Driving planning method and system, and vehicle

Abstract

The present invention discloses a driving planning method, system, and vehicle, wherein the driving planning method includes: determining a first credit level of a driver through bad driving behavior within a first time range, determining a second credit level of the driver through bad driving behavior within a second time range, and calculating a driving safety level based on the first credit level and the second credit level; formulating a short-distance driving plan away from potentially dangerous vehicles based on the driving safety levels of nearby vehicles; obtaining a score for each pre-selected path through path information, and selecting the path with the highest score as the optimal path; calculating the optimal speed of the vehicle through the recommended speed of the path planning of the optimal path and the average speed of nearby vehicles, and periodically adjusting the optimal speed. The present invention provides a comprehensive driving assistance system for drivers and automatic driving systems, which can improve driving efficiency, safety, and comfort, and achieve a more intelligent, efficient, and safe driving experience.

Description

Technical Field

[0001] The present invention relates to the field of automobile driving technology, and in particular to a driving planning method and system, and a vehicle. Background Art

[0002] With the maturity of the automobile market and the improvement of people's quality of life, the number of vehicle users is increasing. As a result, traffic accidents and various road rage are increasing, causing troubles to the entire transportation.

[0003] Currently, many car companies have launched some driving assessment methods to evaluate drivers' driving behavior, but the effect of adjusting behavioral habits cannot be improved immediately. For example, the published Chinese patent (publication number CN115195690A) records that the driver's illegal behavior is compared with the standard behavior to limit the execution of illegal driving operations, such as speeding. However, in actual applications, the driver's bad habits of non-driving operations are not restricted, such as frequent overtaking, sudden stops, etc., as well as the driver's fatigue driving, using mobile phones while driving, etc. These are subjective bad behaviors of the driver under the correct operating specifications. These behaviors cannot be directly restricted, but it is these behaviors that have caused many traffic accidents. To a certain extent, they are directly related to the driver's bad habits. The nearby drivers are not aware of this and cannot avoid it in advance.

[0004] How to provide driving advice to the driver or the vehicle's autonomous driving system to obtain a safe and efficient driving plan, avoid driving vehicles with bad behavior in advance, and reduce the possibility of accidents is an urgent problem that needs to be solved. Summary of the Invention

[0005] The present invention is to solve the above-mentioned prior art problems.

[0006] In order to achieve the above object, the technical solution adopted by the present invention is as follows:

[0007] A driving planning method comprises the following steps:

[0008] Determine the driver's first credit rating based on bad driving behavior within a first time range, determine the driver's second credit rating based on bad driving behavior within a second time range, and calculate a driving safety rating based on the first and second credit ratings;

[0009] Develop short-distance driving plans away from potentially dangerous vehicles based on the driving safety levels of nearby vehicles;

[0010] Obtain the score of each pre-selected path through the path information, and select the path with the highest score as the best path;

[0011] The optimal speed of the vehicle is calculated based on the recommended speed of the optimal path and the average speed of nearby vehicles, and the optimal speed is adjusted periodically.

[0012] Preferably, the first time range and the second time range both represent a specified time range with the current time as the starting node, wherein the first time range is larger than the second time range.

[0013] Preferably, determining the driver's first credit rating based on bad driving behavior within a first time range and determining the driver's second credit rating based on bad driving behavior within a second time range includes:

[0014] Collect data, collect the driver's driving behavior data;

[0015] Identify bad behaviors, analyze and identify the collected data, and determine the bad driving behaviors;

[0016] Calculate the hazard score and assign a hazard score to bad driving behavior based on pre-set scoring rules;

[0017] Determine a first credit rating, calculate a corresponding sum of hazard scores within a first time range, and match the corresponding first credit rating;

[0018] A second credit rating is determined, and within a second time range, a corresponding sum of hazard scores is calculated to match the corresponding second credit rating.

[0019] Preferably, the calculating and obtaining the driving safety level based on the first credit level and the second credit level includes:

[0020] Set the corresponding proportion coefficient according to the size of the first credit rating and the second credit rating;

[0021] The driving safety level is calculated using the following expression:

[0022] SL=a1×L1+a2×L2

[0023] Set the corresponding proportion coefficient according to the size of the first credit rating and the second credit rating;

[0024] Among them, SL represents the driving safety level; a1 represents the proportion coefficient of the first credit level; a2 represents the proportion coefficient of the second credit level.

[0025] Preferably, the setting of corresponding proportion coefficients according to the first credit rating and the second credit rating includes:

[0026] If both the first and second credit ratings are lower than the credit threshold, the ratio coefficients are both 0.5;

[0027] If either or both of the first credit rating and the second credit rating are greater than or equal to the threshold, the proportion coefficient of the first credit rating is less than the proportion coefficient of the second credit rating.

[0028] Preferably, the nearby vehicles are vehicles within a preset radius with the vehicle as the center.

[0029] Preferably, formulating a short-distance driving plan away from potentially dangerous vehicles based on the driving safety levels of nearby vehicles includes:

[0030] Obtain driving safety level information of nearby vehicles;

[0031] Set warning thresholds to identify nearby potentially dangerous vehicles;

[0032] Screen out potentially dangerous vehicles;

[0033] Based on the filtered dangerous vehicles, a new short-term path is planned using an avoidance strategy based on the vehicle's position and destination.

[0034] Generate a short-distance driving plan based on the short-term path updated by the avoidance strategy.

[0035] Preferably, the path information includes: a congestion score, a driving distance score, and an estimated time score.

[0036] Preferably, the calculation expression for obtaining the score of each pre-selected path through the path information is:

[0037] Score=b1×C+b2×D+b3×T

[0038] Among them, Score represents the path score; C represents the congestion score; D represents the driving distance score; T represents the estimated time score; b1, b2, and b3 represent the weight parameters of the congestion score, driving distance score, and estimated time score, respectively.

[0039] Preferably, the expression for calculating the optimal vehicle speed is:

[0040] V=(1-α)×V1+α×V3

[0041] Where V represents the optimal speed of the ego vehicle; V1 represents the recommended speed for the optimal path; V3 represents the average speed of nearby vehicles; and the α parameter represents the willingness of the ego vehicle to maintain a similar speed to nearby vehicles.

[0042] When V>V2, then V=V2

[0043] Among them, V2 represents the road speed limit.

[0044] Preferably, the periodic adjustment of the optimal vehicle speed includes:

[0045] S1. determining a cycle for adjusting the optimal vehicle speed;

[0046] S2. At the beginning of each adjustment cycle, record the current time as the starting time;

[0047] S3. Obtain the speed of nearby vehicles;

[0048] S4. calculating the adjusted optimal vehicle speed;

[0049] S5. Setting the calculated adjusted optimal vehicle speed as the target vehicle speed;

[0050] S6. During the adjustment period, monitor the driving condition and speed change of the vehicle;

[0051] S7. When the current time minus the start time reaches the set adjustment period, the next adjustment period is entered and steps S2 to S7 are repeated.

[0052] A driving planning system, comprising:

[0053] An image monitoring device, installed inside the vehicle, for acquiring image data of the driver's behavior;

[0054] An operation recording device, the operation recording device is used to record the driver's driving behavior;

[0055] A central server, which is used to centrally collect, process and store real-time data uploaded by vehicles;

[0056] A data processing and analysis subsystem, which is located on a central server and is configured to receive, parse, and process data transmitted from vehicles, determine a first credit rating of the driver based on bad driving behavior within a first time range, determine a second credit rating of the driver based on bad driving behavior within a second time range, and calculate a driving safety rating based on the first and second credit ratings; formulate a short-distance driving plan away from potentially dangerous vehicles based on the driving safety levels of nearby vehicles; obtain a score for each pre-selected path based on path information and select the path with the highest score as the optimal path; calculate an optimal speed for the vehicle based on the recommended speed of the optimal path and the average speed of nearby vehicles, and periodically adjust the optimal speed;

[0057] The vehicle control device is used to adjust the vehicle in real time and complete driving planning based on the processing results of the data processing and analysis subsystem.

[0058] Preferably, the first time range and the second time range both represent a specified time range with the current time as the starting node, wherein the first time range is larger than the second time range.

[0059] Preferably, determining the driver's first credit rating based on bad driving behavior within a first time range and determining the driver's second credit rating based on bad driving behavior within a second time range includes:

[0060] Collect data, collect the driver's driving behavior data;

[0061] Identify bad behaviors, analyze and identify the collected data, and determine the bad driving behaviors;

[0062] Calculate the hazard score and assign a hazard score to bad driving behavior based on pre-set scoring rules;

[0063] Determine a first credit rating, calculate a corresponding sum of hazard scores within a first time range, and match the corresponding first credit rating;

[0064] A second credit rating is determined, and within a second time range, a corresponding sum of hazard scores is calculated to match the corresponding second credit rating.

[0065] Preferably, the calculating and obtaining the driving safety level based on the first credit level and the second credit level includes:

[0066] Set the corresponding proportion coefficient according to the size of the first credit rating and the second credit rating;

[0067] The driving safety level is calculated using the following expression:

[0068] SL=a1×L1+a2×L2

[0069] Set the corresponding proportion coefficient according to the size of the first credit rating and the second credit rating;

[0070] Among them, SL represents the driving safety level; a1 represents the proportion coefficient of the first credit level; a2 represents the proportion coefficient of the second credit level.

[0071] Preferably, the setting of corresponding proportion coefficients according to the first credit rating and the second credit rating includes:

[0072] If both the first and second credit ratings are lower than the credit threshold, the ratio coefficients are both 0.5;

[0073] If either or both of the first credit rating and the second credit rating are greater than or equal to the threshold, the proportion coefficient of the first credit rating is less than the proportion coefficient of the second credit rating.

[0074] Preferably, the nearby vehicles are vehicles within a preset radius with the vehicle as the center.

[0075] Preferably, formulating a short-distance driving plan away from potentially dangerous vehicles based on the driving safety levels of nearby vehicles includes:

[0076] Obtain driving safety level information of nearby vehicles;

[0077] Set warning thresholds to identify nearby potentially dangerous vehicles;

[0078] Screen out potentially dangerous vehicles;

[0079] Based on the filtered dangerous vehicles, a new short-term path is planned using an avoidance strategy based on the vehicle's position and destination.

[0080] Generate a short-distance driving plan based on the short-term path updated by the avoidance strategy.

[0081] Preferably, the path information includes: a congestion score, a driving distance score, and an estimated time score.

[0082] Preferably, the calculation expression for obtaining the score of each pre-selected path through the path information is:

[0083] Score=b1×C+b2×D+b3×T

[0084] Among them, Score represents the path score; C represents the congestion score; D represents the driving distance score; T represents the estimated time score; b1, b2, and b3 represent the weight parameters of the congestion score, driving distance score, and estimated time score, respectively.

[0085] Preferably, the expression for calculating the optimal vehicle speed is:

[0086] V=(1-α)×V1+α×V3

[0087] Where V represents the optimal speed of the ego vehicle; V1 represents the recommended speed for the optimal path; V3 represents the average speed of nearby vehicles; and the α parameter represents the willingness of the ego vehicle to maintain a similar speed to nearby vehicles.

[0088] When V>V2, then V=V2

[0089] Among them, V2 represents the road speed limit.

[0090] A vehicle comprises the driving planning system.

[0091] Beneficial effects of the present invention:

[0092] (1) Providing driving advice and planning: The present invention can provide accurate driving advice and planning to the driver or the vehicle's autonomous driving system, regardless of whether the vehicle is driven manually or autonomously. By considering the driving safety level, road conditions, driving distance, driving time, and information about nearby vehicles, the present invention can select the optimal driving path and adjust the optimal vehicle speed for the driver or the autonomous driving system, thereby improving driving efficiency and safety.

[0093] (2) Consideration of comprehensive factors: The present invention comprehensively considers factors such as driving safety level, road congestion level, driving distance and driving time to comprehensively evaluate driving conditions and take them into account in path planning and vehicle speed adjustment. This ensures that driving suggestions and plans meet comprehensive performance requirements and meet the needs of the driver or the autonomous driving system;

[0094] (3) Periodic Speed ​​Adjustment: This invention introduces the concept of periodic speed adjustment. By periodically monitoring the vehicle's driving conditions and speed changes, the optimal speed is adjusted at the appropriate time. This periodic adjustment can reduce frequent speed changes and improve driving safety and comfort.

[0095] (4) Applicable to both human and autonomous driving: The present invention is not only applicable to human driving, but also to autonomous driving systems. Both human drivers and autonomous driving systems can obtain real-time driving suggestions and planning from the solution to improve driving efficiency and safety.

[0096] (5) Based on real-time data: The solution relies on real-time data collection, including driving behavior, vehicle status and information about nearby vehicles. This data is collected and processed by monitoring devices and related equipment in the vehicle to ensure the accuracy and reliability of driving suggestions and planning;

[0097] Combining the above advantages, the present invention provides a comprehensive driving assistance system for drivers and automatic driving systems, which can improve driving efficiency, safety and comfort, and achieve a more intelligent, efficient and safe driving experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0098] Figure 1 Schematic diagram of the process of the present invention;

[0099] Figure 2 A schematic diagram of the process of obtaining a credit rating in the present invention;

[0100] Figure 3 A schematic diagram of the process of formulating a short-distance driving plan in the present invention;

[0101] Figure 4 This is a schematic diagram of the process of periodically adjusting the optimal vehicle speed in the present invention;

[0102] Figure 5It is a structural block diagram of the system of the present invention. DETAILED DESCRIPTION

[0103] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are merely exemplary and are not intended to limit the scope of the present disclosure. In the detailed description below, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present disclosure. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of well-known structures and technologies are omitted to avoid unnecessary confusion of the concepts of the present disclosure.

[0104] The terms used herein are only for describing specific embodiments and are not intended to limit the present disclosure. The terms "comprise," "include," etc. used herein indicate the presence of the features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0105] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification and should not be interpreted in an idealized or overly rigid manner.

[0106] When expressions such as “at least one of A, B, and C, etc.” are used, they should generally be interpreted in accordance with the meaning commonly understood by those skilled in the art (e.g., “a system having at least one of A, B, and C” should include but is not limited to systems having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, and C, etc.). When expressions such as “at least one of A, B, or C, etc.” are used, they should generally be interpreted in accordance with the meaning commonly understood by those skilled in the art (e.g., “a system having at least one of A, B, or C” should include but is not limited to systems having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, and C, etc.).

[0107] Some block diagrams and / or flow charts are shown in the accompanying drawings. It should be understood that some blocks in the block diagrams and / or flow charts or their combinations can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that these instructions, when executed by the processor, can create a device for implementing the functions / operations described in these block diagrams and / or flow charts. The technology of the present disclosure can be implemented in the form of hardware and / or software (including firmware, microcode, etc.). In addition, the technology of the present disclosure can take the form of a computer program product on a computer-readable storage medium having instructions stored thereon, which can be used by an instruction execution system or in combination with an instruction execution system.

[0108] like Figure 1 As shown, a driving planning method includes the following steps:

[0109] Determine the driver's first credit rating based on bad driving behavior within a first time range, determine the driver's second credit rating based on bad driving behavior within a second time range, and calculate a driving safety rating based on the first and second credit ratings;

[0110] Develop short-distance driving plans away from potentially dangerous vehicles based on the driving safety levels of nearby vehicles;

[0111] Obtain the score of each pre-selected path through the path information, and select the path with the highest score as the best path;

[0112] The optimal speed of the vehicle is calculated based on the recommended speed of the optimal path and the average speed of nearby vehicles, and the optimal speed is adjusted periodically.

[0113] This invention assesses drivers' poor driving behavior to determine their credit rating and calculates their driving safety rating based on that rating. It also assesses the driving safety of nearby vehicles to develop short-distance driving plans to avoid potentially dangerous vehicles. Route information is used to evaluate the pros and cons of preselected routes and select the optimal one. The recommended speed for the optimal route and the average speed of nearby vehicles are used to calculate the optimal speed, which is then periodically adjusted.

[0114] The present invention provides a driving safety grade, which can evaluate the driver's behavior and reflect the safety level of his driving.

[0115] The present invention formulates a short-distance driving plan to avoid encountering potentially dangerous vehicles and reduce the risk of traffic accidents.

[0116] The present invention uses path evaluation and selection of the best path to provide an optimal driving route, taking into account factors such as road conditions and traffic flow.

[0117] The present invention provides a suitable vehicle speed by calculating the optimal vehicle speed and adjusting it periodically, thereby balancing driving efficiency and safety.

[0118] This invention can improve driving safety, optimize driving route selection, reduce contact with potentially dangerous vehicles, provide an appropriate driving speed, and enhance the driving experience and safety. Both human and autonomous driving systems can apply this solution to obtain driving advice and plan the optimal driving path.

[0119] Preferably, the first time range and the second time range both represent a specified time range with the current time as the starting node, wherein the first time range is larger than the second time range.

[0120] Set the first time range and the second time range: the first time range refers to a longer specified time range in the past, such as the past 168 hours; the second time range refers to a shorter specified time range in the past, such as the past 3 hours.

[0121] The present invention evaluates a driver's driving behavior data and determines the driver's credit rating by setting a first time range and a second time range. The first time range represents driving behavior over a longer period of time, while the second time range represents driving behavior over a shorter period of time. The driver's first and second credit ratings are determined by analyzing and evaluating bad driving behavior within these two time ranges.

[0122] Set the first time range and the second time range: the first time range is a longer specified time range in the past, such as the past 168 hours (7 days), and the second time range is a shorter specified time range in the past, such as the past 3 hours.

[0123] Collecting driver behavior data: Use monitoring devices and violation recording devices to collect driver non-operational and operational behavior data, such as talking on the phone while driving, speeding, and sudden stops.

[0124] Evaluate driving behavior within a first time frame: Based on the driving behavior data within the first time frame, calculate the driver's first credit rating, which is used to represent the safety of driving behavior over a longer period of time.

[0125] Evaluate driving behavior within a second time frame: Based on the driving behavior data within the second time frame, calculate the driver's second credit rating, which is used to indicate the safety of driving behavior within a shorter period of time.

[0126] By setting both the first and second time ranges, the driver's driving behavior over longer periods of time can be comprehensively considered, leading to a more accurate assessment of their driving safety. This approach provides a more comprehensive analysis of driving behavior and a more accurate basis for subsequent driving recommendations and route planning. By assessing the driving safety level, the driver and the autonomous driving system can receive real-time driving recommendations, improving driving safety and efficiency.

[0127] Preferably, Figure 2 As shown, determining the first credit rating of a driver based on bad driving behavior within a first time range and determining the second credit rating of a driver based on bad driving behavior within a second time range includes:

[0128] Collect data, collect the driver's driving behavior data;

[0129] Identify bad behaviors, analyze and identify the collected data, and determine the bad driving behaviors;

[0130] Calculate the hazard score and assign a hazard score to bad driving behavior based on pre-set scoring rules;

[0131] Determine a first credit rating, calculate a corresponding sum of hazard scores within a first time range, and match the corresponding first credit rating;

[0132] A second credit rating is determined, and within a second time range, a corresponding sum of hazard scores is calculated to match the corresponding second credit rating.

[0133] Bad driving behavior includes both non-operational and operational behaviors. Non-operational behaviors include talking on the phone while driving and driving while fatigued, while operational behaviors include speeding, sudden stops, illegal lane changes, etc. Different behaviors are assigned different scores based on their degree of harmfulness, which are used to calculate the first and second credit ratings.

[0134] The assessment is based on the driver's driving behavior data. By collecting the driver's driving behavior data and identifying bad behaviors, the hazard score is calculated according to the preset scoring rules, and the driver's first credit level and second credit level are finally determined.

[0135] In one embodiment, determining a driver's first credit rating based on bad driving behavior within a first time range and determining a driver's second credit rating based on bad driving behavior within a second time range includes:

[0136] Collect data: Use monitoring devices and other equipment to collect the driver's driving behavior data, including non-operational behavior and operational behavior.

[0137] Identify bad behaviors: Analyze and identify the collected data to determine bad driving behaviors, such as talking on the phone while driving, fatigue driving, speeding, sudden stops, illegal lane changes, etc.

[0138] Calculate the hazard score: According to the preset scoring rules, the bad driving behavior is assigned a corresponding hazard score, and the score is determined according to the degree of harmfulness of the behavior.

[0139] Determine the first credit rating: within the first time range, calculate the total hazard score of the corresponding bad driving behavior, and match the total score to the corresponding first credit rating according to preset rules.

[0140] Determine the second credit rating: within the second time range, calculate the total hazard score of the corresponding bad driving behavior, and match the total score to the corresponding second credit rating according to preset rules.

[0141] By collecting driver behavior data and assessing its harmfulness, the system can accurately determine the driver's driving safety level. By calculating behavioral scores within different timeframes, it can comprehensively consider the driver's adverse driving behaviors over longer and shorter periods of time, thereby more accurately assessing the driver's driving safety. This also provides a reliable basis for subsequent driving recommendations and route planning, further enhancing driving safety and efficiency.

[0142] The first credit rating and the second credit rating of the driver are calculated based on the driving behavior in the first time range and the driving behavior in the second time range, respectively. A smaller credit rating indicates a smaller risk.

[0143] First Credit Rating Calculation: The driver's risk score is calculated and tallied within the first timeframe. For example, the driver's bad driving behavior scores over the past 168 hours are accumulated to obtain the first credit rating (L1).

[0144] Second Credit Level Calculation: Within the second timeframe, the driver's risk score is also calculated. For example, the scores for bad driving behaviors within the past three hours are accumulated to obtain the second credit level (L2).

[0145] When calculating the first credit level (L1) and the second credit level (L2), the following expression can be used to accumulate the scores:

[0146] First credit rating (L1) calculation:

[0147] L1=∑(S1_i)

[0148] Among them, S1_i represents the harm score of each bad behavior in the first time range, i represents the index of the bad behavior, and ∑ represents the summation operation.

[0149] Calculation of the second credit rating (L2):

[0150] L2=∑(S2_j)

[0151] Among them, S2_j represents the harm score of each bad behavior in the second time range, j represents the index of the bad behavior, and ∑ represents the summation operation.

[0152] The present invention calculates a first credit rating and a second credit rating by accumulating scores for the driver's bad driving behaviors within different time frames, so as to evaluate the driver's driving safety level.

[0153] In one embodiment,

[0154] First Credit Rating Calculation: Count and calculate the total harm score of the driver's bad driving behavior within a first timeframe (e.g., the past 168 hours). Accumulate the scores for bad driving behaviors within the past 168 hours to obtain the first credit rating (L1).

[0155] L1=∑(S1_i), where S1_i represents the harm score of each bad behavior within the first time range, i represents the index of the bad behavior, and ∑ represents a summation operation.

[0156] Second Credit Level Calculation: Within a second timeframe (e.g., the past three hours), the driver's bad driving behavior is similarly counted and calculated for the sum of the hazard scores. The scores for the bad driving behaviors within the past three hours are accumulated to determine the second credit level (L2).

[0157] L2=∑(S2_j), where S2_j represents the harm score of each bad behavior within the second time range, j represents the index of the bad behavior, and ∑ represents a summation operation.

[0158] This invention objectively assesses a driver's driving safety level by calculating a first credit rating and a second credit rating. By setting different timeframes, the impact of a driver's poor driving behavior over longer and shorter periods on driving safety can be comprehensively considered. By accumulating the scores for poor driving behavior, the driver's driving safety level can be quantitatively quantified and mapped to a corresponding credit rating. This solution provides an actionable method that enables drivers to clearly understand their driving safety status and take appropriate measures to improve their driving behavior and enhance driving safety.

[0159] Preferably, the calculating and obtaining the driving safety level based on the first credit level and the second credit level includes:

[0160] Set the corresponding proportion coefficient according to the size of the first credit rating and the second credit rating;

[0161] The driving safety level is calculated using the following expression:

[0162] SL=a1×L1+a2×L2

[0163] Set the corresponding proportion coefficient according to the size of the first credit rating and the second credit rating;

[0164] Among them, SL represents the driving safety level; a1 represents the proportion coefficient of the first credit level; a2 represents the proportion coefficient of the second credit level.

[0165] This formula comprehensively considers the risk of the first and second credit ratings, and uses a weighted calculation based on a set ratio to calculate the final driving safety level. A higher driving safety level indicates a lower risk.

[0166] The present invention calculates the driving safety level based on the size of the first and second credit levels by setting corresponding weighting coefficients. The calculation of the driving safety level takes into account the harmfulness of the first and second credit levels and performs a weighted calculation based on the set weighting coefficients.

[0167] The final driving safety rating is determined by comprehensively considering the riskiness of the first and second credit ratings and weighting them according to a pre-set weighting factor. A higher driving safety rating indicates lower risk. By setting an appropriate weighting factor, a driver's driving safety level can be more accurately assessed based on actual conditions. This solution provides a simple and effective method, allowing drivers to intuitively understand their driving safety level and take appropriate actions based on the assessment results, thereby improving driving safety.

[0168] Preferably, the setting of corresponding proportion coefficients according to the first credit rating and the second credit rating includes:

[0169] If both the first and second credit ratings are lower than the credit threshold, the ratio coefficients are both 0.5;

[0170] If either or both of the first credit rating and the second credit rating are greater than or equal to the threshold, the proportion coefficient of the first credit rating is less than the proportion coefficient of the second credit rating.

[0171] In one embodiment, the threshold is set to th. If the first credit rating is ≥ th and the second credit rating is ≥ th, the first proportion coefficient is 0.3 and the second proportion coefficient is 0.7.

[0172] Otherwise, the first proportion coefficient is 0.5 and the second proportion coefficient is 0.5.

[0173] The driving safety rating is calculated based on the ratio and the values ​​of the first and second credit ratings. The final driving safety rating will take into account the risk of the first and second credit ratings, with a higher driving safety rating indicating lower risk.

[0174] The present invention calculates the driving safety level by setting corresponding weighting coefficients based on the magnitude of the first and second credit levels. Based on the weighting coefficients and the values ​​of the credit levels, the final driving safety level is determined by comprehensively considering the harmfulness of the first and second credit levels.

[0175] In one embodiment,

[0176] Set a threshold: Based on actual needs, set a threshold (th) to determine whether the first credit rating and the second credit rating are greater than or equal to the threshold.

[0177] Set the ratio: Set the corresponding ratio based on the relationship between the threshold and the credit rating.

[0178] If both the first credit rating and the second credit rating are lower than the threshold, the proportion coefficient is 0.5.

[0179] If either or both of the first credit rating and the second credit rating are greater than or equal to the threshold, the proportion coefficient of the first credit rating is less than the proportion coefficient of the second credit rating.

[0180] Driving safety level calculation: Calculate the driving safety level based on the set ratio coefficient and the values ​​of the first credit level and the second credit level.

[0181] The final driving safety rating will take into account the harmfulness of the first and second credit ratings, with a higher driving safety rating indicating lower danger.

[0182] By setting a threshold value and a proportion coefficient, the present invention can calculate a driving safety level that comprehensively considers the harmfulness of the first credit level and the second credit level based on the size of the two. If both credit levels are less than the threshold value, it means that the driving behavior is relatively safe, and the proportion coefficient is 0.5, which affects the driving safety level equally. If one or both are greater than or equal to the threshold value, it means that the driving behavior has a certain degree of danger. At this time, the proportion coefficient of the first credit level is less than the proportion coefficient of the second credit level, and more attention is paid to the impact of the second credit level. The final driving safety level will comprehensively consider the harmfulness of both, and a higher level indicates a lower risk. By flexibly adjusting the proportion coefficient, this solution can accurately evaluate and reflect the driving safety level according to actual needs and evaluation standards.

[0183] Preferably, the nearby vehicles are vehicles within a preset radius with the vehicle as the center.

[0184] Specifically:

[0185] Determine the vehicle's location: Obtain the vehicle's accurate location information, which can be obtained through on-board sensors, GPS, etc.

[0186] Set Radius: Based on actual needs and traffic conditions, you can set a preset radius. This radius is centered around your vehicle's location and determines the range of surrounding vehicles that need to be considered.

[0187] Identify nearby vehicles: Utilize vehicle detection and recognition technology to detect and identify vehicles within a radius. This can be achieved using sensor data, image processing algorithms, etc.

[0188] Data filtering and screening: Filter and screen the identified nearby vehicle data according to specific needs.

[0189] Further processing: Based on the identified nearby vehicle information, further processing and analysis are performed, including evaluating the vehicle's safety level, tracking the vehicle's behavior, and planning the driving path.

[0190] By setting a radius, this solution can limit the range of nearby vehicles to be considered, making analysis and processing more focused and accurate. The process of identifying and screening nearby vehicles can be flexibly adjusted to meet specific needs and meet different driving safety requirements. This solution can help drivers better perceive and respond to the dangers of surrounding vehicles, thereby improving driving safety and comfort.

[0191] Preferably, Figure 3 As shown, the short-distance driving plan for staying away from potentially dangerous vehicles based on the driving safety levels of nearby vehicles includes:

[0192] Obtain driving safety level information of nearby vehicles;

[0193] Set warning thresholds to identify nearby potentially dangerous vehicles;

[0194] Screen out potentially dangerous vehicles;

[0195] Based on the filtered dangerous vehicles, a new short-term path is planned using an avoidance strategy based on the vehicle's position and destination.

[0196] Generate a short-distance driving plan based on the short-term path updated by the avoidance strategy.

[0197] Based on the driving safety level information of nearby vehicles, this invention screens out potentially dangerous vehicles and develops short-distance driving strategies away from them. By acquiring driving safety level information and setting warning thresholds, potentially dangerous vehicles can be identified and a safe driving path can be planned through path planning and avoidance strategies.

[0198] In one embodiment, the driving safety level information of nearby vehicles is obtained: the driving safety level information of nearby vehicles, including the vehicle's behavior, speed, distance, and other information, is obtained using a vehicle perception system, a traffic monitoring system, or other related technologies.

[0199] Set a warning threshold: Based on safety requirements and specific circumstances, set a warning threshold to identify potentially dangerous vehicles. This threshold can be set based on factors such as driving experience and traffic regulations.

[0200] Screening dangerous vehicles: Based on the driving safety level information of nearby vehicles, screen out vehicles whose driving safety level exceeds the warning threshold, that is, vehicles with potential dangers.

[0201] Path planning based on the vehicle's location and destination: A path planning algorithm is used to calculate a new short-term path based on the vehicle's current location and destination. When planning a path, the system considers avoiding areas or road sections where potentially dangerous vehicles are located.

[0202] Generate a short-distance driving plan: Based on the short-term path updated with the avoidance strategy, a final short-distance driving plan is generated. This plan will provide the driver with necessary steering instructions, speed recommendations, and other information to help the driver safely avoid dangerous vehicles.

[0203] The present invention, based on the driving safety level information of nearby vehicles and the setting of warning thresholds, can screen out potentially dangerous vehicles and formulate safe driving plans through path planning and avoidance strategies. Drivers can avoid dangerous vehicles based on the generated short-distance driving plan, thereby improving driving safety. This solution can help drivers better perceive and respond to the dangers of surrounding vehicles, reduce the risk of potential traffic accidents, improve driving safety, and promote the smoothness of road traffic. By avoiding potentially dangerous vehicles, drivers can reduce contact and conflicts with them, reducing the probability of accidents. In addition, the application of path planning and avoidance strategies can also improve the driver's driving experience, reduce traffic jams and congestion, and improve overall road traffic efficiency.

[0204] By comprehensively considering the driving safety levels of nearby vehicles, warning thresholds, and path planning, the present invention can quickly respond to traffic changes and adjust driving plans in real time, enabling drivers to drive safely and efficiently. Effectively identifying and avoiding potentially dangerous vehicles can proactively detect potential traffic hazards, helping drivers prevent accidents and providing more reliable navigation guidance.

[0205] This technology uses information about the driving safety levels of nearby vehicles to screen for dangerous vehicles and develop avoidance strategies, providing drivers with safer and more reliable driving solutions. It can reduce potential traffic accident risks, improve driver safety and comfort, and enhance overall road traffic conditions, providing a better travel experience.

[0206] Preferably, the path information includes: a congestion score, a driving distance score, and an estimated time score.

[0207] Route information evaluation is based on a comprehensive consideration of congestion scores, travel distance scores, and estimated time scores. These scores help drivers choose the best route, taking into account factors such as traffic congestion, travel distance, and estimated time of arrival to provide the best driving plan.

[0208] Congestion Score: Each road is evaluated and scored based on real-time traffic volume and congestion conditions. A higher congestion score indicates a more congested road section and slower travel speeds.

[0209] Driving distance score: The route is evaluated and scored based on the actual driving distance. Generally, shorter driving distances are scored higher because they reduce driving time and fuel consumption.

[0210] Estimated Time Score: Evaluates and scores based on the estimated time it will take to reach your destination. A shorter estimated time score means you can reach your destination faster.

[0211] These scoring indicators can be calculated and updated based on real-time traffic data and path planning algorithms to provide accurate path evaluation results.

[0212] By evaluating route information such as congestion, travel distance, and estimated time, drivers can choose the best driving plan. This has the following effects:

[0213] Reduce travel time: Choosing routes with less congestion, shorter distances, and shorter estimated times can help drivers reach their destinations faster, saving time and energy.

[0214] Reduce fuel consumption and emissions: Choosing a shorter driving distance can reduce the vehicle's fuel consumption and emissions, which is more environmentally friendly.

[0215] Improve driving comfort: Avoiding congested roads and choosing routes with shorter estimated travel times can reduce drivers' time stuck in traffic jams and improve driving comfort and experience.

[0216] In summary, by evaluating route information such as congestion conditions, driving distance, and estimated time, the best driving plan can be provided to the driver, reducing driving time, lowering fuel consumption, improving driving comfort, and optimizing overall traffic mobility.

[0217] Preferably, the calculation expression for obtaining the score of each pre-selected path through the path information is:

[0218] Score=b1×C+b2×D+b3×T

[0219] Among them, Score represents the path score; C represents the congestion score; D represents the driving distance score; T represents the estimated time score; b1, b2, and b3 represent the weight parameters of the congestion score, driving distance score, and estimated time score, respectively.

[0220] The route score is calculated based on a weighted sum of the congestion score, travel distance score, and estimated travel time score. By assigning appropriate weights to each metric, the impact of different factors on the route is comprehensively considered, resulting in a final score for each preselected route.

[0221] Congestion Score (C): This is an assessment and scoring based on the real-time traffic volume and congestion conditions of the road. A higher congestion score indicates a higher degree of congestion on the road section.

[0222] Driving distance score (D): Evaluates and scores based on the actual driving distance of the route. A shorter driving distance scores higher because it reduces driving time and fuel consumption.

[0223] Estimated Time Score (T): Evaluates and scores based on the estimated time required to reach the destination. A shorter estimated time score indicates a faster arrival time.

[0224] Weight parameters (b1, b2, b3): These parameters are used to adjust the relative importance of different scoring indicators. By setting appropriate weight parameters, the weights of different scoring indicators can be determined according to specific needs and priorities.

[0225] By calculating the path score, a comprehensive evaluation index can be provided for each pre-selected path to assist the driver in selecting the best driving plan. Specific effects include:

[0226] Comprehensive consideration of multiple factors: Through weighted summation, multiple factors such as congestion, driving distance and estimated time are taken into account to provide a comprehensive path evaluation.

[0227] Personalized selection: By adjusting weight parameters, you can flexibly select a route that prioritizes congestion, travel distance, or estimated time based on the driver's personal preferences and needs.

[0228] Provide a reference basis: Route scoring provides drivers with a quantitative indicator that can be used as a reference for decision-making, helping drivers make more informed route choices.

[0229] In summary, the calculation expression for route scoring and the setting of weighting parameters can comprehensively consider factors such as congestion, driving distance, and estimated time, providing drivers with quantitative route selection recommendations and references. Drivers can compare the scores of different routes based on the route score and select the higher-scoring route as their driving plan. This helps drivers avoid congested roads, achieve shorter driving distances, and achieve faster arrival times, thereby improving driving efficiency and saving time. Furthermore, route scoring provides an objective metric, enabling drivers to make more rational route selection decisions and reducing the influence of subjective factors.

[0230] By comprehensively considering scoring metrics such as congestion, driving distance, and estimated time, drivers can better plan their routes, reducing potential traffic delays and congestion, and improving overall driving safety and efficiency. Furthermore, the use of route scoring can encourage drivers to develop safer driving habits by being more inclined to choose routes with higher scores and avoid those with lower scores and potentially riskier routes.

[0231] By calculating the scoring of route information and providing drivers with quantitative route selection suggestions, it can help them make more informed driving decisions, reduce potential traffic accident risks, and improve driving safety and efficiency.

[0232] Preferably, the expression for calculating the optimal vehicle speed is:

[0233] V=(1-α)×V1+α×V3

[0234] Where V represents the optimal speed of the ego vehicle; V1 represents the recommended speed for the optimal path; V3 represents the average speed of nearby vehicles; and the α parameter represents the willingness of the ego vehicle to maintain a similar speed to nearby vehicles.

[0235] When V>V2, then V=V2

[0236] Among them, V2 represents the road speed limit.

[0237] A larger α parameter indicates that the driver prefers to maintain a similar speed to nearby vehicles, seeking speed consistency and stability. In this case, the adjusted optimal speed V is closer to the average speed of nearby vehicles, maintaining a similar driving state. This improves coordination and safety between vehicles, helping to cope with emergencies.

[0238] Conversely, a smaller α parameter indicates that the driver prefers to stay closer to the route planner's recommended speed V1, meaning they place more emphasis on the route planner's recommendations. In this case, the adjusted optimal speed V is closer to the recommended speed, allowing for faster destination arrival. However, a smaller α parameter may result in a larger speed difference between the vehicle and nearby vehicles, reducing inter-vehicle coordination and safety.

[0239] The optimal speed expression is used to calculate the optimal speed of the ego vehicle, taking into account the recommended speed of the optimal path and the average speed of nearby vehicles. The α parameter is used to adjust the willingness of the ego vehicle to maintain a similar speed to nearby vehicles.

[0240] Based on this expression, the ego vehicle's optimal speed, V, is calculated through linear interpolation, combining the recommended speed V1 for the optimal path and the average speed V3 of nearby vehicles. The α parameter adjusts the ego vehicle's willingness to maintain a similar speed to nearby vehicles. A larger α parameter increases the ego vehicle's preference for maintaining a similar speed to nearby vehicles; a smaller α parameter increases the ego vehicle's preference for a speed closer to the recommended speed for the optimal path.

[0241] In one embodiment, specifically:

[0242] Obtain the recommended speed V1 for the optimal path planning;

[0243] Get the average speed V3 of nearby vehicles.

[0244] The setting value of the α parameter determines the willingness of the vehicle to maintain a similar speed to nearby vehicles.

[0245] According to the expression V = (1-α) × V1 + α × V3

[0246] Calculate the optimal vehicle speed V.

[0247] If the calculated optimal vehicle speed V exceeds the road speed limit V2, the optimal vehicle speed is limited to the road speed limit V2.

[0248] Effect: By calculating the optimal speed of the ego vehicle, it can be adjusted according to the driver's preference for speed consistency and path planning suggestions. When the α parameter is large, the ego vehicle tends to maintain a speed similar to that of nearby vehicles to improve coordination and safety between vehicles. When the α parameter is small, the ego vehicle tends to be closer to the recommended speed of path planning to reach the destination faster. This can balance speed consistency, safety, and arrival efficiency according to the driver's wishes and road conditions. However, too small or too large an α parameter value may result in a large difference with nearby vehicles or an excessive pursuit of speed consistency, affecting coordination and safety between vehicles.

[0249] In summary, this method calculates the optimal speed of the vehicle, takes into account the recommended speed of the optimal path and the average speed of nearby vehicles, and adjusts the speed according to the driver's willingness to achieve a balance between speed coordination, safety, and arrival efficiency.

[0250] Therefore, the selection of the α parameter should be adjusted according to the driver's usage needs and personal preferences to balance driving safety and efficiency. Drivers can choose the appropriate α parameter value based on traffic conditions, road conditions, and personal driving habits to meet their needs.

[0251] The route planning recommended speed V1 is the ideal speed for given road conditions, calculated by the system's route planning algorithm. It takes into account multiple factors, such as road speed limits, traffic flow, and road conditions, to provide the driver with a reasonable recommended speed.

[0252] However, V1 is an ideal speed calculated by a path planning algorithm, taking into account factors such as road speed limits, traffic flow, and road conditions. It is a recommended speed based on road conditions and the optimal driving strategy, without considering the impact of nearby vehicles.

[0253] V is the optimal speed, adjusted based on the speeds of nearby vehicles. It is calculated based on the recommended speed (V1) from route planning and the average speed of nearby vehicles. By incorporating speed information from nearby vehicles, V can better adapt to the current traffic environment, improving driving safety and smoothness.

[0254] In general, V1 is the result of path planning and is an ideal recommended speed, while V is the optimal speed adjusted based on actual traffic conditions and the speeds of nearby vehicles. V takes into account more real-time traffic information to enable the vehicle to better adapt to current road conditions and maintain a certain speed coordination with surrounding vehicles.

[0255] Preferably, Figure 4 As shown, the periodic adjustment of the optimal vehicle speed includes:

[0256] S1. determining a cycle for adjusting the optimal vehicle speed;

[0257] S2. At the beginning of each adjustment cycle, record the current time as the starting time;

[0258] S3. Obtain the speed of nearby vehicles;

[0259] S4. calculating the adjusted optimal vehicle speed;

[0260] S5. Setting the calculated adjusted optimal vehicle speed as the target vehicle speed;

[0261] S6. During the adjustment period, monitor the driving condition and speed change of the vehicle;

[0262] S7. When the current time minus the start time reaches the set adjustment period, the next adjustment period is entered and steps S2 to S7 are repeated.

[0263] The present invention sets an adjustment cycle, records the start time at the beginning of each adjustment cycle, obtains the speed of nearby vehicles, and sets the target speed of the vehicle based on the calculated adjusted optimal speed. The vehicle's driving conditions and speed changes are monitored, and the next adjustment cycle begins when the set adjustment cycle is reached, repeating the above steps.

[0264] In one embodiment, a period for adjusting the optimal vehicle speed is set, such as every minute, every hour, or every time the vehicle is started.

[0265] At the beginning of each adjustment cycle, the current time is recorded as the start time.

[0266] The speed information of nearby vehicles can be obtained through vehicle sensors, vehicle communications or vehicle location information.

[0267] According to the previous method (such as the expression mentioned above), the adjusted optimal vehicle speed is calculated.

[0268] The calculated adjusted optimal vehicle speed is set as the target vehicle speed of the vehicle, which can be set through the vehicle's control system.

[0269] During the adjustment period, the driving condition and speed changes of the vehicle are continuously monitored, which can be done using vehicle sensors or a vehicle control system.

[0270] When the current time minus the start time reaches the set adjustment period, the next adjustment period is entered and steps 2 to 6 are executed again.

[0271] The effect is that periodic adjustments to the optimal speed allow the driver to maintain a reasonable speed under varying road conditions and traffic environments. By acquiring real-time speed information from nearby vehicles and calculating the adjusted optimal speed, the vehicle can better adapt to road changes. This adjusted optimal speed serves as the vehicle's target speed, helping the driver better control the vehicle and improving driving smoothness, safety, and fuel efficiency. Furthermore, periodic adjustments allow for flexible adaptation to actual conditions, maintaining a reasonable and stable speed.

[0272] In summary, this method helps the driver maintain a reasonable speed under different road and traffic conditions by periodically adjusting the optimal speed and combining the speed information of nearby vehicles with the calculated adjusted optimal speed, thereby improving driving smoothness and safety.

[0273] like Figure 5 As shown, a driving planning system includes:

[0274] An image monitoring device, installed inside the vehicle, for acquiring image data of the driver's behavior;

[0275] An operation recording device, the operation recording device is used to record the driver's driving behavior;

[0276] A central server, which is used to centrally collect, process and store real-time data uploaded by vehicles;

[0277] A data processing and analysis subsystem, which is located on a central server and is configured to receive, parse, and process data transmitted from vehicles, determine a first credit rating of the driver based on bad driving behavior within a first time range, determine a second credit rating of the driver based on bad driving behavior within a second time range, and calculate a driving safety rating based on the first and second credit ratings; formulate a short-distance driving plan away from potentially dangerous vehicles based on the driving safety levels of nearby vehicles; obtain a score for each pre-selected path based on path information and select the path with the highest score as the optimal path; calculate an optimal speed for the vehicle based on the recommended speed of the optimal path and the average speed of nearby vehicles, and periodically adjust the optimal speed;

[0278] The vehicle control device is used to adjust the vehicle in real time and complete driving planning based on the processing results of the data processing and analysis subsystem.

[0279] Specifically:

[0280] Image monitoring device: installed inside the vehicle, used to obtain driver behavior image data, such as driving posture, eye movements, smoking, etc., to identify violations such as fatigue driving and one-handed driving.

[0281] Operation recording device: records the driver's driving behavior, including acceleration, braking, steering and other operations, and is used in conjunction with other equipment to identify speeding, sudden stops, and illegal lane changes.

[0282] Central server: Centrally collects, processes and stores real-time data uploaded by vehicles, including image data and driving behavior data.

[0283] Data Processing and Analysis Subsystem: This subsystem, located on a central server, receives, analyzes, and processes data transmitted from vehicles. By analyzing the driver's poor driving behavior over different timeframes, it determines the driver's first and second credit ratings. Based on these ratings, a driving safety rating is calculated.

[0284] Based on the driving safety level of nearby vehicles: Develop short-distance driving plans away from potentially dangerous vehicles based on the driving safety level of nearby vehicles.

[0285] Route information scoring: Calculates a score for each preselected route based on route information including congestion score, travel distance score, and estimated time score, and selects the route with the highest score as the optimal route.

[0286] Optimal speed calculation and adjustment: Calculates the optimal speed for the vehicle based on the recommended speed for the optimal route and the average speed of nearby vehicles. Periodically adjusts the optimal speed to adapt to varying road conditions and traffic environments.

[0287] Vehicle control device: Based on the processing results of the data processing and analysis subsystem, the vehicle is adjusted in real time to complete driving planning.

[0288] The drive planning system is designed to improve driving safety and efficiency by:

[0289] Driver behavior monitoring: The driver's behavior data is obtained through image monitoring devices and operation recording devices, and driving behavior is monitored and recorded in order to evaluate the driver's driving behavior and safety.

[0290] Credit rating assessment: By analyzing the driver's bad driving behavior over different time frames, the driver's first and second credit ratings are determined to quantify the driver's driving ability and risk level.

[0291] Driving safety level calculation: The driving safety level is calculated based on the calculation results of the first credit level and the second credit level, combined with the driving safety levels of nearby vehicles.

[0292] Short-distance driving strategies: Develop short-distance driving strategies to avoid potentially dangerous vehicles based on the driving safety levels of nearby vehicles. By screening potentially dangerous vehicles and using avoidance strategies based on the vehicle's location and destination, the system plans new short-term routes to reduce potential traffic accident risks.

[0293] Route Evaluation and Selection: Each preselected route is scored by evaluating congestion, distance, and estimated travel time. The highest-scoring route is selected as the optimal route, allowing the driver to select the optimal route to improve driving efficiency and avoid congestion.

[0294] Optimal Speed ​​Calculation and Adjustment: The optimal speed is calculated based on the recommended speed for the optimal route and the average speed of nearby vehicles. The optimal speed is periodically adjusted to adapt to varying road speed limits and traffic conditions. Drivers can choose to maintain a similar speed to nearby vehicles based on their preferences and actual conditions, balancing speed consistency and driving efficiency.

[0295] Through the above principles and implementation methods, the driving planning system provides drivers with quantitative driving safety assessments and guidance. Based on driving safety levels, short-distance driving plans, and optimal routes and speed recommendations, drivers can make more informed driving decisions. The system's benefits include improved driving safety, reduced potential traffic accident risks, optimized route selection, and improved driving efficiency. Furthermore, through real-time monitoring and data processing and analysis, the system can provide timely adjustment instructions to vehicle control devices, further enhancing the effectiveness and practicality of driving planning.

[0296] Preferably, the first time range and the second time range both represent a specified time range with the current time as the starting node, wherein the first time range is larger than the second time range.

[0297] Set the first time range and the second time range: the first time range refers to a longer specified time range in the past, such as the past 168 hours; the second time range refers to a shorter specified time range in the past, such as the past 3 hours.

[0298] The present invention evaluates a driver's driving behavior data and determines the driver's credit rating by setting a first time range and a second time range. The first time range represents driving behavior over a longer period of time, while the second time range represents driving behavior over a shorter period of time. The driver's first and second credit ratings are determined by analyzing and evaluating bad driving behavior within these two time ranges.

[0299] Set the first time range and the second time range: the first time range is a longer specified time range in the past, such as the past 168 hours (7 days), and the second time range is a shorter specified time range in the past, such as the past 3 hours.

[0300] Collecting driver behavior data: Use monitoring devices and violation recording devices to collect driver non-operational and operational behavior data, such as talking on the phone while driving, speeding, and sudden stops.

[0301] Evaluate driving behavior within a first time frame: Based on the driving behavior data within the first time frame, calculate the driver's first credit rating, which is used to represent the safety of driving behavior over a longer period of time.

[0302] Evaluate driving behavior within a second time frame: Based on the driving behavior data within the second time frame, calculate the driver's second credit rating, which is used to indicate the safety of driving behavior within a shorter period of time.

[0303] By setting both the first and second time ranges, the driver's driving behavior over longer periods of time can be comprehensively considered, leading to a more accurate assessment of their driving safety. This approach provides a more comprehensive analysis of driving behavior and a more accurate basis for subsequent driving recommendations and route planning. By assessing the driving safety level, the driver and the autonomous driving system can receive real-time driving recommendations, improving driving safety and efficiency.

[0304] Preferably, determining the driver's first credit rating based on bad driving behavior within a first time range and determining the driver's second credit rating based on bad driving behavior within a second time range includes:

[0305] Collect data, collect the driver's driving behavior data;

[0306] Identify bad behaviors, analyze and identify the collected data, and determine the bad driving behaviors;

[0307] Calculate the hazard score and assign a hazard score to bad driving behavior based on pre-set scoring rules;

[0308] Determine a first credit rating, calculate a corresponding sum of hazard scores within a first time range, and match the corresponding first credit rating;

[0309] A second credit rating is determined, and within a second time range, a corresponding sum of hazard scores is calculated to match the corresponding second credit rating.

[0310] Bad driving behavior includes both non-operational and operational behaviors. Non-operational behaviors include talking on the phone while driving and driving while fatigued, while operational behaviors include speeding, sudden stops, illegal lane changes, etc. Different behaviors are assigned different scores based on their degree of harmfulness, which are used to calculate the first and second credit ratings.

[0311] The assessment is based on the driver's driving behavior data. By collecting the driver's driving behavior data and identifying bad behaviors, the hazard score is calculated according to the preset scoring rules, and the driver's first credit level and second credit level are finally determined.

[0312] In one embodiment, determining a driver's first credit rating based on bad driving behavior within a first time range and determining a driver's second credit rating based on bad driving behavior within a second time range includes:

[0313] Collect data: Use monitoring devices and other equipment to collect the driver's driving behavior data, including non-operational behavior and operational behavior.

[0314] Identify bad behaviors: Analyze and identify the collected data to determine bad driving behaviors, such as talking on the phone while driving, fatigue driving, speeding, sudden stops, illegal lane changes, etc.

[0315] Calculate the hazard score: According to the preset scoring rules, the bad driving behavior is assigned a corresponding hazard score, and the score is determined according to the degree of harmfulness of the behavior.

[0316] Determine the first credit rating: within the first time range, calculate the total hazard score of the corresponding bad driving behavior, and match the total score to the corresponding first credit rating according to preset rules.

[0317] Determine the second credit rating: within the second time range, calculate the total hazard score of the corresponding bad driving behavior, and match the total score to the corresponding second credit rating according to preset rules.

[0318] By collecting driver behavior data and assessing its harmfulness, the system can accurately determine the driver's driving safety level. By calculating behavioral scores within different timeframes, it can comprehensively consider the driver's adverse driving behaviors over longer and shorter periods of time, thereby more accurately assessing the driver's driving safety. This also provides a reliable basis for subsequent driving recommendations and route planning, further enhancing driving safety and efficiency.

[0319] The first credit rating and the second credit rating of the driver are calculated based on the driving behavior in the first time range and the driving behavior in the second time range, respectively. A smaller credit rating indicates a smaller risk.

[0320] First Credit Rating Calculation: The driver's risk score is calculated and tallied within the first timeframe. For example, the driver's bad driving behavior scores over the past 168 hours are accumulated to obtain the first credit rating (L1).

[0321] Second Credit Level Calculation: Within the second timeframe, the driver's risk score is also calculated. For example, the scores for bad driving behaviors within the past three hours are accumulated to obtain the second credit level (L2).

[0322] When calculating the first credit level (L1) and the second credit level (L2), the following expression can be used to accumulate the scores:

[0323] First credit rating (L1) calculation:

[0324] L1=∑(S1_i)

[0325] Among them, S1_i represents the harm score of each bad behavior in the first time range, i represents the index of the bad behavior, and ∑ represents the summation operation.

[0326] Calculation of the second credit rating (L2):

[0327] L2=∑(S2_j)

[0328] Among them, S2_j represents the harm score of each bad behavior in the second time range, j represents the index of the bad behavior, and ∑ represents the summation operation.

[0329] The present invention calculates a first credit rating and a second credit rating by accumulating scores for the driver's bad driving behaviors within different time frames, so as to evaluate the driver's driving safety level.

[0330] In one embodiment,

[0331] First Credit Rating Calculation: Count and calculate the total harm score of the driver's bad driving behavior within a first timeframe (e.g., the past 168 hours). Accumulate the scores for bad driving behaviors within the past 168 hours to obtain the first credit rating (L1).

[0332] L1=∑(S1_i), where S1_i represents the harm score of each bad behavior within the first time range, i represents the index of the bad behavior, and ∑ represents a summation operation.

[0333] Second Credit Level Calculation: Within a second timeframe (e.g., the past three hours), the driver's bad driving behavior is similarly counted and calculated for the sum of the hazard scores. The scores for the bad driving behaviors within the past three hours are accumulated to determine the second credit level (L2).

[0334] L2=∑(S2_j), where S2_j represents the harm score of each bad behavior within the second time range, j represents the index of the bad behavior, and ∑ represents a summation operation.

[0335] This invention objectively assesses a driver's driving safety level by calculating a first credit rating and a second credit rating. By setting different timeframes, the impact of a driver's poor driving behavior over longer and shorter periods on driving safety can be comprehensively considered. By accumulating the scores for poor driving behavior, the driver's driving safety level can be quantitatively quantified and mapped to a corresponding credit rating. This solution provides an actionable method that enables drivers to clearly understand their driving safety status and take appropriate measures to improve their driving behavior and enhance driving safety.

[0336] Preferably, the calculating and obtaining the driving safety level based on the first credit level and the second credit level includes:

[0337] Set the corresponding proportion coefficient according to the size of the first credit rating and the second credit rating;

[0338] The driving safety level is calculated using the following expression:

[0339] SL=a1×L1+a2×L2

[0340] Set the corresponding proportion coefficient according to the size of the first credit rating and the second credit rating;

[0341] Among them, SL represents the driving safety level; a1 represents the proportion coefficient of the first credit level; a2 represents the proportion coefficient of the second credit level.

[0342] This formula comprehensively considers the risk of the first and second credit ratings, and uses a weighted calculation based on a set ratio to calculate the final driving safety level. A higher driving safety level indicates a lower risk.

[0343] The present invention calculates the driving safety level based on the size of the first and second credit levels by setting corresponding weighting coefficients. The calculation of the driving safety level takes into account the harmfulness of the first and second credit levels and performs a weighted calculation based on the set weighting coefficients.

[0344] The final driving safety rating is determined by comprehensively considering the riskiness of the first and second credit ratings and weighting them according to a pre-set weighting factor. A higher driving safety rating indicates lower risk. By setting an appropriate weighting factor, a driver's driving safety level can be more accurately assessed based on actual conditions. This solution provides a simple and effective method, allowing drivers to intuitively understand their driving safety level and take appropriate actions based on the assessment results, thereby improving driving safety.

[0345] Preferably, the setting of corresponding proportion coefficients according to the first credit rating and the second credit rating includes:

[0346] If both the first and second credit ratings are lower than the credit threshold, the ratio coefficients are both 0.5;

[0347] If either or both of the first credit rating and the second credit rating are greater than or equal to the threshold, the proportion coefficient of the first credit rating is less than the proportion coefficient of the second credit rating.

[0348] In one embodiment, the threshold is set to th. If the first credit rating is ≥ th and the second credit rating is ≥ th, the first proportion coefficient is 0.3 and the second proportion coefficient is 0.7.

[0349] Otherwise, the first proportion coefficient is 0.5 and the second proportion coefficient is 0.5.

[0350] The driving safety rating is calculated based on the ratio and the values ​​of the first and second credit ratings. The final driving safety rating will take into account the risk of the first and second credit ratings, with a higher driving safety rating indicating lower risk.

[0351] The present invention calculates the driving safety level by setting corresponding weighting coefficients based on the magnitude of the first and second credit levels. Based on the weighting coefficients and the values ​​of the credit levels, the final driving safety level is determined by comprehensively considering the harmfulness of the first and second credit levels.

[0352] In one embodiment,

[0353] Set a threshold: Based on actual needs, set a threshold (th) to determine whether the first credit rating and the second credit rating are greater than or equal to the threshold.

[0354] Set the ratio: Set the corresponding ratio based on the relationship between the threshold and the credit rating.

[0355] If both the first credit rating and the second credit rating are lower than the threshold, the proportion coefficient is 0.5.

[0356] If either or both of the first credit rating and the second credit rating are greater than or equal to the threshold, the proportion coefficient of the first credit rating is less than the proportion coefficient of the second credit rating.

[0357] Driving safety level calculation: Calculate the driving safety level based on the set ratio coefficient and the values ​​of the first credit level and the second credit level.

[0358] The final driving safety rating will take into account the harmfulness of the first and second credit ratings, with a higher driving safety rating indicating lower danger.

[0359] By setting a threshold value and a proportion coefficient, the present invention can calculate a driving safety level that comprehensively considers the harmfulness of the first credit level and the second credit level based on the size of the two. If both credit levels are less than the threshold value, it means that the driving behavior is relatively safe, and the proportion coefficient is 0.5, which affects the driving safety level equally. If one or both are greater than or equal to the threshold value, it means that the driving behavior has a certain degree of danger. At this time, the proportion coefficient of the first credit level is less than the proportion coefficient of the second credit level, and more attention is paid to the impact of the second credit level. The final driving safety level will comprehensively consider the harmfulness of both, and a higher level indicates a lower risk. By flexibly adjusting the proportion coefficient, this solution can accurately evaluate and reflect the driving safety level according to actual needs and evaluation standards.

[0360] Preferably, the nearby vehicles are vehicles within a preset radius with the vehicle as the center.

[0361] Specifically:

[0362] Determine the vehicle's location: Obtain the vehicle's accurate location information, which can be obtained through on-board sensors, GPS, etc.

[0363] Set Radius: Based on actual needs and traffic conditions, you can set a preset radius. This radius is centered around your vehicle's location and determines the range of surrounding vehicles that need to be considered.

[0364] Identify nearby vehicles: Utilize vehicle detection and recognition technology to detect and identify vehicles within a radius. This can be achieved using sensor data, image processing algorithms, etc.

[0365] Data filtering and screening: Filter and screen the identified nearby vehicle data according to specific needs.

[0366] Further processing: Based on the identified nearby vehicle information, further processing and analysis are performed, including evaluating the vehicle's safety level, tracking the vehicle's behavior, and planning the driving path.

[0367] By setting a radius, this solution can limit the range of nearby vehicles to be considered, making analysis and processing more focused and accurate. The process of identifying and screening nearby vehicles can be flexibly adjusted to meet specific needs and meet different driving safety requirements. This solution can help drivers better perceive and respond to the dangers of surrounding vehicles, thereby improving driving safety and comfort.

[0368] Preferably, formulating a short-distance driving plan away from potentially dangerous vehicles based on the driving safety levels of nearby vehicles includes:

[0369] Obtain driving safety level information of nearby vehicles;

[0370] Set warning thresholds to identify nearby potentially dangerous vehicles;

[0371] Screen out potentially dangerous vehicles;

[0372] Based on the filtered dangerous vehicles, a new short-term path is planned using an avoidance strategy based on the vehicle's position and destination.

[0373] Generate a short-distance driving plan based on the short-term path updated by the avoidance strategy.

[0374] Based on the driving safety level information of nearby vehicles, this invention screens out potentially dangerous vehicles and develops short-distance driving strategies away from them. By acquiring driving safety level information and setting warning thresholds, potentially dangerous vehicles can be identified and a safe driving path can be planned through path planning and avoidance strategies.

[0375] In one embodiment, the driving safety level information of nearby vehicles is obtained: the driving safety level information of nearby vehicles, including the vehicle's behavior, speed, distance, and other information, is obtained using a vehicle perception system, a traffic monitoring system, or other related technologies.

[0376] Set a warning threshold: Based on safety requirements and specific circumstances, set a warning threshold to identify potentially dangerous vehicles. This threshold can be set based on factors such as driving experience and traffic regulations.

[0377] Screening dangerous vehicles: Based on the driving safety level information of nearby vehicles, screen out vehicles whose driving safety level exceeds the warning threshold, that is, vehicles with potential dangers.

[0378] Path planning based on the vehicle's location and destination: A path planning algorithm is used to calculate a new short-term path based on the vehicle's current location and destination. When planning a path, the system considers avoiding areas or road sections where potentially dangerous vehicles are located.

[0379] Generate a short-distance driving plan: Based on the short-term path updated with the avoidance strategy, a final short-distance driving plan is generated. This plan will provide the driver with necessary steering instructions, speed recommendations, and other information to help the driver safely avoid dangerous vehicles.

[0380] The present invention, based on the driving safety level information of nearby vehicles and the setting of warning thresholds, can screen out potentially dangerous vehicles and formulate safe driving plans through path planning and avoidance strategies. Drivers can avoid dangerous vehicles based on the generated short-distance driving plan, thereby improving driving safety. This solution can help drivers better perceive and respond to the dangers of surrounding vehicles, reduce the risk of potential traffic accidents, improve driving safety, and promote the smoothness of road traffic. By avoiding potentially dangerous vehicles, drivers can reduce contact and conflicts with them, reducing the probability of accidents. In addition, the application of path planning and avoidance strategies can also improve the driver's driving experience, reduce traffic jams and congestion, and improve overall road traffic efficiency.

[0381] By comprehensively considering the driving safety levels of nearby vehicles, warning thresholds, and path planning, the present invention can quickly respond to traffic changes and adjust driving plans in real time, enabling drivers to drive safely and efficiently. Effectively identifying and avoiding potentially dangerous vehicles can proactively detect potential traffic hazards, helping drivers prevent accidents and providing more reliable navigation guidance.

[0382] This technology uses information about the driving safety levels of nearby vehicles to screen for dangerous vehicles and develop avoidance strategies, providing drivers with safer and more reliable driving solutions. It can reduce potential traffic accident risks, improve driver safety and comfort, and enhance overall road traffic conditions, providing a better travel experience.

[0383] Preferably, the path information includes: a congestion score, a driving distance score, and an estimated time score.

[0384] Route information evaluation is based on a comprehensive consideration of congestion scores, travel distance scores, and estimated time scores. These scores help drivers choose the best route, taking into account factors such as traffic congestion, travel distance, and estimated time of arrival to provide the best driving plan.

[0385] Congestion Score: Each road is evaluated and scored based on real-time traffic volume and congestion conditions. A higher congestion score indicates a more congested road section and slower travel speeds.

[0386] Driving distance score: The route is evaluated and scored based on the actual driving distance. Generally, shorter driving distances are scored higher because they reduce driving time and fuel consumption.

[0387] Estimated Time Score: Evaluates and scores based on the estimated time it will take to reach your destination. A shorter estimated time score means you can reach your destination faster.

[0388] These scoring indicators can be calculated and updated based on real-time traffic data and path planning algorithms to provide accurate path evaluation results.

[0389] By evaluating route information such as congestion, travel distance, and estimated time, drivers can choose the best driving plan. This has the following effects:

[0390] Reduce travel time: Choosing routes with less congestion, shorter distances, and shorter estimated times can help drivers reach their destinations faster, saving time and energy.

[0391] Reduce fuel consumption and emissions: Choosing a shorter driving distance can reduce the vehicle's fuel consumption and emissions, which is more environmentally friendly.

[0392] Improve driving comfort: Avoiding congested roads and choosing routes with shorter estimated travel times can reduce drivers' time stuck in traffic jams and improve driving comfort and experience.

[0393] In summary, by evaluating route information such as congestion conditions, driving distance, and estimated time, the best driving plan can be provided to the driver, reducing driving time, lowering fuel consumption, improving driving comfort, and optimizing overall traffic mobility.

[0394] Preferably, the calculation expression for obtaining the score of each pre-selected path through the path information is:

[0395] Score=b1×C+b2×D+b3×T

[0396] Among them, Score represents the path score; C represents the congestion score; D represents the driving distance score; T represents the estimated time score; b1, b2, and b3 represent the weight parameters of the congestion score, driving distance score, and estimated time score, respectively.

[0397] The route score is calculated based on a weighted sum of the congestion score, travel distance score, and estimated travel time score. By assigning appropriate weights to each metric, the impact of different factors on the route is comprehensively considered, resulting in a final score for each preselected route.

[0398] Congestion Score (C): This is an assessment and scoring based on the real-time traffic volume and congestion conditions of the road. A higher congestion score indicates a higher degree of congestion on the road section.

[0399] Driving distance score (D): Evaluates and scores based on the actual driving distance of the route. A shorter driving distance scores higher because it reduces driving time and fuel consumption.

[0400] Estimated Time Score (T): Evaluates and scores based on the estimated time required to reach the destination. A shorter estimated time score indicates a faster arrival time.

[0401] Weight parameters (b1, b2, b3): These parameters are used to adjust the relative importance of different scoring indicators. By setting appropriate weight parameters, the weights of different scoring indicators can be determined according to specific needs and priorities.

[0402] By calculating the path score, a comprehensive evaluation index can be provided for each pre-selected path to assist the driver in selecting the best driving plan. Specific effects include:

[0403] Comprehensive consideration of multiple factors: Through weighted summation, multiple factors such as congestion, driving distance and estimated time are taken into account to provide a comprehensive path evaluation.

[0404] Personalized selection: By adjusting weight parameters, you can flexibly select a route that prioritizes congestion, travel distance, or estimated time based on the driver's personal preferences and needs.

[0405] Provide a reference basis: Route scoring provides drivers with a quantitative indicator that can be used as a reference for decision-making, helping drivers make more informed route choices.

[0406] In summary, the calculation expression for route scoring and the setting of weighting parameters can comprehensively consider factors such as congestion, driving distance, and estimated time, providing drivers with quantitative route selection recommendations and references. Drivers can compare the scores of different routes based on the route score and select the higher-scoring route as their driving plan. This helps drivers avoid congested roads, achieve shorter driving distances, and achieve faster arrival times, thereby improving driving efficiency and saving time. Furthermore, route scoring provides an objective metric, enabling drivers to make more rational route selection decisions and reducing the influence of subjective factors.

[0407] By comprehensively considering scoring metrics such as congestion, driving distance, and estimated time, drivers can better plan their routes, reducing potential traffic delays and congestion, and improving overall driving safety and efficiency. Furthermore, the use of route scoring can encourage drivers to develop safer driving habits by being more inclined to choose routes with higher scores and avoid those with lower scores and potentially riskier routes.

[0408] By calculating the scoring of route information and providing drivers with quantitative route selection suggestions, it can help them make more informed driving decisions, reduce potential traffic accident risks, and improve driving safety and efficiency.

[0409] Preferably, the expression for calculating the optimal vehicle speed is:

[0410] V=(1-α)×V1+α×V3

[0411] Where V represents the optimal speed of the ego vehicle; V1 represents the recommended speed for the optimal path; V3 represents the average speed of nearby vehicles; and the α parameter represents the willingness of the ego vehicle to maintain a similar speed to nearby vehicles.

[0412] When V>V2, then V=V2

[0413] Among them, V2 represents the road speed limit.

[0414] A larger α parameter indicates that the driver prefers to maintain a similar speed to nearby vehicles, seeking speed consistency and stability. In this case, the adjusted optimal speed V is closer to the average speed of nearby vehicles, maintaining a similar driving state. This improves coordination and safety between vehicles, helping to cope with emergencies.

[0415] Conversely, a smaller α parameter indicates that the driver prefers to stay closer to the route planner's recommended speed V1, meaning they place more emphasis on the route planner's recommendations. In this case, the adjusted optimal speed V is closer to the recommended speed, allowing for faster destination arrival. However, a smaller α parameter may result in a larger speed difference between the vehicle and nearby vehicles, reducing inter-vehicle coordination and safety.

[0416] The optimal speed expression is used to calculate the optimal speed of the ego vehicle, taking into account the recommended speed of the optimal path and the average speed of nearby vehicles. The α parameter is used to adjust the willingness of the ego vehicle to maintain a similar speed to nearby vehicles.

[0417] Based on this expression, the ego vehicle's optimal speed, V, is calculated through linear interpolation, combining the recommended speed V1 for the optimal path and the average speed V3 of nearby vehicles. The α parameter adjusts the ego vehicle's willingness to maintain a similar speed to nearby vehicles. A larger α parameter increases the ego vehicle's preference for maintaining a similar speed to nearby vehicles; a smaller α parameter increases the ego vehicle's preference for a speed closer to the recommended speed for the optimal path.

[0418] In one embodiment, specifically:

[0419] Obtain the recommended speed V1 for the optimal path planning;

[0420] Get the average speed V3 of nearby vehicles.

[0421] The setting value of the α parameter determines the willingness of the vehicle to maintain a similar speed to nearby vehicles.

[0422] According to the expression V = (1-α) × V1 + α × V3

[0423] Calculate the optimal vehicle speed V.

[0424] If the calculated optimal vehicle speed V exceeds the road speed limit V2, the optimal vehicle speed is limited to the road speed limit V2.

[0425] Effect: By calculating the optimal speed of the ego vehicle, it can be adjusted according to the driver's preference for speed consistency and path planning suggestions. When the α parameter is large, the ego vehicle tends to maintain a speed similar to that of nearby vehicles to improve coordination and safety between vehicles. When the α parameter is small, the ego vehicle tends to be closer to the recommended speed of path planning to reach the destination faster. This can balance speed consistency, safety, and arrival efficiency according to the driver's wishes and road conditions. However, too small or too large an α parameter value may result in a large difference with nearby vehicles or an excessive pursuit of speed consistency, affecting coordination and safety between vehicles.

[0426] In summary, this method calculates the optimal speed of the vehicle, takes into account the recommended speed of the optimal path and the average speed of nearby vehicles, and adjusts the speed according to the driver's willingness to achieve a balance between speed coordination, safety, and arrival efficiency.

[0427] Therefore, the selection of the α parameter should be adjusted according to the driver's usage needs and personal preferences to balance driving safety and efficiency. Drivers can choose the appropriate α parameter value based on traffic conditions, road conditions, and personal driving habits to meet their needs.

[0428] The route planning recommended speed V1 is the ideal speed for given road conditions, calculated by the system's route planning algorithm. It takes into account multiple factors, such as road speed limits, traffic flow, and road conditions, to provide the driver with a reasonable recommended speed.

[0429] However, V1 is an ideal speed calculated by a path planning algorithm, taking into account factors such as road speed limits, traffic flow, and road conditions. It is a recommended speed based on road conditions and the optimal driving strategy, without considering the impact of nearby vehicles.

[0430] V is the optimal speed, adjusted based on the speeds of nearby vehicles. It is calculated based on the recommended speed (V1) from route planning and the average speed of nearby vehicles. By incorporating speed information from nearby vehicles, V can better adapt to the current traffic environment, improving driving safety and smoothness.

[0431] In general, V1 is the result of path planning and is an ideal recommended speed, while V is the optimal speed adjusted based on actual traffic conditions and the speeds of nearby vehicles. V takes into account more real-time traffic information to enable the vehicle to better adapt to current road conditions and maintain a certain speed coordination with surrounding vehicles.

[0432] Preferably, the periodic adjustment of the optimal vehicle speed includes:

[0433] S1. determining a cycle for adjusting the optimal vehicle speed;

[0434] S2. At the beginning of each adjustment cycle, record the current time as the starting time;

[0435] S3. Obtain the speed of nearby vehicles;

[0436] S4. calculating the adjusted optimal vehicle speed;

[0437] S5. Setting the calculated adjusted optimal vehicle speed as the target vehicle speed;

[0438] S6. During the adjustment period, monitor the driving condition and speed change of the vehicle;

[0439] S7. When the current time minus the start time reaches the set adjustment period, the next adjustment period is entered and steps S2 to S7 are repeated.

[0440] The present invention sets an adjustment cycle, records the start time at the beginning of each adjustment cycle, obtains the speed of nearby vehicles, and sets the target speed of the vehicle based on the calculated adjusted optimal speed. The vehicle's driving conditions and speed changes are monitored, and the next adjustment cycle begins when the set adjustment cycle is reached, repeating the above steps.

[0441] In one embodiment, a period for adjusting the optimal vehicle speed is set, such as every minute, every hour, or every time the vehicle is started.

[0442] At the beginning of each adjustment cycle, the current time is recorded as the start time.

[0443] The speed information of nearby vehicles can be obtained through vehicle sensors, vehicle communications or vehicle location information.

[0444] According to the previous method (such as the expression mentioned above), the adjusted optimal vehicle speed is calculated.

[0445] The calculated adjusted optimal vehicle speed is set as the target vehicle speed of the vehicle, which can be set through the vehicle's control system.

[0446] During the adjustment period, the driving condition and speed changes of the vehicle are continuously monitored, which can be done using vehicle sensors or a vehicle control system.

[0447] When the current time minus the start time reaches the set adjustment period, the next adjustment period is entered and steps 2 to 6 are executed again.

[0448] The effect is that periodic adjustments to the optimal speed allow the driver to maintain a reasonable speed under varying road conditions and traffic environments. By acquiring real-time speed information from nearby vehicles and calculating the adjusted optimal speed, the vehicle can better adapt to road changes. This adjusted optimal speed serves as the vehicle's target speed, helping the driver better control the vehicle and improving driving smoothness, safety, and fuel efficiency. Furthermore, periodic adjustments allow for flexible adaptation to actual conditions, maintaining a reasonable and stable speed.

[0449] In summary, this method helps the driver maintain a reasonable speed under different road and traffic conditions by periodically adjusting the optimal speed and combining the speed information of nearby vehicles with the calculated adjusted optimal speed, thereby improving driving smoothness and safety.

[0450] A vehicle comprises the driving planning system.

[0451] The vehicle incorporates the aforementioned driving planning system, which combines multiple components and functions to provide drivers with quantitative driving safety assessments and guidance. The system collects and analyzes behavioral imaging data, driving behavior records, and real-time data from within the vehicle, uploading it to a central server. The data processing and analysis subsystem then processes and calculates the driver's primary and secondary credit ratings, as well as their driving safety rating. The system also develops short-distance driving plans based on the driving safety ratings of nearby vehicles, evaluates and selects the optimal route, and calculates the adjusted optimal speed. Finally, the vehicle control unit makes real-time adjustments to the vehicle based on the data processing and analysis subsystem's results, completing the driving plan.

[0452] The vehicle's driving planning system brings multiple effects and advantages:

[0453] Driving safety assessment and guidance: The system provides drivers with accurate driving safety assessments through quantified driving safety levels, helping them understand the risk level of their driving behavior and providing corresponding guidance measures.

[0454] Reduction of potential traffic accident risks: By formulating short-distance driving plans based on driver behavior and the driving safety levels of nearby vehicles, the system can help drivers stay away from potentially dangerous vehicles and reduce the risk of potential traffic accidents.

[0455] Optimal route selection and driving efficiency optimization: The system evaluates and selects the score of each pre-selected route and provides the best route recommendation with the highest score. This helps drivers choose a more optimized driving route, avoid congestion, reduce driving distance, and improve driving efficiency.

[0456] Optimal Speed ​​Adjustment: The system calculates the optimal speed for the vehicle and periodically adjusts it based on the driver's preferences to adapt to road speed limits and traffic conditions. This helps improve coordination and safety between vehicles while balancing speed consistency and driving efficiency.

[0457] In summary, the vehicle's driving planning system improves driving safety, reduces the risk of traffic accidents, and optimizes driving efficiency and the driving experience by providing quantitative driving safety assessments, developing short-distance driving plans, selecting optimal routes, and adjusting optimal speeds. The system provides drivers with a clearer understanding of their driving behavior and potential risks, allowing them to take appropriate measures to improve. The system's route selection and optimal speed adjustment functions help drivers avoid congested roads and shorten driving distances. These adjustments are based on road speed limits and the average speed of nearby vehicles, improving driving efficiency and adaptability to road conditions.

[0458] Furthermore, the driving planning system's periodic adjustment mechanism dynamically optimizes based on real-time data and the driver's driving behavior. By continuously monitoring the vehicle's driving conditions and speed changes and updating them within a set adjustment period, the system can promptly adapt to changing driving conditions and road conditions, maintaining the accuracy and effectiveness of driving planning.

[0459] In summary, the vehicle's driving planning system provides the driver with comprehensive driving safety assessment, route planning and driving guidance by combining components such as image monitoring devices, operation recording devices, central servers and data processing and analysis subsystems, as well as functions such as route selection and optimal vehicle speed adjustment, thereby improving driving safety, efficiency and comfort.

[0460] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0461] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0462] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0463] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0464] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0465] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0466] Computer-readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. The information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD)

[0467] or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory media such as modulated data signals and carrier waves.

[0468] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0469] The above are merely embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should all be included within the scope of the claims of the present application.

Claims

1. A driving planning method, characterized in that: The following steps are involved: Determine the driver's first credit rating based on bad driving behavior within a first time range, determine the driver's second credit rating based on bad driving behavior within a second time range, and calculate a driving safety rating based on the first and second credit ratings; Develop short-distance driving plans away from potentially dangerous vehicles based on the driving safety levels of nearby vehicles; Obtain the score of each pre-selected path through the path information, and select the path with the highest score as the best path; The optimal speed of the vehicle is calculated based on the recommended speed of the optimal path and the average speed of nearby vehicles, and the optimal speed is adjusted periodically.

2. The driving planning method according to claim 1, characterized in that: The first time range and the second time range both represent a specified time range starting at the current time, wherein the first time range is larger than the second time range.

3. The driving planning method according to claim 1, characterized in that: Determining the driver's first credit rating based on bad driving behavior within a first time range and determining the driver's second credit rating based on bad driving behavior within a second time range includes: Collect data, collect the driver's driving behavior data; Identify bad behaviors, analyze and identify the collected data, and determine the bad driving behaviors; Calculate the hazard score and assign a hazard score to bad driving behavior based on pre-set scoring rules; Determine a first credit rating, calculate a corresponding sum of hazard scores within a first time range, and match the corresponding first credit rating; A second credit rating is determined, and within a second time range, a corresponding sum of hazard scores is calculated to match the corresponding second credit rating.

4. The driving planning method according to claim 1, characterized in that: The calculation of the driving safety level based on the first credit level and the second credit level includes: Set the corresponding proportion coefficient according to the size of the first credit rating and the second credit rating; The driving safety level is calculated using the following expression: SL=a1×L1+a2×L2 Set the corresponding proportion coefficient according to the size of the first credit rating and the second credit rating; Among them, SL represents the driving safety level; a1 represents the proportion coefficient of the first credit level; a2 represents the proportion coefficient of the second credit level; L1 is the first credit level; L2 is the second credit level.

5. The driving planning method according to claim 4, characterized in that: The setting of corresponding proportion coefficients according to the first credit rating and the second credit rating includes: If both the first and second credit ratings are lower than the credit threshold, the ratio coefficients are both 0.5; If either or both of the first credit rating and the second credit rating are greater than or equal to the credit threshold, the proportion coefficient of the first credit rating is less than the proportion coefficient of the second credit rating.

6. The driving planning method according to claim 1, characterized in that: The nearby vehicles are vehicles within a preset radius with the vehicle as the center.

7. The driving planning method according to claim 1, characterized in that: The short-distance driving plan for staying away from potentially dangerous vehicles based on the driving safety level of nearby vehicles includes: Obtain driving safety level information of nearby vehicles; Set warning thresholds to identify nearby potentially dangerous vehicles; Screen out potentially dangerous vehicles; Based on the filtered dangerous vehicles, a new short-term path is planned using an avoidance strategy based on the vehicle's position and destination. Generate a short-distance driving plan based on the short-term path updated by the avoidance strategy.

8. The driving planning method according to claim 1, characterized in that: The path information includes: a congestion score, a driving distance score, and an estimated time score.

9. The driving planning method according to claim 8, characterized in that: The calculation expression for obtaining the score of each pre-selected path through the path information is: Score=b1×C+b2×D+b3×T Among them, Score represents the path score; C represents the congestion score; D represents the driving distance score; T represents the estimated time score; b1, b2, and b3 represent the weight parameters of the congestion score, driving distance score, and estimated time score, respectively.

10. The driving planning method according to claim 1, characterized in that: The expression for calculating the optimal vehicle speed is: V=(1-α)×V1+α×V3 Where V represents the optimal speed of the ego vehicle; V1 represents the recommended speed for the optimal path; V3 represents the average speed of nearby vehicles; and the α parameter represents the willingness of the ego vehicle to maintain a similar speed to nearby vehicles. When V>V2, then V=V2 Among them, V2 represents the road speed limit.

11. The driving planning method according to claim 1, characterized in that: The periodic adjustment of the optimal vehicle speed includes: S1. determining a cycle for adjusting the optimal vehicle speed; S2. At the beginning of each adjustment cycle, record the current time as the starting time; S3. Obtain the speed of nearby vehicles; S4. calculating the adjusted optimal vehicle speed; S5. Setting the calculated adjusted optimal vehicle speed as the target vehicle speed; S6. During the adjustment period, monitor the driving condition and speed change of the vehicle; S7. When the current time minus the start time reaches the set adjustment period, the next adjustment period is entered and steps S2 to S7 are repeated.

12. A driving planning system, characterized in that: include: An image monitoring device, installed inside the vehicle, for acquiring image data of the driver's behavior; An operation recording device, the operation recording device is used to record the driver's driving behavior; A central server, which is used to centrally collect, process and store real-time data uploaded by vehicles; a data processing and analysis subsystem, which is disposed on a central server and is configured to receive, parse, and process data transmitted from the vehicle, determine a first credit rating of the driver based on bad driving behavior within a first time range, determine a second credit rating of the driver based on bad driving behavior within a second time range, and calculate a driving safety rating based on the first and second credit ratings; Based on the driving safety levels of nearby vehicles, a short-distance driving plan is developed to avoid potentially dangerous vehicles. Each pre-selected path is scored using path information, and the highest-scoring path is selected as the optimal path. The optimal speed of the vehicle is calculated based on the recommended speed of the optimal path and the average speed of nearby vehicles, and the optimal speed is periodically adjusted. The vehicle control device is used to adjust the vehicle in real time and complete driving planning based on the processing results of the data processing and analysis subsystem.

13. The driving planning system according to claim 12, characterized in that: The first time range and the second time range both represent a specified time range starting at the current time, wherein the first time range is larger than the second time range.

14. The driving planning system according to claim 13, characterized in that: Determining the driver's first credit rating based on bad driving behavior within a first time range and determining the driver's second credit rating based on bad driving behavior within a second time range includes: Collect data, collect the driver's driving behavior data; Identify bad behaviors, analyze and identify the collected data, and determine the bad driving behaviors; Calculate the hazard score and assign a hazard score to bad driving behavior based on pre-set scoring rules; Determine a first credit rating, calculate a corresponding sum of hazard scores within a first time range, and match the corresponding first credit rating; A second credit rating is determined, and within a second time range, a corresponding sum of hazard scores is calculated to match the corresponding second credit rating.

15. The driving planning system according to claim 12, characterized in that: The calculation of the driving safety level based on the first credit level and the second credit level includes: Set the corresponding proportion coefficient according to the size of the first credit rating and the second credit rating; The driving safety level is calculated using the following expression: SL=a1×L1+a2×L2 Set the corresponding proportion coefficient according to the size of the first credit rating and the second credit rating; Among them, SL represents the driving safety level; a1 represents the proportion coefficient of the first credit level; a2 represents the proportion coefficient of the second credit level; L1 is the first credit level; L2 is the second credit level.

16. The driving planning system according to claim 15, characterized in that: The setting of corresponding proportion coefficients according to the first credit rating and the second credit rating includes: If both the first and second credit ratings are lower than the credit threshold, the ratio coefficients are both 0.5; If either or both of the first credit rating and the second credit rating are greater than or equal to the credit threshold, the proportion coefficient of the first credit rating is less than the proportion coefficient of the second credit rating.

17. The driving planning system according to claim 12, characterized in that: The nearby vehicles are vehicles within a preset radius with the vehicle as the center.

18. The driving planning system according to claim 12, characterized in that: The short-distance driving plan for staying away from potentially dangerous vehicles based on the driving safety level of nearby vehicles includes: Obtain driving safety level information of nearby vehicles; Set warning thresholds to identify nearby potentially dangerous vehicles; Screen out potentially dangerous vehicles; Based on the filtered dangerous vehicles, a new short-term path is planned using an avoidance strategy based on the vehicle's position and destination. Generate a short-distance driving plan based on the short-term path updated by the avoidance strategy.

19. The driving planning system according to claim 12, characterized in that: The path information includes: a congestion score, a driving distance score, and an estimated time score.

20. The driving planning system according to claim 19, characterized in that The calculation expression for obtaining the score of each pre-selected path through the path information is: Score=b1×C+b2×D+b3×T Among them, Score represents the path score; C represents the congestion score; D represents the driving distance score; T represents the estimated time score; b1, b2, and b3 represent the weight parameters of the congestion score, driving distance score, and estimated time score, respectively.

21. The driving planning system according to claim 12, characterized in that: The expression for calculating the optimal vehicle speed is: V=(1-α)×V1+α×V3 Where V represents the optimal speed of the ego vehicle; V1 represents the recommended speed for the optimal path; V3 represents the average speed of nearby vehicles; and the α parameter represents the willingness of the ego vehicle to maintain a similar speed to nearby vehicles. When V>V2, then V=V2 Among them, V2 represents the road speed limit.

22. A vehicle, characterized in that: The vehicle comprises a driving planning system according to any one of claims 12-21.

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