Riding monitoring method, device and system and electric vehicle

Abstract

The invention relates to the technical field of riding safety monitoring, in particular to a riding monitoring method, device and system and an electric vehicle. The method is applied to the electric vehicle and comprises the steps that physical sign information of a user in a riding task is obtained, and the physical sign information at least comprises the body temperature, the heart rate and the breathing frequency; vehicle state information of the target vehicle is obtained, the riding behavior level of the user is determined based on the vehicle state information, and the behavior level represents the intense degree of riding the target vehicle by the user; the vehicle state information at least comprises a vehicle body inclination angle, a driving speed, braking times and a braking speed; the riding risk level of the user is determined based on the physical sign information and the behavior level, an early warning instruction is generated when the riding risk level meets the set requirement, and the early warning instruction is used for conducting risk prompting on the user and / or conducting deceleration on the target vehicle. By the adoption of the scheme, the safety of a user in the riding process can be improved.

Description

Technical Field

[0001] This application relates to the technical field of cycling safety monitoring, and particularly to a cycling monitoring method, device, monitoring system, and electric vehicle. Background Art

[0002] Shared electric vehicles are widely used as a convenient means of transportation and have gradually become the preferred mode for people during short-distance travel; especially during urban commuting, the application of shared electric vehicles is more common.

[0003] During the user's cycling process, due to physical reasons such as illness or emotional fluctuations, the user's ability to control the vehicle and perceive the environment may be reduced, which poses a significant safety hazard.

[0004] Therefore, how to improve the safety of users during cycling is an urgent problem to be solved. Summary of the Invention

[0005] Based on this, in view of the above technical problems, it is necessary to provide a cycling monitoring method, device, monitoring system, and electric vehicle that can improve the safety of users during cycling.

[0006] In a first aspect, this application provides a cycling monitoring method applied to an electric vehicle, and the method includes:

[0007] Obtain the physical sign information of the user during the cycling task, where the physical sign information at least includes body temperature, heart rate, and respiratory rate;

[0008] Obtain the vehicle state information of the target vehicle, and determine the behavior level of the user's cycling based on the vehicle state information, where the behavior level represents the intensity of the user's cycling of the target vehicle; the vehicle state information at least includes body inclination, driving speed, number of brakes, and braking speed;

[0009] Determine the cycling risk level of the user based on the physical sign information and the behavior level, and generate a warning instruction when the cycling risk level meets the set requirements, where the warning instruction is used to give a risk prompt to the user and / or decelerate the target vehicle.

[0010] In one of the embodiments, the determining the cycling risk level of the user based on the physical sign information and the behavior level includes:

[0011] Determine the physical sign status level of the user based on the abnormal item parameters in the physical sign information, where the abnormal item parameters are the parameters that do not conform to the standard interval corresponding to the item parameters;

[0012] Determine the cycling risk level of the user based on the physical sign status level and the behavior level.

[0013] In one embodiment, determining the physical sign status level of the user based on the abnormal item parameters in the physical sign information includes:

[0014] For each abnormal item parameter, determining the abnormal level of the abnormal item parameter based on the parameter value of the abnormal item parameter and the corresponding standard interval;

[0015] Based on the number of abnormal item parameters and the abnormal levels of the abnormal item parameters, determining the physical sign status level of the user.

[0016] In one embodiment, determining the riding risk level of the user based on the physical sign status level and the behavior level includes:

[0017] In the case where the physical sign status level and the behavior level do not conform to the preset relationship, determining the riding risk level as the first risk level;

[0018] In the case where the physical sign status level and the behavior level conform to the preset relationship, if the physical sign status level or the behavior level exceeds their respective defined levels, determining the riding risk level as the second risk level.

[0019] In one embodiment, the method further includes:

[0020] Determining the average behavior level of the user based on the user's historical riding records, and determining the average behavior level as the defined level corresponding to the current behavior level; the historical riding records include the behavior levels corresponding to the user's previous riding tasks;

[0021] Obtaining the current time and the location of the target vehicle, and determining the defined level corresponding to the current behavior level based on the current time and the location.

[0022] In one embodiment, generating a warning instruction when the riding risk level meets the set requirements includes:

[0023] When the riding risk level is the first risk level, generating a first warning instruction; the first warning instruction is used to give a risk prompt to the user and is also used to control the target vehicle to decelerate or end the riding task;

[0024] When the riding risk level is the second risk level, generating a second warning instruction; the second warning instruction is used to give a risk prompt to the user.

[0025] In one embodiment, the method further includes:

[0026] When it is determined that the user is wearing a protective helmet and is seated, a pre-inspection instruction is initiated; the pre-inspection instruction is used to control the corresponding module to perform a pre-inspection of the user's blood alcohol concentration and a pre-inspection of the physical sign information.

[0027] When both the pre-inspection of the blood alcohol concentration and the pre-inspection of the physical sign information are passed, it is determined to execute the riding task.

[0028] In a second aspect, the present application further provides a riding monitoring device, which includes a first information acquisition module, a second information acquisition module, and an early warning module, wherein:

[0029] The first information acquisition module is used to acquire the physical sign information of the user during the riding task, and the physical sign information at least includes body temperature, heart rate, and respiratory rate.

[0030] The second information acquisition module is used to acquire the vehicle state information of the target vehicle, and determine the riding behavior level of the user based on the vehicle state information, where the riding behavior level represents the intensity of the user riding the target vehicle; the vehicle state information at least includes body inclination, driving speed, number of brakes, and braking speed.

[0031] The early warning module is used to determine the riding risk level of the user based on the physical sign information and the riding behavior level, and generate an early warning instruction when the riding risk level meets the set requirements, where the early warning instruction is used to give a risk prompt to the user and / or decelerate the target vehicle.

[0032] In a third aspect, the present application further provides a riding monitoring system, which includes a physical sign detection unit, a vehicle detection unit, an ECU, and an early warning unit, wherein:

[0033] The physical sign detection unit is used to acquire the physical sign information of the user during the riding task, and the physical sign information at least includes body temperature, heart rate, and respiratory rate.

[0034] The vehicle detection unit is used to acquire the vehicle state information of the target vehicle, and determine the riding behavior level of the user based on the vehicle state information, where the riding behavior level represents the intensity of the user riding the target vehicle; the vehicle state information at least includes body inclination, driving speed, number of brakes, and braking speed.

[0035] The ECU is used to execute the riding monitoring method described in any one of the above first aspects.

[0036] The early warning unit responds to the early warning instruction generated by the ECU to give a risk prompt to the user and / or decelerate the target vehicle.

[0037] Fourth aspect, the present application further provides an electric vehicle, which includes a vehicle body, wherein a riding monitoring system as described in the third aspect above is configured in the vehicle body.

[0038] In the above-mentioned riding monitoring method, device, monitoring system and electric vehicle, during a riding task, by obtaining the user's physical sign information and determining the user's riding behavior level through vehicle state data, and then determining the user's riding risk level through the physical sign information and the behavior level; the riding risk level represents the user's physical state and the matching degree between the user's current physical state and the riding behavior in the current riding task, that is, it represents the level of the user's control ability of the target vehicle and the level of the user's environmental perception ability in the current riding task. Furthermore, the determined riding risk level is matched with the set requirements to determine whether to generate a warning instruction; when the riding risk level meets the set requirements, a warning instruction is generated to give a risk prompt to the user and / or decelerate the target vehicle; in this way, on the one hand, it can prompt the user to improve the environmental perception ability, and on the other hand, it can reduce the speed of the target vehicle, which can improve the user's control ability of the target vehicle, thereby enhancing the user's safety in the riding task. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following will briefly introduce the drawings required for use in the description of the embodiments or related technologies. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0040] Figure 1 It is a flowchart of the riding monitoring method in an embodiment;

[0041] Figure 2 It is a flowchart of generating a warning instruction in an embodiment;

[0042] Figure 3 It is a logical diagram of the riding monitoring method in an embodiment;

[0043] Figure 4 It is a structural diagram of the riding monitoring device in an embodiment;

[0044] Figure 5 It is a structural diagram of the riding monitoring system in an embodiment;

[0045] Figure 6 It is a schematic diagram of the setting position of the sensor in the protective helmet in an embodiment. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0046] In order to make the objectives, technical solutions and advantages of this application more clear, the following further elaborates on this application in combination with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not used to limit this application.

[0047] In an exemplary embodiment, a riding monitoring method is provided. This method is applied to any type of two-wheeled or three-wheeled electric vehicle. In the embodiments of this application, the riding monitoring method applied to a two-wheeled shared electric vehicle is taken as an example for illustration. As Figure 1 shown, the riding monitoring method of the embodiments of this application includes the following steps 10 to 30, where:

[0048] Step 10: Obtain the physical sign information of the user during the riding task. The physical sign information includes at least body temperature, heart rate, and respiratory rate.

[0049] For the embodiments of this application, the start of the riding task means that the user unlocks the target vehicle after passing the permission verification. Whether the vehicle is being ridden or not, as long as the user does not lock and change the vehicle, it is called that the target vehicle is in the riding task. The physical sign information includes at least body temperature, heart rate, and respiratory rate; in fact, the physical sign information can also include blood oxygen saturation rate, specifically based on the actual hardware configuration of the target vehicle. Since the start of the riding task, the physical sign information is obtained once every unit measurement period; the duration of the unit period can be 3 minutes or 5 minutes, and the specific duration can be set by oneself. This application does not specifically limit this in the embodiments.

[0050] Furthermore, the acquisition of the physical sign information depends on the hardware basis configured in the target vehicle, and there can be at least two specific acquisition methods.

[0051] The first acquisition method of the physical sign information is: Set a wearable bracelet that can be configured to communicate with the target vehicle. The bracelet can communicate with the ECU (Electronic Control Unit) of the target vehicle in a wired or wireless manner; during the riding task, the user configures the wearable bracelet on the wrist position, and obtains the physical sign information of the user through the wearable bracelet.

[0052] The second acquisition method of the physical sign information is: Set a protective helmet that can be configured to communicate with the target vehicle. The protective helmet can communicate with the ECU of the target vehicle in a wired or wireless manner; during the riding task, the user wears the protective helmet on the head position, and obtains the physical sign information of the user through the protective helmet.

[0053] Further, in order to accurately obtain the user's physical sign information during the riding task, the user directly communicates with the target vehicle through the terminal for permission verification, or the user communicates with the background server of the target vehicle through the terminal for permission verification. After the user's permission verification is passed, it is also necessary to determine that the user is correctly wearing the wearable bracelet and / or the safety helmet before the unlocking instruction for the target vehicle can be executed. Among them, contact sensors can be set at corresponding positions of the wearable bracelet and the safety helmet, and a temperature detection threshold is set. For example, the temperature detection threshold can be set to 35 degrees Celsius. That is, after the user passes the permission verification, only when the user's body temperature is greater than or equal to the temperature detection threshold and the contact sensor is in a triggered state can the target vehicle be unlocked.

[0054] Step 20: Obtain the vehicle state information of the target vehicle, and determine the behavior level of the user's riding based on the vehicle state information. The behavior level characterizes the intensity of the user's riding of the target vehicle; the vehicle state information at least includes the body inclination angle, the driving speed, the number of braking times, and the braking speed.

[0055] For the embodiments of the present application, the vehicle state information of the target vehicle can be obtained by corresponding function sensors arranged on the vehicle body, and these function sensors communicate with the ECU of the target vehicle in a wired manner; in the embodiments of the present application, the types and installation positions of these function sensors are not specifically limited, as long as the vehicle state information can be obtained. Among them, the braking speed refers to the speed at the previous moment when the brake is triggered (that is, the initial speed when braking).

[0056] Further, the behavior level of the user's riding is determined through the obtained vehicle state information and a preset behavior formula. Among them, the vehicle state information is obtained in real-time and updated. The real-time acquisition method here refers to a relatively fast acquisition frequency and a short acquisition interval duration. For example, it can be 150 milliseconds; however, the specific interval duration of the real-time acquisition method is not specifically limited in the embodiments of the present application either.

[0057] Step 30: Determine the riding risk level of the user based on the physical sign information and the behavior level, and generate a warning instruction when the riding risk level meets the set requirements. The warning instruction is used to give a risk prompt to the user and / or decelerate the target vehicle.

[0058] For the embodiments of the present application, during the riding task, the user's physical sign information is obtained once every unit measurement period, and when the user's physical sign information is obtained each time, the riding risk level of the user is determined based on the physical sign information and the behavior level, and the determined riding risk level is matched with the set requirements; and a warning instruction is generated when the riding risk level meets the set requirements, so as to give a risk prompt to the user and / or decelerate the target vehicle.

[0059] In the above cycling monitoring method, during a cycling task, by obtaining the user's physical signs information and determining the user's cycling behavior level through vehicle status data, and then determining the user's cycling risk level based on the physical signs information and the behavior level; the cycling risk level represents the user's physical state and the matching degree between the user's current physical state and the cycling behavior in the current cycling task, that is, it represents the level of the user's control ability over the current target vehicle and the level of the user's environmental perception ability. Furthermore, the determined cycling risk level is matched with the set requirements to determine whether to generate a warning instruction; when the cycling risk level meets the set requirements, a warning instruction is generated to give a risk prompt to the user and / or decelerate the target vehicle; in this way, on the one hand, it can prompt the user to improve the environmental perception ability, and on the other hand, it can reduce the speed of the target vehicle, which can enhance the user's control ability over the target vehicle, thereby improving the safety of the user during the cycling task.

[0060] In an exemplary embodiment, as Figure 2 shown, step 30 may specifically include step 31 and step 32, where:

[0061] Step 31: Determine the user's physical signs status level based on the abnormal item parameters in the physical signs information, where the abnormal item parameters are the parameters that do not conform to the standard interval corresponding to this item of parameters;

[0062] Step 32: Determine the user's cycling risk level based on the physical signs status level and the behavior level.

[0063] In the embodiment of the present application, a corresponding standard interval is set in advance for each item of parameter in the physical signs information. For example, the standard interval corresponding to body temperature is 36.3 degrees Celsius to 37.0 degrees Celsius; the specific range of the standard interval corresponding to each item of parameter is not specifically limited in the embodiment of the present application. When the physical signs information is obtained, each item of parameter in the physical signs information is compared with the corresponding standard interval, and the parameter that does not conform to the standard interval is determined as the abnormal item parameter.

[0064] Furthermore, based on the abnormal item parameters and the number of abnormal item parameters in the physical signs information, the physical signs status level is determined. Specifically, there are at least two ways to determine the physical signs status level; among them, the first way to determine the physical signs status level is: determine the physical signs status level based on the number and type of abnormal item parameters.

[0065] Specifically, in the first way, the evaluation conditions of the physical signs status level can be shown in Table (1); where the larger the physical signs status level (for example, level four > level three > level two > level one), the worse the user's physical state; correspondingly, the worse the user's physical state, the lower the user's environmental perception ability and vehicle control ability.

[0066] Table (1)

[0067]

[0068] The second way to determine the physical sign status level is as follows: for each abnormal item parameter, determine the abnormal level of the abnormal item parameter based on the parameter value of the abnormal item parameter and the corresponding standard interval; based on the number of abnormal item parameters and the abnormal levels of each abnormal item parameter, determine the physical sign status level of the user.

[0069] Specifically, take the median value of the standard interval corresponding to each parameter in the physical sign information as the standard value; for each abnormal item parameter, determine the abnormal amplitude of the parameter value of this abnormal parameter relative to the standard value, and determine the abnormal level based on the abnormal amplitude of the abnormal item parameter. However, it should be noted that a mapping relationship between the abnormal amplitude and the abnormal level needs to be constructed in advance for each parameter, and based on the pre-constructed mapping relationship, determine the abnormal level corresponding to the corresponding abnormal item parameter. Specifically, the mapping relationships corresponding to each parameter are not specifically limited in the embodiments of the present application. Among them, the abnormal level corresponding to each parameter can be divided into level one to level two. Among them, the larger the abnormal level (level two > level one), the greater the abnormal amplitude of the parameter value of this abnormal item parameter.

[0070] Further, in the second way, the evaluation conditions for the physical sign status level can be as shown in Table (2).

[0071] Table (2)

[0072]

[0073] Of course, the evaluation conditions for the physical sign status level disclosed in Table (1) of the first way and Table (2) of the second way are just a realizable way; in fact, as long as other evaluation conditions that can quantify the health degree of the user's physical state through hierarchical division are also within the protection scope of the present application.

[0074] Further, in the embodiments of the present application, the first way can be used to determine the physical sign status level of the user, or the second way can be used to determine the physical sign status level of the user. It is also possible to use a combination of the first way and the second way to determine the physical sign status level of the user.

[0075] In one of the embodiments, for each user, since the start of the cycling task, first determine the physical sign status level of the user through the first way; when the physical sign status level of the user determined through the first way is at least level two, then use the second way to re-determine the physical sign status level of the user, and always use the second way to determine the physical sign status level before the end of the current cycling task.

[0076] The first method for determining the physical sign state level only needs to check the number of abnormal item parameters, and the calculation logic is relatively simple and rapid. However, there is a certain deviation in its accuracy. Therefore, in order to set a certain redundancy, only when the physical sign state level determined by the first method is not less than level two, the second method is used to determine the physical sign state level of the user. The second method for determining the physical sign state level comprehensively considers the abnormal amplitude and quantity of abnormal items, and thus can more accurately represent the health level of the user's body, with high accuracy and reliability.

[0077] Specifically, the method for determining the behavior level specifically includes: normalizing each parameter in the vehicle state information to unify the dimension of each parameter; and then determining the behavior level based on the normalized parameters and the behavior formula. The following first elaborates in detail on each parameter and the process of normalization.

[0078] Body tilt angle Characterizes the maximum tilt angle of the vehicle body from the vertical direction during riding, with the unit of degree (°); the larger the body tilt angle, the more intense the turning (direction change / passing / rocking); for the body tilt angle perform normalization, that is: divide the body tilt angle by the preset safety threshold , where ; the normalized body tilt angle is: .

[0079] Travel speed Characterizes the average speed during riding, with the unit of km / h; the higher the travel speed, the greater the difficulty of controlling the vehicle; for the travel speed perform normalization, that is: divide the travel speed by the speed threshold , and the speed threshold can be the legal speed limit or the vehicle's maximum speed; in the embodiments of the present application, . The normalized travel speed is: .

[0080] Braking times , the total number of brakes in the riding task; the more the braking times, the more it indicates traffic congestion or unstable riding operation; perform normalization on the braking times, that is: divide the braking times by the riding duration , and the normalized result represents the braking frequency.

[0081] Braking speed Is the average value of the initial speed of each brake, with the unit of km / h; the greater the braking speed, the greater the indication of danger; perform normalization on the braking speed, that is: divide the braking speed by the speed threshold , and the speed threshold is the legal speed limit or the vehicle's maximum speed.

[0082] The behavior formula is as follows: .

[0083] Wherein, is the intensity index of cycling, is the inclination weight, is the driving speed weight, is the braking frequency weight, is the braking speed weight. , , , .

[0084] Specifically, based on the intensity index, the behavior level can also be divided into four levels; namely, level one, level two, level three, and level four; wherein, the larger the level of the behavior level, the more intense the driving degree of the user to the target vehicle. The division rules of the behavior level are shown in Table (3) below.

[0085] Table (3)

[0086]

[0087] In one embodiment, after determining the physical sign state level of the user, step 32 may specifically include: matching the physical sign state level and the behavior level with a preset relationship; wherein, in the case that the physical sign state level and the behavior level do not conform to the preset relationship, determining that the cycling risk level is the first risk level; in the case that the physical sign state level and the behavior level conform to the preset relationship, if the physical sign state level or the behavior level exceeds their respective corresponding limit levels, determining that the cycling risk level is the second risk level.

[0088] A one-to-one preset relationship is established between the behavior level and the physical sign state level in advance, wherein: there is a reverse one-to-one correspondence between the physical sign state level and the behavior level; as shown in Table (4) below. That is, level one, level two, level three, and level four of the physical sign state level correspond to level four, level three, level two, and level one of the behavior level in sequence.

[0089] Table (4)

[0090]

[0091] The logic of the preset relationship is as follows: when the user's physical condition is good, the user is allowed to perform relatively intense cycling behaviors; when the user's physical condition is poor, only cycling behaviors with a lower intensity are allowed. Therefore, in the actual preset relationship here, the behavior level corresponding to each physical condition level is the maximum behavior level that can be matched; for example, when the physical condition level is level two and the corresponding behavior level is level three, then when the user's actual behavior level is level one, level two, and level three, it all conforms to the preset relationship; however, if the user's behavior level is level four, it means that it does not conform to the preset relationship.

[0092] Specifically, the physical condition level and the behavior level are matched with the preset relationship; among them, the situation where the physical condition level and the behavior level do not conform to the preset relationship is: the user's actual behavior level is greater than the behavior level corresponding to his actual physical condition level; that is to say, the intensity of the user's current cycling does not match his current physical condition, that is, the user has an excessive cycling behavior; at this time, it is determined that the user's corresponding cycling risk level is the first risk level.

[0093] Specifically, in the case where the physical condition level and the behavior level conform to the preset relationship, if the physical condition level or the behavior level exceeds their respective corresponding limit levels, it is determined that the user's cycling risk is the second risk level; that is to say, although the user's current cycling behavior can match his current physical condition; however, if the user's physical condition level exceeds its corresponding limit level, it means that the user's current physical condition is poor. Therefore, although his cycling level is low, there is still a greater danger; therefore, at this time, it is determined that the user's cycling risk level is the second risk level.

[0094] If the user's cycling behavior level exceeds the limit level, it means that the user's current cycling behavior is too intense; although the user's current cycling behavior conforms to his physical condition, in public road traffic, there are peak traffic periods, or there is a large traffic flow and road congestion in specific sections; and cycling more intensely during these periods and / or sections poses a greater risk. Therefore, even if the user's current behavior level and physical condition level conform to the preset relationship, but as long as his behavior level exceeds the limit level, the user's cycling risk level can be determined to be the second risk level.

[0095] Furthermore, the limit level corresponding to the user's physical condition level can be determined based on the user's gender; for example, for male users, the limit level corresponding to their physical condition level is higher than that of female users. And the limit level corresponding to the user's cycling behavior level is determined in real time.

[0096] The first way to determine the limit level corresponding to the user's behavior level is as follows: Based on the user's historical riding records, determine the user's average behavior level, and determine the average behavior level as the limit level corresponding to the current behavior level; the historical riding records include the behavior levels corresponding to the user's previous riding tasks.

[0097] Specifically, based on the account used by the user for permission verification or the user's personal information, retrieve the user's historical riding records from the background server. The historical riding records record the behavior level curves corresponding to the user's previous riding tasks. Then, based on the behavior level curves corresponding to the user's previous riding tasks, determine the user's average behavior level, and the average behavior level is the limit level corresponding to the behavior level of the user in the current riding task.

[0098] The second way to determine the limit level corresponding to the user's behavior level is as follows: Obtain the current time and the location of the target vehicle, and determine the limit level corresponding to the current behavior level based on the current time and the location.

[0099] Specifically, determine the traffic flow at the current location through the current time, and determine the limit level corresponding to the current behavior level based on the traffic flow. Among them, the limit level is negatively correlated with the traffic flow, that is, the greater the traffic flow, the smaller the limit level (only allowing the user to perform a lower-intensity ride).

[0100] Furthermore, when the riding risk level is the first risk level, generate a first warning instruction; the first warning instruction is used to give a risk prompt to the user and is also used to control the target vehicle to decelerate or end the riding task. When the riding risk level is the second risk level, generate a second warning instruction; the second warning instruction is used to give a risk prompt to the user. The logical schematic diagram of the riding monitoring method provided by the embodiments of the present application is as Figure 3 shown.

[0101] Specifically, the target vehicle can be configured with an audio device capable of playing voice; the audio device can be configured on the vehicle body, or can be configured inside the protective helmet or the wearable bracelet. For the specific setting position of the audio device, it is not specifically limited in the embodiments of the present application.

[0102] Both the first warning instruction and the second warning instruction can call the pre-stored relevant voice data and control the audio device to play the relevant voice data, so as to give corresponding prompts to the user. At the same time, the first warning instruction is also used to control the target vehicle to decelerate, that is, when the user keeps the rotation angle of the handlebar of the target vehicle unchanged, the first warning instruction is used to control the target vehicle to slow down. Specifically, the way to slow down can be: a digital potentiometer is connected in series in the power supply circuit of the drive motor of the target vehicle, and the ECU of the target vehicle generates a sequence of increasing equivalent resistances based on the first warning instruction, and generates multiple control signals for the digital potentiometer based on the sequence of equivalent resistances; the digital potentiometer receives the digital signal, and its corresponding equivalent resistance will change.

[0103] During the process that the ECU generates multiple control signals to adjust the digital potentiometer based on the sequence of equivalent resistances, the equivalent resistance of the digital potentiometer will increase, so that the effective voltage across the drive motor decreases, and thus the speed of the drive motor gradually decreases, thereby realizing the slowdown of the target vehicle. At the same time, in this way, the sensitivity of the target vehicle can be reduced, that is, the change amount of the power of the drive motor caused by the user rotating the handlebar by a unit angle will decrease.

[0104] Furthermore, in order to further improve the safety of the user during the riding task, after the user passes the permission verification and when it is confirmed that the user correctly configures the wearing of the bracelet and / or the safety helmet and is seated, the pre-inspection instruction is started; the pre-inspection instruction is used to control the corresponding module to perform the pre-inspection of the alcohol concentration and the pre-inspection of the physical sign information of the user; when both the pre-inspection of the alcohol concentration and the pre-inspection of the physical sign information pass, it is determined to execute the riding task.

[0105] Specifically, the alcohol concentration generated by the user's breath is measured by an alcohol sensor arranged on the helmet; among them, the alcohol sensor can be an electrochemical sensor or a semiconductor gas sensor; when the user wears the safety helmet, the alcohol sensor can quickly detect the alcohol concentration in the surrounding air and transmit the detection data including the alcohol concentration to the ECU. Among them, the passing of the pre-inspection of the alcohol concentration means that the alcohol concentration does not exceed the dangerous threshold, and the dangerous threshold can be set to a relatively low value. The passing of the pre-inspection of the physical sign information means that the physical sign state level of the user determined by the above first method does not exceed the second level.

[0106] By performing pre-checks on alcohol and physical signs before a cycling task, the physical sign status and blood alcohol concentration of the user can be determined in advance. That is to say, it can be judged whether the user's current physical condition is suitable for cycling. When the user passes the pre-checks on blood alcohol concentration and physical signs, the cycling task is started. Thus, only users with relatively healthy physical conditions are allowed to start cycling, avoiding the participation of users in poor physical or mental states, and therefore improving the safety of users during cycling.

[0107] It should be understood that although the steps in the flowcharts involved in the above embodiments are shown in sequence according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear indication in this article, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be executed alternately or in turn with at least a part of other steps or steps or stages in other steps.

[0108] Based on the same inventive concept, an embodiment of the present application also provides a cycling monitoring device for implementing the above-mentioned cycling monitoring method. The solution provided by this device to solve the problem is similar to the solution described in the above method. Therefore, the specific limitations in one or more embodiments of the cycling monitoring device provided below can refer to the limitations on the cycling monitoring method in the above text, and will not be repeated here.

[0109] In an exemplary embodiment, as Figure 4 shown, a cycling monitoring device 400 is provided, including a first information acquisition module 401, a second information acquisition module 402, and an early warning module 403, where:

[0110] The first information acquisition module 401 is configured to acquire physical sign information of the user during the cycling task, and the physical sign information includes at least body temperature, heart rate, and respiratory rate;

[0111] The second information acquisition module 402 is configured to acquire vehicle status information of the target vehicle and determine the behavior level of the user's cycling based on the vehicle status information. The behavior level represents the intensity of the user's cycling of the target vehicle; the vehicle status information includes at least body tilt angle, driving speed, and number of braking times;

[0112] The warning module 403 is configured to determine the riding risk level of the user based on the physical sign information and the behavior level, and generate a warning instruction when the riding risk level meets the set requirements. The warning instruction is used to prompt the user of the risk and / or decelerate the target vehicle.

[0113] In one embodiment, the warning module 403 is specifically configured to:

[0114] Determine the physical sign status level of the user based on the abnormal item parameters in the physical sign information, where the abnormal item parameter is a parameter that does not conform to the standard interval corresponding to this item parameter;

[0115] Determine the riding risk level of the user based on the physical sign status level and the behavior level.

[0116] In one embodiment, the warning module 403 is specifically configured to:

[0117] For each abnormal item parameter, determine the abnormal level of the abnormal item parameter based on the parameter value of the abnormal item parameter and the corresponding standard interval;

[0118] Determine the physical sign status level of the user based on the number of abnormal item parameters and the abnormal levels of each abnormal item parameter.

[0119] In one embodiment, the warning module 403 is specifically configured to:

[0120] When the physical sign status level and the behavior level do not conform to the preset relationship, determine that the riding risk level is the first risk level;

[0121] When the physical sign status level and the behavior level conform to the preset relationship, if the physical sign status level or the behavior level exceeds their respective corresponding limit levels, determine that the riding risk level is the second risk level.

[0122] In one embodiment, the riding monitoring device 400 further includes a limit level determination module, which is specifically configured to:

[0123] Determine the average behavior level of the user based on the user's historical riding records, and determine the average behavior level as the limit level corresponding to the current behavior level; the historical riding records include the behavior levels corresponding to the user's previous riding tasks;

[0124] Obtain the current time and the location of the target vehicle, and determine the limit level corresponding to the current behavior level based on the current time and the location.

[0125] In one embodiment, the riding monitoring device 400 further includes a warning instruction generation module, which is specifically configured to:

[0126] When the riding risk level is the first risk level, a first warning instruction is generated; the first warning instruction is used to give a risk prompt to the user and also used to control the target vehicle to decelerate or end the riding task;

[0127] When the riding risk level is the second risk level, a second warning instruction is generated; the second warning instruction is used to give a risk prompt to the user.

[0128] In one embodiment, the riding monitoring device 400 further includes a pre-inspection module, which is specifically used for:

[0129] When it is determined that the user is wearing a safety helmet and seated, a pre-inspection instruction is started; the pre-inspection instruction is used to control the corresponding module to perform a pre-inspection of the alcohol concentration and a pre-inspection of the physical sign information of the user;

[0130] When both the pre-inspection of the alcohol concentration and the pre-inspection of the physical sign information pass, it is determined to execute the riding task.

[0131] Each module in the above-mentioned riding monitoring device can be implemented in whole or in part by software, hardware and their combination. The above-mentioned modules can be embedded in the processor in the computer device in the form of hardware or independent of the processor, or stored in the memory in the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above-mentioned modules.

[0132] In an exemplary embodiment, as Figure 5 shown, a riding monitoring system is provided, and the system includes a physical sign detection unit, a vehicle detection unit, an ECU and a warning unit, wherein:

[0133] The physical sign detection unit is used to obtain the physical sign information of the user during the riding task, and the physical sign information at least includes body temperature, heart rate and respiratory rate;

[0134] The vehicle detection unit is used to obtain the vehicle state information of the target vehicle and determine the riding behavior level of the user based on the vehicle state information, and the behavior level represents the intensity of the user riding the target vehicle; the vehicle state information at least includes the body inclination angle, the driving speed and the number of braking times;

[0135] The ECU, as the calculation and processing unit of the target vehicle, is used to execute any one of the riding monitoring methods in the above-mentioned riding monitoring method embodiments.

[0136] The warning unit gives a risk prompt to the user and / or decelerates the target vehicle in response to the warning instruction generated by the ECU.

[0137] For the embodiments of the present application, the physical sign detection unit includes sensors for obtaining various parameters in the physical sign information; the physical sign detection unit can be a wearable bracelet capable of being configured to communicate with the target vehicle, or a protective helmet capable of being configured to communicate with the target vehicle; each sensor can be integrated in the wearable bracelet or the protective helmet; the bracelet can communicate with the ECU of the target vehicle in a wired or wireless manner.

[0138] As Figure 6 shown, it is a schematic diagram of a protective helmet. Among them, the heart rate sensor can be set at the position corresponding to the human temple inside the protective helmet, and relatively accurate heart rate measurement can be carried out through the temporal artery here. The temperature sensor can be set at the position near the ear inside the protective helmet. The respiratory rate sensor is set at a position near the forehead, directly above the nose tip. An alcohol sensor is set on each of the left and right sides, and the average value of the alcohol concentrations actually measured by the two is taken. A respiratory rate sensor is installed on the protective helmet, and using pressure sensing or airflow detection technology, the pressure changes or airflow fluctuations generated when the user breathes are monitored in real time, and then the respiratory rate is calculated. By combining the sensor with the helmet, it is ensured that the user's respiratory information can be accurately obtained without causing an additional burden on the user.

[0139] In another embodiment, the heart rate sensor can be integrated on the handlebar of the target vehicle, and the heart rate sensor adopts optoelectronic sensor technology; when the user holds the handlebar, the heart rate sensor detects the blood flow change in the finger part by emitting and receiving infrared rays, so as to accurately obtain the user's heart rate and pulse data. This design method can continuously and stably collect data when the user is unconscious. Thus, even when the protective helmet or the wearable bracelet fails, the user's heart rate data can still be continuously collected.

[0140] Further, the warning unit includes at least one audio device for playing corresponding audio data in response to any warning instruction generated by the ECU, so as to give corresponding prompts to the user. The warning unit can also include a display screen. On the one hand, the display screen can display the physical sign state information and the riding state of the user; on the other hand, the display screen can also respond to any warning instruction generated by the ECU and give a warning prompt to the user in the form of displaying different colors or flashing lights or characters.

[0141] Further, the warning unit also includes a digital potentiometer. Among them, the digital potentiometer is connected in series in the power supply circuit of the drive motor of the target vehicle. The ECU of the target vehicle generates a sequence of increasing equivalent resistances based on the first warning instruction, and generates a plurality of control signals for the digital potentiometer based on the sequence of equivalent resistances; the digital potentiometer receives the digital signal, and its corresponding equivalent resistance will change.

[0142] During the process of the ECU generating multiple control signals based on the equivalent resistance value to adjust the digital potentiometer, the equivalent resistance value of the digital potentiometer will increase, thereby reducing the effective voltage across the drive motor, and thus gradually reducing the speed of the drive motor, thereby achieving the slowdown and deceleration of the target vehicle. At the same time, in this way, the sensitivity of the target vehicle can be reduced, that is, the change in the power of the drive motor caused by the user rotating the handlebar by a unit angle will be reduced.

[0143] A riding monitoring system provided by an embodiment of the present application is used to implement the riding monitoring method involved above. This system is the corresponding hardware structure for the real-time above-mentioned riding monitoring method. The implementation solutions provided to solve problems are similar to the implementation solutions described in the above method. Therefore, the specific limitations in one or more embodiments of the riding monitoring system provided can refer to the limitations on the riding monitoring method in the above text and will not be elaborated here.

[0144] Those skilled in the art can understand that Figure 5 the structure shown in is only a block diagram of some structures related to the solution of the present application and does not constitute a limitation on the riding monitoring system to which the solution of the present application is applied. The specific riding monitoring system may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0145] In an exemplary embodiment, an electric vehicle is provided. Specifically, the electric vehicle can be a two-wheeled or three-wheeled electric vehicle; the electric vehicle includes a vehicle body, and the above-mentioned riding monitoring system is configured on the vehicle body. Through the riding monitoring system configured on the electric vehicle, the steps of any one of the riding monitoring methods in the above-mentioned riding monitoring method embodiments can be executed.

[0146] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in the present application are all information and data authorized by the user or fully authorized by all parties, and the collection, use, and processing of relevant data need to comply with relevant regulations.

[0147] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memories. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., and are not limited thereto. The processors involved in the embodiments provided in the present application can be general-purpose processors, central processors, graphics processors, digital signal processors, programmable logic devices, data processing logics based on quantum computing, etc., and are not limited thereto.

[0148] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope recorded in this specification.

[0149] The above embodiments only represent several implementation manners of the present application. The description is relatively specific and detailed, but it should not be construed as a limitation on the patent scope of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the appended claims.

Claims

1. A cycling monitoring method, characterized in that, Applied to an electric vehicle, the method includes: Obtaining the physical sign information of the user during a riding task, where the physical sign information at least includes body temperature, heart rate, and respiratory rate; Obtaining the vehicle state information of the target vehicle, and determining the behavior level of the user's riding based on the vehicle state information, where the behavior level characterizes the intensity of the user's riding of the target vehicle; the vehicle state information at least includes body inclination, driving speed, number of braking times, and braking speed; Determining the riding risk level of the user based on the physical sign information and the behavior level, and generating a warning instruction when the riding risk level meets the set requirements, where the warning instruction is used to give a risk prompt to the user and / or decelerate the target vehicle.

2. The method according to claim 1, characterized in that The determining the riding risk level of the user based on the physical sign information and the behavior level includes: Determining the physical sign state level of the user based on the abnormal item parameters in the physical sign information, where the abnormal item parameters are the parameters that do not conform to the standard interval corresponding to this item of parameters; Determining the riding risk level of the user based on the physical sign state level and the behavior level.

3. The method according to claim 2, wherein The determining the physical sign state level of the user based on the abnormal item parameters in the physical sign information includes: For each of the abnormal item parameters, determining the abnormal level of the abnormal item parameter based on the parameter value of the abnormal item parameter and the corresponding standard interval; Determining the physical sign state level of the user based on the number of the abnormal item parameters and the abnormal levels of the respective abnormal item parameters.

4. The method according to claim 2 or 3, characterized in that, The determining the riding risk level of the user based on the physical sign state level and the behavior level includes: In the case where the physical sign state level and the behavior level do not conform to the preset relationship, determining that the riding risk level is the first risk level; In the case where the physical sign state level and the behavior level conform to the preset relationship, if the physical sign state level or the behavior level exceeds their respective defined levels, determining that the riding risk level is the second risk level.

5. The method according to claim 4, wherein The method further includes: Determining the average behavior level of the user based on the user's historical riding records, and determining the average behavior level as the defined level corresponding to the current behavior level; the historical riding records include the behavior levels corresponding to the user's previous riding tasks; Obtaining the current time and the location of the target vehicle, and determining the defined level corresponding to the current behavior level based on the current time and the location.

6. The method according to claim 5, wherein The generating a warning instruction when the riding risk level meets the set requirements includes: When the riding risk level is the first risk level, generating a first warning instruction; the first warning instruction is used to give a risk prompt to the user and is also used to control the target vehicle to decelerate or end the riding task; When the riding risk level is the second risk level, generating a second warning instruction; the second warning instruction is used to give a risk prompt to the user.

7. The method according to claim 1, characterized in that, The method further includes: When it is determined that the user is wearing a protective helmet and is seated, start the pre-check instruction; the pre-check instruction is used to control the corresponding module to perform a pre-check of the user's alcohol concentration and a pre-check of the physical sign information; When both the pre-check of the alcohol concentration and the pre-check of the physical sign information pass, determine to execute the riding task.

8. A cycling monitoring device, characterized in that, The device includes a first information acquisition module, a second information acquisition module, and a warning module, where: The first information acquisition module is used to acquire the physical sign information of the user during the riding task, and the physical sign information at least includes body temperature, heart rate, and respiratory rate; The second information acquisition module is used to acquire the vehicle status information of the target vehicle and determine the riding behavior level of the user based on the vehicle status information, and the riding behavior level represents the intensity of the user riding the target vehicle; the vehicle status information at least includes body inclination, driving speed, number of brakes, and braking speed; The warning module is used to determine the riding risk level of the user based on the physical sign information and the riding behavior level, and generate a warning instruction when the riding risk level meets the set requirements, and the warning instruction is used to give a risk prompt to the user and / or decelerate the target vehicle.

9. A cycling monitoring system, characterized in that, The system includes a physical sign detection unit, a vehicle detection unit, an ECU, and a warning unit, where: The physical sign detection unit is used to acquire the physical sign information of the user during the riding task, and the physical sign information at least includes body temperature, heart rate, and respiratory rate; The vehicle detection unit is used to acquire the vehicle status information of the target vehicle and determine the riding behavior level of the user based on the vehicle status information, and the riding behavior level represents the intensity of the user riding the target vehicle; the vehicle status information at least includes body inclination, driving speed, number of brakes, and braking speed; The ECU is used to determine the riding risk level of the user based on the physical sign information and the riding behavior level, and generate a warning instruction when the riding risk level meets the set requirements; The warning unit responds to the warning instruction to give a risk prompt to the user and / or decelerate the target vehicle.

10. An electric vehicle, characterized in that, The vehicle includes a vehicle body, and a riding monitoring system as described in claim 9 is configured in the vehicle body.

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