Safety distance calculation method of intelligent connected vehicle adaptive cruise control system

Abstract

This invention discloses a method for calculating the safe distance of an adaptive cruise control system for intelligent connected vehicles. The steps are as follows: the vehicle uses vehicle-to-vehicle communication to acquire the braking performance parameters, vehicle status information, and vehicle type of the preceding vehicle; the vehicle acquires its own braking performance parameters and vehicle status information, and uses vehicle-to-road communication to collect road condition information; the braking efficiency attenuation of the vehicle's brakes is determined using a brake state perception formula; the maximum braking deceleration correction factor between the preceding and following vehicles is calculated; the corrected estimated braking distance of the preceding vehicle is calculated using a preceding vehicle braking simulation formula; the corrected estimated braking distance of the vehicle is calculated using a following vehicle braking simulation formula; the expected stationary distance between the vehicle and the preceding vehicle is calculated using an expected distance adjustment formula; and the adaptive cruise safety distance is calculated. This method can calculate a suitable adaptive cruise safety distance, balancing vehicle driving safety and efficiency.

Description

Technical Field

[0001] This invention belongs to the field of intelligent connected vehicle safety, and specifically relates to a method for calculating the safe distance of an adaptive cruise control system for intelligent connected vehicles. Background Technology

[0002] Intelligent connected vehicles are an emerging automotive system that combines vehicle networking with intelligent vehicles. Through vehicle networking technology, it enables information interaction between vehicles, between vehicles and people, between vehicles and roads, and between vehicles and cloud platforms. Combined with environmental perception, intelligent decision-making, and collaborative control functions, it improves the safety, comfort, efficiency, and convenience of vehicle driving, and ultimately replaces humans to achieve autonomous driving.

[0003] Adaptive cruise control is an advanced driver assistance function developed from cruise control. When there are no vehicles ahead, the adaptive cruise control system controls the vehicle to travel at the speed set by the driver. When a vehicle appears ahead, the adaptive cruise control system automatically controls the vehicle speed to maintain a safe following distance from the vehicle in front. This achieves automatic control of the vehicle's longitudinal movement, reduces the driver's workload, and improves driving safety and passenger comfort.

[0004] According to road traffic accident statistics, rear-end collisions account for a large proportion of all road traffic accidents. Most of these rear-end collisions are caused by excessive speed, insufficient following distance, and driver inattention. Therefore, applying adaptive cruise control and using an appropriate safe distance as the control target of the adaptive cruise control system can significantly reduce the likelihood of rear-end collisions.

[0005] Currently, the main methods for calculating the safe distance of adaptive cruise control include the fixed distance method, the headway method, the braking process analysis method, and the driver characteristic estimation method. Existing methods have the following problems: 1) They fail to consider the emergency braking process of the vehicle in extreme situations, and cannot guarantee that the vehicle can avoid rear-end collisions under any following conditions; 2) When analyzing the braking process, they only consider the braking performance of the vehicle itself, and fail to consider the braking performance of the vehicle in front. When the braking performance of the vehicle in front is good, an excessively short safe distance is difficult to avoid a rear-end collision, and when the braking performance of the vehicle in front is poor, an excessively long safe distance is difficult to guarantee driving efficiency; 3) They fail to consider the impact of driver characteristics on the safe distance, resulting in the calculated safe distance not meeting the driver's expectations. Summary of the Invention

[0006] To address the aforementioned problems, this invention provides a method for calculating the safe distance of an intelligent connected vehicle's adaptive cruise control system, which calculates a suitable adaptive cruise safety distance, balancing vehicle driving safety and efficiency.

[0007] To achieve the above objectives, the specific technical solution of the present invention is as follows:

[0008] A method for calculating the safe distance of an adaptive cruise control system for intelligent connected vehicles includes the following steps:

[0009] Step 1: Based on the vehicle-to-vehicle communication function of the Internet of Vehicles (IoV), this vehicle obtains the braking performance parameters, vehicle status information, and vehicle type of the vehicle in front. This vehicle is equipped with an adaptive cruise control system, which controls the vehicle's speed to ensure that the actual distance between this vehicle and the vehicle in front is greater than or equal to the adaptive cruise safety distance calculated by this vehicle. The vehicle in front is the closest vehicle to this vehicle in its lane. The braking performance parameters include the standard braking distance s0, braking coordination time t, and critical load factor n. The vehicle status information includes the vehicle speed v, load factor k, and current peak adhesion coefficient.

[0010] Step 2: This vehicle acquires its own braking performance parameters and vehicle status information. Based on the vehicle-to-road communication function of the Internet of Vehicles, this vehicle collects road condition information; wherein, the road condition information includes the current road slope angle α, the current road segment traffic density ρ, and the current road segment limit traffic density ρ0.

[0011] Step 3: The vehicle collects real-time internal state information of its brakes, uses the brake state perception formula to determine the degree of brake performance attenuation, and determines the brake performance attenuation coefficient K based on the degree of brake performance attenuation; wherein, the real-time internal state information of the brakes includes the temperature, remaining thickness and surface water film thickness of the brake friction linings.

[0012] Step 4: Determine the available ground adhesion for both the preceding vehicle and the current vehicle. Based on the load factor, critical load factor, current peak adhesion factor, and current road slope angle, calculate the maximum braking deceleration correction factor e for both the preceding vehicle and the current vehicle. f e r The availability of ground adhesion is determined based on the load factor k and the critical load factor n. When the vehicle's load factor k is less than or equal to the critical load factor n, the vehicle has the ability to fully utilize ground adhesion, and the maximum braking force of the vehicle is the ground adhesion force. When the vehicle's load factor k is greater than the critical load factor n, the vehicle cannot fully utilize ground adhesion, and the maximum braking force of the vehicle is the maximum braking force of the brake. The maximum braking force of the brake is the maximum total braking force that the brake can provide when all wheels do not slip.

[0013] Step 5: Based on the current road slope angle α and the speed v of the vehicle in front.f The standard braking distance s of the vehicle in front 0，f Braking coordination time t of the vehicle in front f and the maximum braking deceleration correction factor e of the vehicle in front f The corrected estimated braking distance s of the preceding vehicle is calculated using the preceding vehicle braking simulation formula. f ;

[0014] Step 6: Based on the current road slope angle α and the vehicle's speed v r The standard braking distance of this vehicle is s 0，r The braking coordination time t of this vehicle r The maximum braking deceleration correction factor e of this vehicle r Using the braking performance attenuation coefficient K of the vehicle's brakes, the corrected estimated braking distance s of the vehicle is calculated using the vehicle's braking simulation formula. r ;

[0015] Step 7: Consider the impact of road traffic conditions, driver style, and the type of vehicle in front on the actual driving of the driver. Based on the traffic flow density ρ of the current road segment, the maximum traffic flow density ρ0 of the current road segment, the conservative driving style X, and the type of vehicle in front, use the expected distance adjustment formula to calculate the stationary expected distance d0 between the vehicle and the vehicle in front.

[0016] Step 8: Estimate the braking distance s based on the corrections made by the vehicle in front. f The corrected estimated braking distance s of this vehicle r 1. The expected stationary distance d0 between this vehicle and the vehicle in front; 2. The vehicle's speed v. r Calculate the adaptive cruise control safe distance x based on the vehicle's dangerous reaction time T.

[0017] As a further improvement of the present invention, in step 1, the standard braking distance s0 is the distance traveled by the vehicle from the start of braking to the complete stop of the vehicle when the vehicle is at the standard driving speed v0 and the maximum braking deceleration is applied. The driving road surface is a dry asphalt road surface. The standard driving speed v0 of the passenger car is 100km / h and the standard driving speed v0 of the commercial vehicle is 50km / h.

[0018] The critical load factor n is determined by the road adhesion and the vehicle's braking performance, and is used to determine whether the vehicle currently has the ability to fully utilize the ground adhesion.

[0019] The load factor k represents the current load level of the vehicle, and its calculation formula is as follows:

[0020]

[0021] In the formula, k is the load factor, m is the current total mass of the vehicle, and m0 is the curb weight of the vehicle.

[0022] The current peak adhesion coefficient The estimation formula is related to the current road surface, tires, and vehicle speed:

[0023]

[0024] In the formula, This is the vehicle's current peak adhesion coefficient, used to correct for the vehicle's maximum braking deceleration;

[0025] Let be the peak adhesion coefficient of the i-th typical road surface under standard conditions, where the standard conditions are the measured values. The corresponding vehicle speed and tire condition, i = 1, 2, 3, 4, 5, 6, represent dry asphalt road surface, wet asphalt road surface, dry cement road surface, wet cobblestone road surface, snow-covered road surface, and icy road surface, respectively;

[0026] ρ i (i = 1, 2, 3, 4, 5, 6) represents the degree of matching between the current road surface and the i-th typical road surface, where i = 1, 2, 3, 4, 5, 6 represent dry asphalt road surface, wet asphalt road surface, dry cement road surface, wet cobblestone road surface, snow-covered road surface, and icy road surface, respectively.

[0027] γ1, γ2, γ3, and γ4 are weighting factors, which are trained through a neural network to obtain appropriate values.

[0028] p is the current tire pressure, and p0 is the tire pressure under standard conditions;

[0029] B is the current tire section width, and B0 is the tire section width under standard conditions.

[0030] h represents the current tire tread depth, and h0 represents the tire tread depth under standard conditions.

[0031] v represents the vehicle's current speed, and v′0 represents the vehicle's speed under standard conditions.

[0032] As a further improvement of the present invention, in step 3, the degree of brake performance attenuation is related to the temperature, moisture content, and wear of the brake friction linings. The degree of brake performance attenuation of the vehicle's brakes is determined according to the brake state perception formula.

[0033]

[0034] In the formula, P b It is a dimensionless value used to determine the degree of brake performance degradation of the vehicle's brakes;

[0035] ω1, ω2, and ω3 are weight factors, which are trained using a neural network to obtain appropriate values.

[0036] T j Let T0 be the temperature of the friction lining in the j-th wheel, and T0 be the temperature limit of the friction lining under normal braking performance. j = 1, 2, 3, 4, representing the left front wheel, right front wheel, left rear wheel, and right rear wheel, respectively.

[0037] L j L0 represents the surface water film thickness of the friction lining in the j-th wheel, and L0 is the limit value of the surface water film thickness of the friction lining under normal braking performance. j = 1, 2, 3, 4, representing the left front wheel, right front wheel, left rear wheel, and right rear wheel, respectively.

[0038] δ j δ0 represents the remaining thickness of the friction lining in the j-th wheel, and δ0 is the limit value of the remaining thickness of the friction lining under normal braking performance. j = 1, 2, 3, 4, representing the left front wheel, right front wheel, left rear wheel, and right rear wheel, respectively.

[0039] The vehicle brake P is set. b Given four threshold values ​​a1, a2, a3, and a4, then P b The five values ​​correspond to the five braking performance attenuation coefficients of this vehicle's brakes:

[0040] When P b When ≤a1, the braking efficiency attenuation coefficient K of the vehicle's brake is K1;

[0041] When a1 <P b When ≤a2, the braking efficiency attenuation coefficient K of the vehicle's brake is K2;

[0042] When a2 <P b When ≤a3, the braking efficiency attenuation coefficient K of the vehicle's brake is K3;

[0043] When a3 <P b When ≤a4, the braking efficiency attenuation coefficient K of the vehicle's brake is K4;

[0044] When P b When >a4, the braking efficiency attenuation coefficient K of the vehicle brake is K5.

[0045] As a further improvement of the present invention, in step 4, the maximum braking deceleration correction factors for the preceding vehicle and the current vehicle are respectively:

[0046]

[0047]

[0048] In the formula, ef is the correction factor for the maximum braking deceleration of the preceding vehicle, e r This is the correction factor for the maximum braking deceleration of this vehicle;

[0049] α is the current slope angle of the road, used to represent the magnitude of the slope in the direction the vehicle is moving;

[0050] k f n is the load factor of the vehicle in front. f k is the critical load factor of the vehicle in front. r n is the load factor of this vehicle. r This is the critical load factor for this vehicle;

[0051] This represents the current peak adhesion coefficient of the vehicle in front. This is the current peak adhesion coefficient of the vehicle. The peak adhesion coefficient of dry asphalt pavement under standard conditions, where standard conditions refer to the measurement... The corresponding vehicle speed and tire condition.

[0052] As a further improvement of the present invention, in step 5, the corrected estimated braking distance s of the preceding vehicle is... f Calculations are performed using the aforementioned front vehicle braking simulation formula:

[0053]

[0054] In the formula, s f The corrected estimated braking distance for the vehicle in front represents the distance the vehicle in front needs to travel from its current state to a standstill with maximum braking deceleration. It is divided into two cases: uphill braking and downhill braking.

[0055] v f Let α be the speed of the vehicle in front, α be the current slope angle of the road, g be the acceleration due to gravity, and s be the speed of the vehicle in front. f e is the braking coordination time of the vehicle in front. f The correction factor for the maximum braking deceleration of the vehicle in front;

[0056] s 0，f v is the standard braking distance of the vehicle in front. 0，f The standard driving speed is 100 km / h for passenger cars and 50 km / h for commercial vehicles.

[0057] As a further improvement of the present invention, in step 6, the corrected estimated braking distance s of the vehicle is... r Calculations were performed using the vehicle's braking simulation formula.

[0058]

[0059] In the formula, s r The corrected estimated braking distance for this vehicle represents the distance the vehicle needs to travel from its current state to a standstill when braking at its maximum deceleration. It is divided into two cases: uphill braking and downhill braking.

[0060] K is the braking efficiency attenuation coefficient of the vehicle's brakes, which indicates the degree of decline in the vehicle's braking performance;

[0061] v r α is the vehicle's speed, α is the current road's incline angle, g is the acceleration due to gravity, and t is the acceleration due to gravity. r e is the braking coordination time of this vehicle. r This is the correction factor for the maximum braking deceleration of this vehicle;

[0062] s 0，r This is the standard braking distance for this vehicle, v 0，r This is the standard driving speed of the vehicle. The standard driving speed for passenger cars is 100 km / h, and the standard driving speed for commercial vehicles is 50 km / h.

[0063] As a further improvement of the present invention, in step 7, the expected stationary distance d0 between the vehicle and the vehicle in front is calculated using the expected vehicle distance adjustment formula:

[0064]

[0065] In the formula, d0 is the expected stationary distance between the vehicle and the vehicle in front, representing the minimum distance the driver expects when the vehicle and the vehicle in front are stationary at the same time.

[0066] ρ is the traffic density of the current road segment, and ρ0 is the maximum traffic density of the current road segment. The degree of traffic congestion of the current road segment is judged based on the ratio of ρ to ρ0.

[0067] X represents the driving style conservatism level, indicating how conservative the driver is in maintaining a following distance. It is manually set by the driver on the in-vehicle touchscreen. The maximum value for the driving style conservatism level is 100, the minimum value is 0, and the default value is 50.

[0068] D is the standard stationary distance, which is determined by the vehicle type of the vehicle in front. The vehicle type is classified according to the maximum permissible gross vehicle weight, including light vehicles, medium vehicles, heavy vehicles, and extra-heavy vehicles.

[0069] The light vehicle is a vehicle with a maximum permissible gross weight of less than or equal to 2500 kg;

[0070] The medium-sized vehicle is defined as a vehicle with a maximum permissible gross weight greater than 2,500 kg and less than or equal to 6,000 kg.

[0071] The heavy-duty vehicle is defined as a vehicle with a maximum permissible gross weight greater than 6,000 kg and less than or equal to 14,000 kg.

[0072] The extra-heavy vehicles are those with a maximum permissible gross weight greater than 14,000 kg;

[0073] The method for determining the static standard distance D is as follows:

[0074] When the vehicle type of the vehicle in front is a light vehicle, the standard stationary distance D is 2.5m;

[0075] When the current vehicle is a medium-sized vehicle, the standard stationary distance D is 3m;

[0076] When the vehicle type of the current vehicle is a heavy vehicle, the standard stationary distance D is 3.5m;

[0077] When the vehicle type of the current vehicle is an extra-heavy vehicle, the standard stationary distance D is 4m.

[0078] As a further improvement of the present invention, in step 8, the formula for calculating the adaptive cruise safety distance x is:

[0079] x = max(0, s) r -s f )+d o +v r T

[0080] In the formula, x is the adaptive cruise safety distance, which is the control target of the adaptive cruise system of intelligent connected vehicles. If the actual distance between the vehicle and the vehicle in front is less than the adaptive cruise safety distance x, the adaptive cruise system will start to control the vehicle to decelerate in order to ensure that the actual distance between the vehicle and the vehicle in front is greater than or equal to the adaptive cruise safety distance x.

[0081] s r For the corrected estimated braking distance of this vehicle, s f The corrected estimated braking distance for the vehicle in front, d0 is the expected stationary distance between the current vehicle and the vehicle in front, v r This is the vehicle's speed.

[0082] T represents the vehicle's reaction time to danger, which is the time required for the vehicle to start braking from the moment it detects the emergency braking of the vehicle in front. Its specific value is determined by the signal acquisition time, data processing time, and braking decision time.

[0083] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0084] 1. This invention takes into account both the braking performance of the vehicle in question and the braking performance of the vehicle in front. Based on the difference in braking performance between the vehicle in question and the vehicle in front, it calculates the adaptive cruise safety distance that best suits the current driving conditions, avoiding following distances that are too small or too large. This not only minimizes the possibility of a collision between the vehicle in question and the vehicle in front, but also improves driving efficiency.

[0085] 2. This invention modifies the maximum braking deceleration of the vehicle based on the vehicle's load, road surface adhesion, and road slope, making the estimated braking distance more realistic. It also takes into account the real-time performance of the vehicle's brakes, thus preventing the vehicle from colliding with the vehicle in front due to brake performance degradation.

[0086] 3. This invention utilizes vehicle-to-everything (V2X) technology to collect information about the vehicle ahead and the road, ensuring the accuracy and real-time nature of the information and improving the calculation accuracy and efficiency of the adaptive cruise safety distance.

[0087] 4. This invention takes into account the impact of road traffic conditions, driver style, and the type of vehicle in front on real-world driving, making the adaptive cruise safety distance more in line with the driver's expectations. Attached Figure Description

[0088] Figure 1 This is a flowchart illustrating the method of the present invention. Detailed Implementation

[0089] The invention will now be further explained with reference to the accompanying drawings.

[0090] This invention provides a method for calculating the safe distance of an adaptive cruise control system for intelligent connected vehicles, such as... Figure 1 As shown, it includes the following steps:

[0091] Step 1: Based on the vehicle-to-vehicle communication function of the Internet of Vehicles (IoV), this vehicle obtains the braking performance parameters, vehicle status information, and vehicle type of the vehicle in front. Here, this vehicle is equipped with an adaptive cruise control system, which controls the vehicle's speed to ensure that the actual distance between this vehicle and the vehicle in front is greater than or equal to the adaptive cruise safety distance calculated by this vehicle. The vehicle in front is the closest vehicle to this vehicle in its lane. The braking performance parameters of the vehicle in front include its standard braking distance s. 0，f Braking coordination time t of the vehicle in front f The critical load factor n of the vehicle in front f The vehicle status information of the vehicle in front includes the vehicle speed v. f The load factor k of the vehicle in front f And the current peak adhesion coefficient of the vehicle in front

[0092] The standard braking distance s0 is the distance a vehicle travels from the start of braking to a complete stop when it is at its standard driving speed v0 and at maximum braking deceleration. The driving surface is a dry asphalt road surface. The standard driving speed v0 for passenger cars is 100 km / h, and the standard driving speed v0 for commercial vehicles is 50 km / h.

[0093] The critical load factor n is determined by the road adhesion and the vehicle's braking performance, and is used to determine whether the vehicle currently has the ability to fully utilize the ground adhesion.

[0094] The load factor k represents the current load level of the vehicle, and its specific value is calculated by the vehicle. The calculation formula is as follows:

[0095]

[0096] Where k is the load factor, m is the current total mass of the vehicle, and m0 is the curb weight of the vehicle.

[0097] The current peak adhesion coefficient The estimation formula is related to the current road surface, tires, and vehicle speed:

[0098]

[0099] in, This is the vehicle's current peak adhesion coefficient, used to correct for the vehicle's maximum braking deceleration;

[0100] The peak adhesion coefficient is the i-th typical road surface under standard conditions. The specific value is obtained through testing. The standard conditions refer to the measurement... The corresponding vehicle speed and tire condition, i = 1, 2, 3, 4, 5, 6, represent dry asphalt road surface, wet asphalt road surface, dry cement road surface, wet cobblestone road surface, snow-covered road surface, and icy road surface, respectively;

[0101] ρ i (i = 1, 2, 3, 4, 5, 6) represents the degree of matching between the current road surface and the i-th typical road surface. The specific values ​​are measured by the vehicle-mounted sensor. i = 1, 2, 3, 4, 5, 6 represent dry asphalt road surface, wet asphalt road surface, dry cement road surface, wet cobblestone road surface, snow-covered road surface, and icy road surface, respectively.

[0102] γ1, γ2, γ3, and γ4 are weighting factors, which are trained through a neural network to obtain appropriate values.

[0103] p is the current tire pressure, and p0 is the tire pressure under standard conditions;

[0104] B is the current tire section width, and B0 is the tire section width under standard conditions.

[0105] h represents the current tire tread depth, and h0 represents the tire tread depth under standard conditions.

[0106] v represents the vehicle's current speed, and v′0 represents the vehicle's speed under standard conditions.

[0107] Step 2: This vehicle acquires its own braking performance parameters and vehicle status information. Based on the vehicle-to-road communication function of the Internet of Vehicles (IoV), this vehicle collects road condition information; wherein, the braking performance parameters of this vehicle include the vehicle's standard braking distance s. 0，r The braking coordination time t of this vehicle r And the critical load factor n of this vehicle r The vehicle status information includes the vehicle's speed v. r The load factor k of this vehicle r And the current peak coefficient of adhesion of this vehicle The road condition information includes the current road slope angle α, the current traffic density ρ of the current road segment, and the maximum traffic density ρ0 of the current road segment.

[0108] Step 3: The vehicle collects real-time internal state information of its brakes, uses the brake state perception formula to determine the degree of brake performance attenuation, and determines the brake performance attenuation coefficient K based on the degree of brake performance attenuation; wherein, the real-time internal state information of the brakes includes the temperature, remaining thickness and surface water film thickness of the brake friction linings.

[0109] The degree of brake performance degradation of the brake system is related to the temperature, moisture level, and wear of the brake friction linings. The degree of brake performance degradation of the vehicle's brakes is determined based on the brake state sensing formula.

[0110]

[0111] Among them, P b It is a dimensionless value used to determine the degree of brake performance degradation of the vehicle's brakes;

[0112] ω1, ω2, and ω3 are weight factors, which are trained using a neural network to obtain appropriate values.

[0113] T j Let T0 be the temperature of the friction lining in the j-th wheel, and T0 be the temperature limit of the friction lining under normal braking performance. j = 1, 2, 3, 4, representing the left front wheel, right front wheel, left rear wheel, and right rear wheel, respectively.

[0114] L jL0 represents the surface water film thickness of the friction lining in the j-th wheel, and L0 is the limit value of the surface water film thickness of the friction lining under normal braking performance. j = 1, 2, 3, 4, representing the left front wheel, right front wheel, left rear wheel, and right rear wheel, respectively.

[0115] δ j δ0 represents the remaining thickness of the friction lining in the j-th wheel, and δ0 is the limit value of the remaining thickness of the friction lining under normal braking performance. j = 1, 2, 3, 4, representing the left front wheel, right front wheel, left rear wheel, and right rear wheel, respectively.

[0116] The vehicle brake P is set. b Given four threshold values ​​a1, a2, a3, and a4, then P b The five values ​​correspond to the five braking performance attenuation coefficients of this vehicle's brakes:

[0117] When P b When ≤a1, the braking efficiency attenuation coefficient K of the vehicle's brake is K1;

[0118] When a1 <P b When ≤a2, the braking efficiency attenuation coefficient K of the vehicle's brake is K2;

[0119] When a2 <P b When ≤a3, the braking efficiency attenuation coefficient K of the vehicle's brake is K3;

[0120] When a3 <P b When ≤a4, the braking efficiency attenuation coefficient K of the vehicle's brake is K4;

[0121] When P b When >a4, the braking efficiency attenuation coefficient K of the vehicle's brake is K5;

[0122] Wherein, K5>K4>K3>K2>K1=1, and the specific values ​​of K2, K3, K4, and K5 are determined by the manufacturer.

[0123] Step 4: Determine the available ground adhesion for both the preceding vehicle and the current vehicle. Based on the load factor, critical load factor, current peak adhesion factor, and current road slope angle, calculate the maximum braking deceleration correction factor e for both the preceding vehicle and the current vehicle. f e r ;

[0124] The availability of ground adhesion is determined based on the load factor k and the critical load factor n. When the vehicle's load factor k is less than or equal to the critical load factor n, the vehicle has the ability to fully utilize ground adhesion, and the maximum braking force of the vehicle is the ground adhesion. When the vehicle's load factor k is greater than the critical load factor n, the vehicle cannot fully utilize ground adhesion, and the maximum braking force of the vehicle is the maximum braking force of the brake. The maximum braking force of the brake is the maximum total braking force that the brake can provide when all wheels do not slip.

[0125] The maximum braking deceleration correction factors for the preceding vehicle and the current vehicle are respectively:

[0126]

[0127]

[0128] Among them, e f e is the correction factor for the maximum braking deceleration of the vehicle in front. r This is the correction factor for the maximum braking deceleration of this vehicle;

[0129] α is the current road slope angle, used to represent the slope in the direction the vehicle is moving. The specific value of α is measured by the on-board sensor.

[0130] k f n is the load factor of the vehicle in front. f k is the critical load factor of the vehicle in front. r n is the load factor of this vehicle. r This is the critical load factor for this vehicle;

[0131] This represents the current peak adhesion coefficient of the vehicle in front. This is the current peak adhesion coefficient of the vehicle. The peak adhesion coefficient of dry asphalt pavement under standard conditions, where standard conditions refer to the measurement... The corresponding vehicle speed and tire condition.

[0132] Step 5: Based on the current road slope angle α and the speed v of the vehicle in front. f The standard braking distance s of the vehicle in front 0，f Braking coordination time t of the vehicle in front f and the maximum braking deceleration correction factor e of the vehicle in front f The corrected estimated braking distance s of the preceding vehicle is calculated using the preceding vehicle braking simulation formula. f ;

[0133] The corrected estimated braking distance s of the preceding vehicle f Calculations are performed using the aforementioned front vehicle braking simulation formula:

[0134]

[0135] Among them, s f The corrected estimated braking distance for the vehicle in front represents the distance the vehicle in front needs to travel from its current state to a standstill with maximum braking deceleration. It is divided into two cases: uphill braking and downhill braking.

[0136] v f Let α be the speed of the vehicle in front, α be the current slope angle of the road, g be the acceleration due to gravity, and s be the speed of the vehicle in front. f e is the braking coordination time of the vehicle in front. f The correction factor for the maximum braking deceleration of the vehicle in front;

[0137] s 0，f v is the standard braking distance of the vehicle in front. 0，f The standard driving speed is 100 km / h for passenger cars and 50 km / h for commercial vehicles.

[0138] Step 6: Based on the current road slope angle α and the vehicle's speed v r The standard braking distance of this vehicle is s 0，r The braking coordination time t of this vehicle r The maximum braking deceleration correction factor e of this vehicle r Using the braking performance attenuation coefficient K of the vehicle's brakes, the corrected estimated braking distance s of the vehicle is calculated using the vehicle's braking simulation formula. r ;

[0139] The corrected estimated braking distance s of this vehicle r Calculations were performed using the vehicle's braking simulation formula.

[0140]

[0141] Among them, s r The corrected estimated braking distance for this vehicle represents the distance the vehicle needs to travel from its current state to a standstill when braking at its maximum deceleration. It is divided into two cases: uphill braking and downhill braking.

[0142] K is the braking efficiency attenuation coefficient of the vehicle's brakes, which indicates the degree of decline in the vehicle's braking performance;

[0143] v r α is the vehicle's speed, α is the current road's incline angle, g is the acceleration due to gravity, and t is the acceleration due to gravity. r e is the braking coordination time of this vehicle. r This is the correction factor for the maximum braking deceleration of this vehicle;

[0144] s0，r This is the standard braking distance for this vehicle, v 0，r This is the standard driving speed of the vehicle. The standard driving speed for passenger cars is 100 km / h, and the standard driving speed for commercial vehicles is 50 km / h.

[0145] Step 7: Consider the impact of road traffic conditions, driver style, and the type of vehicle in front on the actual driving of the driver. Based on the traffic flow density ρ of the current road segment, the maximum traffic flow density ρ0 of the current road segment, the conservative driving style X, and the type of vehicle in front, use the expected distance adjustment formula to calculate the stationary expected distance d0 between the vehicle and the vehicle in front.

[0146] The desired stationary distance d0 between this vehicle and the vehicle in front is calculated using the desired vehicle distance adjustment formula:

[0147]

[0148] Where d0 is the expected stationary distance between the vehicle and the vehicle in front, representing the minimum distance the driver expects when the vehicle and the vehicle in front are both stationary.

[0149] ρ is the traffic density of the current road segment, and ρ0 is the maximum traffic density of the current road segment. The degree of traffic congestion of the current road segment is judged based on the ratio of ρ to ρ0.

[0150] X represents the driving style conservatism level, indicating how conservative the driver is in maintaining a following distance. It is manually set by the driver on the in-vehicle touchscreen. The maximum value for the driving style conservatism level is 100, the minimum value is 0, and the default value is 50.

[0151] D is the standard stationary distance, which is determined by the vehicle type of the vehicle in front. The vehicle type is classified according to the maximum permissible gross vehicle weight, including light vehicles, medium vehicles, heavy vehicles, and extra-heavy vehicles.

[0152] The light vehicle is a vehicle with a maximum permissible gross weight of less than or equal to 2500 kg;

[0153] The medium-sized vehicle is defined as a vehicle with a maximum permissible gross weight greater than 2,500 kg and less than or equal to 6,000 kg.

[0154] The heavy-duty vehicle is defined as a vehicle with a maximum permissible gross weight greater than 6,000 kg and less than or equal to 14,000 kg.

[0155] The extra-heavy vehicles are those with a maximum permissible gross weight greater than 14,000 kg;

[0156] The method for determining the static standard distance D is as follows:

[0157] When the vehicle type of the vehicle in front is a light vehicle, the standard stationary distance D is 2.5m;

[0158] When the current vehicle is a medium-sized vehicle, the standard stationary distance D is 3m;

[0159] When the vehicle type of the current vehicle is a heavy vehicle, the standard stationary distance D is 3.5m;

[0160] When the vehicle type of the current vehicle is an extra-heavy vehicle, the standard stationary distance D is 4m.

[0161] Step 8: Estimate the braking distance s based on the corrections made by the vehicle in front. f The corrected estimated braking distance s of this vehicle r 1. The expected stationary distance d0 between this vehicle and the vehicle in front; 2. The vehicle's speed v. r Calculate the adaptive cruise control safe distance x based on the vehicle's dangerous reaction time T;

[0162] The formula for calculating the adaptive cruise safety distance x is as follows:

[0163] x = max(0, s) r -s f )+d0+v r T

[0164] Where x is the adaptive cruise safety distance, which is the control target of the adaptive cruise system of intelligent connected vehicles. If the actual distance between the vehicle and the vehicle in front is less than the adaptive cruise safety distance x, the adaptive cruise system will start to control the vehicle to decelerate in order to ensure that the actual distance between the vehicle and the vehicle in front is greater than or equal to the adaptive cruise safety distance x.

[0165] s r For the corrected estimated braking distance of this vehicle, s f The corrected estimated braking distance for the vehicle in front, d0 is the expected stationary distance between the current vehicle and the vehicle in front, v r This is the vehicle's speed.

[0166] T represents the vehicle's reaction time to danger, which is the time required for the vehicle to start braking from the moment it detects the emergency braking of the vehicle in front. Its specific value is determined by the signal acquisition time, data processing time, and braking decision time.

Claims

1.A safety distance calculation method for an intelligent vehicle adaptive cruise control system, characterized in that, The method comprises the following steps: Step 1: Based on the vehicle-to-vehicle communication function of the Internet of Vehicles, the host vehicle acquires the braking performance parameters, vehicle state information and vehicle type of the preceding vehicle; The vehicle is a vehicle equipped with an adaptive cruise control system, the adaptive cruise control system controls the driving speed of the vehicle to ensure that the actual distance between the vehicle and a preceding vehicle is greater than or equal to a calculated adaptive cruise control safety distance; the preceding vehicle is a vehicle in front of the vehicle in a lane in which the vehicle is located and closest to the vehicle; the braking performance parameters include a standard braking distance s0, a braking coordination time t, and a critical load coefficient n; the vehicle state information includes a driving speed v, a load coefficient k, and a current peak adhesion coefficient Step 2: The host vehicle acquires the braking performance parameters and vehicle state information of the host vehicle, and based on the vehicle-to-road communication function of the Internet of Vehicles, the host vehicle collects road condition information; The road condition information comprises the uphill / downhill angle α of the current road, the traffic density ρ of the current road section and the limit traffic density ρ0 of the current road section; Step 3: The host vehicle collects real-time internal state information of the host vehicle brake, and judges the braking efficiency attenuation degree of the host vehicle brake by using a brake state sensing formula, and determines the braking efficiency attenuation coefficient K of the host vehicle brake based on the braking efficiency attenuation degree; The real-time internal state information of the brake comprises the temperature, residual thickness and surface water film thickness of the brake friction pad; Step 4: judging the available degree of the ground adhesion force of the front vehicle and the vehicle respectively, calculating the maximum braking deceleration correction factor e of the front vehicle and the vehicle respectively according to the load coefficient, the critical load coefficient, the current peak adhesion coefficient and the up and down slope angle of the current road f ,e r ; The available degree of the ground adhesion force is judged according to the load coefficient k and the critical load coefficient n; when the load coefficient k of the vehicle is less than or equal to the critical load coefficient n, the vehicle has the ability to fully utilize the ground adhesion force, and at this time the maximum braking force of the vehicle is the ground adhesion force; when the load coefficient k of the vehicle is greater than the critical load coefficient n, the vehicle cannot fully utilize the ground adhesion force, and at this time the maximum braking force of the vehicle is the maximum braking force of the brake; the maximum braking force of the brake is the maximum total braking force that the brake can provide under the condition that all wheels do not slip; Step 5: According to the uphill and downhill angle α of the current road, the driving speed v of the preceding vehicle f , the standard braking distance s of the preceding vehicle 0,f , the braking coordination time t of the preceding vehicle f , and the maximum braking deceleration correction factor e of the preceding vehicle f , the modified estimated braking distance s f of the preceding vehicle is calculated by using the preceding vehicle braking simulation formula. Step 6: The modified estimated braking distance s of the host vehicle is calculated by using the host vehicle braking simulation formula according to the uphill / downhill angle a of the current road, the running speed v of the host vehicle r , the standard braking distance s of the host vehicle 0,r , the braking coordination time t of the host vehicle r , the maximum braking deceleration correction factor e of the host vehicle r , and the braking efficiency attenuation coefficient K of the host vehicle brake r ; Step 7: Considering the influence of the road section traffic condition, the driver style and the vehicle type of the preceding vehicle on the driving of the driver in reality, the static expected distance d0 between the host vehicle and the preceding vehicle is calculated by using an expected distance adjustment formula according to the traffic density ρ of the current road section, the limit traffic density ρ0 of the current road section, the driving style conservativeness X and the vehicle type of the preceding vehicle; Step 8: Correcting the estimated braking distance s of the preceding vehicle f the corrected estimated braking distance s of the host vehicle r the stationary desired distance d0 between the host vehicle and the preceding vehicle, and the travel speed v of the host vehicle r and the dangerous reaction time T of the host vehicle, to calculate the adaptive cruise safety distance x. 2.The safety distance calculation method of the intelligent vehicle adaptive cruise control system according to claim 1, characterized in that In step 1 of claim 1, the standard braking distance s0 is the distance traveled by the vehicle from starting braking to complete stop at the maximum braking deceleration under the condition that the vehicle is at the standard driving speed v0, the driving road surface is a dry asphalt road surface, the standard driving speed v0 of the passenger vehicle is 100 km / h, and the standard driving speed v0 of the commercial vehicle is 50 km / h; The critical load coefficient n is determined by the adhesion condition of the road and the braking performance of the vehicle, and is used to judge whether the vehicle currently has the ability to fully utilize the ground adhesion force; The load coefficient k represents the current loading degree of the vehicle, and the calculation formula is: Wherein, k is the load coefficient, m is the current total mass of the vehicle, and m0 is the curb weight of the vehicle; the current peak adhesion coefficient which depends on the current road surface, the tire and the vehicle speed. wherein, is the current peak adhesion coefficient of the vehicle, used to correct the maximum braking deceleration of the vehicle; is the peak adhesion coefficient of the ith typical road surface under standard conditions, the standard conditions being the vehicle speed and tire conditions corresponding to the time of measurement, i = 1, 2, 3, 4, 5, 6, respectively representing a dry asphalt road surface, a wet asphalt road surface, a dry cement road surface, a wet cobblestone road surface, a snowy road surface, and an icy road surface. is the peak adhesion coefficient of the ith typical road surface under standard conditions, the standard conditions being the vehicle speed and tire conditions corresponding to the time of measurement, i = 1, 2, 3, 4, 5, 6, respectively representing a dry asphalt road surface, a wet asphalt road surface, a dry cement road surface, a wet cobblestone road surface, a snowy road surface, and an icy road surface. ρ i (i = 1, 2, 3, 4, 5, 6) represents the matching degree of the current road surface with the ith typical road surface, i = 1, 2, 3, 4, 5, 6, respectively representing dry asphalt road surface, wet asphalt road surface, dry cement road surface, wet cobblestone road surface, snow-covered road surface, and icy road surface; γ1, γ2, γ3, γ4 are weight factors, and appropriate values are obtained by training a neural network; p is the current tire air pressure, and p0 is the tire air pressure under standard conditions; B is the current tire section width, and B0 is the tire section width under standard conditions; h is the current tire pattern depth, and h0 is the tire pattern depth under standard conditions; v is the current driving speed of the vehicle, and v'0 is the driving speed of the vehicle under standard conditions. 3.The safety distance calculation method of the intelligent vehicle adaptive cruise control system according to claim 1, characterized in that The brake performance attenuation degree of the brake is related to the temperature, water wet degree and wear degree of the brake friction pad, and the brake performance attenuation degree of the vehicle brake is determined according to the brake state sensing formula: where P b is a dimensionless value used to determine the degree of brake effectiveness degradation of the host vehicle. ω1, ω2, ω3 are weight factors, and appropriate values are obtained through neural network training; T j Tj is the temperature of the friction pad in the jth wheel, To is the temperature limit value of the friction pad in the case of normal braking performance, j = 1, 2, 3, 4, respectively representing the left front wheel, the right front wheel, the left rear wheel, the right rear wheel; L j Lj is the surface water film thickness of the friction pad in the jth wheel, L0 is the surface water film thickness limit value of the friction pad under normal braking performance, j = 1, 2, 3, 4, respectively representing the left front wheel, the right front wheel, the left rear wheel, the right rear wheel; δ j δj is the residual thickness of the friction pad in the jth wheel, δ0 is the limit value of the residual thickness of the friction pad in the case of normal braking efficiency, j = 1, 2, 3, 4, respectively representing the left front wheel, the right front wheel, the left rear wheel, the right rear wheel; The host vehicle brake P is set b The four threshold values a1, a2, a3, a4 of the value P b The five situations of the value correspond to five brake effectiveness decay coefficients of the host vehicle brake respectively: When P b When a1, the braking effectiveness attenuation coefficient K of the host vehicle brake is K1; When a1 < P b When a1 < P b When a1 < P b When a1 < P b When a1 < P b When a1 < P b When a1 < P b When When a2 b When a3, the braking effectiveness attenuation coefficient K of the host vehicle brake is K3. When a3 < P b When a4 < P, the braking effectiveness attenuation coefficient K of the host vehicle brake is K4. When P b a4, the braking effectiveness decay coefficient K of the host vehicle brake is K5. 4.The safety distance calculation method of the intelligent vehicle adaptive cruise control system according to claim 1, wherein In step 4 of claim 1, the maximum brake deceleration correction factors of the preceding vehicle and the vehicle are respectively: where e f is a maximum braking deceleration correction factor for the preceding vehicle, e r is a maximum braking deceleration correction factor for the subject vehicle; α is the up-and-down slope angle of the current road, and is used to represent the slope size of the vehicle advancing direction; k f is the load coefficient of the preceding vehicle, n f is the critical load coefficient of the preceding vehicle, k r is the load coefficient of the subject vehicle, n r is the critical load coefficient of the subject vehicle; the current peak adhesion coefficient of the preceding vehicle, the current peak adhesion coefficient of the subject vehicle, the peak adhesion coefficient of a dry asphalt road under standard conditions, said standard conditions corresponding to the vehicle speed and tire conditions at the time of measurement the current peak adhesion coefficient of the subject vehicle, 5.The safety distance calculation method of the intelligent vehicle adaptive cruise control system according to claim 1, characterized in that In the step 5 of the claim 1, the modified estimated braking distance s of the preceding vehicle f The calculation is made by the preceding vehicle braking simulation formula: where s f is the corrected estimated braking distance of the preceding vehicle, representing the distance the preceding vehicle needs to travel to come to a stop from the current state with maximum deceleration, and is divided into uphill braking and downhill braking. v f is the driving speed of the preceding vehicle, a is the uphill / downhill angle of the current road, g is the acceleration of gravity, t f is the braking coordination time of the preceding vehicle, e f is the maximum braking deceleration correction factor of the preceding vehicle; s 0，f is the standard braking distance of the preceding vehicle, v 0，f is the standard driving speed of the preceding vehicle, the standard driving speed of a passenger car being 100 km / h and the standard driving speed of a commercial vehicle being 50 km / h. 6.The safety distance calculation method of the intelligent vehicle adaptive cruise control system according to claim 1, characterized in that In the step 6 of the claim 1, the modified estimated braking distance s of the host vehicle r The modified estimated braking distance s of the host vehicle is calculated by the host vehicle braking simulation formula: wherein s r is the corrected estimated braking distance of the host vehicle, representing the distance the host vehicle needs to travel to stop from the current state with the maximum braking deceleration, and is divided into two cases of uphill braking and downhill braking. K is the brake performance attenuation coefficient of the vehicle brake, and represents the decline of the vehicle brake performance; v r is the running speed of the vehicle, a is the uphill / downhill angle of the current road, g is the acceleration of gravity, t r is the brake coordination time of the vehicle, e r is the maximum brake deceleration correction factor of the vehicle; s 0，r This is the standard braking distance for this vehicle, v 0，r This is the standard driving speed of the vehicle. The standard driving speed for passenger cars is 100 km / h, and the standard driving speed for commercial vehicles is 50 km / h. 7.The safety distance calculation method of the intelligent vehicle adaptive cruise control system according to claim 1, characterized in that In step 7 of claim 1, the static desired distance d0 of the vehicle and the preceding vehicle is calculated through the desired distance adjustment formula: d0 is the static desired distance of the vehicle and the preceding vehicle, and represents the minimum distance expected by the driver when the vehicle and the preceding vehicle are static; ρ is the traffic density of the current section, and ρ0 is the limit traffic density of the current section, and the traffic congestion degree of the current section is determined according to the ratio of ρ and ρ0; X is the driving style conservatism, which represents the conservatism of the driver to the following distance, and is manually set by the driver on the vehicle-mounted touch screen, the maximum value of the driving style conservatism is 100, the minimum value is 0, and the default value is 50; D is the static standard distance, which is determined by the vehicle type of the preceding vehicle, and the vehicle type is classified according to the maximum allowable total mass, including light vehicle, medium vehicle, heavy vehicle and super heavy vehicle; The light vehicle is a vehicle with a maximum allowable total mass less than or equal to 2500 kg; The medium vehicle is a vehicle with a maximum allowable total mass greater than 2500 kg and less than or equal to 6000 kg; The heavy vehicle is a vehicle with a maximum allowable total mass greater than 6000 kg and less than or equal to 14000 kg; The super heavy vehicle is a vehicle with a maximum allowable total mass greater than 14000 kg; The value of the static standard distance D is: When the vehicle type of the current vehicle is light vehicle, the static standard distance D is 2.5 m; When the vehicle type of the current vehicle is medium vehicle, the static standard distance D is 3 m; When the vehicle type of the current vehicle is heavy vehicle, the static standard distance D is 3.5 m; When the vehicle type of the current vehicle is super heavy vehicle, the static standard distance D is 4 m. 8.The safety distance calculation method of the intelligent vehicle adaptive cruise control system according to claim 1, characterized in that In step 8 of claim 1, the calculation formula of the adaptive cruise safety distance x is: x = max(0, s r - s f + d0+ v r T x is the adaptive cruise safety distance, which is the control target of the adaptive cruise control system, and if the actual distance between the vehicle and the preceding vehicle is less than the adaptive cruise safety distance x, the adaptive cruise control system starts to control the vehicle to slow down, so that the actual distance between the vehicle and the preceding vehicle is greater than or equal to the adaptive cruise safety distance x; s r s is a corrected estimated braking distance of the host vehicle f d0 is a static desired distance between the host vehicle and the preceding vehicle, v r v is a running speed of the host vehicle T is the dangerous reaction time of the vehicle, which represents the time required for the vehicle to start braking after detecting the emergency braking of the preceding vehicle, and the specific value is determined by the signal acquisition time, data processing time and braking decision time.

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