CN115817471A - Safe distance calculation method of intelligent networked automobile self-adaptive cruise control system - Google Patents
Safe distance calculation method of intelligent networked automobile self-adaptive cruise control system Download PDFInfo
- Publication number
- CN115817471A CN115817471A CN202211552279.5A CN202211552279A CN115817471A CN 115817471 A CN115817471 A CN 115817471A CN 202211552279 A CN202211552279 A CN 202211552279A CN 115817471 A CN115817471 A CN 115817471A
- Authority
- CN
- China
- Prior art keywords
- vehicle
- braking
- distance
- brake
- current
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Landscapes
- Control Of Driving Devices And Active Controlling Of Vehicle (AREA)
Abstract
The invention discloses a safe distance calculation method of an intelligent networked automobile self-adaptive cruise control system, which comprises the following steps: the vehicle obtains the braking performance parameters, the vehicle state information and the vehicle type of the front vehicle by using a vehicle-to-vehicle communication function; the method comprises the steps that the vehicle obtains braking performance parameters and vehicle state information of the vehicle, and road condition information is collected by utilizing a vehicle-to-road communication function; judging the attenuation degree of the braking efficiency of the vehicle brake by using a brake state perception formula; calculating a maximum braking deceleration correction factor of a front vehicle and a self vehicle; calculating the corrected estimated braking distance of the front vehicle by using a front vehicle braking simulation formula; calculating the corrected estimated braking distance of the vehicle by using a vehicle braking simulation formula; calculating a static expected distance between the vehicle and the front vehicle by using an expected distance adjusting formula; and calculating the self-adaptive cruise safe distance. By adopting the method, the appropriate self-adaptive cruise safe distance can be calculated, and the driving safety and the driving efficiency of the automobile are considered.
Description
Technical Field
The invention belongs to the field of intelligent networked automobile safety, and particularly relates to a safe distance calculation method of an intelligent networked automobile self-adaptive cruise control system.
Background
The intelligent internet automobile is a new automobile system combining the internet of vehicles and the intelligent automobile, realizes information interaction between vehicles, between vehicles and people, between vehicles and roads, between vehicles and cloud platforms through the internet of vehicles technology, combines the functions of environment perception, intelligent decision and cooperative control, improves the safety, comfort, efficiency and convenience of automobile driving, and finally replaces people to realize automatic driving.
The adaptive cruise control is an advanced driving assistance function developed on the basis of the constant-speed cruise control. When no vehicle exists in front, the self-adaptive cruise control system controls the vehicle to run at the speed set by the driver, and when the vehicle appears in the front, the self-adaptive cruise control system automatically controls the speed to enable the vehicle and the front vehicle to keep a safe following distance, so that the longitudinal running of the vehicle is automatically controlled, the labor intensity of the driver is reduced, and the running safety and the riding comfort are improved.
According to the statistics of road traffic accidents, rear-end collision accidents occupy a large proportion of the road traffic accidents, and most of the rear-end collision accidents are caused by too high driving speed, too short following distance and inattentive attention of drivers. Therefore, applying adaptive cruise control and adopting an appropriate safe distance as a control target of the adaptive cruise system can greatly reduce the possibility of occurrence of a rear-end collision accident.
At present, methods for calculating the self-adaptive cruise safe distance mainly comprise a fixed vehicle distance method, a vehicle head time distance method, a braking process analysis method, a driver characteristic estimation method and the like, and the existing methods have the following problems: 1) The emergency braking process of the vehicle under extreme conditions cannot be considered, and the vehicle cannot be ensured to avoid rear-end collision under any vehicle following condition; 2) When the braking process is analyzed, only the braking performance of the vehicle is considered, and the quality of the braking performance of the front vehicle cannot be considered, when the braking performance of the front vehicle is good, the rear-end collision is difficult to avoid due to too short safety distance, and when the braking performance of the front vehicle is poor, the driving efficiency is difficult to ensure due to too long safety distance; 3) Failure to take into account the effect of driver characteristics on the safe distance results in the calculated safe distance not meeting the driver's expectations.
Disclosure of Invention
In view of the above problems, the present invention provides a safe distance calculation method for an intelligent networked automobile adaptive cruise control system, which is used for calculating an appropriate adaptive cruise safe distance and considering both the driving safety and the driving efficiency of an automobile.
In order to achieve the purpose, the specific technical scheme of the invention is as follows:
a safe distance calculation method of an intelligent networked automobile self-adaptive cruise control system comprises the following steps:
step 1: based on the vehicle-to-vehicle communication function of the Internet of vehicles, the vehicle acquires the brake performance parameters, the vehicle state information and the vehicle type of the front vehicle; the self-adaptive cruise control system controls the running speed of the self-adaptive cruise control system to ensure that the actual distance between the self-adaptive cruise control system and a front vehicle is greater than or equal to the self-adaptive cruise safe distance calculated by the self-adaptive cruise control system; the front vehicle is a vehicle which is positioned in front of the vehicle and is closest to the vehicle in the lane where the vehicle is positioned; the braking performance parameter comprises a standard braking distance s 0 Braking coordination time t and critical load factor n; the vehicle state information comprises a running vehicle speed v, a load factor k and a current peak adhesion coefficient
Step 2: the method comprises the steps that the vehicle acquires braking performance parameters and vehicle state information of the vehicle, and the vehicle acquires road condition information based on a vehicle-to-road communication function of the Internet of vehicles; the road condition information comprises an up-down slope angle alpha of the current road, traffic density rho of the current road section and limit traffic density rho of the current road section 0 ；
And step 3: the vehicle acquires real-time internal state information of the vehicle brake, judges the braking efficiency attenuation degree of the vehicle brake by using a brake state perception formula, and determines the braking efficiency attenuation coefficient K of the vehicle brake on the basis of the braking efficiency attenuation degree; the real-time internal state information of the brake comprises the temperature, the residual thickness and the surface water film thickness of a brake friction lining;
and 4, step 4: respectively judging the available degree of the adhesion force of the front vehicle and the self vehicle to the ground, and respectively calculating the maximum braking deceleration correction factor e of the front vehicle and the self vehicle according to the load coefficient, the critical load coefficient, the current peak adhesion coefficient and the current up-down slope angle of the road f ，e r (ii) a The usable degree of the ground adhesion is judged according to a load factor k and a critical load factor n, when the load factor k of the vehicle is less than or equal to the critical load factor n, the vehicle has the capacity of completely utilizing the ground adhesion, and the maximum braking force of the vehicle is the ground adhesion; when the load factor k of the vehicle is greater than the critical load factor n, the vehicle cannot fully utilize the 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 which can be provided by the brake under the condition that all wheels do not slip;
and 5: according to the up-down slope angle alpha of the current road and the running speed v of the front vehicle f Standard braking distance s of front vehicle 0，f Braking coordination time t of front vehicle f And the maximum braking deceleration correction factor e of the preceding vehicle f Calculating the corrected estimated braking distance s of the front vehicle by using a front vehicle braking simulation formula f ；
Step 6: according to the up-down slope angle alpha of the current road and the running speed v of the vehicle r Standard braking distance s of the vehicle 0，r Braking coordination time t of the vehicle r Maximum braking deceleration correction factor e of the vehicle r And calculating the corrected estimated braking distance s of the vehicle by using a vehicle braking simulation formula r ；
And 7: considering the influence of road section traffic conditions, driver styles and front vehicle types on the real-world driving of the driver, and according to the traffic flow density rho of the current road section and the limit traffic flow density rho of the current road section 0 The driving style conservative degree X and the vehicle type of the front vehicle, and calculating the static expected distance d between the vehicle and the front vehicle by utilizing an expected vehicle distance adjusting formula 0 ；
And 8: estimating braking distance s according to correction of preceding vehicle f Corrected estimated braking distance s of the vehicle r Expected stationary distance d between the vehicle and the preceding vehicle 0 The running speed v of the vehicle r And calculating the self-adaptive cruise safe distance x according to the dangerous reaction time T of the vehicle.
As a further improvement of the invention, in step 1, the standard braking distance s 0 Is that the vehicle is at a standard driving speed v 0 In the case of a maximum braking deceleration over the distance traveled from the start of braking to the complete standstill of the vehicle, the running road surface being a dry asphalt road surface, the standard running speed v of the passenger vehicle 0 100km/h, standard driving speed v of a commercial vehicle 0 Is 50km/h;
the critical load factor n is determined by the adhesion condition of the road and the braking performance of the vehicle and is used for judging whether the vehicle has the capability of completely utilizing the ground adhesion at present;
the load factor k represents the current loading degree of the vehicle, and the calculation formula is as follows:
wherein k is the weight coefficient and m isCurrent total mass of the vehicle, m 0 A service mass for the vehicle;
the current peak adhesion coefficient
The estimation formula is related to the current road surface, the tire and the vehicle speed:
in the formula (I), the compound is shown in the specification,
the current peak adhesion coefficient of the vehicle is used for correcting the maximum braking deceleration of the vehicle;
ρ i (i =1,2,3,4,5,6) represents the degree of matching of the current pavement with the i-th typical pavement, i =1,2,3,4,5,6 represents dry asphalt pavement, wet asphalt pavement, dry cement pavement, wet cobble pavement, snow pavement, ice pavement, respectively;
γ 1 ，γ 2 ，γ 3 ，γ 4 training the weight factor through a neural network to obtain a proper value;
p is the current tire pressure, p 0 Is the air pressure of the tire under standard conditions;
b is the section width of the current tire, B 0 Is the section width of the tire under the standard condition;
h is the current pattern depth of the tire, h 0 The pattern depth of the tire under the standard condition;
v is the current running speed of the vehicle, v' 0 Is the running speed of the vehicle under the standard condition.
As a further improvement of the present invention, in step 3, the degree of attenuation of the braking effectiveness of the brake is related to the temperature, the degree of moisture and the degree of wear of the brake lining, and the degree of attenuation of the braking effectiveness of the brake of the vehicle is determined according to the brake state sensing formula:
in the formula, P b The brake performance attenuation degree of the vehicle brake is judged according to the dimensionless value;
ω 1 ，ω 2 ，ω 3 training the weight factor through a neural network to obtain a proper value;
T j is the temperature, T, of the friction lining in the jth wheel 0 J =1,2,3,4, which indicates a left front wheel, a right front wheel, a left rear wheel, and a right rear wheel, respectively, for a temperature limit value of the friction lining in a case where braking performance is normal;
L j is the surface water film thickness, L, of the friction lining in the jth wheel 0 J =1,2,3,4, which indicates a left front wheel, a right front wheel, a left rear wheel, and a right rear wheel, respectively, for a limit value of a thickness of a surface water film of the friction lining in a case where braking performance is normal;
δ j is the residual thickness of the friction lining in the jth wheel, delta 0 J =1,2,3,4, which indicates a left front wheel, a right front wheel, a left rear wheel, and a right rear wheel, respectively, for a remaining thickness limit value of the friction lining in a case where braking performance is normal;
setting the vehicle brake P b Four thresholds a of value 1 ，a 2 ，a 3 ，a 4 Then P is b Value is atThe five conditions respectively correspond to five braking efficiency attenuation coefficients of the vehicle brake:
when P is present b ≤a 1 When the vehicle brake has the braking efficiency attenuation coefficient K of K 1 ；
When a is 1 <P b ≤a 2 When the vehicle brake has the braking efficiency attenuation coefficient K of K 2 ；
When a is 2 <P b ≤a 3 When the vehicle brake has the braking efficiency attenuation coefficient K of K 3 ；
When a is 3 <P b ≤a 4 When the vehicle brake has the braking efficiency attenuation coefficient K of K 4 ；
When P is present b >a 4 When the vehicle brake has the braking efficiency attenuation coefficient K of K 5 。
As a further improvement of the present invention, in the step 4, the maximum braking deceleration correction factors of the preceding vehicle and the own vehicle are respectively:
wherein ef is a maximum braking deceleration correction factor of the preceding vehicle, e r A maximum braking deceleration correction factor for the host vehicle;
alpha is the up-down slope angle of the current road and is used for representing the slope of the advancing direction of the vehicle;
k f is the load factor of the front vehicle, n f Is the critical load factor, k, of the leading vehicle r Is the load factor of the vehicle, n r The critical load coefficient of the vehicle;
As a further improvement of the present invention, in the step 5, the predicted braking distance s of the preceding vehicle is corrected f Calculating through the front vehicle brake simulation formula:
in the formula, s f Estimating the braking distance for the correction of the front vehicle, wherein the estimated braking distance represents the distance which the front vehicle needs to travel from the current state to the static state by the maximum braking deceleration and is divided into two conditions of uphill braking and downhill braking;
v f the running speed of the front vehicle, alpha is the up-down slope angle of the current road, g is the gravity acceleration, s f Coordinating the time for braking of the preceding vehicle, e f A maximum braking deceleration correction factor for the preceding vehicle;
s 0，f is the standard braking distance of the front vehicle, v 0，f The standard running speed of the front vehicle is 100km/h, and the standard running speed of the commercial vehicle is 50km/h.
As a further improvement of the present invention, in the step 6, the estimated braking distance s of the host vehicle is corrected r Calculating by the vehicle brake simulation formula:
in the formula, s r Estimating the braking distance for the correction of the vehicle, representing the distance which the vehicle needs to travel from the current state to the static state by the maximum braking deceleration, and dividing the braking into two situations of uphill braking and downhill braking;
k is the brake efficiency attenuation coefficient of the vehicle brake and represents the reduction condition of the vehicle brake performance;
v r the running speed of the vehicle, alpha is the up-down slope angle of the current road, g is the gravity acceleration, t r For the braking coordination time of the vehicle, e r A maximum braking deceleration correction factor for the host vehicle;
s 0，r is the standard braking distance, v, of the vehicle 0，r The standard running speed of the vehicle is 100km/h, and the standard running speed of the commercial vehicle is 50km/h.
As a further improvement of the present invention, in the step 7, the stationary desired distance d between the host vehicle and the preceding vehicle is set 0 Calculating by the desired vehicle distance adjustment formula:
in the formula (d) 0 The static expected distance between the vehicle and the front vehicle represents the minimum distance expected by a driver when the vehicle and the front vehicle are static simultaneously;
rho is the traffic density of the current road section, rho 0 According to rho and rho for the limit traffic density of the current road section 0 Judging the traffic jam degree of the current road section according to the ratio;
x is the conservative degree of the driving style, represents the conservative degree of the driver to the following distance, and is manually set on the vehicle-mounted touch screen by the driver, wherein the maximum value of the conservative degree of the driving style is 100, the minimum value is 0, and the default value is 50;
d is a static standard distance and is determined by the vehicle types of the front vehicles, wherein the vehicle types are classified according to the maximum allowable total mass of the vehicles and comprise light vehicles, medium-sized vehicles, heavy vehicles and extra-heavy vehicles;
the light vehicle is a vehicle with the maximum allowable total mass less than or equal to 2500 kg;
the maximum allowable total mass of the medium-sized vehicle is more than 2500kg and less than or equal to 6000 kg;
the maximum allowable total mass of the heavy-duty vehicle is more than 6000kg and less than or equal to 14000 kg;
the maximum allowable total mass of the special heavy vehicle is more than 14000 kg;
the value taking method of the static standard distance D comprises the following steps:
when the current vehicle is a light vehicle, the static standard distance D is 2.5m;
when the vehicle type of the current vehicle is a medium-sized vehicle, the static standard distance D is 3m;
when the current vehicle is a heavy vehicle, the static standard distance D is 3.5m;
when the vehicle type of the current vehicle is a very heavy vehicle, the stationary standard distance D is 4m.
As a further improvement of the present invention, in step 8, the calculation formula of the adaptive cruise safe distance x is:
x＝max(0，s r -s f )+d o +v r T
wherein x is a self-adaptive cruise safe distance which is a control target of the self-adaptive cruise system of the intelligent networked automobile, if the actual distance between the automobile and the front automobile is less than the self-adaptive cruise safe distance x, the self-adaptive cruise system starts to control the automobile to decelerate so as to ensure that the actual distance between the automobile and the front automobile is greater than or equal to the self-adaptive cruise safe distance x;
s r estimating braking distance, s, for correction of the vehicle f Estimating braking distance for correction of preceding vehicle, d 0 Is the stationary desired distance, v, of the host vehicle from the front vehicle r The running speed of the vehicle;
and T is the dangerous reaction time of the vehicle, represents the time required by the vehicle from the detection of the emergency braking of the front vehicle to the start of the braking of the vehicle, and the specific value is determined by the signal acquisition time, the data processing time and the braking decision time.
Compared with the prior art, the invention has the following beneficial effects:
1. the invention fully considers the braking performance of the front vehicle on the basis of considering the braking performance of the vehicle, calculates the self-adaptive cruising safety distance most conforming to the current vehicle condition according to the braking performance difference of the vehicle and the front vehicle, avoids over-small or over-large following distance, not only furthest reduces the possibility of collision between the vehicle and the front vehicle, but also improves the running efficiency.
2. The invention corrects the maximum braking deceleration of the vehicle according to the loading condition of the vehicle, the road adhesion condition and the road gradient, so that the estimated braking distance is more in line with the reality, and the real-time performance condition of the brake of the vehicle is considered, thereby avoiding the collision between the vehicle and the front vehicle caused by the attenuation of the braking efficiency of the brake.
3. The invention utilizes the internet of vehicles technology to collect the information of the front vehicle and the road information, thereby ensuring the accuracy and the real-time performance of the information and improving the calculation precision and the calculation efficiency of the self-adaptive cruise safe distance.
4. The invention considers the influence of road traffic conditions, driver styles and front vehicle types on the actual driving of the driver, so that the self-adaptive cruising safety distance is more in line with the expectation of the driver.
Drawings
FIG. 1 is a schematic flow diagram of the process of the present invention.
Detailed Description
The invention is further explained below with reference to the drawings.
The invention provides a safe distance calculation method of an intelligent networked automobile self-adaptive cruise control system, which comprises the following steps as shown in figure 1:
step 1: based on the vehicle-to-vehicle communication function of the Internet of vehicles, the vehicle acquires the brake performance parameters of the front vehicle, the vehicle state information of the front vehicle and the vehicle type of the front vehicle; the self-vehicle is a vehicle provided with an adaptive cruise control system, and the adaptive cruise control system controls the running speed of the self-vehicle to ensure the reality of the self-vehicle and a front vehicleThe distance is greater than or equal to the self-adaptive cruise safe distance calculated by the vehicle; the front vehicle is a vehicle which is positioned in front of the vehicle and is closest to the vehicle in the lane where the vehicle is positioned; the brake performance parameter of the front vehicle comprises a standard brake distance s of the front vehicle 0，f Braking coordination time t of front vehicle f And the critical load factor n of the front vehicle f (ii) a The vehicle state information of the preceding vehicle includes a running vehicle speed v of the preceding vehicle f Load factor k of front vehicle f And the current peak adhesion coefficient of the leading vehicle
The standard braking distance s 0 Is that the vehicle is at a standard running speed v 0 In the case of a maximum braking deceleration over the distance traveled from the start of braking to the complete standstill of the vehicle, the running road surface being a dry asphalt road surface, the standard running speed v of the passenger vehicle 0 100km/h, standard driving speed v of a commercial vehicle 0 Is 50km/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 for judging whether the vehicle has the capability of completely utilizing the ground adhesion at present;
the load factor k represents the current loading degree of the vehicle, and a specific value is obtained by vehicle calculation, wherein the calculation formula is as follows:
wherein k is the load factor, m is the current total mass of the vehicle, m 0 A service mass for the vehicle;
the current peak adhesion coefficient
The estimation formula is related to the current road surface, the tire and the vehicle speed:
wherein the content of the first and second substances,
the current peak adhesion coefficient of the vehicle is used for correcting the maximum braking deceleration of the vehicle;
ρ i (i =1,2,3,4,5, 6) represents the matching degree of the current road surface and the ith typical road surface, and the specific value is measured by a vehicle-mounted sensor, i =1,2,3,4,5,6 represents a dry asphalt road surface, a wet asphalt road surface, a dry cement road surface, a wet cobblestone road surface, a snow covered road surface and an icy road surface respectively;
γ 1 ，γ 2 ，γ 3 ，γ 4 training the weight factor through a neural network to obtain a proper value;
p is the current tire pressure, p 0 Is the air pressure of the tire under standard conditions;
b is the section width of the current tire, B 0 Is the section width of the tire under the standard condition;
h is the current pattern depth of the tire, h 0 The pattern depth of the tire under the standard condition;
v is the current running speed of the vehicle, v' 0 Is the running speed of the vehicle under the standard condition.
Step 2: the vehicle obtains the braking performance parameter and the vehicle state information of the vehicle, and is based on the vehicle networkA vehicle-to-road communication function, in which a vehicle collects road condition information; wherein the braking performance parameter of the vehicle comprises a standard braking distance s of the vehicle 0，r Braking coordination time t of the vehicle r And critical load factor n of the vehicle r The vehicle state information of the host vehicle comprises the running vehicle speed v of the host vehicle r The load factor k of the vehicle r And the current peak value attachment coefficient of the host vehicle
The road condition information comprises an up-down gradient angle alpha of the current road, traffic flow density rho of the current road section and limit traffic flow density rho of the current road section 0 。
And 3, step 3: the vehicle acquires real-time internal state information of the vehicle brake, judges the braking efficiency attenuation degree of the vehicle brake by using a brake state perception formula, and determines the braking efficiency attenuation coefficient K of the vehicle brake on the basis of the braking efficiency attenuation degree; the real-time internal state information of the brake comprises the temperature, the residual thickness and the surface water film thickness of a brake friction lining;
the brake efficiency attenuation degree of the brake is related to the temperature, the water humidity degree and the abrasion degree of a brake friction lining, and the brake efficiency attenuation degree of the brake of the vehicle is judged according to the brake state perception formula:
wherein, P b The brake performance attenuation degree of the vehicle brake is judged according to the dimensionless value;
ω 1 ，ω 2 ，ω 3 training the weight factor through a neural network to obtain a proper value;
T j is the temperature, T, of the friction lining in the jth wheel 0 In order to set the temperature limit value of the friction lining in a normal braking performance, j =1,2,3,4, which indicates the left front wheel, the right front wheel, the left rear wheel, and the right rear wheel, respectivelyA wheel;
L j is the surface water film thickness, L, of the friction lining in the jth wheel 0 J =1,2,3,4, which indicates a left front wheel, a right front wheel, a left rear wheel, and a right rear wheel, respectively, for a limit value of a thickness of a surface water film of the friction lining in a case where braking performance is normal;
δ j is the residual thickness of the friction lining in the jth wheel, delta 0 J =1,2,3,4, which represents a left front wheel, a right front wheel, a left rear wheel, and a right rear wheel, respectively, for a residual thickness limit value of the friction lining in a case where braking performance is normal;
setting the vehicle brake P b Four thresholds a of value 1 ，a 2 ，a 3 ，a 4 Then P is b The five conditions of the value respectively correspond to five braking efficiency attenuation coefficients of the vehicle brake:
when P is present b ≤a 1 When the vehicle brake has the braking efficiency attenuation coefficient K of K 1 ；
When a is 1 <P b ≤a 2 When the vehicle brake has the braking efficiency attenuation coefficient K of K 2 ；
When a is 2 <P b ≤a 3 When the vehicle brake has the braking efficiency attenuation coefficient K of K 3 ；
When a is 3 <P b ≤a 4 When the vehicle brake has the braking efficiency attenuation coefficient K of K 4 ；
When P is present b >a 4 When the vehicle brake has the braking efficiency attenuation coefficient K of K 5 ；
Wherein, K 5 >K 4 >K 3 >K 2 >K 1 =1, above K 2 ，K 3 ，K 4 ，K 5 The specific value of (a) is determined by a manufacturer,
and 4, step 4: respectively judging the available degree of the adhesion force of the front vehicle and the self vehicle to the ground, and determining the available degree of the adhesion force of the front vehicle and the self vehicle to the ground according to the load factor, the critical load factor, the current peak adhesion factor and the current up-down slope angle of the roadCalculating the maximum braking deceleration correction factor e of the front vehicle and the host vehicle respectively f ，e r ；
The usable degree of the ground adhesion is judged according to the load factor k and the critical load factor n, when the load factor k of the vehicle is less than or equal to the critical load factor n, the vehicle has the capacity of completely utilizing the ground adhesion, and the maximum braking force of the vehicle is the ground adhesion; when the load factor k of the vehicle is greater than the critical load factor n, the vehicle cannot fully utilize the 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 which can be provided by the brake under the condition that all wheels do not slip;
the maximum braking deceleration correction factors of the front vehicle and the host vehicle are respectively as follows:
wherein e is f Correction factor for maximum braking deceleration of preceding vehicle, e r A maximum braking deceleration correction factor for the host vehicle;
alpha is the up-down slope angle of the current road and is used for representing the slope of the advancing direction of the vehicle, and the specific value of the alpha is measured by a vehicle-mounted sensor;
k f is the load factor of the front vehicle, n f Is the critical load factor, k, of the leading vehicle r Is the load factor of the vehicle, n r The critical load coefficient of the vehicle;
And 5: according to the up-down slope angle alpha of the current road and the running speed v of the front vehicle f Standard braking distance s of front vehicle 0，f Braking coordination time t of front vehicle f And the maximum braking deceleration correction factor e of the preceding vehicle f Calculating the corrected estimated braking distance s of the front vehicle by using a front vehicle braking simulation formula f ；
The corrected estimated braking distance s of the preceding vehicle f Calculating through the front vehicle brake simulation formula:
wherein s is f Estimating the braking distance for the correction of the front vehicle, wherein the estimated braking distance represents the distance which the front vehicle needs to travel from the current state to the static state by the maximum braking deceleration and is divided into two conditions of uphill braking and downhill braking;
v f the running speed of the front vehicle, alpha is the up-down slope angle of the current road, g is the gravity acceleration, and s f Coordinating the time for braking of the preceding vehicle, e f A maximum braking deceleration correction factor for the preceding vehicle;
s 0，f is the standard braking distance of the front vehicle, v 0，f The standard running speed of the front vehicle is 100km/h, and the standard running speed of the commercial vehicle is 50km/h.
Step 6: according to the up-down slope angle alpha of the current road and the running speed v of the vehicle r Standard braking distance s of the vehicle 0，r Braking coordination time t of the vehicle r Maximum braking deceleration correction factor e of the vehicle r And calculating the corrected estimated braking distance s of the vehicle by using a vehicle braking simulation formula r ；
Corrected estimated braking distance s of the vehicle r Calculating by the vehicle brake simulation formula:
wherein s is r Estimating the braking distance for the correction of the vehicle, representing the distance which the vehicle needs to travel from the current state to the static state by the maximum braking deceleration, and dividing the braking into two situations of uphill braking and downhill braking;
k is the brake efficiency attenuation coefficient of the vehicle brake and represents the reduction condition of the vehicle brake performance;
v r the running speed of the vehicle, alpha is the up-down slope angle of the current road, g is the gravity acceleration, t r For the braking coordination time of the vehicle, e r A maximum braking deceleration correction factor for the host vehicle;
s 0，r is the standard braking distance, v, of the vehicle 0，r The standard running speed of the vehicle is 100km/h, and the standard running speed of the commercial vehicle is 50km/h.
And 7: considering the influence of road section traffic conditions, driver styles and front vehicle types on the real-world driving of the driver, and according to the traffic flow density rho of the current road section and the limit traffic flow density rho of the current road section 0 The driving style conservative degree X and the vehicle type of the front vehicle, and calculating the static expected distance d between the vehicle and the front vehicle by utilizing an expected vehicle distance adjusting formula 0 ；
The static expected distance d between the vehicle and the front vehicle 0 Calculating by the desired vehicle distance adjustment formula:
wherein d is 0 The static expected distance between the vehicle and the front vehicle represents the minimum distance expected by a driver when the vehicle and the front vehicle are static simultaneously;
rho is the traffic density of the current road section, rho 0 According to rho and rho for the limit traffic density of the current road section 0 Judging the traffic jam degree of the current road section according to the ratio;
x is the conservative degree of the driving style, represents the conservative degree of the driver to the following distance, and is manually set on the vehicle-mounted touch screen by the driver, wherein the maximum value of the conservative degree of the driving style is 100, the minimum value is 0, and the default value is 50;
d is a static standard distance and is determined by the vehicle types of the front vehicles, wherein the vehicle types are classified according to the maximum allowable total mass of the vehicles and comprise light vehicles, medium-sized vehicles, heavy vehicles and extra-heavy vehicles;
the light vehicle is a vehicle with the maximum allowable total mass less than or equal to 2500 kg;
the maximum allowable total mass of the medium-sized vehicle is more than 2500kg and less than or equal to 6000 kg;
the maximum allowable total mass of the heavy-duty vehicle is more than 6000kg and less than or equal to 14000 kg;
the maximum allowable total mass of the special heavy vehicle is more than 14000 kg;
the value method of the static standard distance D comprises the following steps:
when the current vehicle is a light vehicle, the static standard distance D is 2.5m;
when the vehicle type of the current vehicle is a medium-sized vehicle, the static standard distance D is 3m;
when the current vehicle is a heavy vehicle, the static standard distance D is 3.5m;
when the vehicle type of the current vehicle is a very heavy vehicle, the stationary standard distance D is 4m.
And 8: estimating braking distance s according to correction of preceding vehicle f Corrected estimated braking distance s of the vehicle r The expected static distance d between the vehicle and the front vehicle 0 The running vehicle of the vehicleVelocity v r Calculating the self-adaptive cruise safe distance x according to the dangerous reaction time T of the vehicle;
the calculation formula of the self-adaptive cruise safe distance x is as follows:
x＝max(0，s r -s f )+d 0 +v r T
if the actual distance between the vehicle and the front vehicle is less than the adaptive cruise safe distance x, the adaptive cruise system starts to control the vehicle to decelerate so as to ensure that the actual distance between the vehicle and the front vehicle is greater than or equal to the adaptive cruise safe distance x;
s r estimating braking distance, s, for correction of the vehicle f Estimating braking distance for correction of preceding vehicle, d 0 Is the stationary desired distance, v, of the host vehicle from the front vehicle r The running speed of the vehicle;
and T is the dangerous reaction time of the vehicle, represents the time required by the vehicle from the detection of the emergency braking of the front vehicle to the start of the braking of the vehicle, and the specific value is determined by the signal acquisition time, the data processing time and the braking decision time.
Claims (8)
1. A safe distance calculation method of an intelligent networked automobile self-adaptive cruise control system is characterized by comprising the following steps:
step 1: based on the vehicle-to-vehicle communication function of the Internet of vehicles, the vehicle acquires the brake performance parameters, the vehicle state information and the vehicle type of the front vehicle;
the self-adaptive cruise control system controls the running speed of the self-adaptive cruise control system to ensure that the actual distance between the self-adaptive cruise control system and a front vehicle is greater than or equal to the self-adaptive cruise safe distance calculated by the self-adaptive cruise control system; the front vehicle is a vehicle which is positioned in front of the vehicle and is closest to the vehicle in the lane where the vehicle is positioned; the braking performance parameter comprises a standard braking distance s 0 Braking coordination time t and critical load factor n; the vehicle state information comprises a running vehicle speed v, a load factor k and a current peak valueCoefficient of adhesion
Step 2: the method comprises the steps that the vehicle acquires braking performance parameters and vehicle state information of the vehicle, and the vehicle acquires road condition information based on a vehicle-to-road communication function of the Internet of vehicles;
the road condition information comprises an up-down gradient angle alpha of the current road, traffic flow density rho of the current road section and limit traffic flow density rho of the current road section 0 ；
And step 3: the vehicle acquires real-time internal state information of the vehicle brake, judges the braking efficiency attenuation degree of the vehicle brake by using a brake state perception formula, and determines the braking efficiency attenuation coefficient K of the vehicle brake on the basis of the braking efficiency attenuation degree;
the real-time internal state information of the brake comprises the temperature, the residual thickness and the surface water film thickness of a brake friction lining;
and 4, step 4: respectively judging the available degree of the adhesion force of the front vehicle and the self vehicle to the ground, and respectively calculating the maximum braking deceleration correction factor e of the front vehicle and the self vehicle according to the load coefficient, the critical load coefficient, the current peak adhesion coefficient and the current up-down slope angle of the road f ,e r ；
The usable degree of the ground adhesion is judged according to a load factor k and a critical load factor n, when the load factor k of the vehicle is less than or equal to the critical load factor n, the vehicle has the capacity of completely using the ground adhesion, and the maximum braking force of the vehicle is the ground adhesion; when the load factor k of the vehicle is greater than the critical load factor n, the vehicle cannot fully utilize the 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 which can be provided by the brake under the condition that all wheels do not slip;
and 5: according to the up-down slope angle alpha of the current road and the running speed v of the front vehicle f Standard braking distance s of front vehicle 0,f Front vehicle brake coordinationTime t f And the maximum braking deceleration correction factor e of the preceding vehicle f Calculating the corrected estimated braking distance s of the front vehicle by using a front vehicle braking simulation formula f ；
Step 6: according to the up-down slope angle alpha of the current road and the running speed v of the vehicle r Standard braking distance s of the vehicle 0,r Braking coordination time t of the vehicle r Maximum braking deceleration correction factor e of the vehicle r And calculating the corrected estimated braking distance s of the vehicle by using a vehicle braking simulation formula r ；
And 7: considering the influence of road section traffic conditions, driver styles and front vehicle types on the real-life driving of the driver, and according to the traffic flow density rho of the current road section and the limit traffic flow density rho of the current road section 0 Driving style conservative degree X and vehicle type of the front vehicle, and calculating static expected distance d between the vehicle and the front vehicle by using an expected vehicle distance adjusting formula 0 ；
And 8: estimating braking distance s according to correction of preceding vehicle f Corrected estimated braking distance s of the vehicle r Expected stationary distance d between the vehicle and the preceding vehicle 0 The running speed v of the vehicle r And calculating the self-adaptive cruise safe distance x according to the dangerous reaction time T of the vehicle.
2. The method for calculating the safe distance of the intelligent networked automobile adaptive cruise control system according to claim 1, wherein in step 1 of claim 1, the standard braking distance s 0 Is that the vehicle is at a standard driving speed v 0 In the case of a maximum braking deceleration over the distance traveled from the start of braking to the complete standstill of the vehicle, the running road surface being a dry asphalt road surface, the standard running speed v of the passenger vehicle 0 100km/h, standard driving speed v of a commercial vehicle 0 Is 50km/h;
the critical load factor n is determined by the adhesion condition of the road and the braking performance of the vehicle and is used for judging whether the vehicle has the capability of completely utilizing the ground adhesion at present;
the load factor k represents the current loading degree of the vehicle, and the calculation formula is as follows:
wherein k is the load factor, m is the current total mass of the vehicle, m 0 A service mass for the vehicle;
the current peak adhesion coefficient
The estimation formula is related to the current road surface, the tire and the vehicle speed:
wherein the content of the first and second substances,
the current peak adhesion coefficient of the vehicle is used for correcting the maximum braking deceleration of the vehicle;
ρ i (i =1,2,3,4,5,6) represents the degree of matching of the current pavement with the i-th typical pavement, i =1,2,3,4,5,6 represents dry asphalt pavement, wet asphalt pavement, dry cement pavement, wet cobble pavement, snow pavement, ice pavement, respectively;
γ 1 ，γ 2 ，γ 3 ，γ 4 training the weight factor through a neural network to obtain a proper value;
p is the current tire pressure, p 0 Is the air pressure of the tire under standard conditions;
b is the section width of the current tire, B 0 Is the section width of the tire under the standard condition;
h is the current pattern depth of the tire, h 0 The pattern depth of the tire under the standard condition;
v is the current running speed of the vehicle, v' 0 Is the running speed of the vehicle under the standard condition.
3. The method for calculating the safe distance of the intelligent networked automobile adaptive cruise control system according to claim 1, wherein in step 3 of claim 1, the brake performance attenuation degree of the brake is related to the temperature, the water humidity degree and the wear degree of the brake lining, and the brake performance attenuation degree of the brake of the vehicle is judged according to the brake state perception formula:
wherein, P b The non-dimensional value is used for judging the attenuation degree of the braking efficiency of the vehicle brake;
ω 1 ，ω 2 ，ω 3 training the weight factor through a neural network to obtain a proper value;
T j is the temperature, T, of the friction lining in the jth wheel 0 J =1,2,3,4, which represents a left front wheel, a right front wheel, a left rear wheel, and a right rear wheel, respectively, for a temperature limit value of the friction lining in a case where braking performance is normal;
L j is the surface water film thickness, L, of the friction lining in the jth wheel 0 The surface water film thickness of the friction lining is extremely high under the condition of normal braking effectA limit value, j =1,2,3,4, representing the left front wheel, the right front wheel, the left rear wheel, the right rear wheel, respectively;
δ j is the residual thickness of the friction lining in the jth wheel, delta 0 J =1,2,3,4, which indicates a left front wheel, a right front wheel, a left rear wheel, and a right rear wheel, respectively, for a remaining thickness limit value of the friction lining in a case where braking performance is normal;
setting the vehicle brake P b Four thresholds a of values 1 ，a 2 ，a 3 ，a 4 Then P is b The values of the five conditions respectively correspond to five braking efficiency attenuation coefficients of the vehicle brake:
when P is present b ≤a 1 When the vehicle brake has the braking efficiency attenuation coefficient K of K 1 ；
When a is 1 ＜P b ≤a 2 When the braking efficiency attenuation coefficient K of the vehicle brake is K 2 ；
When a is 2 ＜P b ≤a 3 When the vehicle brake has the braking efficiency attenuation coefficient K of K 3 ；
When a is 3 ＜P b ≤a 4 When the vehicle brake has the braking efficiency attenuation coefficient K of K 4 ；
When P is present b ＞a 4 When the vehicle brake has the braking efficiency attenuation coefficient K of K 5 。
4. The method for calculating the safe distance of the intelligent networked automobile adaptive cruise control system according to claim 1, wherein in the step 4 of claim 1, the maximum braking deceleration correction factors of the leading automobile and the host automobile are respectively:
wherein e is f Correction factor for maximum braking deceleration of preceding vehicle, e r A maximum braking deceleration correction factor for the host vehicle;
alpha is the up-down slope angle of the current road and is used for representing the slope of the advancing direction of the vehicle;
k f is the load factor of the front vehicle, n f Is the critical load factor, k, of the leading vehicle r Is the load factor of the vehicle, n r The critical load coefficient of the vehicle;
5. The method for calculating the safe distance of the intelligent networked automobile adaptive cruise control system according to claim 1, wherein in step 5 of claim 1, the corrected estimated braking distance s of the leading automobile f Calculating through the front vehicle brake simulation formula:
wherein s is f Estimating the braking distance for the correction of the preceding vehicle, indicating that the preceding vehicle decelerates with maximum brakingThe distance required to be driven from the current state braking to the static state is divided into two conditions of uphill braking and downhill braking;
v f the running speed of the front vehicle, alpha is the up-down slope angle of the current road, g is the gravity acceleration, t f Coordinating the time for braking of the preceding vehicle, e f A maximum braking deceleration correction factor for the preceding vehicle;
s 0，f is the standard braking distance of the front vehicle, v 0，f The standard running speed of the front vehicle is 100km/h, and the standard running speed of the commercial vehicle is 50km/h.
6. The method of claim 1, wherein in step 6 of claim 1, the vehicle's corrected estimated braking distance s is calculated r Calculating by the vehicle brake simulation formula:
wherein s is r Estimating a braking distance for the correction of the vehicle, representing the distance which the vehicle needs to travel from the current state to the static state by the maximum braking deceleration, and dividing the braking into two situations of uphill braking and downhill braking;
k is the brake efficiency attenuation coefficient of the vehicle brake and represents the reduction condition of the vehicle brake performance;
v r the running speed of the vehicle, alpha is the up-down slope angle of the current road, g is the gravity acceleration, t r For the braking coordination time of the vehicle, e r A maximum braking deceleration correction factor for the host vehicle;
s 0，r is the standard braking distance, v, of the vehicle 0，r The standard running speed of the vehicle is 100km/h, and the standard running speed of the commercial vehicle is 50km/h.
7. According to the rightThe method for calculating the safe distance of the intelligent networked automobile adaptive cruise control system according to claim 1, wherein in step 7 of claim 1, the expected stationary distance d between the host vehicle and the preceding vehicle is 0 Calculating by the desired vehicle distance adjustment formula:
wherein d is 0 The static expected distance between the vehicle and the front vehicle represents the minimum distance expected by a driver when the vehicle and the front vehicle are static simultaneously;
rho is the traffic density of the current road section, rho 0 According to rho and rho for the limit traffic density of the current road section 0 Judging the traffic jam degree of the current road section according to the ratio;
x is the conservative degree of the driving style, represents the conservative degree of the driver to the following distance, and is manually set on the vehicle-mounted touch screen by the driver, wherein the maximum value of the conservative degree of the driving style is 100, the minimum value is 0, and the default value is 50;
d is a static standard distance and is determined by the vehicle types of the front vehicles, wherein the vehicle types are classified according to the maximum allowable total mass of the vehicles and comprise light vehicles, medium-sized vehicles, heavy vehicles and extra-heavy vehicles;
the light vehicle is a vehicle with the maximum allowable total mass less than or equal to 2500 kg;
the maximum allowable total mass of the medium-sized vehicle is more than 2500kg and less than or equal to 6000 kg;
the maximum allowable total mass of the heavy-duty vehicle is more than 6000kg and less than or equal to 14000 kg;
the special heavy vehicle is a vehicle with the maximum allowable total mass of more than 14000 kg;
the value method of the static standard distance D comprises the following steps:
when the current vehicle is a light vehicle, the static standard distance D is 2.5m;
when the vehicle type of the current vehicle is a medium-sized vehicle, the static standard distance D is 3m;
when the current vehicle is a heavy vehicle, the static standard distance D is 3.5m;
when the vehicle type of the current vehicle is a very heavy vehicle, the stationary standard distance D is 4m.
8. The method for calculating the safe distance of the intelligent networked automobile adaptive cruise control system according to claim 1, wherein in step 8 of claim 1, the adaptive cruise safe distance x is calculated by the following formula:
x＝max(0，s r -s f )+d 0 +v r T
if the actual distance between the vehicle and the front vehicle is less than the adaptive cruise safe distance x, the adaptive cruise control system starts to control the vehicle to decelerate so as to ensure that the actual distance between the vehicle and the front vehicle is greater than or equal to the adaptive cruise safe distance x;
s r estimating braking distance, s, for correction of the vehicle f Estimating braking distance for correction of preceding vehicle, d 0 Is the stationary desired distance, v, of the host vehicle from the front vehicle r The running speed of the vehicle;
and T is the dangerous reaction time of the vehicle, represents the time required by the vehicle from the detection of the emergency braking of the front vehicle to the start of the braking of the vehicle, and the specific value is determined by the signal acquisition time, the data processing time and the braking decision time.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211552279.5A CN115817471A (en) | 2022-12-05 | 2022-12-05 | Safe distance calculation method of intelligent networked automobile self-adaptive cruise control system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211552279.5A CN115817471A (en) | 2022-12-05 | 2022-12-05 | Safe distance calculation method of intelligent networked automobile self-adaptive cruise control system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN115817471A true CN115817471A (en) | 2023-03-21 |
Family
ID=85544102
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211552279.5A Pending CN115817471A (en) | 2022-12-05 | 2022-12-05 | Safe distance calculation method of intelligent networked automobile self-adaptive cruise control system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115817471A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117649213A (en) * | 2024-01-30 | 2024-03-05 | 四川宽窄智慧物流有限责任公司 | Front-end management method and system for transportation safety |
-
2022
- 2022-12-05 CN CN202211552279.5A patent/CN115817471A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117649213A (en) * | 2024-01-30 | 2024-03-05 | 四川宽窄智慧物流有限责任公司 | Front-end management method and system for transportation safety |
| CN117649213B (en) * | 2024-01-30 | 2024-04-19 | 四川宽窄智慧物流有限责任公司 | Front-end management method and system for transportation safety |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| KR100793869B1 (en) | Adative cruise control system for vehicle | |
| CN108860138B (en) | LTE-V-based curve vehicle speed automatic control method | |
| CN107031634B (en) | Driving assistance apparatus, vehicle, and method of controlling longitudinal speed of vehicle | |
| CN107406077B (en) | Method of controlling gaps between vehicles in a fleet of vehicles | |
| US10501087B2 (en) | Method and arrangement for determining the speed behaviour of a leading vehicle | |
| US9493145B2 (en) | Method for automatically preventing aquaplaning | |
| US11226620B2 (en) | Automated driving systems and control logic with enhanced longitudinal control for transitional surface friction conditions | |
| CN103857550A (en) | Method and system for adaptively controlling distance and speed and for stopping a motor vehicle, and a motor vehicle which works with same | |
| US6470731B1 (en) | Method and device for determining a parameter for an instantaneously maximal frictional force coefficient | |
| JPH08318765A (en) | Controlling device and method for intelligent automobile | |
| CN112550284B (en) | Self-adaptive cruise driving risk assessment method under vehicle-road coupling effect | |
| WO2020001447A1 (en) | Safe driving method for vehicle | |
| CN106394524B (en) | Active brake method based on VANET wireless short range communication | |
| CN112298132A (en) | Vehicle autonomous emergency braking control system and control method | |
| CN115817471A (en) | Safe distance calculation method of intelligent networked automobile self-adaptive cruise control system | |
| CN101663189B (en) | Device and method for adjusting the driveability of an automobile | |
| KR101410259B1 (en) | Adaptive cruise control method on the inclined road | |
| CN116552252A (en) | Kinetic energy recovery control system | |
| CN103231710A (en) | Driver workload based system and method for scheduling driver interface tasks | |
| KR20130005110A (en) | Method for controlling vehicle interval | |
| Guo et al. | Collision Avoidance Strategy of High-Speed Aeb System Based on Minimum Safety Distance | |
| CN107804305B (en) | A kind of braking distance increment Prediction System and method considering mounted mass variation | |
| WO2013114625A1 (en) | Operation assist apparatus | |
| CN103264697A (en) | Driver-workload-based driver interface task scheduling system and method | |
| CN117382590A (en) | Anti-collision braking control method and braking control system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |