Vehicle remote calling method, vehicle, medium and product

Abstract

The invention discloses a vehicle remote calling method, a vehicle, a medium and a product, and the method comprises the steps: if the vehicle receives a remote calling instruction, obtaining an environment map of the current environment of the vehicle, and obtaining multi-source data of the vehicle, the multi-source data comprising vehicle parameters and environment parameters of the vehicle; determining at least one candidate path from the environment map based on the initial position of the vehicle and the final position corresponding to the calling instruction; based on the multi-source data, total energy consumption of driving according to each candidate path in the at least one candidate path is determined, and the total energy consumption comprises driving energy consumption, air conditioner energy consumption and recovery potential energy of the vehicle; and determining a target candidate path with the lowest total energy consumption, and controlling the vehicle to run along the target candidate path. According to the scheme, the driving path with the lowest energy consumption in remote calling can be determined, and the endurance mileage of the vehicle is effectively prolonged.

Description

Technical Field

[0001] The present invention relates to the field of vehicle technology, and in particular to a vehicle remote summoning method, a vehicle, a medium and a product. Background Art

[0002] With the continuous development of science and technology, the functions of vehicles are becoming increasingly diverse. The remote summon function of a vehicle refers to the vehicle driving to the user's designated location in an unmanned manner. The remote summon function is mainly used in closed road scenarios such as parking lots and campuses. When the user is unable to get on the vehicle or is far away from the vehicle, the vehicle can be controlled by remote summoning to leave the parking space and drive to the user's designated location, greatly improving the user experience. In related technologies, when a vehicle executes a remote summon, it is necessary to plan the route. Therefore, how to reasonably plan the driving route is a technical problem that needs to be solved urgently. Summary of the Invention

[0003] Embodiments of the present invention provide a vehicle remote summoning method, a vehicle, a medium, and a product.

[0004] In a first aspect, an embodiment of the present invention provides a method for remotely summoning a vehicle, comprising:

[0005] If the vehicle receives a remote summon command, obtain an environmental map of the vehicle's current environment and obtain multi-source data of the vehicle, the multi-source data including vehicle parameters and environmental parameters of the vehicle;

[0006] Determining at least one candidate path from the environment map based on the initial position of the vehicle and the end position corresponding to the summon instruction;

[0007] determining, based on the multi-source data, a total energy consumption of traveling along each candidate route of the at least one candidate route, the total energy consumption including driving energy consumption, air conditioning energy consumption, and recovered potential energy of the vehicle;

[0008] A target candidate path with the lowest total energy consumption is determined, and the vehicle is controlled to travel along the target candidate path.

[0009] In some embodiments, obtaining multi-source data of the vehicle includes:

[0010] Based on a building information model of an environment in which the vehicle is currently located, extracting a slope angle of the environment in which the vehicle is currently located from the building information model;

[0011] Acquiring the air density of the vehicle's current environment, wherein the environmental parameters include the slope angle and the air density;

[0012] Obtaining the vehicle's drag coefficient, vehicle frontal area, vehicle mass, and tire rolling resistance coefficient as the vehicle parameters;

[0013] The determining, based on the multi-source data, the total energy consumption of traveling along each candidate path of the at least one candidate path includes:

[0014] The driving energy consumption corresponding to each candidate path is determined based on the slope angle, the air density, the drag coefficient, the vehicle frontal area, the vehicle mass, and the tire rolling resistance coefficient.

[0015] In some embodiments, obtaining multi-source data of the vehicle includes:

[0016] Acquiring the ambient temperature of the vehicle's current environment as the environmental parameter;

[0017] Acquiring the vehicle's air conditioning set temperature, air conditioning energy efficiency ratio, vehicle body thermal inertia coefficient, and preset ventilation power as the vehicle parameters;

[0018] The determining, based on the multi-source data, the total energy consumption of traveling along each candidate path of the at least one candidate path includes:

[0019] The air conditioning energy consumption corresponding to each candidate path is determined based on the ambient temperature, the air conditioning set temperature, the air conditioning energy efficiency ratio, the vehicle body thermal inertia coefficient, and the preset ventilation power.

[0020] In some embodiments, obtaining multi-source data of the vehicle includes:

[0021] Based on a building information model of the environment currently located by the vehicle, extracting from the building information model the slope angle of each downhill section in the environment currently located by the vehicle and the vertical height difference of each downhill section as the environmental parameters;

[0022] Obtaining the regenerative braking efficiency of the vehicle and the vehicle mass of the vehicle as the vehicle parameters;

[0023] The determining, based on the multi-source data, the total energy consumption of traveling along each candidate path of the at least one candidate path includes:

[0024] The recovery potential energy of each candidate path is determined based on the slope angle of each downhill section, the vertical height difference of each downhill section, the regenerative braking efficiency, and the vehicle mass.

[0025] In some embodiments, after controlling the vehicle to travel along the candidate target path, the method further includes:

[0026] If the vehicle detects a target environment state different from the initial environment state of the target candidate path when traveling to the target location, replanning at least one local candidate path from the target location to the end location;

[0027] determining a target area in each of the at least one local candidate path;

[0028] For each local candidate path, determining a single-step energy consumption of the vehicle traveling on the local candidate path and an avoidance function based on a target area on the local candidate path, determining a single-step avoidance cost, and performing an iterative calculation based on the single-step energy consumption and the single-step avoidance cost to obtain an energy consumption for the local path;

[0029] The local candidate path with the lowest energy consumption is used as the updated path, and the vehicle is controlled to travel along the updated path.

[0030] In some embodiments, the target area includes a charging station area, and determining the single-step avoidance cost includes:

[0031] Obtaining the power of the charging pile corresponding to the charging pile area;

[0032] Determining a avoidance radius of the charging pile based on the power of the charging pile;

[0033] A single-step avoidance cost of the vehicle for the charging pile area is determined based on the avoidance radius of the charging pile, the distance between the vehicle and the charging pile, and the avoidance function corresponding to the charging pile area.

[0034] In some embodiments, the target area includes a vent area, and determining the single-step avoidance cost includes:

[0035] Obtaining location information of a vent area in the current environment of the vehicle, and obtaining a current temperature difference between the inside and outside of the vehicle;

[0036] Determining a temperature difference in the ventilation area based on the location information of the ventilation area, the current location information of the vehicle, the current inside and outside temperatures of the vehicle, and a preset temperature attenuation model;

[0037] A single-step avoidance cost of the vehicle for the vent area is determined based on the temperature difference in the ventilation area and the avoidance function corresponding to the vent area.

[0038] In a second aspect, an embodiment of the present invention provides a vehicle remote summoning device, comprising:

[0039] an acquisition module, configured to acquire an environmental map of the vehicle's current environment and multi-source data of the vehicle when the vehicle receives a remote summon command, the multi-source data including vehicle parameters and environmental parameters of the vehicle;

[0040] a path planning module, configured to determine at least one candidate path from the environment map based on an initial position of the vehicle and a terminal position corresponding to the summon instruction;

[0041] an energy consumption determination module, configured to determine, based on the multi-source data, a total energy consumption of traveling along each of the at least one candidate path, the total energy consumption including driving energy consumption, air conditioning energy consumption, and recovered potential energy of the vehicle;

[0042] The processing module is used to determine a target candidate path with the lowest total energy consumption and control the vehicle to travel along the target candidate path.

[0043] In a third aspect, the present invention provides a vehicle comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps in the above-mentioned vehicle remote summoning method when executing the program.

[0044] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, which implements the steps in the above-mentioned vehicle remote summoning method when executed by a processor.

[0045] In a fifth aspect, an embodiment of the present invention provides a computer program product, which includes a computer program. When the computer program is executed by a processor, it is used to load and execute the steps in the above-mentioned vehicle remote summoning method.

[0046] The above one or at least one technical solution in the embodiments of the present application has at least the following technical effects:

[0047] The vehicle remote summoning method provided in the embodiments of this specification is as follows: if the vehicle receives a remote summoning command, it obtains an environmental map of the vehicle's current environment and multi-source data of the vehicle, the multi-source data including vehicle parameters and environmental parameters; based on the vehicle's initial position and the end position corresponding to the summoning command, at least one candidate path is determined from the environmental map; based on the vehicle's multi-source data, the total energy consumption of traveling along each candidate path in the at least one candidate path is determined, wherein the total energy consumption includes the vehicle's driving energy consumption, air conditioning energy consumption, and recovered potential energy; the target candidate path with the lowest total energy consumption is determined, and the vehicle is controlled to travel along the target candidate path. This solution, by obtaining multi-source data of the vehicle, determines the vehicle's driving energy consumption, air conditioning energy consumption, and recovered potential energy, and comprehensively considers multiple types of energy consumption during driving, can accurately evaluate the energy consumption consumed by the vehicle, and then determine the driving path with the lowest energy consumption. For electric vehicles, this can effectively extend the range of the electric vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 A flowchart of a vehicle remote summoning method provided in an embodiment of this specification;

[0049] Figure 2 A schematic diagram of a vehicle remote summoning device provided in an embodiment of this specification;

[0050] Figure 3 A schematic diagram of a vehicle provided in an embodiment of this specification. DETAILED DESCRIPTION

[0051] The overall idea of the technical solution of the embodiment of the present application is as follows: if a vehicle receives a remote summoning command, an environmental map of the vehicle's current environment is obtained, and multi-source data of the vehicle is obtained, wherein the multi-source data includes vehicle parameters and environmental parameters of the vehicle; based on the initial position of the vehicle and the end position corresponding to the summoning command, at least one candidate path is determined from the environmental map; based on the multi-source data, the total energy consumption of traveling along each candidate path of the at least one candidate path is determined, wherein the total energy consumption includes the driving energy consumption, air-conditioning energy consumption and recovered potential energy of the vehicle; a target candidate path with the lowest total energy consumption is determined, and the vehicle is controlled to travel along the target candidate path.

[0052] The solution of the embodiments of this specification obtains multi-source data of the vehicle to determine the vehicle's driving energy consumption, air-conditioning energy consumption, and recovered potential energy. By comprehensively considering multiple types of energy consumption during driving, it can accurately evaluate the energy consumption consumed by the vehicle and then determine the driving path with the lowest energy consumption. For electric vehicles, it can effectively extend the cruising range of electric vehicles.

[0053] In order to better understand the above technical solutions, the technical solutions of the embodiments of this specification are described in detail below through the accompanying drawings and specific embodiments. It should be understood that the embodiments of this specification and the specific features in the embodiments are detailed descriptions of the technical solutions of the embodiments of this specification, rather than limitations on the technical solutions of this specification. In the absence of conflict, the embodiments of this specification and the technical features in the embodiments can be combined with each other.

[0054] First, the term "and / or" as used herein simply describes a relationship between associated objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A alone, A and B together, or B alone. Furthermore, the character " / " in this document generally indicates an "or" relationship between the associated objects.

[0055] like Figure 1 FIG. 1 is a flow chart of a method for remotely summoning a vehicle provided in an embodiment of this specification, the method comprising the following steps:

[0056] S101: If a vehicle receives a remote summon command, obtain an environmental map of the vehicle's current environment and obtain multi-source data of the vehicle, the multi-source data including vehicle parameters and environmental parameters of the vehicle;

[0057] S102: Determining at least one candidate path from the environment map based on the initial position of the vehicle and the end position corresponding to the summoning instruction;

[0058] S103: Determining, based on the multi-source data, a total energy consumption of traveling along each candidate path of the at least one candidate path, the total energy consumption including driving energy consumption, air conditioning energy consumption, and recovered potential energy of the vehicle;

[0059] S104: Determine a target candidate path with the lowest total energy consumption, and control the vehicle to travel along the target candidate path.

[0060] The method provided in the embodiments of this specification can be applied to electric vehicles, to servers connected to electric vehicles for communication, or to systems consisting of electric vehicles and servers, without limitation here.

[0061] In the embodiments of this specification, when a user needs to remotely summon a vehicle, they can send a remote summon command via a key or a user terminal (such as a mobile phone). When the vehicle receives the remote summon command, it can obtain an environmental map of the vehicle's current environment and obtain multi-source data about the vehicle in step S101. It should be noted that the multi-source data may include vehicle parameters and environmental parameters.

[0062] In some embodiments, vehicle parameters may include but are not limited to vehicle dynamics parameters, thermal management parameters, and driving parameters. Vehicle dynamics parameters may include vehicle mass, drag coefficient, vehicle frontal area, etc. Thermal management parameters may include vehicle body thermal inertia coefficient, air conditioning energy efficiency ratio, etc. Driving data may include vehicle position information, speed, remaining power, acceleration, steering angle, etc.

[0063] Environmental parameters may include air density, ambient temperature, etc. In some embodiments, environmental parameters may also include object data in the vehicle's current environment, such as the slope angle of the current environment. When the vehicle is in a parking lot, environmental parameters may also include the location information of vents. If there are charging piles in the environment, the location information and power of the charging piles may also be obtained as environmental parameters.

[0064] Next, the method for obtaining some vehicle parameters and environmental parameters in the embodiments of this specification is described.

[0065] Regarding vehicle dynamics parameters, the vehicle may store factory information, and the vehicle dynamics parameters can be obtained by reading the vehicle factory information. Alternatively, the vehicle dynamics parameters can be stored in the cloud, and the vehicle can obtain the vehicle dynamics parameters by sending a data request to the cloud.

[0066] The vehicle's driving parameters can be obtained through various sensors on the vehicle, for example, the vehicle's speed can be collected through the vehicle's speed sensor, the vehicle's acceleration can be collected through the vehicle's acceleration sensor, and the vehicle's location information can be obtained through the Global Positioning System (GPS).

[0067] The vehicle's thermal management parameters can be pre-stored locally on the vehicle and directly read from the local memory. Alternatively, the thermal management parameters can be stored in the cloud, and the vehicle can obtain the thermal management parameters by sending a data request to the cloud.

[0068] Vehicle environmental parameters can be obtained using different methods depending on the type of environmental parameter. For example, slope angles can be obtained from the Building Information Modeling (BIM); parking lot vent locations can be obtained from parking lot ventilation system diagrams; and charging pile power can be obtained through the charging pile communication protocol.

[0069] In the embodiments of this specification, after obtaining the vehicle parameters and environmental parameters, the vehicle parameters and environmental parameters can be directly used as multi-source data, or the vehicle parameters and environmental parameters can be fused and the fused data can be used as multi-source data, which is not limited here.

[0070] It should be noted that the environmental map can be a map of the vehicle's current environment. For example, when the vehicle is currently in a parking lot, the environmental map can be a parking lot map. If the vehicle is currently in a park, the environmental map can be a park map. Of course, the environmental map can also be an offline map downloaded from the cloud that contains route information of the area where the vehicle is currently located, etc. There is no limitation here.

[0071] In step S102, the calling instruction may include an end position. In some embodiments, if the user does not specify an end position, the user's current position may be used as the end position. If the user specifies an end position, the user-specified position may be used as the end position.

[0072] The vehicle's initial position can be its position when the call is received. After determining the initial and final positions, a path planning strategy is used to select at least one candidate path from the environment map. It should be noted that the at least one candidate path can include all navigable paths from the initial position to the final position. The at least one candidate path can also be a path that has been preliminarily screened, for example, by eliminating paths that take too long or have a long travel distance.

[0073] To select the target candidate route with the lowest energy consumption from at least one candidate route, in step S103, the total energy consumption is calculated for each candidate route. In this embodiment, the vehicle's driving energy consumption, air conditioning energy consumption, and regenerated energy are calculated for each candidate route.

[0074] The following describes how to determine the vehicle's driving energy consumption, air conditioning energy consumption, and recovered potential energy.

[0075] 1. Driving energy consumption

[0076] When calculating driving energy consumption, the multi-source data used can be obtained in the following manner: based on a building information model of the vehicle's current environment, extracting the slope angle of the vehicle's current environment from the building information model; obtaining the air density of the vehicle's current environment, wherein the environmental parameters include the slope angle and the air density; and obtaining the vehicle's drag coefficient, vehicle frontal area, vehicle mass, and tire rolling resistance coefficient as vehicle parameters. The vehicle's driving energy consumption can be determined in the following manner: determining the vehicle's driving energy consumption corresponding to each candidate path based on the slope angle, the air density, the drag coefficient, the vehicle frontal area, the vehicle mass, and the tire rolling resistance coefficient.

[0077] It should be noted that, for each candidate path, obtaining the slope angle of the vehicle's current environment may be obtaining the slope angle on the candidate path. In some embodiments, the building information model may be stored in the cloud, and the cloud can match the slope angle of each candidate path by comparing the building information model with the environment map.

[0078] In some embodiments, the driving energy consumption of the vehicle can be calculated using the following formula:

[0079]

[0080] Among them, E drive is the driving energy consumption, ρ is the air density, C d is the drag coefficient, A is the frontal area of the vehicle, m is the vehicle mass, C r is the tire rolling coefficient, g is the acceleration of gravity, θ(t) is the real-time slope angle, and v(t) is the real-time speed.

[0081] 2. Air conditioning energy consumption

[0082] When calculating air conditioning energy consumption, the multi-source data used can be obtained by obtaining the ambient temperature of the vehicle's current environment as the environmental parameter; and obtaining the vehicle's air conditioning set temperature, air conditioning energy efficiency ratio, vehicle thermal inertia coefficient, and preset ventilation power as vehicle parameters. The vehicle's air conditioning energy consumption can be determined by determining the air conditioning energy consumption corresponding to each candidate path based on the ambient temperature, air conditioning set temperature, air conditioning energy efficiency ratio, vehicle thermal inertia coefficient, and preset ventilation power.

[0083] The ambient temperature can be obtained in a variety of ways. In some embodiments, the ambient temperature can be obtained by a temperature sensor installed on the outside of the vehicle. In other embodiments, considering that the temperature inside the vehicle is approximately the same as the temperature outside the vehicle before the vehicle is started, the ambient temperature can be determined as the temperature inside the vehicle when the remote call command is received. Of course, other methods can also be used to determine the ambient temperature, which are not limited here.

[0084] In the embodiment of the present specification, the preset ventilation power may be a pre-set ventilation power of the air conditioner, and the specific value of the preset ventilation power may be set according to actual needs. The air conditioner set temperature may be a set temperature of the vehicle air conditioner.

[0085] In some embodiments, the vehicle's air conditioning energy consumption can be calculated using the following formula:

[0086]

[0087] Among them, E HVAC is the air conditioning energy consumption, k is the thermal inertia coefficient of the vehicle body, ΔT(t) is the temperature difference between the inside and outside of the vehicle, COP is the air conditioning energy efficiency ratio, P base The preset ventilation power.

[0088] In some embodiments, ΔT(t)=T set -T env (x(t),y(t)),T set Set the temperature for the air conditioner, T env (x(t), y(t)) is the ambient temperature. The ambient temperature is related to the ambient coordinates. The ambient temperature may vary depending on the coordinates.

[0089] 3. Recovering Potential Energy

[0090] When calculating the regenerative energy potential, the multi-source data used can be obtained by: extracting the slope angle and vertical height difference of each downhill section in the vehicle's current environment from a building information model (BIM) of the vehicle's current environment as environmental parameters; and obtaining the vehicle's regenerative braking efficiency and vehicle mass as vehicle parameters. The vehicle's regenerative energy potential can be determined by determining the regenerative energy potential for each candidate path based on the slope angle of each downhill section, the vertical height difference of each downhill section, the regenerative braking efficiency, and the vehicle mass.

[0091] Regenerative energy is the conversion or partial conversion of kinetic and potential energy generated by a vehicle during coasting, deceleration, or descent into electrical energy, which is then stored in the battery. Therefore, when calculating regenerative energy, the downhill sections of each candidate route can be identified, along with the slope angle and vertical height difference for each downhill section.

[0092] In some embodiments, the vehicle's recovery potential energy can be calculated using the following formula:

[0093]

[0094] Among them, E regen To recover potential energy, η regen is the regenerative braking efficiency, θ i is the slope angle of the i-th downhill section, Δh i is the vertical height difference of the i-th downhill section, m is the mass of the vehicle, and g is the acceleration due to gravity.

[0095] After obtaining the driving energy consumption, air conditioning energy consumption, and recovery potential energy of the vehicle on each candidate path, the total energy consumption of the vehicle on each candidate path can be calculated. In some embodiments, the total energy consumption E total It can be calculated by the following formula:

[0096] E total =E drive +E HVAC -E regen

[0097] It should be noted that, in the above process of determining the total energy consumption of each candidate path, the corresponding constraint condition may be that the vehicle speed is less than or equal to a preset speed, wherein the preset speed can be set according to actual needs and is not limited here.

[0098] In step S104, after the total energy consumption of each candidate path is obtained, the path with the lowest total energy consumption is selected as the target candidate path, and the vehicle is controlled to travel along the target candidate path.

[0099] In the embodiments of this specification, the target candidate path can serve as the vehicle's initial path. As the vehicle travels along the target candidate path, it is likely that some situations may occur that were not previously predicted or that deviate from the predicted data. For example, a large number of pedestrians may suddenly appear during driving (which was previously unpredictable), or the actual temperature in the ventilation area may deviate from the predicted temperature. Continuing to travel along the target candidate path may result in danger or increased energy consumption, and the vehicle's path may need to be adjusted.

[0100] In some embodiments, when a vehicle is traveling along a target candidate path, if a target environmental state different from the initial environmental state of the target candidate path is detected when the vehicle reaches the target position, at least one local candidate path from the target position to the terminal position is replanned; a target area in each of the at least one local candidate path is determined; for each local candidate path, a single-step energy consumption of the vehicle traveling on the local candidate path and an avoidance function based on the target area on the local candidate path are determined to determine a single-step avoidance cost, and an iterative calculation is performed based on the single-step energy consumption and the single-step avoidance cost to obtain the energy consumption of the local path; the local candidate path with the lowest energy consumption is used as the updated path, and the vehicle is controlled to travel along the updated path.

[0101] It should be noted that the initial environmental state may be an environmental state taken into consideration during the planning of the candidate paths. For example, when planning the candidate paths, the initial environmental state may be that the number of pedestrians on the candidate route does not exceed a preset number, there are no vehicles or other obstacles within a preset range where the charging piles are located, the temperature in the area where the vents are located is a first temperature, etc. When the vehicle travels along the target candidate route, if, upon reaching the target location, the various sensors on the vehicle detect that there is a dense pedestrian area ahead, there is a temporary stop within the preset range where the charging piles are located, or the temperature in the area where the vents are located is actually the second temperature, then this indicates that the actual target environmental state is different from the initial environmental state, and the path from the target location to the end point needs to be replanned.

[0102] In some embodiments, at least one local candidate path from the target location to the end point may be replanned from the environment map, and then each local candidate path may be analyzed to obtain a final driving path.

[0103] When analyzing each local candidate path, it is necessary to consider the impact of special areas, namely target areas, on vehicle energy consumption. The target areas can be areas that have an impact on driving. For example, the target areas can include pedestrian-dense areas, areas with ventilation holes, areas with charging piles, fire passage areas, narrow passage areas, steep slope areas, gentle slope areas, etc.

[0104] For each area in the target area, there is a corresponding avoidance penalty, that is, some areas encourage bypassing the area, while some areas encourage passing through the area. In the embodiment of this specification, since the target area affects the energy consumption of the vehicle, in order to determine the path with the lowest energy consumption, the target area included in each local candidate path can be filtered out. In some embodiments, a target area set can be pre-constructed. For example, the target area set can include the areas listed above, and the target area set is matched with the areas on each local path candidate path to obtain the target area in each local candidate path.

[0105] In the embodiments of this specification, an avoidance cost needs to be calculated for each target area. In some embodiments, for each type of target area, the avoidance cost Cavoid can be determined by the following formula:

[0106] Cavoid=λi·fi

[0107] Among them, λi is the penalty weight coefficient of the i-th type of target area, and fi is the avoidance function of the i-th type of target area.

[0108] In some embodiments, the penalty weight coefficient can be calibrated using historical data sampling. For example, the braking frequency and energy loss of the vehicle in different target areas during a preset number of actual operations (e.g., 1000 times) are counted and fitted. The penalty weight coefficient for each type of target area can be determined using the following formula: λi = average single braking energy loss / baseline energy consumption rate.

[0109] It should be noted that different types of target areas correspond to different avoidance functions. In the embodiments of this specification, when determining the energy consumption of each local path, the single-step avoidance cost and single-step energy consumption of each target area can be determined based on the target area on each local path, and the energy consumption corresponding to each local path can be obtained through iterative calculation.

[0110] To better understand the avoidance costs of different types of target areas, the following describes how to calculate the avoidance costs, taking the target areas of charging piles, ventilation holes, and pedestrian-dense areas as examples.

[0111] 1. Charging pile area

[0112] When the target area is a charging pile area, the single-step avoidance cost of the vehicle can be determined by the following steps: obtaining the power of the charging pile corresponding to the charging pile area; determining the avoidance radius of the charging pile based on the power of the charging pile; and determining the single-step avoidance cost of the vehicle for the charging pile area based on the avoidance radius of the charging pile, the distance between the vehicle and the charging pile, and the avoidance function corresponding to the charging pile area.

[0113] Specifically, when the target area is a charging pile area, the vehicle can obtain the power of the charging pile through the charging pile communication protocol. The avoidance radius of the charging pile can be obtained by the following formula:

[0114]

[0115] Among them, R is the avoidance radius, P charge is the power of the charging pile, 60kw is the average charging power of the charging pile, which can be calibrated according to actual needs and is not limited here.

[0116] After obtaining the avoidance radius, the specific avoidance function value can be calculated using the following avoidance function for the charging pile area:

[0117]

[0118] Where f1 is the avoidance function of the charging pile area, and d1 is the distance between the vehicle and the charging pile.

[0119] Based on the avoidance function and the penalty weight coefficient for the charging station area, the avoidance cost for the charging station area can be calculated. The avoidance function shows that the closer a vehicle is to a charging station, the exponentially higher the avoidance cost, and the more recommended a detour is. In the embodiments of this specification, the single-step avoidance cost of a vehicle can be the avoidance cost corresponding to each preset distance traveled by the vehicle. The preset distance can be set based on actual needs, for example, 3 meters, 5 meters, etc. The single-step avoidance cost corresponding to the vehicle's position in the charging station area can then be further determined.

[0120] 2. Ventilation area

[0121] When the target area is the vent area, the single-step avoidance cost of the vehicle can be determined by the following steps: obtaining the position information of the vent area in the current environment of the vehicle, and obtaining the current temperature difference between the inside and outside of the vehicle; determining the temperature difference of the vent area based on the position information of the vent area, the current position information of the vehicle, the current inside and outside temperature and a preset temperature attenuation model; determining the single-step avoidance cost of the vehicle for the vent area based on the temperature difference of the vent area and the avoidance function corresponding to the vent area.

[0122] Specifically, when a vehicle is located in a parking lot or other environment with ventilation vents, the air conditioning load is reduced when the vehicle approaches the vent, and negative penalties (rewards) are used to encourage routes through this area. For example, if a vehicle is located in a parking lot, the location of the ventilation vent area can be determined using a parking lot ventilation system map, or by comparing the parking lot ventilation system map with an environmental map.

[0123] The current temperature difference between the inside and outside of the vehicle can be calculated by the above ΔT(t)=T set -T env (x(t), y(t)) is obtained, which will not be repeated here. It should be noted that the location of the vents will affect the energy consumption of air conditioning. Based on the influence of the vent location on the energy consumption of air conditioning, the following temperature attenuation model can be established. The temperature difference in the ventilation area can be obtained through the temperature attenuation model:

[0124]

[0125] Where ΔT vent is the temperature difference of the ventilation area, and d2 is the distance between the vehicle and the ventilation area, which can be determined based on the position information of the ventilation area and the current position information of the vehicle.

[0126] After obtaining the temperature difference in the ventilation area, the specific avoidance function value can be calculated through the following avoidance function of the ventilation area:

[0127] f2=-γ·ΔT vent

[0128] Among them, f2 is the avoidance function of the ventilation area, and γ is the temperature energy saving gain coefficient.

[0129] Based on the avoidance function and the penalty weight coefficient of the vent area, the avoidance cost of the vent area can be obtained. Furthermore, the single-step avoidance cost of the vent area can be determined each time the vehicle travels a preset distance.

[0130] 3. Pedestrian-dense areas

[0131] When the target area is a pedestrian-dense area, the vehicle's single-step avoidance cost can be determined by the following steps: determining the number of pedestrians in the pedestrian-dense area and the area of the pedestrian-dense area, determining the vehicle's stay time at the current location, and determining the vehicle's avoidance cost for the pedestrian-dense area based on the number of pedestrians, area, stay time, and avoidance function corresponding to the pedestrian-dense area.

[0132] Specifically, the vehicle's image acquisition device can capture images of the vehicle's surroundings. By processing the captured images, the number of pedestrians and the area of the pedestrian-dense areas can be identified. It should be noted that dense pedestrian areas will cause the vehicle to start and stop frequently, thereby increasing the vehicle's energy consumption.

[0133] In some embodiments, the specific avoidance function value may be calculated using the following pedestrian dense area avoidance function:

[0134]

[0135] Among them, f3 is the avoidance function of the charging pile area.

[0136] Based on the avoidance function and the penalty weight coefficient for dense pedestrian areas, the avoidance cost for dense pedestrian areas can be calculated. The avoidance function shows that higher pedestrian density and longer vehicle dwell times result in higher penalty costs. Furthermore, the single-step avoidance cost for dense pedestrian areas can be determined for each preset distance traveled by the vehicle.

[0137] In the embodiments of this specification, the avoidance cost may be converted into virtual energy consumption, which has the same dimension as the real energy consumption and is used to determine the energy consumption of each local candidate path.

[0138] In some embodiments, when determining the energy consumption of each local candidate path, the vehicle's single-step energy consumption E step The single-step energy consumption of the vehicle can be determined in a similar manner to the total energy consumption, including the driving energy consumption, air conditioning energy consumption, and recovered potential energy per preset distance. In some embodiments, the single-step energy consumption E step The total energy consumption E total get.

[0139] In some embodiments, the energy consumption of each set of local candidate paths may be determined by a dynamic transfer equation, which may be:

[0140]

[0141] Among them, J * (s k ) is the total energy consumption of the kth step, E step (s k ,u k ) represents the single-step energy consumption of step k, C avoid (s k ) represents the avoidance cost of the kth step, J * (s k+1 ) represents the energy consumption of the k+1th step.

[0142] It should be noted that in the above dynamic transfer equation, the iteration starts from the end position to the target position of the vehicle. When the vehicle is at the end position, J * (s end )=0.

[0143] In the above formula, s k is a state variable, which includes the vehicle's position, speed, and remaining power; u k For the control variables, the control variables may include the acceleration and steering angle of the vehicle. For the above dynamic transfer equation, for each state variable, all possible control variables are facilitated and the control action that minimizes the total cost is selected.

[0144] Through the above process, the energy consumption of each local path can be obtained.

[0145] It should be noted that when determining the energy consumption of each local path, the constraints that need to be considered may be:

[0146]

[0147] Among them, soc k+1 is the remaining battery capacity of the vehicle at step k+1, soc k is the remaining battery capacity of the vehicle at step k+1, Q batt is the battery capacity, υ k+1 is the vehicle speed at the k+1th step, υ k is the speed of the vehicle at step k, a k is the acceleration of the vehicle at step k, Δt is the time interval between step k+1 and step k, (x k+1 ,y k+1 ) is the vehicle coordinate at the k+1th step, (x j ,y j ) is the obstacle coordinate, r j is the radius of the obstacle body, and R is the avoidance radius.

[0148] The physical meanings of the above constraints are: (1) the law of change of the vehicle's battery remaining power during driving; (2) the physical law of the change of vehicle speed with acceleration; (3) the safe avoidance radius, which means that the absolute value of the coordinate distance between the vehicle and the obstacle is not less than the sum of the avoidance radius and the radius of the obstacle itself.

[0149] In the embodiments of this specification, when planning global candidate paths, the avoidance radius of charging piles and / or the location of ventilation openings can also be considered. Based on the avoidance radius of charging piles and / or ventilation openings, at least one candidate path between the initial location and the final location is determined from the environmental map. This determines a more accurate candidate path.

[0150] In order to better understand the avoidance cost for each target area in the embodiments of this specification, the avoidance strategies for several scenarios are described below.

[0151] 1. Charging Pile Area Scenario

[0152] In some embodiments, there is a charging pile area on the vehicle's driving path. If the traditional solution is adopted, the vehicle's driving path length is 320m (straight through the charging area), the number of emergency brakes is 2, and the total energy consumption of the vehicle is 8.7kWh. If the avoidance cost for the charging pile area in the embodiment of this specification is used to plan the path, the adjusted path length is 350m (bypassing the charging pile area), the number of emergency brakes is 0, and the total energy consumption is 7.9kWh. It can be seen that by bypassing the charging pile area, the vehicle's energy consumption can be significantly reduced.

[0153] 2. Ventilation Area Scenario

[0154] In some embodiments, there is a vent area on the vehicle's driving path. If a traditional solution is adopted, the air conditioner will be cooled throughout the vehicle's driving process. However, if the avoidance cost for the vent area in the embodiment of this specification is used to determine the air conditioning energy consumption, only 50% of the road section will be cooled, which significantly reduces the vehicle's air conditioning energy consumption.

[0155] 3. Pedestrian-dense Area Scene

[0156] In some embodiments, there are pedestrian-dense areas on the vehicle's travel path. If the traditional solution is used, the average vehicle speed is 5 km / h (the vehicle frequently starts and stops), the driving efficiency is 72%, and the total energy consumption is 0.5 kWh. If the avoidance cost for pedestrian-dense areas in the embodiments of this specification is used to plan the path, the average vehicle speed is 8 km / h (intelligent detour around pedestrian-dense areas), the driving efficiency is 85%, and the total energy consumption is 0.2 kWh. It can be seen that detouring around pedestrian-dense areas can improve driving efficiency and reduce the vehicle's total energy consumption.

[0157] 4. Uphill Scene

[0158] In some embodiments, a vehicle's route involves an uphill slope. Using a traditional approach, the vehicle's travel distance is 30 meters, the uphill slope is 8%, and the vehicle's total energy consumption is 1.5 kWh. If the uphill avoidance cost described in the embodiments of this specification is used to plan the route, the adjusted path length is 50 meters (circumventing the uphill area), the uphill slope is 3%, and the vehicle's total energy consumption is 1 kWh. This indicates that bypassing the uphill area can effectively reduce the vehicle's total energy consumption.

[0159] In order to better understand the vehicle remote summoning method provided in the embodiments of this specification, the path planning process after the vehicle receives the remote summoning command is illustrated below.

[0160] For example, the vehicle is currently located on the B2 floor of the parking lot, and the destination location corresponding to the remote summon command is the exit of the L1 floor of the parking lot. Based on different path generation strategies, the following candidate paths can be generated, with path IDs P01 to P05. The generation strategy, path length, and estimated energy consumption (driving energy consumption + air conditioning energy consumption - recovery energy consumption) of each candidate path are shown in the following table:

[0161] Path ID Generation Strategy Path length Estimated energy consumption (drive + air conditioning - recovery) P01 Shortest Path First 320m 2.2kWh P02 Lowest energy consumption first 350m 1.8kWh P03 Vent temperature control priority 380m 2.0kWh P04 Charging pile direct penetration priority 310m 2.5kWh P05 Balanced Strategy 360m 2.1kWh

[0162] According to the energy consumption of each candidate, the path with the minimum energy consumption, namely P02, is selected as the target candidate path, and the vehicle is controlled to travel along the target candidate path.

[0163] When the vehicle travels 150m on the target candidate path, a crowd suddenly gathers at the elevator entrance in front (the pedestrian density rises to 4.2 people / m 2 ), the vehicle's millimeter-wave radar detects five pedestrians moving laterally within 10 meters. At this point, the target candidate path can be dynamically adjusted. Based on different avoidance strategies, the following local candidate paths can be generated. The path IDs of the local candidate paths are L01 to L03. The avoidance strategy, incremental distance length, and estimated adjusted energy consumption (including avoidance penalties) for each local candidate path are shown in the following table:

[0164] Path ID Avoidance strategy Incremental distance Estimated adjusted energy consumption (including avoidance penalties) L01 Emergency right turn around the freight elevator area +20m 0.5kWh L02 Slow down +5m 0.9kWh L03 Use the opposite lane (no pedestrians) +10m 0.2kWh

[0165] Based on the dynamic programming state transition equation, the energy consumption of each local candidate path is calculated. The energy consumption of L01 is 2.1 kWh, the energy consumption of L02 is 2.4 kWh, and the energy consumption of L03 is 1.9 kWh. L02 can then be used as the adjusted path, and the vehicle can travel along L03.

[0166] As can be seen above, the sudden risk of dense pedestrian traffic was not foreseen at the global stage. After dynamic adjustment, the detour increased the driving distance. Although energy consumption increased slightly compared to the global target candidate path, the actual safety risk was significantly reduced. In the methods described in the embodiments of this specification, global planning focuses on coarse-grained prediction, while local dynamic adjustment achieves refined optimization. The two work together to form a complete energy-saving and safety control system.

[0167] In summary, the solutions of the embodiments of this specification can achieve the following effects: deep coupling of building information and vehicle control is achieved through BIM data; a multi-system energy consumption joint optimization model is established to reduce the collaborative control error of the drive system and the thermal management system; local candidate paths are dynamically planned to improve computing efficiency and meet real-time requirements; and since the driving path with the lowest energy consumption is used as the vehicle's driving path, the vehicle's cruising range can be effectively extended.

[0168] Based on the same inventive concept, the embodiment of this specification also provides a vehicle remote summoning device, such as Figure 2 As shown, the device includes:

[0169] An acquisition module 201 is configured to acquire an environmental map of the vehicle's current environment and multi-source data of the vehicle when the vehicle receives a remote summon command, the multi-source data including vehicle parameters and environmental parameters of the vehicle;

[0170] a path planning module 202 for determining at least one candidate path from the environment map based on the initial position of the vehicle and the end position corresponding to the summon instruction;

[0171] an energy consumption determination module 203 for determining, based on the multi-source data, a total energy consumption of traveling along each of the at least one candidate path, the total energy consumption including driving energy consumption, air conditioning energy consumption, and recovered potential energy of the vehicle;

[0172] The processing module 204 is configured to determine a target candidate path with the lowest total energy consumption and control the vehicle to travel along the target candidate path.

[0173] Regarding the above-mentioned device, the specific implementation method of each step has been described in detail in the embodiment of the vehicle remote summoning method provided in the embodiment of the specification, and will not be elaborated here.

[0174] Based on the same inventive concept, an embodiment of the present invention further provides a vehicle, such as Figure 3 The system includes a memory 304, a processor 302, and a computer program stored in the memory 304 and executable on the processor 302. When the processor 302 executes the program, any one of the embodiments of the vehicle remote summoning method is implemented.

[0175] Among them, Figure 3 In the embodiment of the present invention, a bus architecture (represented by bus 300) is shown. Bus 300 may include any number of interconnected buses and bridges, and bus 300 links together various circuits including one or more processors represented by processor 302 and memory represented by memory 304. Bus 300 may also link together various other circuits such as peripherals, voltage regulators, and power management circuits, which are well known in the art and therefore will not be described further herein. Bus interface 305 provides an interface between bus 300 and receiver 301 and transmitter 303. Receiver 301 and transmitter 303 may be the same component, namely a transceiver, which provides a unit for communicating with various other devices over a transmission medium. Processor 302 is responsible for managing bus 300 and general processing, while memory 304 may be used to store data used by processor 302 when performing operations.

[0176] Based on the same inventive concept, an embodiment of this specification provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the above-mentioned vehicle remote summoning method when executed by a processor.

[0177] Based on the same inventive concept, an embodiment of this specification provides a computer program product, which includes a computer program. When the computer program is executed by a processor, it is used to load and execute the above-mentioned vehicle remote summoning method steps.

[0178] The functions described herein may be implemented in hardware, software executed by a processor, firmware, or any combination thereof. If implemented in software executed by a processor, the functions may be stored as one or more instructions or codes on or transmitted via a computer-readable medium. Other examples and implementations are within the scope and spirit of the present invention and the appended claims. For example, due to the nature of software, the functions described above may be implemented using software executed by a processor, hardware, firmware, hardwiring, or a combination of any of these. Furthermore, the functional units may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit.

[0179] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only exemplary. For example, the division of the units can be a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0180] The units described as separate components may or may not be physically separate, and the components of the control device may or may not be physical units, that is, they may be located in one place or distributed across multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0181] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk, etc. Various media that can store program codes.

[0182] The foregoing description is merely an embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of the claims.

Claims

1. A vehicle remote summoning method, characterized in that: include: If the vehicle receives a remote summon command, obtaining an environmental map of the vehicle's current environment and obtaining multi-source data of the vehicle, the multi-source data including vehicle parameters and environmental parameters of the vehicle; Determining at least one candidate path from the environment map based on the initial position of the vehicle and the end position corresponding to the summon instruction; determining, based on the multi-source data, a total energy consumption of traveling along each candidate route of the at least one candidate route, the total energy consumption including driving energy consumption, air conditioning energy consumption, and recovered potential energy of the vehicle; A target candidate path with the lowest total energy consumption is determined, and the vehicle is controlled to travel along the target candidate path.

2. The method according to claim 1, wherein The acquiring multi-source data of the vehicle includes: Based on a building information model of an environment in which the vehicle is currently located, extracting a slope angle of the environment in which the vehicle is currently located from the building information model; Acquiring the air density of the vehicle's current environment, wherein the environmental parameters include the slope angle and the air density; Obtaining the vehicle speed, drag coefficient, vehicle frontal area, vehicle mass, and tire rolling resistance coefficient of the vehicle as the vehicle parameters; The determining, based on the multi-source data, the total energy consumption of traveling along each candidate path of the at least one candidate path includes: The driving energy consumption corresponding to each candidate path is determined based on the slope angle, the vehicle speed, the air density, the drag coefficient, the vehicle frontal area, the vehicle mass, and the tire rolling resistance coefficient.

3. The method according to claim 1, wherein The acquiring multi-source data of the vehicle includes: Acquiring the ambient temperature of the vehicle's current environment as the environmental parameter; Acquiring the vehicle's air conditioning set temperature, air conditioning energy efficiency ratio, vehicle body thermal inertia coefficient, and preset ventilation power as the vehicle parameters; The determining, based on the multi-source data, the total energy consumption of traveling along each candidate path of the at least one candidate path includes: The air conditioning energy consumption corresponding to each candidate path is determined based on the ambient temperature, the air conditioning set temperature, the air conditioning energy efficiency ratio, the vehicle body thermal inertia coefficient, and the preset ventilation power.

4. The method according to claim 1, wherein The acquiring multi-source data of the vehicle includes: Based on a building information model of the environment currently located by the vehicle, extracting from the building information model the slope angle of each downhill section in the environment currently located by the vehicle and the vertical height difference of each downhill section as the environmental parameters; Obtaining the regenerative braking efficiency of the vehicle and the vehicle mass of the vehicle as the vehicle parameters; The determining, based on the multi-source data, the total energy consumption of traveling along each candidate path of the at least one candidate path includes: The recovery potential energy of each candidate path is determined based on the slope angle of each downhill section, the vertical height difference of each downhill section, the regenerative braking efficiency, and the vehicle mass.

5. The method according to claim 1, wherein After controlling the vehicle to travel along the candidate target path, the method includes: If the vehicle detects a target environment state different from the initial environment state of the target candidate path when traveling to the target location, replanning at least one local candidate path from the target location to the end location; determining a target area in each of the at least one local candidate path; For each local candidate path, determining a single-step energy consumption of the vehicle traveling on the local candidate path and an avoidance function based on a target area on the local candidate path, determining a single-step avoidance cost, and performing an iterative calculation based on the single-step energy consumption and the single-step avoidance cost to obtain an energy consumption for the local path; The local candidate path with the lowest energy consumption is used as the updated path, and the vehicle is controlled to travel along the updated path.

6. The method according to claim 5, wherein The target area includes a charging pile area, and determining a single-step avoidance cost includes: Obtaining the power of the charging pile corresponding to the charging pile area; Determining a avoidance radius of the charging pile based on the power of the charging pile; A single-step avoidance cost of the vehicle for the charging pile area is determined based on the avoidance radius of the charging pile, the distance between the vehicle and the charging pile, and the avoidance function corresponding to the charging pile area.

7. The method according to claim 5, wherein The target area includes a vent area, and determining a single-step avoidance cost includes: Obtaining location information of a vent area in the current environment of the vehicle, and obtaining a current temperature difference between the inside and outside of the vehicle; Determining a temperature difference in the ventilation area based on the location information of the ventilation area, the current location information of the vehicle, the current inside and outside temperatures of the vehicle, and a preset temperature attenuation model; A single-step avoidance cost of the vehicle for the vent area is determined based on the temperature difference in the ventilation area and the avoidance function corresponding to the vent area.

8. A vehicle, characterized in that: The method comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method according to any one of claims 1 to 7 when executing the program.

9. A computer-readable storage medium, characterized in that A computer program is stored thereon, and when the program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the computer program is configured to load and execute the method according to any one of claims 1 to 7.

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