A cycling data full-dimension recording and visualization control method and system

Abstract

This invention relates to a method and system for comprehensive recording and visualization control of cycling data, belonging to the field of data processing technology. It includes: acquiring cycling information in response to a cycling data viewing signal; extracting vehicle information and cycling area from the cycling information; searching for corresponding lap time information in a lap time database based on the vehicle information; extracting optimal cycling information and assist adjustment information from the lap time information based on the cycling area; extracting steering assist data from the vehicle information; adjusting the steering assist data according to the assist adjustment information to obtain an adjusted assist value; integrating the optimal cycling information to form an optimal cycling projection and outputting it; acquiring and recording the current cycling data upon receiving a cycling end signal; comparing the current cycling data with the lap time information to obtain the optimal cycling data and updating the lap time information. This invention improves the practical guiding value and application reference of cycling data.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a method and system for full-dimensional recording and visualization control of cycling data. Background Technology

[0002] In the fields of cycling, cycling training, and cycling event management, the accurate recording, comprehensive aggregation, and intuitive presentation of cycling data are key to improving the cycling experience, optimizing training results, and achieving refined management of venues and cycling conditions.

[0003] Currently, various devices and systems for recording and visualizing cycling data have emerged in the industry. Their core is to automatically collect and summarize basic data such as speed, distance, and heart rate during cycling by integrating hardware devices such as GPS positioning modules, motion sensors, and physiological acquisition modules. Combined with terminal interface display modules, the collected cycling data is visualized in the form of trajectory maps, data reports, and graphs.

[0004] Regarding the aforementioned technologies, most of the generated cycling data graphs are only used for comparing and displaying high-speed and low-speed segments between current and historical data. They cannot provide users with targeted cycling improvement suggestions and operational guidance, resulting in room for improvement in the actual guiding value and application reference of cycling data. Summary of the Invention

[0005] To enhance the practical guiding value and application reference of cycling data, this invention provides a method and system for full-dimensional recording and visualization control of cycling data.

[0006] Firstly, the present invention provides a method for full-dimensional recording and visual control of cycling data, employing the following technical solution:

[0007] A method for comprehensive recording and visualization control of cycling data, including:

[0008] Step 1: Respond to the preset cycling data viewing signal to obtain cycling information;

[0009] Step 2: Extract vehicle information and cycling area from the cycling data;

[0010] Step 3: Search for the corresponding lap time information in the preset lap time database based on the vehicle information;

[0011] Step 4: Extract the optimal riding information and assist adjustment information from the cycling lap time information based on the cycling area;

[0012] Step 5: Extract steering assist data from the vehicle information;

[0013] Step 6: Adjust the steering assist data according to the assist adjustment information to obtain the adjusted assist value;

[0014] Step 7: Integrate the best riding information to form the best riding projection and output it;

[0015] Step 8: When the preset end-of-ride signal is received, acquire and record the data for this ride;

[0016] Step 9: Compare the data from this ride with the lap time information to obtain the optimal riding data and update the lap time information.

[0017] By adopting the above technical solution, vehicle information and riding area are obtained through riding information, then the corresponding riding lap time information is found, then the steering assist is adjusted and the riding projection is generated, and finally the data is recorded and compared with historical data. This allows riders to clearly know the areas that need improvement, outputs the best riding information in real time, and improves the practical guidance value and application reference of riding data.

[0018] Optionally, methods for searching for corresponding cycling lap times in a preset lap time database based on vehicle information include:

[0019] Step 30: Separate the vehicle information into original information and modification information;

[0020] Step 31: Search for the corresponding original riding information in the lap database based on the original information;

[0021] Step 32: If the modification information is not available, define the original riding information as riding lap time information and output it;

[0022] Step 33: If the modification information exists, calculate the optimization information using the modification information and the preset optimization algorithm;

[0023] Step 34: Adjust the original riding information based on the optimization information to obtain modified riding information and define it as the riding lap time information output.

[0024] By adopting the above technical solution, vehicle information is broken down into original information and modified information for separate processing. This allows for accurate matching of the basic riding data of the corresponding vehicle model. Furthermore, by combining modification parameters and using optimized algorithms to adaptively adjust the riding information, the obtained lap time information becomes more consistent with the actual state of the vehicle, improving data matching accuracy and the accuracy of subsequent riding guidance and assist control.

[0025] Optionally, it also includes a method for optimizing cycling lap time information, which includes:

[0026] Step 35: Analyze cycling environment data using original cycling information;

[0027] Step 36: Collect actual environmental data;

[0028] Step 37: Compare the cycling environment data with the actual environment data to obtain the difference in environmental parameters;

[0029] Step 38: Combine the environmental parameter differences with the preset environmental impact algorithm to calculate environmental adjustment data;

[0030] Step 39: Update the cycling lap time information according to the environmental adjustment data to obtain the actual cycling information and output it.

[0031] By adopting the above technical solution, historical cycling environment data is compared with actual environment data, and the adjustment amount is calculated using environmental impact algorithms. This allows for real-time environmental correction of cycling lap time information, making the output actual cycling information more consistent with the current real cycling environment and improving the reliability and applicability of cycling guidance and parameter control.

[0032] Optionally, after optimal cycling projection output, the following are also included:

[0033] Step 70: Analyze the optimal cycling posture for the cycling projection to obtain the pedal area;

[0034] Step 71: Extract the actual pedal area from the cycling information;

[0035] Step 72: If the actual pedal area does not fall into the riding pedal area, adjust the pedal corresponding to the actual pedal area to fall into the riding pedal area.

[0036] Step 73: If the actual pedal area falls into the riding pedal area, do not control the pedal corresponding to the actual pedal area to make adjustments.

[0037] By adopting the above technical solution, the pedal area can be analyzed and compared in real time through optimal cycling projection. When the actual pedal position deviates from the target area, the pedal adjustment can be automatically controlled to keep the rider in the optimal cycling posture and center of gravity distribution, thereby improving cycling stability and control safety.

[0038] Optionally, if the actual pedal area does not fall into the cycling pedal area, the methods to adjust the pedal corresponding to the actual pedal area to fall into the cycling pedal area include:

[0039] Step 720: Obtain the pedal weight;

[0040] Step 721: Obtain the cyclist's weight using cycling information;

[0041] Step 722: Calculate the standing pedal weight by combining the rider's weight with the preset weight distribution algorithm;

[0042] Step 723: If the pedal weight reaches the standing pedal weight, do not adjust the actual pedal area;

[0043] Step 724: If the pedal weight does not reach the standing pedal weight, adjust the pedal corresponding to the actual pedal area to fall into the riding pedal area.

[0044] By adopting the above technical solution, before controlling the pedal adjustment, the standing pedal weight is calculated by combining the pedal weight, rider weight, and weight distribution algorithm. This allows for a precise judgment of the pedal adjustment conditions, avoiding unnecessary adjustments when the rider is standing and the pedals need to bear the corresponding weight. This ensures that the riding posture always conforms to the optimal standard, improving the riding experience and the rationality of control.

[0045] Optionally, if the pedal weight does not reach the standing pedal weight, methods to adjust the pedal corresponding to the actual pedal area to fall into the cycling pedal area include:

[0046] Step 7240: Calculate pedal travel time by comparing the actual pedal area with the pedal area used for cycling;

[0047] Step 7241: Calculate the adjustable time using the cycling area and the optimal cycling projection;

[0048] Step 7242: When the pedal movement time is less than the adjustable time, control the pedal corresponding to the actual pedal area to adjust so that it falls into the riding pedal area;

[0049] Step 7243: When the pedal movement time is greater than the adjustable time, extract the riding posture from the best riding projection and adjust it in combination with the preset key posture rules to obtain the key posture.

[0050] Step 7244: Update the focus posture to the optimal riding projection to obtain the focus riding projection and output it.

[0051] By adopting the above technical solution, the pedal movement time and the adjustable riding time are first calculated and compared. When the time conditions are met, the pedals are directly adjusted to match the optimal riding posture. When the adjustment time is not met, the optimal riding projection is optimized in terms of posture and the output is updated, thereby improving the rationality and feasibility of riding guidance.

[0052] Optionally, methods for comparing the current cycling data with cycling lap time information to obtain optimal cycling data and updating the cycling lap time information include:

[0053] Step 90: Calculate the range of data for the same level based on the data from this ride and the preset same-level judgment rules;

[0054] Step 91: Count the number of data points at the same level based on the range of data at the same level;

[0055] Step 92: If the number of data at the same level reaches the preset effective number, compare the current cycling data with the cycling lap time information to obtain the optimal cycling data and update the cycling lap time information;

[0056] Step 93: If the number of data at the same level does not reach the valid number, define the data of this ride as a private data record.

[0057] By adopting the above technical solution, cycling data at the same level are screened and statistically analyzed according to the same level judgment rules. When the amount of data reaches an effective threshold, the optimal data comparison and lap time database are updated. If the threshold is not met, the data is only saved as private data, which improves the accuracy, representativeness, reliability and practicality of cycling lap time information and data updates.

[0058] Optionally, a method for filtering cycling lap time information may also be included, which includes:

[0059] Step 94: Extract road information and direction of travel from the cycling data;

[0060] Step 95: If the road information is the track information, obtain the extreme riding information based on the road information and the direction of travel;

[0061] Step 96: If the road information is highway information, filter the cycling lap time information according to the direction of travel to obtain standard cycling information;

[0062] Step 97: Update the cycling lap time information based on standard cycling information to obtain safe cycling information.

[0063] By adopting the above technical solution, cycling lap time information is differentiated and processed according to cycling road information and driving direction. Extreme cycling information is generated in track scenarios, and safe cycling information is filtered and updated in road scenarios. This enables the system to adapt to different cycling road environments, taking into account both track performance limits and road safety regulations, thereby improving the pertinence and safety of cycling data guidance.

[0064] Optionally, it also includes optimization methods to help adjust information, which include:

[0065] Step 40: Collect actual cycling data;

[0066] Step 41: Compare the actual cycling data with the optimal cycling information to obtain the cycling data difference;

[0067] Step 42: Calculate the cycling assist difference based on the difference in cycling data and the preset assist adjustment algorithm;

[0068] Step 43: Adjust the assist adjustment information according to the riding assist difference to obtain the actual assist information and output it.

[0069] By adopting the above technical solution, the assist parameters are calculated and corrected in real time based on the difference between actual riding data and optimal riding information, combined with the assist adjustment algorithm, and the actual assist information adapted to the current riding state is output. This enables dynamic optimization and precise adjustment of assist control, improving the smoothness and safety of riding control.

[0070] Secondly, this invention provides a comprehensive recording and visualization control system for cycling data, employing the following technical solution:

[0071] A comprehensive cycling data recording and visualization control system includes:

[0072] The acquisition module is used to acquire cycling information, actual environmental data, pedal weight, and actual cycling data.

[0073] The memory is used to store the program for the full-dimensional recording and visualization control method of cycling data as described above;

[0074] The processor loads and executes programs from memory.

[0075] By adopting the above technical solution, the acquisition module collects various cycling-related data in real time. Combined with the memory to store the control program and the processor to execute calculations and control logic, it is possible to fully realize the functions of recording cycling data in all dimensions, visual projection, and intelligent assistance adjustment. The system has a simple structure and stable operation, which can efficiently support the implementation of the entire cycling data processing and control method, thereby improving the system's practicality and reliability.

[0076] In summary, the present invention has at least one of the following beneficial technical effects:

[0077] 1. Obtain vehicle information and cycling area through cycling information, then find the corresponding cycling lap time information, then adjust the steering assist and generate cycling projection, and finally record the data and compare it with historical data to achieve real-time output of the best cycling data, while improving the practical guidance value and application reference of cycling data;

[0078] 2. By adjusting the pedals, users can more easily and safely execute the operation process when performing the best riding operation, which improves the reliability and security of riding data;

[0079] 3. By distinguishing between racetracks and highways, the system can more accurately output the corresponding optimal route, avoiding the problem of blindly outputting the optimal route and causing potential safety hazards, thus improving the reliability and safety of the optimal cycling data output. Attached Figure Description

[0080] Figure 1 This is a flowchart of a method for full-dimensional recording and visualization control of cycling data in an embodiment of this application. Detailed Implementation

[0081] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments.

[0082] This invention discloses a method for comprehensive recording and visualization control of cycling data. (Refer to...) Figure 1 A method for comprehensive recording and visualization control of cycling data includes:

[0083] Step 1: Respond to the preset cycling data viewing signal to obtain cycling information.

[0084] The cycling data viewing signal refers to a control signal triggered by the user during or before cycling, activated by operating the terminal device, to request the system to display cycling data and cycling guidance information. The response to this cycling data viewing signal can be either a data viewing button on the terminal device that the user presses or clicks, or a voice recognition module that identifies the user's voice prompt.

[0085] Cycling information refers to a comprehensive data set that includes user-inputted vehicle information, model information, planned cycling route information, and real-time data collected by the system, such as current cycling status, riding parameters, posture data, and location information. This cycling information is acquired by receiving pre-configured information through a user input interface and by collecting dynamic data in real-time during the cycling process through onboard sensors, positioning modules, and data acquisition units.

[0086] Step 2: Extract vehicle information and cycling area from the cycling information.

[0087] Vehicle information refers to a set of data that includes original vehicle parameters, modified parts, vehicle type, handling configuration, and steering assist parameters, used to differentiate the riding characteristics of different vehicles. The vehicle information is extracted by the system from the riding information through field matching, data parsing, or tag recognition to filter out data items related to the vehicle's own attributes. The riding area refers to the geographical range, road type, track segment, and location information of the user's current or upcoming riding activity. The riding area is extracted by the system from the riding information's location data, road information, or user input information through location parsing, road segment matching, or area identifier recognition.

[0088] Step 3: Search for the corresponding cycling lap time information in the preset lap time database based on the vehicle information.

[0089] Cycling lap time information refers to a collection of historical data, including lap times, riding trajectories, handling parameters, steering assist data, and riding posture, generated during multiple rides and lap times using the same or similar vehicles within the same riding area. The system retrieves lap time information by using vehicle information as a search criterion and matching keywords such as vehicle model, modification status, and riding area in the lap time database. The database stores a mapping relationship between cycling lap time information and vehicle information; the system automatically categorizes and stores valid cycling lap time information according to vehicle information.

[0090] Step 4: Extract the best riding information and assist adjustment information from the cycling lap time information based on the cycling area.

[0091] Optimal riding information refers to the riding trajectory, riding posture, speed distribution, and control parameter data that are selected from riding lap time information within the same riding area, exhibiting the best lap times, stable handling, and meeting safety standards, and possessing reference value. The optimal riding information is extracted by the system from the riding lap time information based on the riding area, using lap time sorting, stability scoring, and safety threshold filtering to extract the optimal data set. The stability scoring criteria and safety thresholds were obtained by professionals in the field through multiple experiments and then input into the system. Assist adjustment information refers to the set of control parameters and adjustment rules that match the optimal riding information and guide the adaptation and adjustment of vehicle steering assist parameters. The assist adjustment information is extracted by the system retrieving corresponding steering assist adjustment data from the riding lap time information based on the riding area and the optimal riding information.

[0092] Step 5: Extract the steering assist data from the vehicle information.

[0093] Steering assist data refers to parameter data reflecting the steering assist status of a vehicle's steering system, such as the current assist strength, assist characteristics, assist response speed, and assist output curve. The steering assist data is extracted by the system from vehicle information through data parsing, parameter reading, or field matching to obtain the corresponding assist parameters of the vehicle's steering system.

[0094] Step 6: Adjust the steering assist data according to the assist adjustment information to obtain the adjusted assist value.

[0095] Adjusting the steering assist value refers to adapting and correcting the vehicle's original steering assist data based on the assist adjustment information to obtain optimized steering assist parameters that are more suitable for the current riding area and the optimal riding posture. The adjusted assist value is obtained by the system comparing the steering assist data with the assist adjustment information item by item, and then directly adjusting the steering assist data to the target parameters corresponding to the assist adjustment information.

[0096] Step 7: Integrate the best riding information to form the best riding projection and output it.

[0097] Optimal cycling projection refers to the best cycling guidance image displayed in real-time on the cycling interface after visually integrating data such as cycling trajectory, cycling posture, control parameters, and speed distribution from the optimal cycling information. The optimal cycling projection is generated by the system performing data fusion, visualization rendering, and interface layout processing on the optimal cycling information to produce an intuitively displayable guidance screen. The optimal cycling projection is output by the system displaying the generated optimal cycling guidance image to the user in real-time through in-vehicle display terminals, mobile terminal screens, or AR projection devices.

[0098] Step 8: When the preset end-of-ride signal is received, acquire and record the data for this ride.

[0099] The end-of-ride signal is a command signal automatically generated by the system after the user completes the ride, triggered by terminal operation, or after the vehicle is turned off, parking time expires, or the location determines that the ride has ended. It is used to notify the system to stop data collection for the ride. The end-of-ride signal can be received by the system through manual button presses or voice commands by the user, or by determining the stop of the ride through vehicle status detection and location data.

[0100] This cycling data refers to the entire set of actual cycling data collected in real time by the system from the start to the end of the ride, including cycling trajectory, cycling posture, lap time, steering assist data, pedal force data, and control parameters. The method for acquiring and recording this cycling data is as follows: after receiving the end-of-ride signal, the system summarizes, organizes, and stores all the cycling data collected and cached in real time during the ride.

[0101] When a ride ends, the signal indicates that the ride has ended. In order to provide more reliable and effective riding suggestions and to allow users to view changes in their riding data later, the data for this ride is acquired and recorded.

[0102] Step 9: Compare the data from this ride with the lap time information to obtain the optimal riding data and update the lap time information.

[0103] Optimal riding data refers to the riding data selected by comparing the current riding data with existing riding lap time information, resulting in faster lap times, more stable handling, higher safety, and greater reference value. The optimal riding data is obtained by the system comparing the current riding data with existing riding lap time information, retaining the data set with the best performance to obtain the optimal riding data, and simultaneously recording the optimal riding data into the riding lap time information set, thus updating the riding lap time information.

[0104] The methods for searching for corresponding cycling lap times in a pre-set lap time database based on vehicle information include:

[0105] Step 30: Separate the vehicle information into original information and modification information.

[0106] Original equipment (Original) information refers to the original vehicle data that comes with the vehicle at the factory, including its original configuration, structural parameters, performance indicators, handling parameters, and steering assist parameters, without any modifications. The method for extracting Original information is as follows: each vehicle has corresponding original factory parameters and configurations. These are retrieved by professionals in the field through the internet and entered into the system. When the system receives vehicle information, it automatically compares all data with the original factory parameters and configurations, integrating consistent data to form Original information. Modification information refers to data related to modifications made to the vehicle after it leaves the factory, such as added or replaced parts, adjusted parameters, altered performance, and handling characteristics, which differ from the original factory configuration. The method for extracting Modification information is as follows: the system compares vehicle information with the original factory parameters and configurations, defining parameters, parts, and configuration information that are inconsistent with the original factory data as Modification information.

[0107] Step 31: Search for the corresponding original riding information in the lap database based on the original information.

[0108] Original riding information refers to historical riding data such as lap times, riding trajectory, handling parameters, and steering assist data generated within the same riding area when the vehicle has not been modified and uses the original factory configuration. The method for finding original riding information is that the system uses original information as the search criteria and retrieves the corresponding data from the lap time database through vehicle model matching and original factory parameter comparison. The lap time database stores the mapping relationship between original information and original riding information. This database is created by the system by separately categorizing and storing riding data generated by unmodified, original factory vehicles. When the system receives original information, it automatically retrieves and matches the corresponding original riding information.

[0109] Step 32: If the modification information is not available, define the original riding information as riding lap time information and output it.

[0110] The lap time information here is output by the system using the original cycling data as the lap time information, so that the best cycling information and assist adjustment information can be extracted later based on the cycling area.

[0111] If the modification information is not available, it means that the vehicle has not been modified and there is no need to consider the impact of modification on the riding data. Therefore, the original riding information is defined as the riding lap time information and output.

[0112] Step 33: If the modification information exists, calculate the optimization information using the modification information and the preset optimization algorithm.

[0113] Optimization algorithms refer to algorithms that optimize parameters such as braking point, cornering speed, cornering angle, and riding line under safe conditions. These optimization algorithms are pre-input by professionals in the field, such as trajectory segmentation comparison algorithms and safety limit fitting algorithms. Optimization information refers to a set of optimized parameters, including braking point, cornering speed, cornering angle, riding line, and steering assist, that are adapted to the vehicle's modification status and can improve riding efficiency within a safe range. The optimization information is calculated by the system comparing and calculating the differences between the quantification coefficients corresponding to the modified parts and the original riding information segment by segment, and then fitting the data under safety limit constraints.

[0114] If modification information exists, it means that the vehicle has been modified. Therefore, in order to make the generated lap time information more accurate and reliable, optimization information is calculated by combining the modification information with the optimization algorithm.

[0115] Step 34: Adjust the original riding information based on the optimization information to obtain modified riding information and define it as the riding lap time information output.

[0116] Modified riding information refers to comprehensive riding data such as lap times, riding trajectory, handling parameters, and steering assist data that are adapted to the vehicle's modified state, meet safety limits, and improve riding performance. This modified riding information is obtained by the system adjusting the original riding information item by item according to the quantification coefficients and optimization parameters in the optimization information, and then defining it as riding lap time information for subsequent operations.

[0117] This also includes a method for optimizing cycling lap time information, which includes:

[0118] Step 35: Analyze cycling environment data using original cycling information.

[0119] Cycling environment data refers to data reflecting external environmental conditions during historical rides, stored in the original cycling information. This includes, but is not limited to, road surface material, road surface dryness / wetness, gradient, curve type, temperature, wind force, and lighting conditions. The analysis method for this cycling environment data is as follows: different original cycling information records store different cycling environment data. Each time new original cycling information is recorded, the system simultaneously determines and records the corresponding environmental data through onboard sensors and the network. When the system receives original cycling information, it automatically retrieves the corresponding cycling environment data.

[0120] Step 36: Collect actual environmental data.

[0121] Actual environmental data refers to the real-time external environmental conditions collected by the system while the vehicle is being ridden, including but not limited to road surface material, road surface wetness / dryness, slope, curve type, temperature, wind force, and lighting conditions. This actual environmental data is collected by the system through onboard sensors, location information, and network data interfaces to obtain real-time environmental information for the current riding scenario.

[0122] Step 37: Compare the cycling environment data with the actual environment data to obtain the difference in environmental parameters.

[0123] Environmental parameter difference refers to the set of differences between environmental parameters such as temperature, humidity, road surface dryness / wetness, wind force, and sunlight obtained after the system compares the cycling environment data with the actual environment data item by item. The calculation method for environmental parameter difference here is that the system performs difference calculations on the corresponding types of environmental parameters, obtains the difference values ​​of each environmental indicator, and summarizes them to form the environmental parameter difference.

[0124] Step 38: Combine the environmental parameter differences with the preset environmental impact algorithm to calculate the environmental adjustment data.

[0125] The environmental impact algorithm refers to an algorithm that calculates the cycling-related parameters that need to be adjusted based on the difference in environmental parameters, such as environmental difference correction algorithms and road surface condition adaptation algorithms. Environmental adjustment data refers to data that adapts to the current actual environment and corrects cycling parameters, including but not limited to brake point correction values, cornering speed correction values, cornering angle correction values, and line adjustment amounts. The environmental adjustment data is calculated by the system substituting the environmental parameter differences into the environmental impact algorithm.

[0126] Step 39: Update the cycling lap time information according to the environmental adjustment data to obtain the actual cycling information and output it.

[0127] Actual riding information refers to the riding parameters that the system updates and corrects based on environmental adjustment data to adapt to the current actual riding environment and reflect the true state of the vehicle. This actual riding information is obtained by the system applying the correction values ​​from the environmental adjustment data to the original parameters of the riding lap time information, then correcting each parameter individually, and finally outputting this information to the corresponding module.

[0128] The optimal cycling projection output also includes:

[0129] Step 70: Analyze the optimal riding posture for the riding projection to obtain the riding pedal area.

[0130] Cycling posture refers to the comprehensive manifestation of a cyclist's spatial position, force application, and center of gravity distribution during cycling. The analysis of cycling posture here involves the system detecting key human body points, extracting posture features, and recognizing poses within the optimal cycling projection to determine the cyclist's current optimal cycling posture. The pedal area refers to the region within the optimal cycling projection where the cyclist's feet exert force and support body balance. The pedal area is obtained by the system performing key point recognition and region extraction within the optimal cycling projection to determine the region corresponding to the cyclist's foot pedaling position.

[0131] Step 71: Extract the actual pedal area from the cycling information.

[0132] The actual pedaling area refers to the actual location of the cyclist's feet during cycling, where they exert force and support body balance in real time. The actual pedaling area is extracted by the system from cycling information through posture recognition and region localization to determine the actual location of the cyclist's feet during the current ride.

[0133] Step 72: If the actual pedal area does not fall into the riding pedal area, adjust the pedal corresponding to the actual pedal area to fall into the riding pedal area.

[0134] If the actual pedal area does not fall into the cycling pedal area, it means that the cyclist's current riding posture does not match the riding posture corresponding to the optimal riding information. In order to make it more in line with the optimal riding posture so that riding and related operations can be performed according to the optimal riding projection, the pedals corresponding to the actual pedal area are adjusted to fall into the cycling pedal area.

[0135] Step 73: If the actual pedal area falls into the riding pedal area, do not control the pedal corresponding to the actual pedal area to make adjustments.

[0136] If the actual pedal area falls within the riding pedal area, it means that the cyclist's current riding posture is consistent with the riding posture corresponding to the optimal riding information. Therefore, no adjustment is made to the pedal corresponding to the actual pedal area.

[0137] Among them, if the actual pedal area does not fall into the cycling pedal area, the methods to adjust the pedal corresponding to the actual pedal area to fall into the cycling pedal area include:

[0138] Step 720: Obtain the pedal weight.

[0139] Pedal weight refers to the actual weight borne by the pedals during cycling. This pedal weight is obtained in real-time by pressure sensors mounted on the pedals.

[0140] Step 721: Obtain the cyclist's weight using cycling information.

[0141] Cyclist weight refers to the cyclist's actual body weight. The cyclist weight is obtained by the system directly reading pre-stored or historically collected cyclist weight values ​​from the cycling information.

[0142] Step 722: Calculate the standing pedal weight by combining the rider's weight with the preset weight distribution algorithm.

[0143] Weight distribution algorithms are algorithms that calculate the weight a cyclist should bear on the pedals when not seated, based on the cyclist's weight. These algorithms are pre-set by professionals in the field and include, for example, weight ratio distribution algorithms and standing center of gravity distribution algorithms. Standing pedal weight refers to the standard weight that a cyclist should bear on the pedals when not seated, according to a reasonable center of gravity distribution. The calculation method for standing pedal weight involves the system inputting the cyclist's weight into a preset weight distribution algorithm, which then calculates the weight through center of gravity distribution and ratio calculations.

[0144] Step 723: If the pedal weight reaches the standing pedal weight, do not adjust the actual pedal area.

[0145] If the pedal weight reaches the weight of a standing pedal, it means that the cyclist is adjusting their posture and the center of gravity is on their hands and legs. To avoid interfering with the cyclist, the actual pedal area should not be adjusted at this time.

[0146] Step 724: If the pedal weight does not reach the standing pedal weight, adjust the pedal corresponding to the actual pedal area to fall into the riding pedal area.

[0147] If the pedal weight is not equal to the standing pedal weight, it means that the rider has not adjusted their posture. Therefore, in order to enable them to better complete the operation corresponding to the optimal riding projection, the pedals corresponding to the actual pedal area should be adjusted to fall into the riding pedal area.

[0148] Among them, if the pedal weight does not reach the standing pedal weight, the methods to adjust the pedal corresponding to the actual pedal area to fall into the cycling pedal area include:

[0149] Step 7240: Calculate pedal travel time by comparing the actual pedal area with the cycling pedal area.

[0150] Pedal travel time refers to the adjustment time required to move the actual pedal area to the riding pedal area. This time is calculated by the system based on the distance between the actual pedal area and the riding pedal area, combined with the pedal travel speed. The pedal travel speed is obtained by the rider inputting pedal modification data or original factory data into the system.

[0151] Step 7241: Calculate the adjustable time using the cycling area and the optimal cycling projection.

[0152] Adjustable time refers to the available time during cycling that allows for adjustments to pedal position without affecting normal cycling posture. The adjustable time is calculated by the system based on the current cycling area, determining the remaining time required to reach the optimal cycling projection position, which may involve turning, weight shifting, or other posture changes.

[0153] Step 7242: When the pedal movement time is less than the adjustable time, control the pedal corresponding to the actual pedal area to adjust so that it falls into the riding pedal area.

[0154] When the pedal movement time is less than the adjustable time, it means that the rider will not adjust the riding posture during the pedal movement. In order to complete the relevant operations more smoothly in the subsequent riding, the pedal corresponding to the actual pedal area is adjusted to fall into the riding pedal area.

[0155] Step 7243: When the pedal movement time is greater than the adjustable time, extract the riding posture from the best riding projection and adjust it in combination with the preset key posture rules to obtain the key posture.

[0156] The key posture rules refer to the posture adjustment constraints and priority rules that prioritize riding safety and core handling stability. These key posture rules are set and stored in the system by professionals in the field after experimentation based on track type, cornering characteristics, and safety handling requirements. The key posture refers to a preferred riding posture that balances safety and handling stability. The key posture is obtained by the system adapting and adjusting the riding posture in the optimal riding projection according to the priority and constraints of the key posture rules.

[0157] When the pedal movement time is greater than the adjustable time, it means that the pedal adjustment time is insufficient to move the pedal to the required area. Therefore, the riding posture in the optimal riding projection is extracted and adjusted in combination with the preset key posture rules to obtain the key posture.

[0158] Step 7244: Update the focus posture to the optimal riding projection to obtain the focus riding projection and output it.

[0159] Prioritized riding projection refers to a visual image that prioritizes riding guidance to ensure safe and stable handling. This projection is obtained by replacing the corresponding riding posture data in the optimal riding projection with the key posture data, followed by visualization and integration processing. The projection is output in real-time to the user via an in-vehicle display terminal, mobile terminal screen, or AR projection device.

[0160] The methods for comparing the current cycling data with cycling lap time information to obtain optimal cycling data and updating the cycling lap time information include:

[0161] Step 90: Calculate the range of data at the same level based on the data from this ride and the preset same-level judgment rules.

[0162] The "same level" judgment rule refers to the criteria for determining whether historical cycling data belongs to the same level as the current ride. This same level judgment rule is established by professionals in the field, who obtain relevant data through multiple experiments based on cycling level grading standards and then store it in the system. The same level data range refers to the range of data values ​​within the same cycling level interval as the current ride data in terms of lap time, handling parameters, riding posture, and other indicators. This same level data range is calculated by the system applying threshold matching and interval division to various indicators of the current ride data according to the same level judgment rule.

[0163] Step 91: Count the number of data points at the same level based on the range of data at the same level.

[0164] The number of data points at the same level refers to the total number of historical cycling data entries within the same data level range. This number is calculated by the system analyzing cycling lap times one by one and accumulating the lap times falling within the same data level range.

[0165] Step 92: If the number of data at the same level reaches the preset effective number, compare the current cycling data with the cycling lap time information to obtain the optimal cycling data and update the cycling lap time information.

[0166] The effective quantity refers to the minimum number of data points required to determine whether the current cycling data is valuable and can be used to update cycling lap time information. The effective quantity is determined by researchers in this field through experiments based on data statistical validity requirements, and the results are then stored in the system.

[0167] If the number of data points at the same level reaches a valid number, it means that the relevant data for this cycling lap time is achievable by most people and is not the extreme level of a single user. Therefore, the cycling data is compared with the cycling lap time information to obtain the optimal cycling data and the cycling lap time information is updated.

[0168] Step 93: If the number of data at the same level does not reach the valid number, define the data of this ride as a private data record.

[0169] Private data refers to cycling data that is only valid for the current user, not included in public cycling lap time information for general reference, and is used solely for personal cycling recording and viewing. Private data is recorded by the system marking this cycling data as personal data and storing it separately in the user's personal cycling profile.

[0170] If the number of data points at the same level does not reach the valid number, it means that the cycling data is the user's limit data, which can only be achieved by a few people and may be dangerous. Therefore, the cycling data is defined as a private data record.

[0171] This also includes a method for filtering cycling lap time information, which includes:

[0172] Step 94: Extract road information and direction of travel from the cycling information.

[0173] Road information refers to a collection of information reflecting the type of road, road segment attributes, road conditions, and road signs where the cycling is taking place. This road information is extracted by the system from location data, map data, or sensor-collected data within the cycling information, through parsing and matching. Driving direction refers to the vehicle's current forward direction relative to the road's direction of travel. This driving direction is extracted by the system collecting real-time direction data through a positioning module, gyroscope, or direction sensor and integrating it into the cycling information. The system then extracts direction-related data characters for further processing.

[0174] Step 95: If the road information is the track information, obtain the extreme riding information based on the road information and the direction of travel.

[0175] Extreme riding information refers to a set of data, including riding trajectory and posture, taken within safety constraints and in a track environment, combining road information and riding direction to achieve optimal lap times and control limits. This extreme riding information is obtained by the system through extreme fitting and optimal trajectory calculation based on road information such as curves, straights, and gradients, as well as riding direction.

[0176] If the road information is the same as the track information, it means there are no oncoming vehicles. There will only be vehicles coming from behind or vehicles blocking the way in front. In this case, the track width can be filled. Therefore, the extreme riding information can be obtained based on the road information and the direction of travel.

[0177] Step 96: If the road information is highway information, filter the cycling lap time information according to the direction of travel to obtain standard cycling information.

[0178] Standard cycling information refers to a set of data, including typical cycling trajectories, speeds, and control parameters, selected based on the direction of travel in a road cycling scenario, ensuring compliance with traffic regulations and guaranteeing cycling safety. This standard cycling information is obtained by the system filtering out compliant and safe cycling data from lap time data based on the direction of travel, removing data that does not meet road safety requirements.

[0179] If the road information is highway information, it means that the "track" set by the user is a highway with two-way lanes, and there will be oncoming vehicles. In order to avoid accidents caused by changing lanes at will, the cycling lap time information is filtered according to the direction of travel to obtain standard cycling information.

[0180] Step 97: Update the cycling lap time information based on standard cycling information to obtain safe cycling information.

[0181] Safe riding information refers to a set of data including safe and controllable riding trajectory, speed, and control parameters in a road riding scenario. This safe riding information is obtained by replacing the corresponding data in the original cycling lap time information with the safety compliance data from the standard riding information.

[0182] This also includes optimization methods to help adjust information, which include:

[0183] Step 40: Collect actual cycling data.

[0184] Actual riding data refers to the real-time collection of data, including riding status, vehicle parameters, and environmental factors, collected by sensors during actual riding. This actual riding data is acquired and aggregated in real-time by the system using onboard sensors, a positioning module, and an attitude detection module.

[0185] Step 41: Compare the actual cycling data with the optimal cycling information to obtain the cycling data difference.

[0186] Cycling data difference refers to the difference between actual cycling data and optimal cycling information in each corresponding indicator. This difference is obtained by the system comparing the actual cycling data with the optimal cycling information item by item and then calculating the difference.

[0187] Step 42: Calculate the cycling assist difference based on the difference in cycling data and the preset assist adjustment algorithm.

[0188] The assist adjustment algorithm refers to an algorithm that calculates and outputs the corresponding assist adjustment amount based on the difference in riding data. It is set by those skilled in the art, and examples include: difference ratio adjustment algorithm, adaptive assist compensation algorithm, etc. The riding assist difference refers to the difference between the actual riding assist and the target riding assist. Here, the riding assist difference is obtained by the system substituting the riding data difference into the assist adjustment algorithm for calculation.

[0189] Step 43: Adjust the assist adjustment information according to the riding assist difference to obtain the actual assist information and output it.

[0190] Actual assist information refers to the actual assist parameters used in executing riding assist control. This actual assist information is obtained by the system correcting and compensating for the assist adjustment information based on the riding assist difference. The actual assist information is output by the system sending the corrected and compensated actual assist parameters to the assist actuator for drive control.

[0191] Based on the same inventive concept, embodiments of the present invention provide a comprehensive recording and visualization control system for cycling data.

[0192] One of them is a cycling data full-dimensional recording and visualization control system, including:

[0193] The acquisition module is used to acquire cycling information, actual environmental data, pedal weight, and actual cycling data.

[0194] The memory is used to store a program for a method of recording and visualizing cycling data in all dimensions;

[0195] The processor loads and executes programs from memory.

[0196] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional modules is used as an example. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device, and unit described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0197] The above description is merely a preferred embodiment of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principles of the present invention should also be considered within the scope of protection of the present invention.

Claims

1. A method for comprehensive recording and visualization control of cycling data, characterized in that, include: Step 1: Respond to the preset cycling data viewing signal to obtain cycling information; Step 2: Extract vehicle information and cycling area from the cycling data; Step 3: Search for the corresponding lap time information in the preset lap time database based on the vehicle information; Step 4: Extract the optimal riding information and assist adjustment information from the cycling lap time information based on the cycling area; Step 5: Extract steering assist data from the vehicle information; Step 6: Adjust the steering assist data according to the assist adjustment information to obtain the adjusted assist value; Step 7: Integrate the best riding information to form the best riding projection and output it; Step 8: When the preset end-of-ride signal is received, acquire and record the data for this ride; Step 9: Compare the data from this ride with the lap time information to obtain the optimal riding data and update the lap time information.

2. The method for full-dimensional recording and visualization control of cycling data according to claim 1, characterized in that, Methods for retrieving corresponding lap times from a pre-set lap time database based on vehicle information include: Step 30: Separate the vehicle information into original information and modification information; Step 31: Search for the corresponding original riding information in the lap database based on the original information; Step 32: If the modification information is not available, define the original riding information as riding lap time information and output it; Step 33: If the modification information exists, calculate the optimization information using the modification information and the preset optimization algorithm; Step 34: Adjust the original riding information based on the optimization information to obtain modified riding information and define it as the riding lap time information output.

3. The method for full-dimensional recording and visualization control of cycling data according to claim 2, characterized in that, It also includes methods for optimizing cycling lap time information, which include: Step 35: Analyze cycling environment data using original cycling information; Step 36: Collect actual environmental data; Step 37: Compare the cycling environment data with the actual environment data to obtain the difference in environmental parameters; Step 38: Combine the environmental parameter differences with the preset environmental impact algorithm to calculate environmental adjustment data; Step 39: Update the cycling lap time information according to the environmental adjustment data to obtain the actual cycling information and output it.

4. The method for full-dimensional recording and visualization control of cycling data according to claim 1, characterized in that, The optimal cycling projection output also includes: Step 70: Analyze the optimal cycling posture for the cycling projection to obtain the pedal area; Step 71: Extract the actual pedal area from the cycling information; Step 72: If the actual pedal area does not fall into the riding pedal area, adjust the pedal corresponding to the actual pedal area to fall into the riding pedal area. Step 73: If the actual pedal area falls into the riding pedal area, do not control the pedal corresponding to the actual pedal area to make adjustments.

5. The method for full-dimensional recording and visualization control of cycling data according to claim 4, characterized in that, If the actual pedal area is not within the designated riding pedal area, methods to adjust the pedals corresponding to the actual pedal area to ensure they fall within the designated riding pedal area include: Step 720: Obtain the pedal weight; Step 721: Obtain the cyclist's weight using cycling information; Step 722: Calculate the standing pedal weight by combining the rider's weight with the preset weight distribution algorithm; Step 723: If the pedal weight reaches the standing pedal weight, do not adjust the actual pedal area; Step 724: If the pedal weight does not reach the standing pedal weight, adjust the pedal corresponding to the actual pedal area to fall into the riding pedal area.

6. The method for full-dimensional recording and visualization control of cycling data according to claim 5, characterized in that, If the pedal weight is not at the same level as the standing pedal weight, methods to adjust the pedals corresponding to the actual pedal area to ensure they fall into the cycling pedal area include: Step 7240: Calculate pedal travel time by comparing the actual pedal area with the pedal area used for cycling; Step 7241: Calculate the adjustable time using the cycling area and the optimal cycling projection; Step 7242: When the pedal movement time is less than the adjustable time, control the pedal corresponding to the actual pedal area to adjust so that it falls into the riding pedal area; Step 7243: When the pedal movement time is greater than the adjustable time, extract the riding posture from the best riding projection and adjust it in combination with the preset key posture rules to obtain the key posture. Step 7244: Update the focus posture to the optimal riding projection to obtain the focus riding projection and output it.

7. The method for full-dimensional recording and visualization control of cycling data according to claim 1, characterized in that, Methods for comparing the current cycling data with cycling lap time information to obtain optimal cycling data and updating cycling lap time information include: Step 90: Calculate the range of data for the same level based on the data from this ride and the preset same-level judgment rules; Step 91: Count the number of data points at the same level based on the range of data at the same level; Step 92: If the number of data at the same level reaches the preset effective number, compare the current cycling data with the cycling lap time information to obtain the optimal cycling data and update the cycling lap time information; Step 93: If the number of data at the same level does not reach the valid number, define the data of this ride as a private data record.

8. The method for full-dimensional recording and visualization control of cycling data according to claim 7, characterized in that, It also includes a method for filtering cycling lap time information, which includes: Step 94: Extract road information and direction of travel from the cycling data; Step 95: If the road information is the track information, obtain the extreme riding information based on the road information and the direction of travel; Step 96: If the road information is highway information, filter the cycling lap time information according to the direction of travel to obtain standard cycling information; Step 97: Update the cycling lap time information based on standard cycling information to obtain safe cycling information.

9. The method for full-dimensional recording and visualization control of cycling data according to claim 1, characterized in that, It also includes optimization methods to help adjust information, which include: Step 40: Collect actual cycling data; Step 41: Compare the actual cycling data with the optimal cycling information to obtain the cycling data difference; Step 42: Calculate the cycling assist difference based on the difference in cycling data and the preset assist adjustment algorithm; Step 43: Adjust the assist adjustment information according to the riding assist difference to obtain the actual assist information and output it.

10. A comprehensive cycling data recording and visualization control system, characterized in that, include: The acquisition module is used to acquire cycling information, actual environmental data, pedal weight, and actual cycling data. A memory for storing a program for a method of full-dimensional recording and visualization control of cycling data as described in any one of claims 1 to 9; The processor loads and executes programs from memory.

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