Safety threshold determination method and vehicle

Abstract

The invention discloses a safety threshold determination method and a vehicle, and belongs to the technical field of intelligent driving function safety control, and the method comprises the steps: determining a target correction factor of a controllability level of the vehicle according to driving data of a driver, performance data of the vehicle and environment data; correcting the initial controllability grade of the vehicle by using the target correction factor to obtain a target controllability grade; and correcting a preset safety threshold by using the target controllability level to obtain a dynamic safety threshold. According to the scheme, the dynamic safety threshold value can be calculated according to the actual driving condition of the vehicle, and the problem of false triggering or response lag of the safety function is reduced.

Description

Technical Field

[0001] The present application belongs to the field of intelligent driving function safety control technology, and in particular relates to a method for determining a safety threshold and a vehicle. Background Art

[0002] Intelligent driving safety systems usually have multiple safety functions such as autonomous emergency braking (AEB) and emergency lane keeping (ELK), which rely on safety threshold triggering.

[0003] At present, the safety thresholds for triggering these safety functions are fixed values. For example, the deceleration threshold for triggering the AEB function is fixed at 0.8g, and the steering torque threshold for triggering the ELK function is uniformly set at 3Nm. However, the operating conditions of each vehicle during driving are different. Using fixed safety thresholds is prone to problems such as false triggering of safety functions or delayed response. Summary of the Invention

[0004] The embodiments of the present application provide a method for determining a safety threshold and a vehicle, which can, at least to a certain extent, calculate a dynamic safety threshold based on the actual driving conditions of the vehicle, thereby reducing the problem of false triggering or delayed response of safety functions.

[0005] Other features and advantages of the present application will become apparent from the following detailed description, or may be learned in part by practice of the present application.

[0006] According to a first aspect of an embodiment of the present application, a method for determining a safety threshold is provided, which is applied to a vehicle and includes:

[0007] determining a target correction factor for the vehicle's controllability level based on the driver's driving data, the vehicle's performance data, and environmental data;

[0008] The target correction factor is used to correct the initial controllability level of the vehicle to obtain the target controllability level;

[0009] The target controllability level is used to modify the preset safety threshold to obtain a dynamic safety threshold.

[0010] In some embodiments, the environmental data includes traffic flow data, weather data, and geographic feature data. Determining a target correction factor for the vehicle's controllability level based on the driver's driving data, the vehicle's performance data, and the environmental data includes:

[0011] determining a first correction factor according to the driver's driving data;

[0012] determining a second correction factor based on the performance data of the vehicle;

[0013] Determine a third correction factor based on traffic volume data, weather data, and geographic feature data;

[0014] A target correction factor for the controllability level of the vehicle is determined based on the first correction factor, the second correction factor, and the third correction factor.

[0015] In some embodiments, the traffic flow data includes vehicle density, the weather data includes rainfall intensity and visibility, and the geographic feature data includes tunnel length ratio and road slope. The third correction factor is determined based on the traffic flow data, weather data, and geographic feature data, including:

[0016] Determine the traffic flow correction factor based on vehicle density and road type;

[0017] Determine weather correction factors based on rainfall intensity and visibility;

[0018] Determine the geographic correction factor based on the tunnel length ratio and road slope;

[0019] The product of the traffic flow correction factor, the weather correction factor and the geographical correction factor is determined as the third correction factor.

[0020] In some embodiments, the performance data includes brake data, tire data, and suspension data. Determining the second correction factor based on the vehicle performance data includes:

[0021] determining a brake correction factor based on the brake data;

[0022] Determine tire correction factors based on tire data;

[0023] Determine suspension correction factors based on suspension data;

[0024] A second correction factor is determined based on the brake correction factor, the tire correction factor, and the suspension correction factor.

[0025] In some embodiments, the braking data includes a material type of the brake pad, an initial thickness of the brake pad, a current thickness of the brake pad, a current operating temperature of the brake disc, a braking method, and a vehicle speed. Determining a braking correction factor based on the braking data includes:

[0026] Determine the basic friction coefficient, material attenuation coefficient, optimal operating temperature of the brake disc and friction coefficient attenuation temperature according to the material type;

[0027] Construct a temperature attenuation factor based on the current working temperature, material attenuation coefficient, optimal working temperature and friction coefficient attenuation temperature;

[0028] Determine a speed correction factor based on vehicle speed;

[0029] Determining a brake pad wear correction factor based on the initial thickness and the current thickness;

[0030] Determine the braking mode gain factor according to the braking mode;

[0031] The product of the basic friction coefficient, the temperature attenuation factor, the speed correction factor, the wear correction factor and the braking mode gain factor is determined as the braking correction factor.

[0032] In some embodiments, the tire data includes a dynamic rolling radius, tire pressure, and road adhesion coefficient of the tire, and determining the tire correction factor based on the tire data includes:

[0033] Calculate the tire correction factor based on the dynamic rolling radius, tire pressure and road adhesion coefficient.

[0034] In some embodiments, the suspension data includes suspension travel, a damping coefficient of a shock absorber, an oil temperature of the shock absorber, a front axle load, and a rear axle load. Determining the suspension correction factor based on the suspension data includes:

[0035] The suspension correction factor is calculated based on the suspension travel, the damping coefficient of the shock absorber, the oil temperature of the shock absorber, the front axle load, the rear axle load and the total mass of the vehicle.

[0036] In some embodiments, before modifying the initial controllability level of the vehicle using the target modification factor, the method further includes:

[0037] The vehicle's initial controllability level is determined based on the driver's reaction time, maximum deceleration and road adhesion coefficient.

[0038] In some embodiments, the target safety threshold includes at least one of a target deceleration threshold, a target steering torque threshold, a target following distance threshold, and a target lane departure warning angle threshold.

[0039] According to a second aspect of an embodiment of the present application, a vehicle is provided, comprising a processor and a memory, wherein the memory stores computer program instructions that can be executed by the processor, and when the processor executes the computer program instructions, the steps of any method of the first aspect described above are implemented.

[0040] In this application, a target correction factor for the vehicle's controllability level is determined based on the driver's driving data, the vehicle's performance data, and environmental data. The target correction factor is used to correct the vehicle's initial controllability level to obtain a target controllability level. The target controllability level is then used to correct a preset safety threshold to obtain a dynamic safety threshold. This approach can calculate a dynamic safety threshold based on the vehicle's actual driving conditions, reducing the risk of false triggering or delayed response of safety functions.

[0041] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The accompanying drawings are incorporated into and constitute a part of the specification, illustrating embodiments consistent with the present application and, together with the specification, explaining the principles of the present application. Obviously, the drawings described below are only some embodiments of the present application, and those skilled in the art can derive other drawings based on these drawings without inventive effort. In the drawings:

[0043] Figure 1 A schematic diagram showing a flow chart of a method for determining a safety threshold according to some embodiments of the present application is shown;

[0044] Figure 2 A block diagram of a device for determining a safety threshold according to some embodiments of the present application is shown;

[0045] Figure 3 A schematic structural diagram of a vehicle according to some embodiments of the present application is shown. DETAILED DESCRIPTION

[0046] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0047] In addition, described feature, structure or characteristic can be combined in one or more embodiments in any suitable manner.In the following description, many specific details are provided so as to provide a full understanding of the embodiments of the present application. However, it will be appreciated by those skilled in the art that the technical scheme of the present application can be put into practice without one or more of the specific details, or other methods, components, devices, steps etc. can be adopted. In other cases, known methods, devices, implementations or operations are not shown or described in detail to avoid blurring the various aspects of the application.

[0048] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically separate entities. That is, these functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0049] The flowcharts shown in the accompanying drawings are for illustrative purposes only and do not necessarily include all contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may be decomposed, while others may be combined or partially combined. Therefore, the actual execution order may vary depending on the actual situation.

[0050] Figure 1 FIG2 shows a flow chart of a method for determining a safety threshold according to some embodiments of the present application. Figure 1 As shown, a method for determining a safety threshold is provided, which may include the following steps 101 to 103.

[0051] In step 101 , a target correction factor for the controllability level of the vehicle is determined based on the driver's driving data, the vehicle's performance data, and the environment data.

[0052] Among them, driving data is data related to the driver's driving of the vehicle, which may include the driver's age, gender, historical reaction time, fatigue level, distraction duration and other data.

[0053] Performance data is data related to the performance of the vehicle and may include brake data, tire data, suspension data, and the like.

[0054] Environmental data refers to data related to the environment in which the vehicle is located, and may include data such as traffic flow data, weather data, and geographical feature data.

[0055] The vehicle's controllability level describes the degree to which the vehicle is controllable under specific conditions (e.g., system failure, environmental changes, or human intervention). In step 101, a target correction factor is determined based on driving data, performance data, and environmental data. The target correction factor is then used to adjust the controllability level.

[0056] In some embodiments, the environmental data includes traffic flow data, weather data and geographical feature data, and the target correction factor of the vehicle's controllability level is determined based on the driver's driving data, the vehicle's performance data and the environmental data, including: determining a first correction factor based on the driver's driving data; determining a second correction factor based on the vehicle's performance data; determining a third correction factor based on the traffic flow data, weather data and geographical feature data; and determining the target correction factor of the vehicle's controllability level based on the first correction factor, the second correction factor and the third correction factor.

[0057] It is understandable that traffic flow data can be collected through equipment such as millimeter-wave radar, which not only affects the controllability level, but also affects the deceleration threshold when the vehicle brakes; weather data can be collected through cameras, rain sensors, lidar and other equipment, which not only affects the driver's reaction time, but also affects the vehicle's steering torque threshold; geographic feature data can be obtained through high-precision maps, which not only affects the controllability level, but also affects the deceleration threshold and acceleration threshold when the vehicle brakes.

[0058] Related technologies typically use a fixed driver reaction time of, for example, 1 second to determine the vehicle's controllability level, without considering individual driver differences. Studies have shown that the average reaction time of older drivers is 0.3-0.5 seconds longer than that of younger drivers. This application can determine a first correction factor based on the driver's gender, age, historical reaction time, fatigue level, and duration of distraction, enabling personalized driver modeling and improving the reliability of dynamic safety thresholds.

[0059] In some embodiments, the performance data includes braking data, tire data, and suspension data. Determining a second correction factor based on the performance data of the vehicle includes: determining a braking correction factor based on the braking data; determining a tire correction factor based on the tire data; determining a suspension correction factor based on the suspension data; and determining a second correction factor based on the braking correction factor, the tire correction factor, and the suspension correction factor.

[0060] Among them, the braking data may include the material type of the brake pad, the initial thickness of the brake pad, the current thickness of the brake pad, the current operating temperature of the brake disc, the braking method and the vehicle speed; the tire data may include the dynamic rolling radius, tire pressure and road adhesion coefficient of the tire; the suspension data includes the suspension travel, the damping coefficient of the shock absorber, the oil temperature of the shock absorber, the front axle load and the rear axle load.

[0061] It is understandable that brake data can be collected through the electronic brake force distribution system (EBD), tire data can be collected through wheel speed sensors and tire pressure monitoring system (TPMS), and suspension data can be collected through height sensors and shock absorbers.

[0062] In some embodiments, a braking correction factor is determined based on braking data, including: determining the basic friction coefficient, material attenuation coefficient, optimal operating temperature and friction coefficient attenuation temperature of the brake disc based on the material type; constructing a temperature attenuation factor based on the current operating temperature, material attenuation coefficient, optimal operating temperature and friction coefficient attenuation temperature; determining a speed correction factor based on the vehicle speed; determining a wear correction factor of the brake pad based on the initial thickness and the current thickness; determining a braking mode gain factor based on the braking mode; and determining the product of the basic friction coefficient, temperature attenuation factor, speed correction factor, wear correction factor and braking mode gain factor as the braking correction factor.

[0063] It is understood that brake pad materials typically include ceramic, semi-metallic, and carbon fiber composite materials. Brake pads made of different materials have different corresponding basic friction coefficients. For example, a ceramic brake pad has a basic friction coefficient of 0.42, a semi-metallic brake pad has a basic friction coefficient of 0.38, and a carbon fiber composite brake pad has a basic friction coefficient of 0.45. The corresponding basic friction coefficient can be determined based on the corresponding relationship between material type and basic friction coefficient.

[0064] The optimal operating temperature of the brake disc refers to the temperature when the friction coefficient is the highest. The friction coefficient attenuation temperature refers to the temperature after the friction coefficient decreases. The material attenuation coefficient is used to characterize the maximum loss ratio of the friction coefficient at high or low temperatures. The temperature attenuation factor is used to quantify the impact of the brake disc temperature on the friction coefficient.

[0065] For different types of brake pad materials, the corresponding optimal operating temperature, friction coefficient attenuation temperature, and material attenuation coefficient are also different. For example, the optimal operating temperature of semi-metallic brake pads is usually 250℃, the friction coefficient attenuation temperature is 150℃, and the material attenuation coefficient is 0.35; the optimal operating temperature of ceramic brake pads is usually 300℃, the friction coefficient attenuation temperature is 200℃, and the material attenuation coefficient is 0.25; the optimal operating temperature of carbon-ceramic brake pads is usually 500℃, the friction coefficient attenuation temperature is 300℃, and the material attenuation coefficient is 0.4; the optimal operating temperature of carbon fiber composite brake pads is usually 600℃, the friction coefficient attenuation temperature is 250℃, and the material attenuation coefficient is 0.55. Based on the corresponding relationship between the material type and the optimal operating temperature, friction coefficient attenuation temperature, and material attenuation coefficient, the corresponding optimal operating temperature, friction coefficient attenuation temperature, and material attenuation coefficient can be determined, and then the temperature attenuation function can be constructed to obtain the temperature attenuation factor as follows:

[0066]

[0067] Among them, T disk is the current operating temperature, T opt is the optimal operating temperature, Tdecay is the friction coefficient attenuation temperature, and α is the material attenuation coefficient.

[0068] The friction coefficient of a vehicle will also change at different speeds. For example, the friction coefficient will drop by 10% at a speed of 100 km / h. Therefore, the basic friction coefficient can be corrected using the vehicle speed. During implementation, the speed correction factor can be determined according to the following formula:

[0069]

[0070] Where v is the vehicle speed.

[0071] When the brake pad is worn, the friction coefficient will also change. For example, when the brake pad is worn by 50%, the friction coefficient will drop by 12.5%. Therefore, the wear of the brake pad can be used to correct the basic friction coefficient. The wear correction factor can be determined according to the following formula:

[0072]

[0073] Among them, d initial is the initial thickness, d current is the current thickness.

[0074] When the braking mode is different, the friction coefficient will also change. Different braking mode gain factors can be set for different braking modes. For example, the braking mode gain factor corresponding to the integrated power brake system (IPB) is 1.15, and the braking mode gain factor corresponding to the traditional hydraulic system is 1.0.

[0075] After determining the basic friction coefficient, temperature attenuation factor, speed correction factor, wear correction factor and braking mode gain factor, the product of these parameters can be determined as the braking correction factor.

[0076] In some embodiments, determining the tire correction factor based on the tire data includes calculating the tire correction factor based on a dynamic rolling radius, tire pressure, and road adhesion coefficient.

[0077] The dynamic rolling radius can be calculated by integrating GPS vehicle speed and wheel speed pulse count, tire pressure can be collected by TPMS, and the road adhesion coefficient can be inferred from the tire slip rate. The tire correction factor can be determined according to the following formula:

[0078]

[0079] Among them, η tire is the tire correction factor, r dynamic is the dynamic rolling radius, r nominalis the standard radius of the tire, P tire is the real-time tire pressure, P std is the standard tire pressure, μ road is the road adhesion coefficient, fwater(h) is the influence function of water film thickness on adhesion, and h is the road water film thickness.

[0080] The standard tire radius can be obtained by matching the vehicle identification number (VIN), usually 315mm; the standard tire pressure can be obtained from the vehicle owner's manual or the tire sidewall marking, usually 220kPa; the road surface water film thickness can be determined based on lidar point cloud reflection intensity analysis and camera texture recognition, usually 0.5-2mm on rainy days; the influence function of water film thickness on adhesion can be: fwater(h) = e-0.2h, when h = 1mm, fwater(h) = 0.8187.

[0081] By introducing the tire correction factor when calculating the dynamic safety threshold, when the tire is worn, the dynamic rolling radius r dynamic Smaller than the standard radius r nominal , can automatically reduce the slip rate threshold, and then can trigger the anti-lock braking system (ABS) function intervention in advance; when low tire pressure occurs, such as the real-time tire pressure P tire When it is less than 180kPa, the steering torque threshold can be automatically increased to prevent understeer; when the road surface is wet, for example, the road water film thickness h is greater than 0.5mm, the lateral acceleration threshold can be limited to prevent tire skidding; in low tire pressure and wetland scenarios, the AEB deceleration threshold is automatically lowered.

[0082] In some embodiments, determining the suspension correction factor based on the suspension data includes calculating the suspension correction factor based on the suspension travel, the damping coefficient of the shock absorber, the oil temperature of the shock absorber, the front axle load, the rear axle load, and the total mass of the vehicle.

[0083] Among them, the suspension travel can include the front left suspension travel Z FL , front right suspension travel Z FR , rear left suspension travel Z RL , rear right suspension travel Z RR These parameters can be collected by the suspension height sensor. Usually on a flat road, the front left suspension travel Z of the vehicle is FL and front right suspension travel Z FR 120±5mm; rear left suspension travel Z RL , rear right suspension travel Z RR 130±5mm.

[0084] The damping coefficient of the shock absorber may include the current damping coefficient k of the shock absorber damper and the standard damping coefficient K new The former can be obtained through real-time feedback from the CDC system or inversely deduced based on the current-speed characteristic curve, and the latter can be obtained from the vehicle maintenance manual or supplier data. Usually the latter is 1500N·s / m.

[0085] Shock absorber oil temperature T oil It can be collected through the temperature sensor built into the shock absorber. Usually when the shock absorber is working normally, the oil temperature range is about 50 to 80°C.

[0086] Front axle load m front It can be obtained by collecting air spring pressure sensor or reverse deduction of suspension deformation. For SUV models, the front axle load m front Usually 800-1200kg; rear axle load m rear It can be collected by the air spring pressure sensor. For SUV models, the front axle load m rear Usually 600-1000kg.

[0087] The suspension correction factor can be calculated using the following formula:

[0088]

[0089] Among them, η suspension is the suspension correction factor, Z avg is the average suspension travel, m total is the total mass.

[0090] By introducing a suspension correction factor when calculating the dynamic safety threshold, the vehicle speed threshold can be limited and the steering torque threshold can be increased in scenarios where the suspension is aging and overloaded. In scenarios where the shock absorber oil temperature is >100°C, the ESC intervention threshold is automatically lowered by 20% to prevent oversteering.

[0091] It should be noted that tire data and suspension data can be synchronized through the AUTOSAR AP platform with an error of <1ms. When key sensors (such as TPMS) fail, the tire pressure estimation algorithm based on wheel speed jitter can be used to calculate real-time tire pressure with an accuracy loss of <5%. When a new car rolls off the production line, full-condition calibration (dry / wet ground, different loads) can be performed to generate the road adhesion coefficient μ road By clearly defining variables and refining model details, the vehicle can complete complex state assessments within milliseconds, enabling precise dynamic adjustment of safety thresholds to meet ASIL-D functional safety requirements.

[0092] After determining the brake correction factor, tire correction factor, and suspension correction factor, the second correction factor can be calculated using the following formula:

[0093] η2=0.5×μ brake +0.3×η tire +0.2×η suspension ;

[0094] Among them, η2 is the second correction factor, μ brake is the braking correction factor, η tire is the tire correction factor, η suspension is the suspension correction factor.

[0095] Take the brake overheating and low tire pressure scenario as an example. =0.3 (ceramic brake pad, 500℃), =0.6 (tire pressure 180kPa), =0.8 (normal suspension), the second correction factor can be obtained by calculation =0.5×0.3+0.3×0.6+0.2×0.8=0.15+0.18+0.16=0.49. The second correction factor can be used to adjust the deceleration threshold that triggers the AEB function, lowering the deceleration threshold and extending the braking distance, allowing the system to trigger a warning in advance and avoid a collision.

[0096] Taking the snowy and aging suspension scenario as an example, μ brake =0.9 (new brake pad), η tire =0.4 (snow + icy road), η suspension =0.5 (damping attenuation 40%), the second correction factor η can be obtained by calculation vehicle = 0.5 × 0.9 + 0.3 × 0.4 + 0.2 × 0.5 = 0.45 + 0.12 + 0.1 = 0.67. The second correction factor can be used to adjust the steering torque threshold that triggers the ELK function. Lowering the steering torque threshold increases steering sensitivity, thereby preventing vehicle skidding. In simulation tests, the skidding probability was reduced from 25% to 8%.

[0097] In some embodiments, the traffic flow data includes vehicle density, the weather data includes rainfall intensity and visibility, and the geographic feature data includes tunnel length ratio and road slope. A third correction factor is determined based on the traffic flow data, weather data and geographic feature data, including: determining the traffic flow correction factor based on vehicle density and road type; determining the weather correction factor based on rainfall intensity and visibility; determining the geographic correction factor based on tunnel length ratio and road slope; and determining the product of the traffic flow correction factor, the weather correction factor and the geographic correction factor as the third correction factor.

[0098] Among them, road types can be divided into urban roads, highways, etc. Considering that the vehicle density has different effects on the vehicle controllability level when the vehicle is traveling on urban roads and highways, the traffic flow correction factor can be determined according to the following formula:

[0099]

[0100] Among them, η traffic is the traffic flow correction factor, and ρ is the vehicle density.

[0101] The weather correction factor can be determined according to the following formula:

[0102]

[0103] Among them, η weather is the weather correction factor, v rain is the rainfall intensity, v vis For visibility.

[0104] The geographic correction factor can be determined according to the following formula:

[0105]

[0106] Among them, η geo is the geographical correction factor, is the proportion of tunnel length, and θ_slope is the road slope.

[0107] The third correction factor can be determined by the following formula:

[0108] η3=η traffic ×η weather ×η geo .

[0109] After determining the first correction factor, the second correction factor, and the third correction factor, the target correction factor of the vehicle's controllability level can be determined by the following formula:

[0110] η0=η1×η2×η3;

[0111] Among them, η0 is the target correction factor, and η1 is the first correction factor.

[0112] In step 102 , the initial controllability level of the vehicle is corrected using a target correction factor to obtain a target controllability level.

[0113] It is understood that the initial controllability level can be determined based on national road vehicle functional safety standards, or it can be determined based on the driver's reaction time, maximum deceleration, and road adhesion coefficient. Typically, the driver's reaction time, maximum deceleration, and road adhesion coefficient are set to fixed values, so the initial controllability level is also fixed.

[0114] During the implementation process, the target controllability level can be determined according to the following formula:

[0115] C dynamic =C base ×η0;

[0116] Among them, C dynamic is the target controllability level, C base is the initial controllability level, and η0 is the target correction factor. Since η0 changes continuously according to the vehicle's driving conditions, the target controllability level C dynamic It also changes dynamically.

[0117] In step 103, the preset safety threshold is modified using the target controllability level to obtain a dynamic safety threshold.

[0118] The target safety threshold includes at least one of a target deceleration threshold, a target steering torque threshold, a target following distance threshold, and a target lane departure warning angle threshold.

[0119] For the safety function AEB, the corresponding safety threshold is the deceleration threshold. The target deceleration threshold can be determined according to the following formula:

[0120] a th =a base ×C dynamic ×g;

[0121] Among them, a th is the target deceleration threshold, a base is the preset deceleration threshold.

[0122] For example, a base The value can be taken as 0.8. From the formula, we can know that when the target controllability level C dynamic The smaller the value, the smaller the target deceleration threshold, and the earlier the forced braking is triggered.

[0123] For the safety function ELK, the corresponding safety threshold is the steering torque threshold. The target steering torque threshold can be determined according to the following formula:

[0124] T steer =T base ×C dynamic ;

[0125] Among them, T steer is the target steering torque threshold, T base Preset steering torque threshold.

[0126] For example, T base The value can be 5. From the formula, we can know that when the target controllability level C dynamic The smaller the speed, the more torque is needed to maintain the lane.

[0127] For the safety function ACC, the corresponding safety threshold is the following distance threshold. The target following distance threshold can be determined according to the following formula:

[0128]

[0129] Among them, TTC safe is the target following time threshold, TTC bast It is the preset following distance threshold.

[0130] For example, TTC bast The value can be 2.5. From the formula, we can know that when the target controllability level C dynamic The larger it is, the higher the risk is and the following distance needs to be shortened.

[0131] For the safety function LKA, the corresponding safety threshold is the lane departure warning angle threshold. The target lane departure warning angle threshold can be determined according to the following formula:

[0132] θ warn =θ base ×C dynamic ;

[0133] Among them, θ warn is the target lane departure warning angle threshold, θ base The preset lane departure warning angle threshold.

[0134] For example, θ base The value can be 3. From the formula, we can know that when the target controllability level C dynamic The larger it is, the higher the risk and the more sensitive the lane departure detection needs to be.

[0135] In some embodiments, after the target controllability level is determined, a dynamic automotive safety integrity level (ASIL) may also be determined based on the target controllability level.

[0136] During the implementation process, the dynamic ASIL level can be determined based on the target controllability level and the preset level classification rules. For example, when the target controllability level is greater than or equal to 0.8, the dynamic ASIL level is determined to be QM. The safety goal at this time is: no risk, fully open functions, and the response measures can be: unlimited ACC, automatic lane change; when the target controllability level is greater than or equal to 0.6 and less than 0.8, the dynamic ASIL level is determined to be ASIL-A. The safety goal at this time is: low risk, basic monitoring is required, and the response measures can be: HUD prompt risk, slight braking pre-filling; when the target controllability level is greater than or equal to 0.4 and less than 0.6, the dynamic ASIL level is determined to be ASIL-B. The safety goal at this time is: medium risk, enhanced intervention, and the response measures can be: speed limit, disable automatic lane change; when the target controllability level is greater than or equal to 0.2 and less than 0.4, the dynamic ASIL level is determined to be ASIL-C, and the safety goal at this time is: high risk, forced takeover, and the response measures can be: emergency braking (0.6g), double flash warning; when the target controllability level is less than 0.2, the dynamic ASIL level is determined to be ASIL-D, and the safety goal at this time is: extreme risk, minimum system safety state, and the response measures can be: full braking (1.0g), call for help.

[0137] During the implementation process, the dynamic ASIL level can also be determined based on the target controllability level and the formula. For example, according to the formula ASIL(t) = floor(4×(1-C dynamic )) Calculate the dynamic ASIL level. During the calculation process, you can also add a hysteresis interval, for example, from ASIL-B to ASIL-C, C dynamic Less than 0.38, downgrade to C dynamic Greater than 0.42, to avoid frequent switching of ASIL levels.

[0138] Through dynamic ASIL level mapping (QM / ASIL-A to ASIL-D), functional freedom can be maximized while ensuring safety. dynamic When ≥0.8 (low risk), the full-speed autonomous driving function can be enabled; when C dynamic When <0.4 (high risk), it is forced to downgrade to the minimum risk state.

[0139] After determining the dynamic ASIL level and dynamic safety threshold, the vehicle can record the dynamic ASIL level and dynamic safety threshold before and after each intervention event, and update the correction factor model through self-learning; it can also run the old and new models in parallel on the cloud and compare the intervention effects, and only push the new model update when the false alarm rate of the new model drops by more than a preset value (for example, 5%).

[0140] The above-mentioned solution of the present application integrates the driver's driving data, vehicle performance data, and environmental data to achieve dynamic updates of the controllability level and adaptive adjustment of safety thresholds (such as the deceleration threshold for triggering the AEB function and the steering torque threshold for triggering the ELK function) based on the controllability level. Compared with traditional solutions using fixed safety thresholds, the false trigger rate can be reduced by 40%-65% (measured data), and early response can be achieved, improving vehicle safety performance. In low-risk scenarios, such as on highways, on sunny days, and with young users driving the vehicle, the following distance threshold for triggering the ACC function is shortened from 2.5 seconds to 1.8 seconds, improving traffic efficiency and achieving an optimal balance between functional safety and driving performance.

[0141] The following describes an embodiment of the device of the present application, which can be used to implement the method for determining the safety threshold in the above-mentioned embodiment of the present application. For details not disclosed in the embodiment of the device of the present application, please refer to the embodiment of the method for determining the safety threshold in the above-mentioned embodiment of the present application.

[0142] Figure 2 FIG. 1 shows a block diagram of a device for determining a safety threshold according to some embodiments of the present application. Figure 2 As shown, the device for determining the safety threshold of an embodiment of the present application includes: a correction factor determination module 201, which is used to determine the target correction factor of the vehicle's controllability level based on the driver's driving data, the vehicle's performance data and environmental data; a controllability level correction module 202, which is used to use the target correction factor to correct the vehicle's initial controllability level to obtain a target controllability level; and a safety threshold correction module 203, which is used to use the target controllability level to correct the preset safety threshold to obtain a dynamic safety threshold.

[0143] In some embodiments, based on the aforementioned scheme, the environmental data includes traffic flow data, weather data and geographical feature data, and the correction factor determination module 201 is also used to determine a first correction factor based on the driver's driving data; determine a second correction factor based on the vehicle's performance data; determine a third correction factor based on the traffic flow data, weather data and geographical feature data; and determine a target correction factor for the vehicle's controllability level based on the first correction factor, the second correction factor and the third correction factor.

[0144] In some embodiments, based on the aforementioned scheme, the traffic flow data includes vehicle density, the weather data includes rainfall intensity and visibility, and the geographical feature data includes tunnel length ratio and road slope. The correction factor determination module 201 is also used to determine the traffic flow correction factor based on vehicle density and road type; determine the weather correction factor based on rainfall intensity and visibility; determine the geographical correction factor based on tunnel length ratio and road slope; and determine the product of the traffic flow correction factor, the weather correction factor and the geographical correction factor as the third correction factor.

[0145] In some embodiments, based on the aforementioned scheme, the performance data includes braking data, tire data, and suspension data, and the correction factor determination module 201 is further used to determine a braking correction factor based on the braking data; determine a tire correction factor based on the tire data; determine a suspension correction factor based on the suspension data; and determine a second correction factor based on the braking correction factor, the tire correction factor, and the suspension correction factor.

[0146] In some embodiments, based on the aforementioned scheme, the braking data includes the material type of the brake pad, the initial thickness of the brake pad, the current thickness of the brake pad, the current operating temperature of the brake disc, the braking method and the vehicle speed. The correction factor determination module 201 is also used to determine the basic friction coefficient, the material attenuation coefficient, the optimal operating temperature and the friction coefficient attenuation temperature of the brake disc according to the material type; construct a temperature attenuation factor according to the current operating temperature, the material attenuation coefficient, the optimal operating temperature and the friction coefficient attenuation temperature; determine the speed correction factor according to the vehicle speed; determine the wear correction factor of the brake pad according to the initial thickness and the current thickness; determine the braking method gain factor according to the braking method; and determine the product of the basic friction coefficient, the temperature attenuation factor, the speed correction factor, the wear correction factor and the braking method gain factor as the braking correction factor.

[0147] In some embodiments, based on the aforementioned solution, the tire data includes the dynamic rolling radius, tire pressure and road adhesion coefficient of the tire, and the correction factor determination module 201 is further used to calculate the tire correction factor based on the dynamic rolling radius, tire pressure and road adhesion coefficient.

[0148] In some embodiments, based on the aforementioned scheme, the suspension data includes suspension stroke, the damping coefficient of the shock absorber, the oil temperature of the shock absorber, the front axle load and the rear axle load, and the correction factor determination module 201 is also used to calculate the suspension correction factor based on the suspension stroke, the damping coefficient of the shock absorber, the oil temperature of the shock absorber, the front axle load, the rear axle load and the total mass of the vehicle.

[0149] In some embodiments, based on the above solution, the controllability level correction module 202 is further configured to determine the initial controllability level of the vehicle according to the driver's reaction time, maximum deceleration, and road adhesion coefficient.

[0150] In some embodiments, based on the aforementioned solution, the target safety threshold includes at least one of a target deceleration threshold, a target steering torque threshold, a target following distance threshold, and a target lane departure warning angle threshold.

[0151] Based on the same inventive concept, the embodiment of the present application further provides a vehicle, referring to Figure 3, shows a schematic structural diagram of a vehicle in an embodiment of the present application, wherein the vehicle includes one or more memories 304, one or more processors 302, and at least one computer program (computer program instruction) stored in the memories 304 and executable on the processors 302, and when the processors 302 execute the computer programs, the method described above is implemented.

[0152] Among them, Figure 3 In the embodiment of the present invention, a bus architecture (represented by bus 300) is shown. Bus 300 may include any number of interconnected buses and bridges, and bus 300 links together various circuits including one or more processors represented by processor 302 and memory represented by memory 304. Bus 300 may also link together various other circuits such as peripherals, voltage regulators, and power management circuits, which are well known in the art and therefore will not be described further herein. Bus interface 305 provides an interface between bus 300 and receiver 301 and transmitter 303. Receiver 301 and transmitter 303 may be the same component, namely a transceiver, which provides a unit for communicating with various other devices over a transmission medium. Processor 302 is responsible for managing bus 300 and general processing, while memory 304 may be used to store data used by processor 302 when performing operations.

[0153] Based on the same inventive concept, an embodiment of the present application provides a computer-readable storage medium, in which computer program instructions are stored. When the computer program instructions are executed by a processor, the processor is prompted to implement the steps of the method as described above.

[0154] Based on the same inventive concept, an embodiment of the present application provides a computer program product, including a computer program. When the computer program product is executed by a processor, it prompts the processor to implement the steps of the method described above.

[0155] The functions described herein may be implemented in hardware, software executed by a processor, firmware, or any combination thereof. If implemented in software executed by a processor, the functions may be stored as one or more instructions or codes on or transmitted via a computer-readable medium. Other examples and implementations are within the scope and spirit of this application and the appended claims. For example, due to the nature of software, the functions described above may be implemented using software executed by a processor, hardware, firmware, hardwiring, or a combination of any of these. Furthermore, the functional units may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit.

[0156] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only exemplary. For example, the division of the units can be a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0157] The units described as separate components may or may not be physically separate, and the components of the control device may or may not be physical units, that is, they may be located in one place or distributed across multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0158] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for enabling a computer device (which can be a personal computer, a server or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk, etc. Various media that can store computer program instructions.

[0159] The foregoing is merely an embodiment of the present application and is not intended to limit the present application. Various modifications and variations are possible for those skilled in the art. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present application shall be included within the scope of the claims of the present application.

Claims

1. A method for determining a safety threshold, applied to a vehicle, characterized in that: include: determining a target correction factor for the vehicle's controllability level based on the driver's driving data, the vehicle's performance data, and environmental data; Correcting the initial controllability level of the vehicle using the target correction factor to obtain a target controllability level; The target controllability level is used to modify the preset safety threshold to obtain a dynamic safety threshold.

2. The method for determining a safety threshold according to claim 1, wherein: The environmental data includes traffic flow data, weather data, and geographical feature data. The target correction factor for the vehicle's controllability level is determined based on the driver's driving data, the vehicle's performance data, and the environmental data, including: determining a first correction factor according to the driver's driving data; determining a second correction factor based on the performance data of the vehicle; determining a third correction factor based on the traffic flow data, the weather data, and the geographic feature data; A target correction factor for the controllability level of the vehicle is determined based on the first correction factor, the second correction factor, and the third correction factor.

3. The method for determining a safety threshold according to claim 2, wherein: The traffic flow data includes vehicle density, the weather data includes rainfall intensity and visibility, and the geographic feature data includes tunnel length ratio and road slope. Determining the third correction factor based on the traffic flow data, the weather data, and the geographic feature data includes: determining a traffic flow correction factor based on the vehicle density and road type; determining a weather correction factor based on the rainfall intensity and visibility; Determine a geographic correction factor based on the tunnel length ratio and road slope; The product of the traffic flow correction factor, the weather correction factor and the geographical correction factor is determined as the third correction factor.

4. The method for determining a safety threshold according to claim 2, wherein: The performance data includes brake data, tire data, and suspension data. Determining the second correction factor based on the vehicle performance data includes: determining a braking correction factor based on the braking data; determining a tire correction factor based on the tire data; determining a suspension correction factor based on the suspension data; The second correction factor is determined based on the brake correction factor, the tire correction factor, and the suspension correction factor.

5. The method for determining a safety threshold according to claim 4, wherein: The braking data includes the material type of the brake pad, the initial thickness of the brake pad, the current thickness of the brake pad, the current operating temperature of the brake disc, the braking mode and the vehicle speed. The determining of the braking correction factor based on the braking data includes: determining a basic friction coefficient, a material attenuation coefficient, an optimal operating temperature of the brake disc, and a friction coefficient attenuation temperature according to the material type; constructing a temperature attenuation factor according to the current operating temperature, the material attenuation coefficient, the optimal operating temperature, and the friction coefficient attenuation temperature; determining a speed correction factor based on the vehicle speed; determining a wear correction factor of the brake pad based on the initial thickness and the current thickness; determining a braking mode gain factor according to the braking mode; The product of the basic friction coefficient, the temperature attenuation factor, the speed correction factor, the wear correction factor and the braking mode gain factor is determined as the braking correction factor.

6. The method for determining a safety threshold according to claim 4, wherein: The tire data includes a dynamic rolling radius, tire pressure, and road adhesion coefficient of the tire, and determining the tire correction factor based on the tire data includes: The tire correction factor is calculated according to the dynamic rolling radius, tire pressure and road adhesion coefficient.

7. The method for determining a safety threshold according to claim 4, wherein: The suspension data includes suspension travel, a damping coefficient of a shock absorber, an oil temperature of the shock absorber, a front axle load, and a rear axle load. Determining a suspension correction factor based on the suspension data includes: The suspension correction factor is calculated according to the suspension stroke, the damping coefficient of the shock absorber, the oil temperature of the shock absorber, the front axle load, the rear axle load and the total mass of the vehicle.

8. The method for determining a safety threshold according to any one of 1 to 7, characterized in that: Before correcting the initial controllability level of the vehicle using the target correction factor, the method further includes: The vehicle's initial controllability level is determined based on the driver's reaction time, maximum deceleration and road adhesion coefficient.

9. The method for determining a safety threshold according to any one of claims 1 to 7, characterized in that: The target safety threshold includes at least one of a target deceleration threshold, a target steering torque threshold, a target following distance threshold, and a target lane departure warning angle threshold.

10. A vehicle comprising a processor and a memory, characterized in that: The memory stores computer program instructions that can be executed by the processor, and when the processor executes the computer program instructions, the steps of the method according to any one of claims 1 to 9 are implemented.

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