Cycling monitoring methods, devices, monitoring systems and electric vehicles

Abstract

This application relates to the technical field of cycling safety monitoring, and in particular to a cycling monitoring method, device, monitoring system, and electric vehicle. The method, applied to an electric vehicle, includes: acquiring a user's vital signs information during a cycling task, including at least body temperature, heart rate, and respiratory rate; acquiring the vehicle status information of the target vehicle, and determining the user's cycling behavior level based on the vehicle status information, the behavior level representing the intensity of the user's cycling of the target vehicle; the vehicle status information including at least the vehicle's lean angle, speed, number of braking attempts, and braking speed; determining the user's cycling risk level based on the vital signs information and behavior level, and generating a warning instruction when the cycling risk level meets set requirements, the warning instruction being used to provide risk warnings to the user and / or to slow down the target vehicle. The solution adopted in this application can improve user safety during cycling.

Description

Technical Field

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

[0002] Shared electric bikes are widely used as a convenient mode of transportation and are gradually becoming the preferred way for people to travel short distances; especially during commutes in urban areas, the application of shared electric bikes is even more common.

[0003] During a ride, users may experience reduced control over the vehicle and decreased awareness of their surroundings due to physical reasons such as illness or emotional fluctuations, which could pose significant safety hazards.

[0004] Therefore, improving user safety during cycling is an urgent problem that needs to be solved. Summary of the Invention

[0005] Therefore, it is necessary to provide a cycling monitoring method, device, monitoring system, and electric vehicle that can improve user safety during cycling, addressing the aforementioned technical issues.

[0006] In a first aspect, this application provides a riding monitoring method applied to electric vehicles, the method comprising:

[0007] Obtain the user's vital signs information during the cycling mission, including at least body temperature, heart rate, and respiratory rate;

[0008] The system acquires the vehicle status information of the target vehicle and determines the user's riding behavior level based on the vehicle status information. The behavior level represents the intensity of the user's riding of the target vehicle. The vehicle status information includes at least the vehicle body tilt angle, driving speed, number of braking actions, and braking speed.

[0009] The user's cycling risk level is determined based on the vital signs information and the behavior level, and a warning instruction is generated when the cycling risk level meets the set requirements. The warning instruction is used to provide risk warnings to the user and / or to slow down the target vehicle.

[0010] In one embodiment, determining the user's cycling risk level based on the vital signs information and the behavior level includes:

[0011] The user's vital sign status level is determined based on the abnormal item parameters in the vital sign information, wherein the abnormal item parameters are parameters that do not conform to the standard range corresponding to the item parameter;

[0012] The user's cycling risk level is determined based on the physical condition level and the behavior level.

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

[0014] For each of the aforementioned anomaly parameters, the anomaly level of the anomaly parameter is determined based on the parameter value of the anomaly parameter and the corresponding standard range;

[0015] The user's vital sign status level is determined based on the number of the abnormal item parameters and the abnormality level of each of the abnormal item parameters.

[0016] In one embodiment, determining the user's cycling risk level based on the vital sign status level and the behavior level includes:

[0017] If the vital sign status level and the behavior level do not conform to a preset relationship, the cycling risk level is determined to be the first risk level;

[0018] If the physical condition level and the behavior level conform to the preset relationship, and if the physical condition level or the behavior level exceeds its corresponding limit level, then the cycling risk level is determined to be the second risk level.

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

[0020] The user's average behavior level is determined based on the user's historical cycling records, and the average behavior level is set as the limit level corresponding to the current behavior level; the historical cycling records include the behavior levels corresponding to the user's previous cycling tasks.

[0021] Obtain the current time and the location of the target vehicle, and determine the limiting 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 cycling risk level meets the set requirements includes:

[0023] When the cycling risk level is the first risk level, a first warning instruction is generated; the first warning instruction is used to provide a risk warning to the user, and also to control the target vehicle to slow down or end the cycling task.

[0024] When the cycling risk level is the second risk level, a second warning instruction is generated; the second warning instruction is used to provide risk alerts to the user.

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

[0026] Once it is confirmed that the user is wearing a protective helmet and seated, a pre-screening command is initiated; the pre-screening command is used to control the corresponding module to perform pre-screening of the user's alcohol concentration and vital signs.

[0027] If both the pre-detection of alcohol concentration and the pre-detection of vital signs are passed, the cycling task will be carried out.

[0028] Secondly, this application also provides a cycling monitoring device, the device comprising 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 user's vital signs information during the cycling task, and the vital signs information includes at least body temperature, heart rate and respiratory rate;

[0030] The second information acquisition module is used to acquire the vehicle status information of the target vehicle and determine the user's riding behavior level based on the vehicle status information. The behavior level represents the intensity of the user's riding of the target vehicle. The vehicle status information includes at least the vehicle body tilt angle, driving speed, number of braking times, and braking speed.

[0031] The early warning module is used to determine the user's cycling risk level based on the vital signs information and the behavior level, and generate an early warning instruction when the cycling risk level meets the set requirements. The early warning instruction is used to provide risk warnings to the user and / or to slow down the target vehicle.

[0032] Thirdly, this application also provides a cycling monitoring system, which includes a vital sign detection unit, a vehicle detection unit, an ECU, and an early warning unit, wherein:

[0033] The vital signs detection unit is used to acquire the user's vital signs information during the cycling task, and the vital signs information includes at least body temperature, heart rate and respiratory rate.

[0034] The vehicle detection unit is used to acquire the vehicle status information of the target vehicle and determine the user's riding behavior level based on the vehicle status information. The behavior level represents the intensity of the user's riding of the target vehicle. The vehicle status information includes at least the vehicle body tilt angle, driving speed, number of braking actions, and braking speed.

[0035] The ECU is used to perform the cycling monitoring method as described in any one of the first aspects above;

[0036] The warning unit, in response to the warning command generated by the ECU, provides risk warnings to the user and / or slows down the target vehicle.

[0037] Fourthly, this application also provides an electric vehicle, the electric vehicle including a vehicle body, wherein the vehicle body is equipped with a riding monitoring system as described in the third aspect above.

[0038] The aforementioned cycling monitoring method, device, monitoring system, and electric vehicle, during a cycling task, acquire the user's vital signs information and determine the user's cycling behavior level through vehicle status data. Then, the user's cycling risk level is determined based on the vital signs information and behavior level. The cycling risk level characterizes the user's physical condition and the degree of matching between the user's current physical condition and cycling behavior during the current cycling task; that is, it characterizes the user's level of control over the target vehicle and their level of environmental awareness. The determined cycling risk level is then matched with 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 alert the user and / or slow down the target vehicle. This, on the one hand, prompts the user to improve their environmental awareness, and on the other hand, reduces the speed of the target vehicle, enhancing the user's control over the target vehicle and thus improving the user's safety during the cycling task. Attached Figure Description

[0039] To more clearly illustrate the technical solutions in the embodiments or related technologies of this application, the accompanying drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0040] Figure 1 This is a flowchart illustrating a cycling monitoring method in one embodiment;

[0041] Figure 2 This is a flowchart illustrating the process of generating an early warning command in one embodiment;

[0042] Figure 3 This is a logical diagram of a cycling monitoring method in one embodiment;

[0043] Figure 4 This is a schematic diagram of the cycling monitoring device in one embodiment;

[0044] Figure 5 This is a schematic diagram of the cycling monitoring system in one embodiment;

[0045] Figure 6 This is a schematic diagram showing the location of the sensors in a protective helmet in one embodiment. Detailed Implementation

[0046] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0047] In one exemplary embodiment, a riding monitoring method is provided, applicable to any type of two-wheeled or three-wheeled electric vehicle. In this embodiment, the riding monitoring method is illustrated using a two-wheeled shared electric vehicle as an example. Figure 1 As shown, the cycling monitoring method of this application embodiment includes the following steps 10-30, wherein:

[0048] Step 10: Obtain the user's vital signs information during the cycling mission. The vital signs information includes at least body temperature, heart rate, and respiratory rate.

[0049] In this embodiment, the start of a cycling task signifies that the user has unlocked the target vehicle after authorization verification. Regardless of whether the vehicle is currently being ridden, as long as the user does not lock and switch vehicles, the target vehicle is considered to be in a cycling task. Vital signs information includes at least body temperature, heart rate, and respiratory rate; in fact, it may also include blood oxygen saturation, depending on the actual hardware configuration of the target vehicle. Vital signs information is acquired at intervals from the start of the cycling task; the duration of each interval can be 3 minutes or 5 minutes, and the specific duration can be set by the user; this embodiment does not impose a specific limitation on this.

[0050] Furthermore, the acquisition of vital signs information depends on the hardware infrastructure of the target vehicle, and there can be at least two specific acquisition methods.

[0051] The first method for obtaining vital signs information is to set up a wearable wristband that can communicate with the target vehicle. The wristband can communicate with the ECU (Electronic Control Unit) of the target vehicle via wired or wireless means. During the riding task, the user sets up the wearable wristband on the wrist and obtains the user's vital signs information through the wearable wristband.

[0052] The second method for obtaining vital signs information is to set up a protective helmet that can communicate with the target vehicle. The protective helmet can communicate with the ECU of the target vehicle via wired or wireless means. The user wears the protective helmet on his head during the riding mission, and the user's vital signs information is obtained through the protective helmet.

[0053] Furthermore, to accurately obtain the user's vital signs during the cycling mission, the user communicates directly with the target vehicle via their terminal for authorization verification, or the user communicates with the target vehicle's backend server via their terminal for authorization verification. After successful authorization verification, it is also necessary to ensure that the user is correctly wearing the wearable wristband and / or protective helmet before executing the unlocking command for the target vehicle. Contact sensors can be installed at corresponding locations on the wearable wristband and protective helmet, with a temperature detection threshold set, for example, 35 degrees Celsius. That is, after authorization verification, the target vehicle can only be unlocked if the user's body temperature is greater than or equal to the temperature detection threshold and the contact sensor is triggered.

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

[0055] In this embodiment, the vehicle status information of the target vehicle can be obtained through corresponding functional sensors installed on the vehicle body. These functional sensors communicate with the ECU of the target vehicle via wired connections. This embodiment does not specifically limit the type or location of these functional sensors, as long as they can acquire vehicle status information. Braking speed refers to the speed at the moment before braking is triggered (i.e., the initial speed at the time of braking).

[0056] Furthermore, the user's riding behavior level is determined by acquiring vehicle status information and a preset behavior formula. The vehicle status information is acquired and updated in real time. "Real-time acquisition" here refers to a high acquisition frequency and short acquisition interval, for example, 150 milliseconds. However, this embodiment does not specify a particular interval for the real-time acquisition method.

[0057] Step 30: Determine the user's cycling risk level based on vital signs and behavioral levels, and generate a warning instruction when the cycling risk level meets the set requirements. The warning instruction is used to provide risk warnings to the user and / or slow down the target vehicle.

[0058] In this embodiment of the application, during the cycling task, the user's vital signs information is acquired once every unit measurement cycle. Each time the user's vital signs information is acquired, the user's cycling risk level is determined based on the vital signs information and behavior level, and the determined cycling risk level is matched with the set requirements. When the cycling risk level meets the set requirements, a warning instruction is generated to provide risk warnings to the user and / or to slow down the target vehicle.

[0059] In the aforementioned cycling monitoring method, during a cycling task, the user's vital signs information is acquired, and the user's cycling behavior level is determined through vehicle status data. Then, the user's cycling risk level is determined based on the vital signs information and behavior level. The cycling risk level represents the user's physical condition and the degree of match between the user's current physical condition and cycling behavior during the current cycling task. In other words, it represents the user's level of control over the target vehicle and their level of environmental awareness. The determined cycling risk level is then matched with 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 alert the user to the risk and / or to slow down the target vehicle. This approach, on the one hand, prompts the user to improve their environmental awareness, and on the other hand, reduces the speed of the target vehicle, enhancing the user's control over the target vehicle and thus improving the user's safety during the cycling task.

[0060] In one exemplary embodiment, such as Figure 2 As shown, step 30 may specifically include steps 31 and 32, wherein:

[0061] Step 31: Determine the user's vital sign status level based on the abnormal item parameters in the vital sign information, where the abnormal item parameters are those that do not conform to the standard range corresponding to the parameter.

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

[0063] In this embodiment, a standard range is pre-defined for each parameter in the vital signs information. For example, the standard range for body temperature is 36.3 degrees Celsius to 37.0 degrees Celsius. This embodiment does not specifically limit the range of the individual standard ranges for each parameter. When vital signs information is obtained, each parameter in the vital signs information is compared with its corresponding standard range, and parameters that do not conform to the standard range are identified as abnormal parameters.

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

[0065] Specifically, in the first method, the assessment criteria for the physical condition level can be as shown in Table (1); where, the higher the physical condition level (for example, level four > level three > level two > level one), the worse the user's physical condition is; correspondingly, the worse the user's physical condition is, the lower the user's ability to perceive the environment and control the vehicle.

[0066] Table (1)

[0067]

[0068] The second method for determining the level of vital signs is as follows: for each abnormal parameter, the abnormality level of the abnormal parameter is determined based on the parameter value and the corresponding standard range; based on the number of abnormal parameters and the abnormality level of each abnormal parameter, the user's level of vital signs is determined.

[0069] Specifically, the median value of the standard interval corresponding to each parameter in the vital signs information is used as the standard value. For each abnormal parameter, the abnormal magnitude of the parameter value relative to the standard value is determined, and the abnormality level is determined based on the abnormal magnitude of the abnormal parameter. However, it should be noted that a mapping relationship between abnormal magnitude and abnormality level needs to be pre-constructed for each parameter, and the abnormality level corresponding to the corresponding abnormal parameter is determined based on the pre-constructed mapping relationship. Specifically, the mapping relationship corresponding to each parameter is not specifically limited in this embodiment. The abnormality level corresponding to each parameter can be divided into two levels, where the larger the abnormality level (level two > level one), the greater the abnormal magnitude of the parameter value.

[0070] Furthermore, in the second approach, the assessment criteria for the level of physical condition can be shown in Table (2).

[0071] Table (2)

[0072]

[0073] Of course, the assessment criteria for the physical condition level disclosed in Table (1) of the first method and Table (2) of the second method are only one possible method; in fact, any other assessment criteria that can quantify the user's physical health status through hierarchical division are also within the scope of protection of this application.

[0074] Furthermore, in the embodiments of this application, the user's vital sign status level can be determined using the first method or the second method. Alternatively, a combination of the first and second methods can be used to determine the user's vital sign status level.

[0075] In one embodiment, for each user, starting from the start of the cycling task, the user's vital signs level is first determined using the first method; if the user's vital signs level is determined to be at least level two using the first method, the user's vital signs level is re-determined using the second method, and the second method is always used to determine the user's vital signs level until the current cycling task ends.

[0076] The first method for determining the vital sign status level only requires checking the number of abnormal parameters, and its calculation logic is relatively simple and fast, but its accuracy has a certain degree of deviation. Therefore, to introduce some redundancy, the second method is only used to determine the user's vital sign status level when the vital sign status level determined by the first method is not lower than level two. The second method for determining the vital sign status level comprehensively considers the abnormality magnitude and number of abnormal items, thus more accurately representing the user's physical health status and possessing higher accuracy and reliability.

[0077] Specifically, the method for determining the behavior level includes: normalizing the various parameters in the vehicle status information to ensure uniformity of their dimensions; and then determining the behavior level based on the normalized parameters and the behavior formula. The following section will first elaborate on the various parameters and the normalization process.

[0078] Body camber The lean angle represents the maximum angle of lean of the vehicle relative to the vertical direction during riding, measured in degrees (°). A larger lean angle indicates more aggressive cornering (changing direction / overtaking / swaying). Normalization is performed, that is: the vehicle body camber angle is normalized. Divide by the preset safety threshold ,in The normalized vehicle body camber angle is: .

[0079] driving speed The average speed during cycling is represented in km / h; the higher the speed, the more difficult it is to control the bike; regarding speed... Normalization is performed, that is, the driving speed is divided by the speed threshold. The speed threshold can be the legal speed limit or the vehicle's maximum speed; in this embodiment of the application, The normalized driving speed is: .

[0080] Number of braking times The total number of braking actions during the cycling task; a higher number of braking actions indicates more congested road conditions or unstable cycling operation; the number of braking actions is normalized by dividing the number of braking actions by the cycling time. The normalized result represents the braking frequency.

[0081] Braking speed The average initial speed for each braking action is expressed in km / h; a higher braking speed indicates a greater level of danger; the braking speed is normalized by dividing it by a speed threshold. The speed threshold is the legal speed limit or the vehicle's maximum speed.

[0082] The behavioral formula is: .

[0083] in, The intensity level of the ride. As the tilt angle weight, Weighted by driving speed, As a weight for the number of braking operations, The braking speed is the weight. , , , .

[0084] Specifically, based on the intensity index, the behavior level can also be divided into four levels: Level 1, Level 2, Level 3, and Level 4. The higher the level of the behavior level, the more intense the user's driving of the target vehicle. The rules for classifying the behavior levels are shown in Table (3) below.

[0085] Table (3)

[0086]

[0087] In one embodiment, after determining the user's vital signs status level, step 32 may specifically include: matching the vital signs status level and behavior level with a preset relationship; wherein, if the vital signs status level and behavior level do not conform to the preset relationship, the cycling risk level is determined to be a first risk level; if the vital signs status level and behavior level conform to the preset relationship, and if the vital signs status level or behavior level exceeds its corresponding limit level, the cycling risk level is determined to be a second risk level.

[0088] A one-to-one correspondence is established between the behavioral level and the physical condition level in advance, wherein the reverse positions of the physical condition level and the behavioral level are in one-to-one correspondence; as shown in Table (4) below. That is, the first, second, third and fourth levels of the physical condition level correspond to the fourth, third, second and first levels of the behavioral level in turn.

[0089] Table (4)

[0090]

[0091] The logic of the preset relationship is as follows: when a user's physical condition is good, they are allowed to engage in more vigorous cycling activities; when a user's physical condition is poor, only low-intensity cycling activities are allowed. Therefore, in the actual preset relationship, the behavior level corresponding to each physical condition level is its maximum matchable behavior level; for example, when the physical condition level is level two, the corresponding behavior level is level three, so the preset relationship is satisfied when the user's actual behavior level is level one, two, or three; however, if the user's behavior level is level four, it indicates that the preset relationship is not satisfied.

[0092] Specifically, the vital signs status level and behavior level are matched with a preset relationship; where the vital signs status level and behavior level do not match the preset relationship, the situation is that the user's actual behavior level is greater than the behavior level corresponding to his / her actual vital signs status level; that is, the intensity of the user's current cycling does not match his / her current physical state, that is, the user is engaging in excessive cycling behavior; in this case, the user's corresponding cycling risk level is determined to be the first risk level.

[0093] Specifically, if the physical condition level and behavior level conform to a preset relationship, and the physical condition level or behavior level exceeds its corresponding limit level, then the user's cycling risk is determined to be the second risk level. That is to say, although the user's current cycling behavior matches the current physical condition, if the user's physical condition level exceeds its corresponding limit level, it indicates that the user's current physical condition is poor. Therefore, although the cycling level is low, there is still a significant danger. Thus, the user's cycling risk level is determined to be the second risk level.

[0094] If a user's cycling behavior level exceeds the specified limit, it indicates that the user's current cycling behavior is too strenuous. Although the user's current cycling behavior is in line with their physical condition, there are peak traffic periods or situations with heavy traffic and congestion on specific road sections. Cycling at these times and / or on these road sections carries a significant risk. Therefore, even if the user's current behavior level and physical condition level meet the preset relationship, if the behavior level exceeds the specified limit, the user's cycling risk level can be determined as the second risk level.

[0095] Furthermore, the restriction level corresponding to a user's physical condition status can be determined based on the user's gender; for example, the restriction level corresponding to a male user's physical condition status is higher than that corresponding to a female user. The restriction level corresponding to a user's cycling behavior level, however, is determined in real time.

[0096] The first method to determine the limit level corresponding to a user's behavior level is to determine the user's average behavior level based on the user's historical cycling records, and then set the average behavior level as the limit level corresponding to the current behavior level; the historical cycling records include the behavior levels corresponding to each of the user's previous cycling tasks.

[0097] Specifically, based on the user's account used for permission verification or the user's personal information, the system retrieves the user's historical riding records from the backend server. The historical riding records contain 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, the system determines the user's average behavior level, which is the limit level corresponding to the user's behavior level in the current riding task.

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

[0099] Specifically, the traffic flow at the current location is determined by the current time, and the restriction level corresponding to the current behavior level is determined based on the traffic flow. The restriction level is negatively correlated with the traffic flow, that is, the greater the traffic flow, the smaller the restriction level (only allowing users to ride at a lower intensity).

[0100] Furthermore, when the cycling risk level is the first risk level, a first warning instruction is generated; the first warning instruction is used to alert the user of the risk and also to control the target vehicle to slow down or end the cycling task; when the cycling risk level is the second risk level, a second warning instruction is generated; the second warning instruction is used to alert the user of the risk. A logical schematic diagram of the cycling monitoring method provided in this application embodiment is shown below. Figure 3 As shown.

[0101] Specifically, the target vehicle may be equipped with an audio device capable of playing voice; the audio device may be installed on the vehicle body or inside a protective helmet or wearable wristband; the specific location of the audio device is not specifically limited in this embodiment.

[0102] Both the first and second warning commands can call up pre-stored relevant voice data and control the audio device to play the relevant voice data, thereby providing corresponding prompts to the user. Simultaneously, the first warning command is also used to control the target vehicle to decelerate; that is, while the user maintains a constant throttle angle on the target vehicle, the first warning command controls the target vehicle to gradually decelerate. Specifically, the gradual deceleration can be achieved by connecting a digital potentiometer in series in the power supply circuit of the target vehicle's drive motor. The target vehicle's ECU generates an incremental sequence of equivalent resistance values ​​based on the first warning command, and generates multiple control signals to the digital potentiometer based on this sequence of equivalent resistance values. The digital potentiometer receives the digital signals, and its corresponding equivalent resistance value changes accordingly.

[0103] During the adjustment of the digital potentiometer by the ECU generating multiple control signals based on the sequence of equivalent resistance values, the equivalent resistance of the digital potentiometer increases, thereby reducing the effective voltage across the drive motor and gradually decreasing the speed of the drive motor, thus achieving gradual deceleration of the target vehicle. Simultaneously, this method reduces the sensitivity of the target vehicle, meaning the change in drive motor power caused by a unit angle of throttle rotation is reduced.

[0104] Furthermore, to enhance user safety during cycling missions, a pre-check command is initiated after the user has passed authorization verification and is confirmed to be correctly configured to wear the wristband and / or protective helmet, and is seated. The pre-check command controls the corresponding module to perform pre-checks on the user's alcohol concentration and vital signs. If both the alcohol concentration and vital signs pre-checks are passed, the cycling mission is confirmed to proceed.

[0105] Specifically, an alcohol sensor located on the helmet measures the concentration of alcohol produced by the user's breath. This alcohol sensor can be an electrochemical sensor or a semiconductor gas sensor. When the user wears the protective helmet, the alcohol sensor quickly detects the alcohol concentration in the surrounding air and transmits the detection data, including the alcohol concentration, to the ECU. Passing the alcohol concentration pre-detection means that the alcohol concentration does not exceed a danger threshold, which can be set to a low value. Passing the vital signs pre-detection means that the user's vital signs level, as determined by the first method described above, does not exceed level two.

[0106] By conducting pre-tests for alcohol and vital signs before a cycling trip, the user's physical condition and alcohol concentration can be determined in advance. This means that it is possible to judge whether the user's current physical condition is suitable for cycling. The cycling trip can only begin if the user passes the pre-tests for alcohol concentration and vital signs. This ensures that only users in relatively good physical condition are allowed to start cycling, avoiding the participation of users in poor physical or mental condition, thus improving the safety of users during cycling.

[0107] It should be understood that although the steps in the flowcharts of the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily completed 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 performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0108] Based on the same inventive concept, this application also provides a cycling monitoring device for implementing the cycling monitoring method described above. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations in one or more cycling monitoring device embodiments provided below can be found in the limitations of the cycling monitoring method described above, and will not be repeated here.

[0109] In one exemplary embodiment, such as Figure 4 As 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, wherein:

[0110] The first information acquisition module 401 is used to acquire the user's vital signs information during the cycling task. The vital signs information includes at least body temperature, heart rate and respiratory rate.

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

[0112] The early warning module 403 is used to determine the user's cycling risk level based on vital signs and behavioral levels, and to generate an early warning command when the cycling risk level meets the set requirements. The early warning command is used to provide risk warnings to the user and / or to slow down the target vehicle.

[0113] In one embodiment, the early warning module 403 is specifically used for:

[0114] The user's vital sign status level is determined based on the abnormal parameters in the vital sign information, where abnormal parameters are those that do not conform to the standard range corresponding to the parameter.

[0115] The user's cycling risk level is determined based on their physical condition level and behavior level.

[0116] In one embodiment, the early warning module 403 is specifically used for:

[0117] For each anomaly parameter, the anomaly level of the anomaly parameter is determined based on the parameter value and the corresponding standard range.

[0118] The user's vital sign status level is determined based on the number of abnormal parameters and the abnormality level of each abnormal parameter.

[0119] In one embodiment, the early warning module 403 is specifically used for:

[0120] If the physical condition level and behavior level do not conform to the preset relationship, the cycling risk level is determined to be the first risk level;

[0121] If the physical condition level and behavior level meet the preset relationship, and the physical condition level or behavior level exceeds the corresponding limit level, then the cycling risk level is determined to be the second risk level.

[0122] In one embodiment, the cycling monitoring device 400 further includes a limit level determination module, specifically used for:

[0123] The user's average behavior level is determined based on the user's historical cycling records, and the average behavior level is set as the limit level corresponding to the current behavior level; the historical cycling records include the behavior levels corresponding to the user's previous cycling tasks.

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

[0125] In one embodiment, the cycling monitoring device 400 further includes a warning command generation module, specifically used for:

[0126] When the riding risk level is the highest, a first warning instruction is generated. The first warning instruction is used to alert the user of the risk and also to control the target vehicle to slow down or end the riding task.

[0127] When the cycling risk level is the second risk level, a second warning instruction is generated; the second warning instruction is used to alert the user of the risk.

[0128] In one embodiment, the cycling monitoring device 400 further includes a pre-detection module, specifically used for:

[0129] Once it is confirmed that the user is wearing a protective helmet and seated, a pre-screening command is initiated; the pre-screening command is used to control the corresponding modules to perform pre-screening of the user's alcohol concentration and vital signs.

[0130] If both the alcohol concentration pre-test and the vital signs pre-test are passed, the cycling mission will proceed.

[0131] The various modules in the aforementioned cycling monitoring device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of a computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0132] In one exemplary embodiment, such as Figure 5 As shown, a cycling monitoring system is provided, which includes a vital sign detection unit, a vehicle detection unit, an ECU, and a warning unit, wherein:

[0133] The vital signs detection unit is used to acquire the user's vital signs information during the cycling mission. The vital signs information includes at least body temperature, heart rate, and respiratory rate.

[0134] The vehicle detection unit is used to acquire the vehicle status information of the target vehicle and determine the user's riding behavior level based on the vehicle status information. The behavior level represents the intensity of the user's riding of the target vehicle. The vehicle status information includes at least the vehicle body tilt angle, driving speed, and number of braking times.

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

[0136] The warning unit responds to warning commands generated by the ECU to provide risk alerts to the user and / or slow down the target vehicle.

[0137] In this embodiment of the application, the vital signs detection unit includes sensors for acquiring various parameters in the vital signs information; the vital signs detection unit can be a wearable wristband that can be configured to communicate with the target vehicle, or a protective helmet that can be configured to communicate with the target vehicle; each sensor can be integrated into the wearable wristband or the protective helmet; the wristband can communicate with the ECU of the target vehicle via wired or wireless means.

[0138] like Figure 6 The diagram shows a protective helmet. The heart rate sensor can be positioned inside the helmet corresponding to the temple, allowing for accurate heart rate measurement via the temporal artery. The temperature sensor can be positioned inside the helmet near the ears. The respiratory rate sensor is positioned near the forehead, directly above the nose. Alcohol sensors are located on both sides; the measured alcohol concentration is the average of the two sensors. By installing respiratory rate sensors on the helmet, pressure sensing or airflow detection technology is used to monitor pressure changes or airflow fluctuations during the user's breathing, thereby calculating the respiratory rate. Integrating the sensors with the helmet ensures accurate acquisition of the user's breathing information without placing any additional burden on the user.

[0139] In another embodiment, the heart rate sensor can be integrated into the handlebars of the target vehicle. The heart rate sensor employs photoelectric sensor technology; when the user grips the handlebars, the heart rate sensor detects changes in blood flow at the fingertips by emitting and receiving infrared light, thereby accurately acquiring the user's heart rate and pulse data. This design allows for continuous and stable data collection without the user's conscious awareness. Therefore, it can continue to collect the user's heart rate data even if the protective helmet or wearable wristband fails.

[0140] Furthermore, the warning unit includes at least one audio device for playing corresponding audio data in response to any warning command generated by the ECU, thereby providing appropriate prompts to the user. The warning unit may also include a display screen, which can display the user's vital signs and riding status; additionally, the display screen can respond to any warning command generated by the ECU and provide warning prompts to the user by displaying different colors, flashing lights, or text.

[0141] Furthermore, the warning unit also includes a digital potentiometer, wherein 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 an incremental sequence of equivalent resistance values ​​based on the first warning command, and generates multiple control signals to the digital potentiometer based on the sequence of equivalent resistance values. The digital potentiometer receives digital signals, and its corresponding equivalent resistance value will change.

[0142] During the adjustment of the digital potentiometer by the ECU generating multiple control signals based on the sequence of equivalent resistance values, the equivalent resistance of the digital potentiometer increases, thereby reducing the effective voltage across the drive motor and gradually decreasing the speed of the drive motor, thus achieving gradual deceleration of the target vehicle. Simultaneously, this method reduces the sensitivity of the target vehicle, meaning the change in drive motor power caused by a unit angle of throttle rotation is reduced.

[0143] This application provides a cycling monitoring system for implementing the cycling monitoring method described above. This system is based on the hardware structure corresponding to the cycling monitoring method described above, and the solution provided is similar to the implementation scheme described in the above method. Therefore, the specific limitations of the one or more cycling monitoring system embodiments provided can be found in the limitations of the cycling monitoring method described above, and will not be repeated here.

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

[0145] In one 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 a riding monitoring system as described above is configured on the vehicle body. The riding monitoring system configured on the electric vehicle can perform the steps of any of the riding monitoring methods described in the above riding monitoring method embodiments.

[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 used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0147] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. 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), magnetic 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 take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0148] The technical features of the above embodiments can be combined in any way. For the sake of brevity, 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, they should be considered to be within the scope of this specification.

[0149] The above embodiments are merely illustrative of several implementation methods of this application, and their descriptions are relatively specific and detailed. However, they should not be construed as limiting the scope of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A cycling monitoring method, characterized in that, Applied to electric vehicles, the method includes: Obtain the user's vital signs information during the cycling mission, including at least body temperature, heart rate, and respiratory rate; The system acquires the vehicle status information of the target vehicle and determines the user's riding behavior level based on the vehicle status information. The behavior level represents the intensity of the user's riding of the target vehicle. The vehicle status information includes at least the vehicle body tilt angle, driving speed, number of braking actions, and braking speed. The user's vital sign status level is determined based on the abnormal item parameters in the vital sign information, wherein the abnormal item parameters are parameters that do not conform to the standard range corresponding to the item parameter; If the physical condition level and the behavior level do not conform to a preset relationship, the cycling risk level is determined to be the first risk level; If the physical condition level and the behavior level meet the preset relationship, and if the physical condition level or the behavior level exceeds the corresponding limit level, then the cycling risk level is determined to be the second risk level. When the riding risk level meets the set requirements, a warning instruction is generated. The warning instruction is used to alert the user of the risk and / or slow down the target vehicle.

2. The method according to claim 1, characterized in that, Determining the user's vital sign status level based on the abnormal item parameters in the vital sign information includes: For each of the aforementioned anomaly parameters, the anomaly level of the anomaly parameter is determined based on the parameter value of the anomaly parameter and the corresponding standard range; The user's vital sign status level is determined based on the number of the abnormal item parameters and the abnormality level of each of the abnormal item parameters.

3. The method according to claim 1, characterized in that, The method further includes: The user's average behavior level is determined based on the user's historical cycling records, and the average behavior level is set as the limit level corresponding to the current behavior level; the historical cycling records include the behavior levels corresponding to the user's previous cycling tasks. Obtain the current time and the location of the target vehicle, and determine the limiting level corresponding to the current behavior level based on the current time and the location.

4. The method according to claim 3, characterized in that, The generation of a warning instruction when the cycling risk level meets the set requirements includes: When the cycling risk level is the first risk level, a first warning instruction is generated; the first warning instruction is used to provide a risk warning to the user, and also to control the target vehicle to slow down or end the cycling task. When the cycling risk level is the second risk level, a second warning instruction is generated; the second warning instruction is used to provide risk alerts to the user.

5. The method according to claim 1, characterized in that, The method further includes: Once it is confirmed that the user is wearing a protective helmet and seated, a pre-screening command is initiated; the pre-screening command is used to control the corresponding module to perform pre-screening of the user's alcohol concentration and vital signs. If both the pre-detection of alcohol concentration and the pre-detection of vital signs are passed, the cycling task will be carried out.

6. A cycling monitoring device, characterized in that, The device includes a first information acquisition module, a second information acquisition module, and an early warning module, wherein: The first information acquisition module is used to acquire the user's vital signs information during the cycling task, and the vital signs information includes at least 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 user's riding behavior level based on the vehicle status information. The behavior level represents the intensity of the user's riding of the target vehicle. The vehicle status information includes at least the vehicle body tilt angle, driving speed, number of braking times, and braking speed. The early warning module is used to determine the user's vital sign status level based on the abnormal item parameters in the vital sign information, wherein the abnormal item parameters are parameters that do not conform to the standard range corresponding to the parameter. If the physical condition level and the behavior level do not conform to a preset relationship, the cycling risk level is determined to be the first risk level; If the physical condition level and the behavior level meet the preset relationship, and if the physical condition level or the behavior level exceeds the corresponding limit level, then the cycling risk level is determined to be the second risk level. When the riding risk level meets the set requirements, a warning instruction is generated. The warning instruction is used to alert the user of the risk and / or slow down the target vehicle.

7. The apparatus according to claim 6, characterized in that, The early warning module is specifically used for: For each anomaly parameter, the anomaly level of the anomaly parameter is determined based on the parameter value and the corresponding standard range. The user's vital sign status level is determined based on the number of abnormal parameters and the abnormality level of each abnormal parameter.

8. The apparatus according to claim 6, characterized in that, The device further includes a limitation level determination module, which is specifically used for: The user's average behavior level is determined based on the user's historical cycling records, and the average behavior level is set as the limit level corresponding to the current behavior level; the historical cycling records include the behavior levels corresponding to the user's previous cycling tasks. Obtain the current time and the location of the target vehicle, and determine the restriction level corresponding to the current behavior level based on the current time and location.

9. A cycling monitoring system, characterized in that, The system includes a vital signs detection unit, a vehicle detection unit, an ECU, and a warning unit, wherein: The vital signs detection unit is used to acquire the user's vital signs information during the cycling task, and the vital signs information includes at least 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 user's riding behavior level based on the vehicle status information. The behavior level represents the intensity of the user's riding of the target vehicle. The vehicle status information includes at least the vehicle body tilt angle, driving speed, number of braking actions, and braking speed. The ECU is used to determine the user's vital sign status level based on abnormal parameters in the vital sign information, wherein the abnormal parameter is a parameter that does not conform to the standard range corresponding to the parameter; if the vital sign status level and the behavior level do not conform to a preset relationship, the cycling risk level is determined to be a first risk level; if the vital sign status level and the behavior level conform to the preset relationship, and if the vital sign status level or the behavior level exceeds its respective limit level, the cycling risk level is determined to be a second risk level; and a warning command is generated when the cycling risk level meets the set requirements. The warning unit responds to the warning command by providing risk alerts to the user and / or slowing down the target vehicle.

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

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