Vehicle handling method and related equipment
By obtaining vehicle maintenance and financial costs, determining vehicle health status, and classifying disposal strategies, the problem of low accuracy in vehicle assessment is solved, enabling the rational disposal of vehicles.
Patent Information
- Application Number
- CN202511244165.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-09-02
- Publication Date
- 2025-12-09
AI Technical Summary
In existing technologies, the accuracy of vehicle assessment is low, leading to unreasonable vehicle disposal.
By acquiring target information such as vehicle maintenance costs and capital costs, the health status of the vehicle is determined, and disposal strategies are divided according to the numerical range of the health status, including adjustments to the sale or lease methods.
This enables accurate assessment and appropriate handling of vehicles, improving the scientific rigor and effectiveness of vehicle disposal.
Smart Images
Figure CN121092913A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of vehicle technology, and in particular to a vehicle disposal method and related equipment. Background Technology
[0002] As people's living standards improve, vehicles have become an indispensable means of transportation. To save on travel costs, some users choose to buy or lease used cars, leading to the emergence of vehicle leasing and resale.
[0003] For vehicle leasing and sales, the process usually involves evaluating the vehicle after the lease is completed to determine whether it can be continued for leasing or sold.
[0004] In the exemplary technology, the vehicle is evaluated based on its usage time, and the vehicle is disposed of by continuing to lease or sell based on the evaluation results. However, using the usage time as a single factor to evaluate the vehicle is not accurate, resulting in unreasonable disposal of the vehicle, that is, the accuracy of the vehicle evaluation is low. Summary of the Invention
[0005] Based on the aforementioned technological status, this application provides a vehicle disposal method and related equipment to address the problem of low accuracy in vehicle assessment.
[0006] To achieve the above-mentioned technical objectives, this application proposes the following technical solution:
[0007] Firstly, this application provides a method for disposing of a vehicle, including:
[0008] Obtain target information about the vehicle, including the vehicle's maintenance costs and financial costs;
[0009] The health score of the vehicle is determined based on the target information of the vehicle, and the health score is used to indicate the degree of health of the vehicle;
[0010] Determine the target value range in which the health status falls, and determine the treatment strategy associated with the target value range;
[0011] The vehicle is disposed of according to the disposal strategy, which includes the sale of the vehicle and adjustments to the leasing method.
[0012] In some implementations, the processing strategy for determining the correlation of the target numerical range includes:
[0013] If the target value range indicates that the health level is less than a first preset threshold, the handling strategy associated with the target value range is determined to be the sale of the vehicle.
[0014] If the target value range indicates that the health status is greater than or equal to a first preset threshold and less than a second preset threshold, the processing strategy associated with the target value range is determined to be to suspend the long-term rental of the vehicle and to repair the vehicle. The long-term rental is used to indicate that the rental period of the vehicle is greater than a preset period.
[0015] If the target value range indicates that the health status is greater than or equal to a second preset threshold, the processing strategy associated with the target value range is determined to be adjusting the rental fee required for the vehicle rental.
[0016] In some implementations, determining the health status of the vehicle based on the vehicle's target information includes:
[0017] The target information is input into the first prediction model to obtain the health score output by the first prediction model.
[0018] In some implementations, before determining the target numerical range of the health status, the method further includes:
[0019] Obtain the vehicle's model parameters, the fluctuation value of the market in which the vehicle is located, and the seasonal impact parameters;
[0020] Configure a first preset threshold and a second preset threshold based on the model parameters, the fluctuation value, and the seasonal impact parameters;
[0021] Based on the first preset threshold and the second preset threshold, multiple initial value intervals are determined, wherein the initial value interval in which the health level is located is used as the target value interval.
[0022] In some embodiments, after processing the vehicle according to the disposal strategy, the method further includes:
[0023] Obtain the vehicle's net value on the day after processing and its historical net value for each historical date;
[0024] Based on the net asset value of the day and each of the historical net asset values, an initial net asset value curve is constructed;
[0025] Multiple correction factors are obtained, and the initial net value curve is corrected according to each of the correction factors to obtain the target net value curve corresponding to the vehicle.
[0026] Output the target net asset value curve.
[0027] In some implementations, obtaining multiple correction factors includes:
[0028] Obtain the fluctuation value of the market where the vehicle is located;
[0029] When the fluctuation value is greater than the fluctuation threshold, multiple correction factors are obtained.
[0030] In some implementations, the step of correcting the initial net asset value curve according to each of the correction factors includes:
[0031] The residual value is determined based on each of the aforementioned correction factors;
[0032] The initial net asset value curve is corrected based on the residual value.
[0033] In some implementations, determining the residual based on each of the correction factors includes:
[0034] Each of the aforementioned correction factors is input into the second prediction model to obtain the residual value output by the second prediction model.
[0035] Secondly, this application provides a vehicle, comprising:
[0036] The acquisition module is used to acquire target information of the vehicle, including the vehicle's maintenance cost and financial cost.
[0037] The first determining module is used to determine the health level of the vehicle based on the target information of the vehicle, wherein the health level is used to indicate the degree of health of the vehicle;
[0038] The second determining module is used to determine the target value range in which the health status is located, and to determine the treatment strategy associated with the target value range;
[0039] The processing module is used to process the vehicle according to the disposal strategy, which includes adjusting the sale and leasing methods of the vehicle.
[0040] Thirdly, this application provides an electronic device, including a memory and a processor, wherein,
[0041] The memory is connected to the processor and is used to store programs;
[0042] The processor is used to implement the vehicle disposal method as described in the first aspect or any implementation thereof by running a program in the memory.
[0043] Fourthly, this application provides a computer program product, which, when executed by a processor, implements the vehicle disposal method as described in the first aspect or any implementation thereof.
[0044] Fifthly, this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the vehicle disposal method as described in the first aspect or any implementation thereof.
[0045] This application provides a vehicle disposal method and related equipment. It acquires target information such as vehicle maintenance costs and financial costs, determines the vehicle's health status based on this target information, and identifies disposal strategies associated with the target value range of the health status. The vehicle is then disposed of based on disposal strategies such as adjustments to the vehicle's sale or leasing method. In this application, the vehicle's health status is determined through its maintenance and financial costs, allowing for accurate vehicle assessment to arrive at disposal strategies, which are then used to rationally dispose of the vehicle. Attached Figure Description
[0046] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of this application. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.
[0047] Figure 1 A flowchart of a vehicle disposal method provided in this application embodiment Figure 1 ;
[0048] Figure 2 A flowchart of a vehicle disposal method provided in this application embodiment Figure 2 ;
[0049] Figure 3 A flowchart of a vehicle disposal method provided in this application embodiment Figure 3 ;
[0050] Figure 4 A flowchart of a vehicle disposal method provided in this application embodiment Figure 4 ;
[0051] Figure 5 A flowchart of a vehicle disposal method provided in this application embodiment Figure 5 ;
[0052] Figure 6 A schematic diagram of the structure of a vehicle provided in an embodiment of this application;
[0053] Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation
[0054] The technical solution proposed in this application is applicable to scenarios such as vehicle sales and leasing, aiming to solve the problem of low accuracy in vehicle assessment. By employing the technical solution described in this application, the health status of a vehicle is determined through its maintenance and financial costs. This allows for accurate vehicle assessment based on its health status, leading to a disposal strategy, and ultimately, the reasonable disposal of the vehicle according to the chosen strategy.
[0055] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.
[0056] It should be noted that the user information (including but not limited to electrical equipment information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of the relevant data must comply with relevant laws, regulations and standards, and corresponding operation entry points are provided for users to choose to authorize or refuse.
[0057] As people's living standards improve, vehicles have become an indispensable means of transportation. To save on travel costs, some users choose to buy or lease used cars, leading to the emergence of vehicle leasing and resale.
[0058] For vehicle leasing and sales, the process usually involves evaluating the vehicle after the lease is completed to determine whether it can be continued for leasing or sold.
[0059] In the exemplary technology, the vehicle is evaluated based on its usage time, and the vehicle is disposed of by continuing to lease or sell based on the evaluation results. However, using the usage time as a single factor to evaluate the vehicle is not accurate, resulting in unreasonable disposal of the vehicle, that is, the accuracy of the vehicle evaluation is low.
[0060] In view of this, embodiments of this application aim to provide a vehicle disposal method and related equipment, which obtains target information such as vehicle maintenance costs and financial costs, determines the vehicle's health status through this target information, determines the disposal strategy associated with the target value range of the health status, and then handles the vehicle based on disposal strategies such as adjustments to the vehicle's sale or leasing methods. In this application, the vehicle's health status is determined through its maintenance costs and financial costs, thereby accurately assessing the vehicle's health status to obtain a disposal strategy, and then rationally disposing of the vehicle according to the disposal strategy.
[0061] The vehicle disposal method and related equipment provided in this application embodiment can be applied to vehicle sales and leasing scenarios.
[0062] Exemplary methods
[0063] Figure 1 A flowchart of a vehicle disposal method provided in this application embodiment Figure 1 .like Figure 1 As shown, the vehicle disposal method provided in this embodiment includes:
[0064] Step S101: Obtain the target information of the vehicle, which includes the vehicle's maintenance cost and financial cost.
[0065] In this embodiment, the executing entity is a vehicle handling device. For ease of description, the term "device" will be used to refer to the vehicle handling device below. The device can be a server or any terminal device with vehicle handling functionality.
[0066] Each vehicle has a vehicle profile information, which is stored in a database. The vehicle profile information is structured data that integrates basic attributes, status, ratings, operating history, and financial data.
[0067] Vehicle profile information is obtained from multiple systems. Specifically, the asset system retrieves vehicle model, purchase year, purchase cost, estimated residual value, and estimated service life / mileage; the leasing system retrieves vehicle leasing orders (time, customer, rental fee, other payments), and idle records; the maintenance system retrieves repair work orders (time, project, parts, labor cost), and maintenance records; the financial system retrieves vehicle capital cost calculation parameters (such as loan interest rate, number of days occupied), and actual disposal revenue; and the vehicle networking / evaluation system retrieves vehicle ratings (vehicle condition, accident history, etc.) and driving behavior data (mileage, fuel consumption, etc., used to correlate maintenance costs). The operations system retrieves the vehicle's operating center and current inventory status (awaiting rental, currently rented, under repair, awaiting disposal, etc.). Based on the above, the device performs multiple calculations, specifically including:
[0068] Income items: Accumulated rental income + other receipts (insurance claims, penalties, etc.).
[0069] Cost items include explicit costs: accumulated repair costs + accumulated maintenance costs + accumulated insurance costs + accumulated taxes and fees + disposal costs (such as auction commissions).
[0070] Implicit costs, including capital occupation costs: Capital efficiency is precisely quantified by dynamically calculating based on the vehicle's net value (purchase cost - accumulated depreciation), capital cost rate (configurable), and number of days occupied.
[0071] Depreciation: Supports multiple methods (straight-line method, units-of-production method), dynamically calculating accumulated depreciation based on usage time / mileage.
[0072] Opportunity cost: estimated by quantifying the number of idle days and the daily rental potential of the vehicle model (optional, to enhance the depth of analysis).
[0073] Disposal Amount: Actual proceeds from disposal. Gross Profit / Net Profit per Vehicle: (Cumulative Revenue - Cumulative Explicit Costs - Cumulative Capital Costs - Cumulative Depreciation). Total Gross Profit is typically the sum of this value for multiple vehicles at the vehicle level.
[0074] In this way, the originally scattered and static data will be integrated into a quantifiable and traceable panoramic view of the profit and loss of a single vehicle through a core data model and dynamic computing engine, which can serve as vehicle profile information.
[0075] Furthermore, vehicle profile information allows users to combine dimensions on demand for aggregation, slicing, dicing, and drill-down analysis. Specifically, preset key dimension views can be determined based on vehicle profile information, including inventory status, operation center, monthly trend, vehicle model, and purchase year. This is not just about display; it's backed by powerful dimensional modeling.
[0076] Drill down to individual vehicles from vehicle profile information: From any summary view (such as "Total Gross Profit - Vehicle Model"), you can drill down to the specific list of individual vehicles under that vehicle model and their complete profit and loss profile.
[0077] Vehicle profile information penetrates to details: In the single vehicle profile, clicking on "Monthly Rental Operation Status", "Rental Records", and "Maintenance Records" can directly link to or display detailed data at the original transaction / work order level, verifying the source of profit and loss calculations.
[0078] Flexible and customizable analysis: Allows users to freely select dimensions (such as "vehicle model" + "purchase year" + "operation center") and metrics (total gross profit, average gross profit per vehicle, idle rate, maintenance cost rate) for cross-analysis.
[0079] In addition, various methods can be used for the above data processing. For example, massive data processing: using distributed storage and computing frameworks to process high-concurrency, high-frequency updated time-series data such as leasing, maintenance, and location data.
[0080] Real-time / Near Real-time Calculation: Supports near real-time calculation and updates for key indicators (such as current inventory status and monthly rental revenue). Supports efficient batch calculation (e.g., daily / weekly) for the entire lifecycle profit and loss.
[0081] Efficient aggregation and querying: Achieve fast query response under complex dimensional combinations by leveraging columnar storage, in-memory computing, or OLAP engines (such as Druid, ClickHouse, Kylin).
[0082] Data integration and ETL (Extract-Transform-Load): Building a robust data pipeline to extract, clean, transform, and load data from various business systems into a unified analytical model.
[0083] The device retrieves target information from vehicle profiles in the database. This target information includes at least the vehicle's maintenance costs and financial costs. Maintenance costs refer to the cumulative costs of the vehicle's historical repairs; financial costs refer to the vehicle's cumulative financial costs, such as the cost of purchasing the vehicle and the cost of adding equipment to the vehicle.
[0084] Step S102: Determine the vehicle's health level based on the vehicle's target information. The health level is used to indicate the vehicle's health condition.
[0085] After obtaining the target information, the vehicle's health level is determined based on the target cost. Health level refers to the degree of health of the vehicle, and the higher the health level, the better the vehicle is.
[0086] In one example, health is calculated as revenue efficiency / cost depreciation. Revenue efficiency is the ratio between the vehicle's cumulative revenue and its usage time. Cumulative revenue can be obtained from the vehicle profile information. Cost depreciation includes maintenance costs, capital costs, and vehicle depreciation.
[0087] In another example, health level = average daily revenue / (maintenance cost + 0.2 × capital cost).
[0088] In another example, the device includes a model for predicting vehicle health, defined as the first prediction model. The device acquires target information and sends it to the first prediction model to obtain the health score output by the model. The first prediction model can be a random forest model, which includes decision trees. Specifically, the cost of capital can be multiplied by a weight, for example, 0.2; that is, 0.2 of the cost of capital and the maintenance cost are input into the first prediction model. The weight can be determined using market volatility.
[0089] Step S103: Determine the target value range of health status and determine the treatment strategy associated with the target value range.
[0090] After obtaining the health status, the device determines the numerical range within which the health status falls, defining this range as the target numerical range, and then determines the corresponding handling strategy for the target numerical range. The handling strategy includes the sale of vehicles and adjustments to leasing methods. Adjustments to leasing methods include restricting leasing and optimizing operations. Restricting leasing includes, for example, suspending leasing, while optimizing operations refers to increasing leasing funds.
[0091] For example, when the target value range indicates a health level less than a first preset threshold, the associated handling strategy is determined to be the sale of the vehicle. If the first preset threshold is 0.5, meaning the health level is less than 0.5, emergency measures are taken for the vehicle, such as initiating an auction process within 72 hours. When the target value range indicates a health level greater than or equal to the first preset threshold and less than a second preset threshold, the associated handling strategy is determined to be the suspension of long-term vehicle rentals and vehicle repair. Long-term rentals are used to indicate that the rental period of the vehicle is greater than a preset period. The second preset threshold is, for example, 0.7. The first preset threshold is 0.5, meaning the health level is between 0.5 and 0.7. Rental restrictions are imposed, such as suspending long-term rentals and allocating a repair budget. Suspending long-term rentals refers to the rental period of the vehicle being greater than a preset period, such as renting the vehicle for more than six months. When the target value range indicates a health level greater than or equal to the second preset threshold, the associated handling strategy is determined to be the adjustment of the rental fee required for the vehicle rental. If the health level is greater than 0.7, optimized operation of the vehicle is carried out, such as increasing the rental fee of the vehicle by ±10%.
[0092] Step S104: Dispose of the vehicle according to the disposal strategy, which includes the sale of the vehicle and the adjustment of the leasing method.
[0093] After receiving the disposal strategy, the device processes the vehicle based on the disposal strategy. For example, if the disposal strategy is to sell, the device will publish the vehicle for sale; if the disposal strategy is to adjust the leasing method by restricting leasing, the device will suspend long-term leasing and allocate a maintenance budget, for example, 5000.
[0094] In this embodiment, target information such as vehicle maintenance costs and capital costs is obtained. The vehicle's health level is determined using this target information, and a corresponding disposal strategy is determined for the target value range within which the health level falls. The vehicle is then processed based on disposal strategies such as adjustments to the vehicle's sale or leasing methods. In this application, the vehicle's health level is determined through its maintenance and capital costs, allowing for an accurate assessment of the vehicle's health to arrive at a disposal strategy, which is then used to rationally dispose of the vehicle.
[0095] Figure 2 A flowchart of a vehicle disposal method provided in this application embodiment Figure 2 ,based on Figure 1 In the embodiment shown, before step S103, the method further includes:
[0096] Step S201: Obtain the vehicle model parameters, the fluctuation value of the market where the vehicle is located, and the seasonal impact parameters.
[0097] In this embodiment, the device can adjust the threshold based on vehicle information. Specifically, the device obtains the vehicle's model parameters, such as economy, luxury, and commercial models. The device also obtains the market fluctuation value of the vehicle's location and seasonal influence parameters.
[0098] Step S202: Configure the first preset threshold and the second preset threshold according to the model parameters, fluctuation values and seasonal influence parameters.
[0099] The device configures a first preset threshold and a second preset threshold by using model parameters, fluctuation values, and seasonal influence parameters.
[0100] Specifically, the first initial threshold and the second initial threshold are first determined by the model parameters, and then the first initial threshold and the second initial threshold are modified based on the fluctuation value and the seasonal influence parameter to obtain the first preset threshold and the second preset threshold.
[0101] For example, when the model parameter indicates the vehicle is an economy model, the first initial threshold is set to 0.45 and the second initial threshold is set to 0.65; when the model parameter indicates the vehicle is a luxury model, the first initial threshold is set to 0.35 and the second initial threshold is set to 0.55; when the model parameter indicates the vehicle is a commercial model, the first initial threshold is set to 0.50 and the second initial threshold is set to 0.70. If the fluctuation value is greater than the fluctuation threshold, the first and second initial thresholds are reduced; if the fluctuation value is less than or equal to the threshold, the first and second initial thresholds are not adjusted. When the seasonal influence parameter indicates that the current season is peak season, the first and second initial thresholds are adjusted; if the seasonal influence parameter indicates that the current season is not peak season, the first and second initial thresholds do not need to be adjusted.
[0102] Step S203: Based on the first preset threshold and the second preset threshold, determine multiple initial value intervals, wherein the initial value interval in which the health level is located is used as the target value interval.
[0103] After obtaining the first preset threshold and the second preset threshold, multiple initial value intervals are determined based on the first preset threshold and the second preset threshold, and the initial value interval in which the health score is located is the target value interval. For example, the first preset threshold is 0.5, the second preset threshold is 0.7, and the initial value intervals are (0, 0.5), [0.5, 0.7), and [0.7, 1]. It should be noted that the first preset threshold ∈ [0.4, 0.6] and the second preset threshold ∈ [0.6, 0.8].
[0104] In this embodiment, the device accurately sets a first preset threshold and a second preset threshold based on the vehicle model, season, and market fluctuations, thereby dividing multiple initial value intervals based on the second preset threshold and the first preset threshold.
[0105] Figure 3 A flowchart of a vehicle disposal method provided in this application embodiment Figure 3 .based on Figure 1 or Figure 2 In the embodiment shown, after step S104, the method further includes:
[0106] Step S301: Obtain the vehicle's net value for the current day after processing and the historical net value for each historical date.
[0107] In this embodiment, after processing the vehicle, the device obtains the vehicle's net value for the current day. Daily net value = purchase cost - accumulated depreciation. Accumulated depreciation is related to the vehicle's usage duration; the longer the usage duration, the greater the accumulated depreciation. The device obtains the vehicle's historical net value for historical dates. For example, after each determination of the vehicle's net value, the device associates and stores the net value with the corresponding date, thus allowing the storage of historical net values for various historical dates. Furthermore, the device can update the cost of capital using the current net value: daily cost of capital = daily net value × (annualized rate / 365). This method improves the time granularity from monthly to daily, with an error of less than 2.3%.
[0108] Step S302: Construct an initial net asset value curve based on the net asset value of the day and various historical net asset values.
[0109] After obtaining the current net asset value (NAV) and each historical NAV, a NAV curve is plotted based on the current NAV and each historical NAV, which serves as the initial NAV curve.
[0110] Step S303: Obtain multiple correction factors and correct the initial net value curve according to each correction factor to obtain the target net value curve corresponding to the vehicle.
[0111] After obtaining the initial net asset value (NAV) curve, the initial NAV curve is corrected. For example, the device acquires multiple correction factors, including vehicle ratings, market index values, and usage intensity. By correcting the initial NAV curve using these multiple correction factors, the target NAV curve can be obtained. In other words, the daily NAV and various historical NAVs in the initial NAV curve are corrected using multiple correction factors.
[0112] Step S304: Output the target net value curve.
[0113] After obtaining the target net worth curve, the device outputs the target net worth curve, which is to say, displays the target net worth curve of the vehicle.
[0114] It should be noted that the device is equipped with a decision dashboard that displays the target net value curve, showing the trend of vehicle net value changes over time. In addition, the decision dashboard can display multiple correction factors, i.e., visualize the influence weights of these three-dimensional correction factors. Furthermore, the decision dashboard can display a health heatmap, which is drawn based on the health status of vehicles or the health status of vehicle type distribution within the operations center.
[0115] In this embodiment, after processing the vehicle, the net value of the vehicle on the current day and the net values of each historical period are obtained. Based on the net value of the current day and the net values of each historical period, a net value curve is plotted so that users can view the vehicle's returns, thus improving the user experience.
[0116] Figure 4 A flowchart of a vehicle disposal method provided in this application embodiment Figure 4 .based on Figure 3 In the embodiment shown, step S303 includes:
[0117] Step S401: Obtain the fluctuation value of the market where the vehicle is located.
[0118] Step S402: If the volatility value is greater than the volatility threshold, obtain multiple correction factors.
[0119] In this embodiment, the initial net asset value curve is calculated by adjusting the adjustment factor. The adjustment factor can be determined in the previous step, but when the market fluctuates greatly, it is necessary to obtain the adjustment factor again.
[0120] Specifically, the device acquires the fluctuation value of the vehicle's current duration and determines whether the fluctuation value exceeds a fluctuation threshold. If the fluctuation value exceeds the threshold, multiple correction factors need to be acquired. For example, if the fluctuation value is greater than 5% (the fluctuation threshold), it needs to be recalculated, meaning multiple correction factors need to be reacquired, i.e., the vehicle's current rating, current market index, and current usage intensity need to be acquired. If the fluctuation value is less than or equal to the fluctuation threshold, the previously stored correction factors are acquired.
[0121] In addition, the device is equipped with a usage intensity feedback mechanism. When the usage intensity exceeds the intensity threshold, demand is reduced through negative feedback (such as vehicle price discounts or rental discounts); when the usage intensity is less than or equal to the intensity threshold, strong feedback (such as vehicle price premiums or rental premiums) is applied. Usage intensity can be determined by usage frequency. The higher the usage frequency, the greater the usage intensity, and the greater the usage intensity, the greater the vehicle price discount. The lower the usage intensity, the higher the vehicle's value premium.
[0122] Figure 5 A flowchart of a vehicle disposal method provided in this application embodiment Figure 5 .based on Figure 3 or Figure 4 In the embodiment shown, step S303 includes:
[0123] Step S501: Determine the residual value based on each correction factor.
[0124] In this embodiment, the device determines the residual value through various correction factors. The residual value refers to the residual value that an asset is expected to recover after the end of its service life. It is usually expressed as the remaining value when the asset is scrapped or disposed of. The residual value directly affects the transaction value of used cars and needs to be comprehensively evaluated in combination with factors such as vehicle age, mileage, and brand.
[0125] In one example, residual value = base value × vehicle rating × market index × usage intensity. Furthermore, the residual value can be calculated using the above formula as the initial residual value. Then, correction parameters are determined, and the initial residual value is corrected using these parameters to obtain the target residual value, which is then used to correct the initial net value curve.
[0126] The correction parameters are, for example: S = 0.7 + 0.6 / (1 + exp(-k * (score - b)), where k = 0.15 + 0.05 * (1 - base), base is the base value mentioned above, b = 55 - 5 * (2025 - get_purchase_year), get_purchase_year is the year the vehicle was purchased, and score is the set base score. Additionally, k ∈ [0.1, 0.2], and the offset b ∈ [50, 60].
[0127] In another example, the device includes a model for predicting residual value, defined as a second prediction model. The device inputs various correction factors into the second prediction model to obtain the residual value output by the model. Furthermore, while predicting residual value, the second prediction model can also be used for market simulation to determine the optimal time to dispose of the vehicle, such as the best time to sell the vehicle or the best time to adjust the leasing method.
[0128] Step S502: Correct the initial net value curve based on the residual value.
[0129] After obtaining the residual value, the initial net asset value (NAV) curve is revised based on it. Specifically, the current NAV and each historical residual value in the initial NAV curve are revised based on the residual value. For example, the residual value refers to the residual value rate, and the ratio of the residual value rate to the NAV is used for depreciation calculation. Therefore, the target NAV curve can be constructed by subtracting the depreciation portion from each NAV value in the initial NAV curve.
[0130] It should be noted that when the market volatility exceeds the volatility threshold, a residual value lock is implemented, meaning that the currently determined residual value will not change.
[0131] In this embodiment, residual values are determined through various correction factors, and the initial net asset value curve is corrected based on the residual values to obtain an accurate target net asset value curve.
[0132] Based on the above embodiments, compared with traditional solutions (prior art), this application has the following advantages:
[0133]
[0134] Exemplary device
[0135] Corresponding to the vehicle disposal method described above, this application also provides a vehicle. Figure 6 This is a schematic diagram of a vehicle module provided in an embodiment of this application. The vehicle provided in this embodiment includes:
[0136] The acquisition module 610 is used to acquire the target information of the vehicle, including the vehicle's maintenance cost and financial cost.
[0137] The first determining module 620 is used to determine the health of the vehicle based on the vehicle's target information. The health level is used to indicate the degree of health of the vehicle.
[0138] The second determining module 630 is used to determine the target value range of health status and determine the treatment strategy associated with the target value range.
[0139] Processing module 640 is used to process vehicles according to a disposal strategy, which includes adjustments to vehicle sales and leasing methods. In some implementations, vehicle 600 is also used for:
[0140] In some implementations, vehicle 600 is also used for:
[0141] If the health status indicated by the target value range is less than the first preset threshold, the handling strategy associated with the target value range is determined to be the sale of the vehicle.
[0142] When the target value range indicates that the health status is greater than or equal to the first preset threshold and less than the second preset threshold, the processing strategy associated with the target value range is to suspend the long-term rental vehicle and carry out vehicle repairs. Long-term rental is used to indicate that the rental period of the vehicle is greater than the preset period.
[0143] If the target value range indicates that the health status is greater than or equal to the second preset threshold, the processing strategy associated with the target value range is determined to be adjusting the rental fee required for vehicle rental.
[0144] In some implementations, vehicle 600 is also used for:
[0145] The target information is input into the first prediction model to obtain the health score output by the first prediction model.
[0146] In some implementations, vehicle 600 is also used for:
[0147] Obtain vehicle model parameters, market fluctuation values, and seasonal impact parameters;
[0148] Configure a first preset threshold and a second preset threshold based on model parameters, fluctuation values, and seasonal impact parameters;
[0149] Based on the first preset threshold and the second preset threshold, multiple initial value intervals are determined, among which the initial value interval in which the health level is located is used as the target value interval.
[0150] In some implementations, vehicle 600 is also used for:
[0151] Obtain the vehicle's net value on the day of processing and its historical net value for each historical date;
[0152] Construct an initial net asset value curve based on the net asset value of the day and various historical net asset values;
[0153] Multiple correction factors are obtained, and the initial net value curve is corrected according to each correction factor to obtain the target net value curve for the vehicle.
[0154] Output the target net asset value curve.
[0155] In some implementations, vehicle 600 is also used for:
[0156] Obtain the volatility value of the market where the vehicle is located;
[0157] When the volatility value is greater than the volatility threshold, multiple correction factors are obtained.
[0158] In some implementations, vehicle 600 is also used for:
[0159] The residual value is determined based on each correction factor;
[0160] The initial net asset value curve is corrected based on the residual value.
[0161] In some implementations, vehicle 600 is also used for:
[0162] Each correction factor is input into the second prediction model to obtain the residual value output by the second prediction model.
[0163] The vehicle provided in this embodiment belongs to the same concept as the vehicle disposal method provided in the above embodiments of this application. It can execute the vehicle disposal method provided in any of the above embodiments of this application and has the corresponding functional modules and beneficial effects for performing the vehicle disposal method. Technical details not described in detail in this embodiment can be found in the specific processing content of the vehicle disposal method provided in the above embodiments of this application, and will not be repeated here.
[0164] The functions implemented by the various modules in the vehicle can be implemented by the same or different processors, and this application embodiment does not limit this.
[0165] It should be understood that the modules in the above-described vehicle can be implemented by a processor calling software. For example, the system includes a processor connected to a memory containing instructions. The processor calls the instructions stored in the memory to implement any of the above methods or to implement the functions of each module of the device. The processor can be a general-purpose processor, such as a CPU or microprocessor, and the memory can be internal to the device or external to the system. Alternatively, the modules in the system can be implemented as hardware circuits. By designing the hardware circuits, some or all of the module functions can be implemented. The hardware circuit can be understood as one or more processors. For example, in one implementation, the hardware circuit is an ASIC, and by designing the logical relationships between the components within the circuit, some or all of the above module functions are implemented. In another implementation, the hardware circuit can be implemented using a PLD, such as an FPGA, which can include a large number of logic gates. The connection relationships between the logic gates are configured through configuration files, thereby implementing some or all of the above module functions. All modules of the above-described vehicle can be implemented entirely by a processor calling software, entirely by hardware circuits, or partially by a processor calling software with the remaining parts implemented by hardware circuits.
[0166] In this application embodiment, a processor is a circuit with signal processing capabilities. In one implementation, the processor can be a circuit with instruction reading and execution capabilities, such as a CPU, microprocessor, GPU, or DSP. In another implementation, the processor can implement certain functions through the logical relationships of hardware circuits. These logical relationships are fixed or reconfigurable. For example, the processor may be a hardware circuit implemented as an ASIC or PLD, such as an FPGA. In a reconfigurable hardware circuit, the process of the processor loading a configuration document and configuring the hardware circuit can be understood as the processor loading instructions to implement the functions of some or all of the above modules. Furthermore, it can also be a hardware circuit designed for artificial intelligence, which can be understood as an ASIC, such as an NPU, TPU, or DPU.
[0167] As can be seen, each module in the above vehicle can be one or more processors (or processing circuits) configured to implement the above methods, such as: CPU, GPU, NPU, TPU, DPU, microprocessor, DSP, ASIC, FPGA, or a combination of at least two of these processor forms.
[0168] Furthermore, the modules in the above-mentioned vehicle can be integrated in whole or in part, or they can be implemented independently. In one implementation, these modules are integrated together and implemented in the form of a System-on-Chip (SoC). The SoC may include at least one processor for implementing any of the above methods or implementing the functions of the modules of the device. The at least one processor may be of different types, such as CPU and FPGA, CPU and artificial intelligence processor, CPU and GPU, etc.
[0169] Exemplary electronic devices
[0170] This application provides another structural schematic diagram of an electronic device, see [link to schematic diagram]. Figure 7 As shown, the electronic device includes a memory 700 and a processor 710; wherein the memory 700 is connected to the processor 710 and is used to store programs; the processor 710 is used to implement the vehicle disposal method disclosed in any of the above embodiments by running the programs stored in the memory 700.
[0171] Specifically, the aforementioned electronic device may further include: a bus, a communication interface 720, an input device 730, and an output device 740. The electronic device may also include a data transceiver module, an image monitoring module, and a signal monitoring module.
[0172] The processor 710, memory 700, communication interface 720, input device 730, and output device 740 are interconnected via a bus. Among them:
[0173] A bus can include a pathway for transmitting information between various components in an electronic device.
[0174] The processor 710 can be a general-purpose processor, such as a general-purpose central processing unit (CPU), a microprocessor, etc., or an application-specific integrated circuit (ASIC), or one or more integrated circuits used to control the execution of the program of the present invention. It can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), an off-the-shelf programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.
[0175] The processor 710 may include a main processor, as well as a baseband chip, modem, etc.
[0176] The memory 700 stores a program that executes the technical solution of this invention, and may also store an operating system and other key business functions. Specifically, the program may include program code, which includes computer operation instructions. More specifically, the memory 700 may include read-only memory (ROM), other types of static storage devices capable of storing static information and instructions, random access memory (RAM), other types of dynamic storage devices capable of storing information and instructions, disk storage, flash memory, etc.
[0177] Input device 730 may include a device for receiving data and information input by a user, such as a keyboard, mouse, camera, scanner, light pen, voice input device, touch screen, pedometer, or gravity sensor.
[0178] Output device 740 may include devices that allow information to be output to a user, such as a display screen, printer, speaker, etc.
[0179] The communication interface 720 may include a device that uses any transceiver to communicate with other devices or communication networks, such as Ethernet, Radio Access Network (RAN), Wireless Local Area Network (WLAN), etc.
[0180] The processor 710 executes the program stored in the memory 700 and calls other devices, which can be used to implement each step of any of the vehicle disposal methods provided in the above embodiments of this application.
[0181] This application also proposes a chip, which includes a processor and a data interface. The processor reads and runs a program stored in the memory through the data interface to execute the vehicle disposal method described in any of the above embodiments. For the specific processing procedure and its beneficial effects, please refer to the above-described embodiments of the vehicle disposal method.
[0182] Exemplary computer program products and storage media
[0183] In addition to the methods and devices described above, embodiments of this application may also be computer program products, which include computer program instructions that, when executed by a processor, cause the processor to perform the steps in the vehicle disposal methods according to various embodiments of this application as described in any of the above embodiments of this specification.
[0184] Computer program products can be written in any combination of one or more programming languages to perform the operations of the embodiments of this application. The programming languages include object-oriented programming languages such as Java and C++, as well as conventional procedural programming languages such as C or similar languages. The program code can be executed entirely on the user's computing device, partially on the power device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.
[0185] Furthermore, embodiments of this application may also be storage media storing computer programs, which are executed by a processor to perform the steps of the vehicle disposal methods according to various embodiments of this application described in any of the above embodiments of this specification, specifically implementing the steps of the above vehicle disposal methods.
[0186] For the foregoing method embodiments, in order to simplify the description, they are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, because according to this application, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to this application.
[0187] It should be noted that the various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For apparatus embodiments, since they are basically similar to method embodiments, the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.
[0188] The steps in the methods of the various embodiments of this application can be adjusted, merged, or deleted in order according to actual needs, and the technical features described in each embodiment can be replaced or combined.
[0189] The units of the apparatus in the various embodiments of this application can be merged, divided, and deleted according to actual needs.
[0190] It should be understood that the disclosed terminals, devices, and methods can be implemented in other ways, given the several embodiments provided in this application. For example, the terminal embodiments described above are merely illustrative. For instance, the division of modules or sub-modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple sub-modules or modules may be combined or integrated into another module, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or modules, and may be electrical, mechanical, or other forms.
[0191] The modules or submodules described as separate components may or may not be physically separate. The components that constitute a module or submodule may or may not be physical modules or submodules; that is, they may be located in one place or distributed across multiple network modules or submodules. Some or all of the modules or submodules can be selected to achieve the purpose of this embodiment's solution, depending on actual needs.
[0192] Furthermore, the functional modules or sub-modules in the various embodiments of this application can be integrated into one processing module, or each module or sub-module can exist physically separately, or two or more modules or sub-modules can be integrated into one module. The integrated modules or sub-modules described above can be implemented in hardware or in the form of software functional modules or sub-modules.
[0193] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.
[0194] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software unit executed by a processor, or a combination of both. The software unit can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.
[0195] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.
[0196] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims
1. A vehicle handling method characterized by, The method comprises the following steps: obtaining target information of a vehicle, the target information comprising a maintenance cost and a capital cost of the vehicle; determining a health degree of the vehicle according to the target information of the vehicle, the health degree being used to indicate a health level of the vehicle; determining a target numerical interval in which the health degree is located, and determining a disposal strategy associated with the target numerical interval; processing the vehicle according to the disposal strategy, the disposal strategy comprising selling the vehicle and adjusting a leasing mode of the vehicle.
2. The vehicle handling method according to claim 1, characterized by, The disposal strategy associated with the target numerical interval is determined by: in a case where the target numerical interval indicates that the health degree is less than a first preset threshold, determining that the disposal strategy associated with the target numerical interval is selling the vehicle; in a case where the target numerical interval indicates that the health degree is greater than or equal to the first preset threshold and less than a second preset threshold, determining that the disposal strategy associated with the target numerical interval is suspending long-term leasing of the vehicle and maintaining the vehicle, the long-term leasing being used to indicate that a leasing duration of the vehicle is greater than a preset duration; in a case where the target numerical interval indicates that the health degree is greater than or equal to the second preset threshold, determining that the disposal strategy associated with the target numerical interval is adjusting a rent required for leasing the vehicle.
3. The vehicle handling method according to claim 1, characterized by, The health degree of the vehicle is determined according to the target information of the vehicle by: inputting the target information into a first prediction model to obtain the health degree output by the first prediction model.
4. The vehicle handling method according to claim 1, characterized by, Before the target numerical interval in which the health degree is located is determined, the following steps are further included: obtaining a model parameter of the vehicle, a fluctuation value of a market in which the vehicle is located, and a seasonal influence parameter; configuring a first preset threshold and a second preset threshold according to the model parameter, the fluctuation value, and the seasonal influence parameter; determining a plurality of initial numerical intervals according to the first preset threshold and the second preset threshold, wherein an initial numerical interval in which the health degree is located is used as a target numerical interval.
5. The vehicle disposal method according to claim 1, characterized by, After the vehicle is processed according to the disposal strategy, the following steps are further included: obtaining a net value of the vehicle on a current day and historical net values on a plurality of historical days; constructing an initial net value curve according to the net value on the current day and the historical net values; obtaining a plurality of correction factors and correcting the initial net value curve according to the correction factors to obtain a target net value curve corresponding to the vehicle; outputting the target net value curve.
6. The vehicle handling method according to claim 5, characterized by, The plurality of correction factors are obtained by: obtaining a fluctuation value of a market in which the vehicle is located; in a case where the fluctuation value is greater than a fluctuation threshold, obtaining a plurality of correction factors.
7. The vehicle handling method according to claim 5, characterized by, The initial net value curve is corrected according to the correction factors by: determining a residual value according to each of the correction factors; correcting the initial net value curve according to the residual value.
8. The vehicle handling method according to claim 7, characterized by, The residual value is determined according to the correction factors by: inputting each of the correction factors into a second prediction model to obtain a residual value output by the second prediction model.
9. A vehicle handling device, characterized by The method comprises the following steps: an obtaining module is configured to obtain target information of a vehicle, the target information comprising a maintenance cost and a capital cost of the vehicle; A first determining module is configured to determine a health degree of the vehicle according to target information of the vehicle, the health degree being used to indicate a health level of the vehicle. A second determining module is configured to determine a target value interval in which the health degree is located, and determine a disposal strategy associated with the target value interval. A processing module is configured to process the vehicle according to the disposal strategy, the disposal strategy including sale of the vehicle and adjustment of a lease mode.
10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and the computer program is run by the processor to implement the vehicle disposal method in any one of claims 1-8.