost of each stage For the front Minimum distance for discretizing km road slope For vehicles in The speed of the stage.

6. The apparatus according to claim 4, characterized in that, The matching module includes: The first matching unit is configured to determine the optimal cruise mode as the predictive cruise mode when the actual vehicle network status meets the preset smooth conditions and the road information ahead exists. The second matching unit is used to determine the optimal cruise mode as the cruise control mode when the actual vehicle network status does not meet the preset smooth conditions or there is no information about the road ahead. The third matching unit is configured to determine the optimal cruise mode as the adaptive cruise mode when the actual vehicle network status meets the preset adaptive cruise conditions.

7. A server, characterized in that, include: A memory, a processor, and a computer program stored in the memory and executable on the processor, the processor executing the program to implement the cloud-controlled commercial vehicle cruise method as described in any one of claims 1-3.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, The program is executed by the processor to implement the cloud-controlled commercial vehicle cruise method as described in any one of claims 1-3.

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