CN113538896B - Critical driving condition analysis method and vehicle safety driving prompt system - Google Patents
Critical driving condition analysis method and vehicle safety driving prompt system Download PDFInfo
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Abstract
The invention discloses a critical driving condition analysis method based on road and weather conditions. The method comprises the following steps: performing three-dimensional modeling on the road based on the gradient and the plane coordinates of the preset road section of the road; determining the maximum wind power borne by the vehicle based on the local air pressure, temperature, wind speed and vehicle size; in the direction perpendicular to the vehicle advancing direction, constructing a vehicle running model of the relationship among road information, vehicle information, maximum wind power and sideslip critical speed of the vehicle on the basis of the critical state stress condition that the vehicle does not sideslip; constructing a vehicle braking model of a road adhesion coefficient, a road gradient, a curve height angle and a braking deceleration rate on the basis of the vehicle stress condition in the direction parallel to the vehicle advancing direction; according to the vehicle running model and the vehicle braking model, the vehicle running speed, the safe vehicle weight, the safe size of the vehicle and/or the safe headway are output.
Description
Technical Field
The invention relates to the technical field of road traffic, in particular to a critical driving condition analysis method and a vehicle safety driving prompt system based on road and weather conditions.
Background
For a traffic road, complex road conditions such as curves and slopes, and severe weather conditions such as ice, snow and strong wind, which may cause serious influence on the safe driving of vehicles, corresponding vehicles and traffic control strategies need to be formulated according to specific conditions. At present, when bad weather occurs, road traffic managers often make management measures by depending on experience, and the standards and the bases of quantitative analysis are lacked. In some of the above cases, when two or more factors occur simultaneously, the coupling between them can complicate the situation. Therefore, it is necessary to provide a road critical running condition analysis method for determining information of a safe running vehicle speed, a safe vehicle weight, a size, and the like under specific conditions on a complicated road and in severe weather conditions. Meanwhile, at the road level, the driving risk of the whole road also needs to be analyzed, so that more attention is given to places with higher risks and targeted measures are taken. On the traffic aspect, the determination of the safe headway can help to make traffic safety management measures and guide vehicles to safely run.
Disclosure of Invention
In view of the above, the present invention has been developed to provide a solution that overcomes, or at least partially solves, the above-mentioned problems. Accordingly, in one aspect of the present invention, there is provided a critical driving condition analysis method based on road and weather conditions, the method including:
performing three-dimensional modeling on the road based on the gradient and the plane coordinates of the preset road section of the road;
determining the maximum wind power borne by the vehicle based on the local air pressure, temperature, wind speed and vehicle size;
in the direction perpendicular to the vehicle advancing direction, a vehicle running model of the relation among road information, vehicle information, maximum wind power and sideslip critical speed of the vehicle is constructed based on the critical state stress condition that the vehicle does not sideslip, wherein the road information comprises road gradient, road friction coefficient, curve height angle and curve radius; the vehicle information comprises vehicle mass and vehicle size;
constructing a vehicle braking model of a road adhesion coefficient, a road gradient, a curve height angle and a braking deceleration rate on the basis of the vehicle stress condition in the direction parallel to the vehicle advancing direction;
and outputting the vehicle running speed, the safe vehicle weight, the safe vehicle size and/or the safe vehicle headway according to the vehicle running model and the vehicle braking model.
Optionally, the road three-dimensional modeling is performed based on the gradient and the plane coordinates of the predetermined section of the road, and includes: collecting gradient data of a plurality of preset road sections of the whole road, wherein the gradient data comprises pile-starting numbers, pile-ending numbers and gradient information, collecting plane coordinates of a plurality of sampling points on the preset road sections on the central line of the whole road,
and performing three-dimensional stretching on the plane coordinates according to the gradient data so as to perform three-dimensional modeling on the road.
Optionally, the vehicle driving model is:
wherein v is a sideslip critical speed, R is the radius of the current curve, g is a gravity coefficient, alpha is a curve height angle, beta is a road slope angle, f is a road transverse force coefficient, h is a vehicle high speed, l is a vehicle length, w is a wind speed, ρ is an air density, and m is a vehicle mass.
Optionally, the vehicle braking model is:
wherein, abFor braking deceleration, g is the gravity coefficient,
for the road adhesion coefficient, α is a curve height angle, β is a road slope angle, i is a road slope, and i is tan β.
Optionally, the method further includes:
determining sideslip critical speed according to road information, vehicle type information and weather conditions on the basis of the vehicle running model, and prompting or controlling the actual running speed of the vehicle on the basis of the sideslip critical speed;
and/or determining the safe weight of the vehicle according to the known running speed, road information, weather conditions and vehicle type information based on the vehicle running model;
and/or determining the safe size of the vehicle according to the known running speed, road information, weather conditions and known vehicle weight based on the vehicle running model;
and/or determining the safe headway according to the vehicle running speed and the driver reaction time based on the vehicle braking model.
Optionally, the method is implemented based on Carsim simulation software.
Optionally, the method further includes:
vehicle dynamic performance parameter based on automobile and driving force F of vehicletWith a running resistance FrBalancing
Determining the maximum driving speed of the vehicle, wherein Mm、MpTorque at maximum torque and maximum power of the engine, nm、npThe rotation speed at maximum torque of the engine and the rotation speed at maximum power of the engine, eta is the mechanical efficiency of the automobile, gamma is the total gear ratio, r is the radius of the wheels, frThe coefficient of rolling friction on the ground, k is the coefficient of air resistance, and A is the axial windward area of the automobile;
collecting road gradient information i, and combining the road gradient information, vehicle dynamic performance parameters, and the balance of the driving force and the running resistance of the vehicle
Determining the driving speed of the automobile on a critical slope;
obtaining road curve information based on algorithm
Determining a critical curve speed of the vehicle, wherein
Is the coefficient of adhesion of the road surface, iyFor super high road surface iyTan α, R is the curve radius, B is the track width of the vehicle, hcG is the gravity coefficient.
Optionally, the above-ground rolling friction coefficient frThe air resistance coefficient k is acquired by road side equipment or obtained by experiments.
The invention also provides a vehicle safe driving prompt system, which comprises an information acquisition module and a calculation module, wherein the information acquisition module is used for acquiring inherent road information, real-time road information and weather information, the inherent road information comprises the radius of a curve, the height angle of the curve and/or the gradient of the road, the real-time road information comprises the rolling friction coefficient and/or the adhesion coefficient of the road surface, the weather information comprises the wind speed, the air resistance coefficient and/or the air density information, and the calculation module analyzes the critical driving condition.
Optionally, the information acquisition module is a road side device, the calculation module is a vehicle-mounted device, and the road side device and the calculation module communicate with each other through a short-distance communication protocol.
The technical scheme provided by the application has at least the following technical effects or advantages:
the practical and feasible safe driving guidance is provided on some complicated road sections or dangerous road sections, so that people can not drive by only depending on experience any more, and the traffic accident can be avoided and the safety can be guaranteed.
The above description is only an overview of the technical solutions of the present invention, and the embodiments of the present invention are described below in order to make the technical means of the present invention more clearly understood and to make the technical solutions of the present invention and the objects, features, and advantages thereof more clearly understandable.
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Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:
FIG. 1 is a flow chart illustrating a method for analyzing critical driving conditions based on road and weather conditions according to the present invention;
FIG. 2 shows a schematic diagram of three-dimensional modeling of a road and coordinate interpolation;
FIG. 3 shows a driving model of a vehicle on a road;
FIG. 4 illustrates the vehicle experiencing a force perpendicular to the forward direction;
FIG. 5 shows the vehicle under force parallel to the forward direction;
FIG. 6 shows a safety headway diagram;
FIG. 7 shows plane information for an example road;
FIG. 8 illustrates three-dimensional information for an example road;
FIG. 9 illustrates a side-slip critical vehicle speed (kilometers per hour) across an example road at an ambient temperature of 0 degrees Celsius;
FIG. 10 illustrates a safe headway on an example road.
Detailed Description
Exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention can be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.
The present invention provides an aspect of the present invention, as shown in fig. 1, which provides a critical driving condition analysis method based on road and weather conditions, the method comprising:
s1, carrying out three-dimensional road modeling based on the gradient and the plane coordinates of a preset road section of a road;
s2, determining the maximum wind power borne by the vehicle based on the local air pressure, temperature, wind speed and vehicle size;
s3, constructing a vehicle running model of the relation among road information, vehicle information, maximum wind power and sideslip critical speed of the vehicle on the basis of the critical state stress condition that the vehicle does not sideslip in the direction perpendicular to the vehicle running direction, wherein the road information comprises road gradient, road friction coefficient, curve height angle and curve radius; the vehicle information comprises vehicle mass and vehicle size;
s4, constructing a vehicle braking model of a road adhesion coefficient, a road gradient, a curve height angle and a braking deceleration rate on the basis of the vehicle stress condition in the direction parallel to the vehicle advancing direction;
and S5, outputting the vehicle running speed, the safe vehicle weight, the safe vehicle size and/or the safe headway by the vehicle running model and the vehicle braking model.
In step S1, the three-dimensional modeling of the road based on the gradient and the plane coordinates of the predetermined section of the road includes: the method comprises the steps of collecting gradient data of a plurality of preset road sections of the whole road, wherein the gradient data comprises pile starting numbers, pile ending numbers and gradient information, collecting plane coordinates of a plurality of sampling points on the preset road sections on the central line of the whole road, and performing three-dimensional stretching on the plane coordinates according to the gradient data so as to perform three-dimensional modeling on the road.
Particularly, the three-dimensional modeling of the road can integrate the gradient information and the curve information, so that the coupling effect of the gradient and the curve can be conveniently analyzed. The content described in this step needs to be based on the following information:
(1) the slope data of the whole road needs to contain pile starting number, final pile number and slope information. The pile starting number is the starting position of the current ramp, the pile ending number is the ending position of the current ramp, and the distance between the pile starting number and the pile ending number represents the slope length. An example of the above information is shown in the following table.
(2) The plane coordinates of the center line of the whole road need to include the abscissa and the ordinate of each sampling point on the center line of the road. The information of the horizontal and vertical coordinates can be replaced by longitude and latitude data, and the accuracy of the data can be ensured. It should be noted that the distance between the sampling points should not be too large to affect the overall road profile, especially at curves. An example of the above information is shown in the following table.
It should be noted that the starting points of the two above-mentioned items of information should coincide. Based on the information, the three-dimensional modeling of the road is realized by the following method, and a series of coordinate points on the road are obtained:
(xk，yk，zk)，k＝0，1，2，... (1)
for convenience, the start point coordinates of a road are defined as:
x0＝0，y0＝0，z0＝0 (2)
since the plane coordinates of the road are already known, the corresponding z-coordinate can be determined in the following way:
table 1: algorithm 1
The above algorithm 1 gives a three-dimensional modeling method for the road under study. The core of the algorithm is to combine the gradient information to perform three-dimensional stretching on the plane coordinates and perform interpolation processing when necessary. For simplicity, linear interpolation is adopted in the algorithm 1, and other interpolation modes can be selected according to specific situations in actual operation. Fig. 2 is a schematic diagram of algorithm 1.
The above step S1 integrates the gradient information and curve information of the road, and in step S2, vehicle form model building will be performed, see fig. 3. In fig. 3, α is the superelevation provided at the curve, β is the gradient of the slope, and x' represents the advancing direction of the vehicle. In the analysis, the stress and the movement of the vehicle are decomposed in two directions which are vertical to the advancing direction and parallel to the advancing direction, and the sideslip problem and the braking problem are respectively considered. In the direction perpendicular to the direction of motion of the vehicle, the vehicle may be force analyzed as shown in fig. 4. In fig. 4, G represents the gravitational force to which the vehicle is subjected; fNRepresenting the supporting force provided by the road surface; ffF represents the lateral friction of the road surface, and since the vehicle tends to slip outward of the curve away from the road when passing through the curve, FfIs directed towards the inside of the curve.
FwRepresenting the wind force, in practice there are many possibilities for the direction of the wind force, wherein the most unfavourable case is that the force of the wind is directed outside the bend, i.e. a strong wind has the effect of causing the vehicle to leave the bend. To take the most unfavorable situation into account, it is assumed that the direction of the wind is directed along the curve towards the outside of the curve and is perpendicular to the vehicle heading direction at the moment during the movement of the vehicle. It should be noted that, in fact, when the wind direction is not changed, as the vehicle advances on the outer lane, the included angle between the direction of the wind and the advancing direction changes, and the modeling manner represents the most unfavorable situation, and can ensure the robustness of the obtained result.
The wind power calculation method comprises the following steps:
Fw＝Aspw＝hlpw (5)
in the formulas (3) to (5), ρ represents an air density; p represents the local air pressure; psStandard atmospheric pressure 101.33 kPa; t iskRepresents the local absolute temperature (kelvin temperature); p is a radical ofwRepresents the dynamic pressure of the wind, w represents the wind speed; a. thesThe lateral frontal area of the vehicle is represented here by the product of the vehicle length l and the height h. If the local atmospheric pressure cannot be measured, the conversion can be carried out through the relation between the altitude and the atmospheric pressure.
Based on the above analysis, in the case where a ramp and a curve coexist:
FN＝Gcosαcosβ＝mg cosαcosβ (6)
Ff＝fFN＝f mg cosαcosβ (7)
where m is the mass (including the load) of the vehicle, g is the local gravitational acceleration, and f is the lateral force coefficient. When the road surface conditions are different, the value of f is also different. Wet and icy roads have lower coefficients of friction than dry roads.
In the horizontal direction, the resultant force of various forces borne by the vehicle provides a centripetal force for the vehicle to make a circular motion along a curve, and when the vehicle is in a critical state without sideslip:
where R denotes the radius of the current curve and v denotes the critical speed of the vehicle.
From (8) in combination of formulae (3) to (5):
according to the formula (9), under the conditions of specific road surface conditions, specific wind power and vehicle size, the critical vehicle speed of each road end on one road can be calculated, so that the vehicle does not sideslip. According to equation (9), the larger the curve radius of the road, the smaller the gradient of the road, the larger the lateral force coefficient of the road surface, the smaller the size (windward area) of the vehicle, the smaller the wind speed, the larger the mass of the vehicle, the larger the critical speed v, and at this time, the higher the safety of the vehicle running on the road.
When considering the braking of the vehicle, the force profile of the vehicle in the direction parallel to the direction of advance of the vehicle is shown in fig. 5. Wherein,
representing the longitudinal friction provided by the road surface, of magnitude equal to the ground bearing force FNCoefficient of adhesion to road surface
The product of (a):
ground braking force F capable of decelerating the vehicle during brakingbAnd braking deceleration abCan be expressed as:
in equations (11) to (12), when the vehicle is traveling in the uphill direction, the gradient i of the road takes a positive value; otherwise, take the negative value. It can be seen that the braking deceleration a of the vehiclebDepending on the waySurface condition, slope and elevation of the road. When the road surface becomes smooth and the adhesion coefficient is reduced, the vehicle is more difficult to brake; at the same time, the downhill gradient also affects the braking of the vehicle.
By the foregoing detailed description, the present invention provides a vehicle driving model algorithm,
Specifically, the provision of the safe driving data of the vehicle is performed in the following aspects:
1) safe vehicle speed: when the road and vehicle type information, the road surface and the weather condition are known, the sideslip critical speed of the vehicle at a certain position of the road can be obtained according to the formula (9), and the actual running speed of the vehicle is not larger than the critical speed obtained by the formula (9) to be ensured.
2) Safe weight: given road, road surface and weather conditions, as well as the speed (road speed limit) and size of the vehicle, so that the vehicle does not sideslip, the weight of the vehicle should satisfy the following condition:
3) and (4) safe size.
When given road, road and weather conditions, as well as the speed of travel (road speed limit) and mass of the vehicle, so that the vehicle does not slip, the dimensions of the vehicle (mainly the side frontal area) should satisfy the following conditions:
4) safe headway determination
The headway of a vehicle when the vehicle runs on a road is an important factor influencing traffic safety, and the maintenance of the safe headway is beneficial to avoiding accidents. The braking process of the vehicle is analyzed, and the safe headway t of the vehicle can be calculated based on the analysis. The distance traveled by the vehicle during braking consists of two stages, constant speed travel during driver reaction time and variable speed travel during braking, as shown in fig. 6. Note also that the vehicle is not a mass point, so when considering the safe headway, the vehicle length needs to be included, i.e. equation (15).
Wherein s isreactIndicating the distance, s, traveled by the vehicle during the driver reaction timebrakeRepresents the distance traveled by the vehicle during braking, l represents the vehicle length, and v' represents the travel speed of the vehicle. By treactIndicating the reaction time of the driver, sreactAnd sbrakeSatisfies the following conditions:
sreact＝v′treact (16)
in combination with the above analysis of the braking deceleration of the vehicle, the safe headway can be obtained as follows:
the data that can provide above-mentioned is used for road analysis and management and control, can be based on the road condition, provides following management and control:
the risk analysis of the whole road mainly comprises the following contents:
1) and sideslip critical vehicle speed.
For a certain traffic road, under the specific vehicle type, road surface and weather conditions, the critical speed of the whole road line can be calculated according to the formula (9) so as to analyze the coupling effect of the curve and the gradient on the safe driving of the vehicle. The obtained critical speed values are different at different positions of the road, such as different gradients, different superelevations and different radii of the curve, and local speed limit sign marks are required to be arranged at places with smaller critical speed, and overspeed is strictly prohibited so as to avoid danger.
2) The braking difficulty of the vehicle.
According to the formula (12), the deceleration which can be achieved when the vehicle brakes is affected by the conditions of the road and the road surface, the road surface is wet and slippery in rainy and snowy days, so that the braking difficulty is increased, and the road section with an overlarge gradient also brings difficulty to the vehicle braking. Under different road surface conditions, the braking deceleration which can be achieved by the vehicle is different at different positions of the road, different in gradient, different in superelevation and different in radius of the curve. When a road surface with a low coefficient of adhesion (icy or snowy road surface) and a large gradient coexist, the vehicle may not even be able to brake. Equation (12) provides a method for determining the braking difficulty of the vehicle, so that under different weather and road conditions, it is determined where to set the safety prompt, and even the road closure management is performed according to the calculation result.
3) And the time headway is safe.
Equation (18) provides a method for calculating a safe headway for a vehicle to travel while taking into account the coupling of weather conditions and road conditions (curves, grade). Based on the calculation result, the safe headway of the whole road can be determined, so that a mark identifier is set at a necessary place to remind a driver of keeping the safe headway, and the risk of accidents is reduced.
The invention provides a method for analyzing critical driving conditions based on road and weather conditions, which further comprises the following steps:
vehicle dynamic performance parameter based on automobile and driving force F of vehicletWith a running resistance FrBalancing
Determining the maximum driving speed of the vehicle, wherein Mm、MpTorque at maximum torque and maximum power of the engine, nm、npThe rotation speed at the maximum torque of the engine and the rotation speed at the maximum power of the engine, eta is the mechanical efficiency of the automobile, gamma is the total speed ratio, r is the wheel radius, frThe coefficient of rolling friction on the ground, k is the coefficient of air resistance, and A is the axial windward area of the automobile;
collecting road gradient information i, combining the road gradient information, vehicle dynamic performance parameters, and the balance between the driving force and the running resistance of the vehicle
Determining the driving speed of the automobile on a critical slope;
obtaining road curve information based on algorithm
Determining a critical curve driving speed of the vehicle, wherein
Is the coefficient of adhesion of the road surface, iyFor super high road surface iyTan α, R is the curve radius, B is the track width of the vehicle, hcG is the gravity coefficient.
Optionally, the above-ground rolling friction coefficient frThe air resistance coefficient k is acquired by road side equipment or obtained by experiments.
As a specific implementation mode, the method provided by the invention can be realized based on Carsim simulation software. Carsim is a vehicle dynamics simulation software that can simulate the response of a vehicle to driver inputs, road inputs, and aerodynamic inputs, and can analyze characteristics of the vehicle such as handling stability, braking performance, and dynamics. Carsim allows for detailed modeling of the body, tires, suspension, steering, braking, and drivetrain of a vehicle. When complex road conditions and severe weather are considered, the driving safety of the vehicle can be analyzed through Carsim simulation, the specific steps comprise the road three-dimensional modeling, the road risk analysis and the management and control, and due to the fact that the road three-dimensional modeling, the road risk analysis and the management and control are realized through simulation software, an experiment scene needs to be built. After the required road information is given, for a certain specific vehicle model, a corresponding vehicle model can be set through input parameters, the influence of wind power is reflected through lateral force, and the influence of the road surface is reflected through a road surface adhesion coefficient. By setting different driving speeds, the driving states of the vehicle under the conditions of different road surfaces and different wind levels can be simulated. The slip angle and the slip rate are selected to judge whether the vehicle sideslips in the driving process. For a certain road section and a certain vehicle type, the critical running speed of the vehicle without sideslip on the road section can be judged by setting different road surface adhesion coefficients and different wind speeds, carrying out multiple times of simulation, observing the change conditions of the slip angle and the slip rate. As described above, the critical speed of non-sideslip is determined by the road condition, the wind level and the vehicle parameters, and if a running speed is set and the weather condition and the vehicle type capable of safely running at the speed need to be considered, the road and the lateral force setting need to be changed and simulated for many times, and the weather condition is given similarly. The results obtained by this embodiment may be more accurate, but often require extensive simulation experiments when coupling effects of various factors are considered.
As a second specific implementation manner, the present invention further provides a vehicle safe driving prompt system, which includes an information obtaining module and a calculating module, wherein the information obtaining module is configured to obtain road intrinsic information, road real-time information and weather information, the road intrinsic information includes a radius of a curve, a height of the curve and/or a road slope angle, the road real-time information includes an on-ground rolling friction coefficient and/or a road adhesion coefficient of a road surface, the weather information includes wind speed, an air resistance coefficient and/or air density information, and the calculating module performs the critical driving condition analysis method described above. The information acquisition module is road side equipment, the calculation module can be vehicle-mounted equipment, and the road side equipment and the calculation module are communicated through a short-distance communication protocol.
The system mainly comprises an on-board unit, road side equipment and a special short-range wireless communication protocol and is used for real-time information exchange of the road side equipment and the on-board equipment from the perspective of vehicle-road cooperation.
Given a road segment L, the road segment may have a grade, a curve, etc. A period of time t is selected during which the road section is exposed to bad weather.
1. Data collection
(1) The roadside apparatus collects vehicle speed data.
And collecting historical positioning of each moment in the driving process of the vehicle on the road section, and obtaining the average driving speed of each short time within t. When the adjacent times of the collected data are close enough, the average driving speed is similar to the instantaneous driving speed. The time, position and speed information of all vehicles is stored in a table.
The historical positioning can be obtained by methods such as GPS positioning, multi-sensor combined positioning and track data obtaining and the like.
(2) Collecting vehicle dimensional data
And collecting the size information of the vehicles passing the road section at each moment by means of a roadside video device and the like. And positioning the same vehicle through the same position and time, and combining the vehicle with the data in the step (1).
(3) Collecting weather and road conditions.
The weather information of the road section including temperature, rain and snow, visibility, wind power level and the like is collected by looking up the meteorological data and the like of a national meteorological information center. The road surface conditions including dry, wet and frozen are calculated according to the air temperature and rain and snow. And (3) merging the data with the data in the (1) and the data in the (2) according to the same time.
2. Data processing
Checking data consistency, processing invalid values and missing values and the like. Obvious unreasonable data values are removed.
3. Data analysis
The relation between the running speed and the position, the size and the weather condition of the vehicle is analyzed. Polynomial fitting can be tried, or prediction can be carried out by adopting a machine learning method of random forests, and the most important factors influencing the driving speed can be obtained.
4. Description of the invention
The method obtains the predicted running speed under corresponding severe conditions, and integrates the running speed prediction of various factors such as road surface characteristics, vehicle characteristics, weather conditions and the like. Although the speed can be slightly increased on the basis of the predicted speed for safe driving, the prediction result represents the driving speed which most drivers can adopt under the condition, and the method has strong guiding significance for safe driving.
The present invention is described in detail with reference to the embodiments, and the technical effects of the method of the present invention will be described below by way of a specific example. Fig. 7 shows a planar alignment of the analyzed road, and the three-dimensional information of the road obtained according to the three-dimensional modeling method of the first item described above is shown in fig. 8. The coordinates in fig. 7 and 8 represent only relative positions, and do not represent absolute positions of roads. The road is a mountain road, the total length is about 7.2 kilometers, the difference of elevation between mountains and mountains is about 520 meters, the whole line circular curve of the road is more than 70, the coupling effect of the ramp and the curve is obvious, and the effect of the method provided by the invention can be better embodied.
The difficulty of braking the vehicle on different road sections under different road surfaces is analyzed, and the maximum deceleration which can be achieved when the vehicle is braked is calculated. In the calculation formula, the three conditions of dry asphalt pavement, wet asphalt pavement, snow-covered pavement and ice pavement are considered, and the corresponding pavement adhesion coefficients are respectively taken
The presence of a curve can have a detrimental effect on braking compared to a straight road, and table 2 gives the maximum braking deceleration at a part of the curve for three road conditions.
Table 2: maximum braking deceleration (unit: m/s) at partial curve under different weather conditions2)
It can be seen that the maximum braking deceleration of the vehicle shows a tendency to become gradually smaller as the road adhesion coefficient decreases; meanwhile, under the same road surface condition, the value of the maximum braking deceleration is different due to different road gradients and curve radiuses. For dry asphalt pavement, the maximum deceleration supported by the road can reach 7-9m/s according to the position on the road2. This is a value close to the acceleration of gravity, which is in fact objectively achievable although the human body generally cannot sustain such large accelerations/decelerations. The maximum braking deceleration on a wet asphalt pavement is about 4-7m/s2Braking is easier when the vehicle runs on an uphill slope, and the vehicle can run on the road safely. However, the maximum braking deceleration on snowy roads is 0-4m/s2The maximum braking deceleration during downhill driving is only 0-2m/s2When braking becomes difficult, the vehicleThe vehicle can be stopped only by a longer braking distance, so that the risk of accidents is increased. For example, on a road with radius of 150 meters and slope of-8%, a road with 5m/s2A complete brake-off of the vehicle running at a speed of (18km/h) takes 4 seconds. When the road surface is frozen, the difficulty of braking the vehicle is further increased, and the maximum braking deceleration of the vehicle running along the uphill slope is only 1-3m/s2(ii) a This value is even lower when the vehicle is downhill, and even in some locations the maximum braking deceleration is negative and braking is impossible, due to the low road adhesion coefficient and the large gradient. By combining the above analysis, for the example road, both normal weather and rainy weather vehicles can run normally; when snow exists on the road surface, advising that the vehicle is prohibited from going downhill, and simultaneously prompting the vehicle going uphill to pay attention to the speed and keep the distance between the vehicles; when the road is frozen on the whole line, the vehicle should be prohibited from running, and when some road sections are frozen, the specific analysis can be performed on the frozen road sections to determine whether bidirectional prohibition is needed or whether the vehicle should be prohibited from running in the downhill direction or whether warning marks are set at necessary positions. When the road surface condition is not good but the vehicle must run, certain anti-skid measures need to be taken.
The critical speed of the vehicle on the road in sideslip is analyzed below. According to a regression formula (19) between the design speed V and the transverse force coefficient mu given by AASHTO (1984), the transverse force coefficients corresponding to different design speeds can be obtained.
f＝0.25-0.204*10-2*V+0.63*10-5*V2 (19)
An exemplary road design speed is 15km/h, which results in a corresponding lateral force coefficient of 0.22. It should be noted that according to AASHTO (1984), this value is not only safe under normal road conditions, but is also effective when the road adhesion coefficient is reduced in rainy or snowy weather, etc. It should be noted that according to equations (3) - (5), the ambient temperature can influence the magnitude of the wind force experienced by the vehicle by affecting the air density. In order to consider the influence of the ambient temperature, two conditions of 0 ℃ and-20 ℃ of the ambient temperature are considered. Furthermore, wind speeds of 0-24m/s are considered to correspond to the real case 0-9 class winds. The values of the other parameters are shown in Table 3.
Table 3: other parameter values in the examples
Based on the analysis and the value, the sideslip critical speed of the road at different positions under different wind speeds is obtained, referring to fig. 9, the deeper the color is, the lower the critical speed is, and the larger the risk of the vehicle sideslip is. It can be seen that the critical speed is gradually reduced as the wind speed increases, and the critical speed at different positions of the road greatly differs under the same wind speed. This can reveal locations on the road where there is a greater risk to specify a targeted regulatory strategy. At two ambient temperatures, when there is nine winds (wind speeds 21-24m/s), Table 4 gives the critical speeds at several locations on the example road where the risk of sideslip is greater. It can be seen that the lower the temperature, the more unfavourable the safety situation of the vehicle, and that at-20 c there are 9 curves each with a critical speed of less than 14 km/h. At 0 degrees celsius, the critical speed of these 9 curves is still less than the design speed, which would create a side-slip hazard if the vehicle were to be driven at the design speed. In other cases, the vehicle can safely run on the road according to the designed speed.
Table 4: side-slip critical speed for example road section position at two temperatures at nine wind speeds
The safe headway for a vehicle traveling on an example road is analyzed below. Taking the driver reaction time treact2.5s, v' takes 15km/h according to the designed speed, and the calculated safe headway is shown in fig. 10. It should be noted that the above analysis of the braking of the vehicle mentions that the maximum braking deceleration that can be achieved by the vehicle is of a large value on dry asphalt pavement and wet asphalt pavement, and that in practice the human body cannot sustain too large a deceleration. Therefore, when calculating the safe headway, the braking deceleration a is taken according to the relevant data for the two road surface conditionsbIs 4.5m/s2. Top in the case of two road surfaces obtained at this timeThe downhill safety headway is the same and is represented in fig. 9 by wet asphalt pavement (downhill). When the road surface is icy, the downhill vehicle cannot brake at a portion of the example road, and therefore the safe headway in this case is not taken into account. As can be seen from fig. 9, in most cases, the safe headway of the example road is between 5 and 7 seconds, and in case of icy road, the headway (uphill) needs to be left for more than 7 seconds in the upper part of the road. This calculation can provide a basis for headway management on the example road.
The technical scheme provided by the application at least has the following technical effects or advantages:
the practical and feasible safe driving guidance is provided on some complicated road sections or dangerous road sections, so that people can not drive by only depending on experience any more, and the traffic accident can be avoided and the safety can be guaranteed.
In the description provided herein, numerous specific details are set forth. It is understood, however, that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.
Similarly, it should be appreciated that in the foregoing description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be interpreted as reflecting an intention that: that the invention as claimed requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.
It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim.
Claims (8)
1. A method for analyzing critical driving conditions based on road and weather conditions, the method comprising:
performing three-dimensional modeling on the road based on the gradient and the plane coordinates of the preset road section of the road;
determining the maximum wind power borne by the vehicle based on the local air pressure, temperature, wind speed and vehicle size; in the direction perpendicular to the vehicle advancing direction, a vehicle running model of the relation among road information, vehicle information, maximum wind power and sideslip critical speed of the vehicle is constructed based on the critical state stress condition that the vehicle does not sideslip, wherein the road information comprises road gradient, road friction coefficient, curve height angle and curve radius; the vehicle information comprises vehicle mass and vehicle size, and the vehicle running model is as follows:
wherein v is a sideslip critical speed, R is the radius of the current curve, g is a gravity coefficient, alpha is a curve height angle, beta is a road slope angle, f is a road transverse force coefficient, h is a vehicle height, l is a vehicle length, w is a wind speed, ρ is an air density, and m is a vehicle mass;
on the direction parallel to the vehicle advancing direction, a vehicle braking model of a road adhesion coefficient, a road gradient, a curve height angle and a braking deceleration is constructed based on the vehicle stress condition, wherein the vehicle braking model is as follows:
wherein, abFor braking deceleration, g is the gravity coefficient,
the method is characterized in that the method comprises the following steps that (1) the road adhesion coefficient is adopted, alpha is a curve height angle, beta is a road slope angle, i is a slope, i is tan beta, when a vehicle goes up a slope, i takes a positive value, and otherwise, i takes a negative value;
and outputting the vehicle running speed, the safe vehicle weight, the safe vehicle size and/or the safe vehicle headway according to the vehicle running model and the vehicle braking model.
2. The method of claim 1, further characterized by three-dimensional modeling of the road based on grade, planar coordinates of a predetermined segment of the road, comprising:
collecting gradient data of a plurality of preset road sections of the whole road, wherein the gradient data comprises pile-starting numbers, pile-ending numbers and gradient information, collecting plane coordinates of a plurality of sampling points on the preset road sections on the central line of the whole road,
and performing three-dimensional stretching on the plane coordinates according to the gradient data so as to perform three-dimensional modeling on the road.
3. The method of claim 1, further characterized in that the method further comprises:
determining sideslip critical speed according to road information, vehicle type information and weather conditions on the basis of the vehicle running model, and prompting or controlling the actual running speed of the vehicle on the basis of the sideslip critical speed;
and/or determining the safe weight of the vehicle according to the known running speed, road information, weather conditions and vehicle type information based on the vehicle running model;
and/or determining the safe size of the vehicle according to the known running speed, road information, weather conditions and known vehicle weight based on the vehicle running model;
and/or determining the safe headway according to the vehicle running speed and the driver reaction time based on the vehicle braking model.
4. The method of claim 1, further characterized in that the method is implemented based on Carsim simulation software.
5. The method of claim 1, further characterized in that the method further comprises:
vehicle dynamic performance parameter based on automobile and driving force F of vehicletWith a running resistance FrBalancing
Determining the maximum driving speed of the vehicle, wherein Mm、MpTorque at maximum torque and maximum power of the engine, nm、npThe rotation speed at the maximum torque of the engine and the rotation speed at the maximum power of the engine, eta is the mechanical efficiency of the automobile, gamma is the total speed ratio, r is the wheel radius, frThe coefficient of rolling friction on the ground, k is the coefficient of air resistance, and A is the axial windward area of the automobile; collecting road gradient information i, combining the road gradient information, vehicle dynamic performance parameters, and the balance between the driving force and the running resistance of the vehicle
Determining the driving speed of the automobile on a critical slope;
obtaining road curve information based on algorithm
Determining a critical curve speed of the vehicle, wherein
Is the coefficient of adhesion of the road surface, iyFor super high road surface iyTan α, R is the curve radius, B is the track width of the vehicle, hcG is the gravity coefficient.
6. The critical driving condition analysis method according to claim 5, further characterized in that the on-ground rolling friction coefficient frThe air resistance coefficient k is acquired by road side equipment or obtained by experiments.
7. A vehicle safe driving prompt system comprises an information acquisition module and a calculation module, wherein the information acquisition module is used for acquiring inherent road information, real-time road information and weather information, the inherent road information comprises the radius of a curve, the height angle of the curve and/or the gradient of the road, the real-time road information comprises the rolling friction coefficient and/or the road adhesion coefficient of the road surface, the weather information comprises the wind speed, the air resistance coefficient and/or the air density information, and the calculation module executes the steps of the critical driving condition analysis method according to any one of claims 1 to 6.
8. The system of claim 7, wherein the information acquisition module is a road side device, the calculation module is an on-board device, and the road side device and the calculation module communicate with each other via a short-distance communication protocol.
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| CN114148321B (en) * | 2021-11-22 | 2023-06-20 | 长安大学 | Automatic emergency braking and safety evaluation method considering collision risk |
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| CN115798239B (en) * | 2022-11-17 | 2023-09-22 | 长安大学 | Vehicle running road area type identification method |
| CN115880905B (en) * | 2022-11-29 | 2024-05-17 | 吉林大学 | Device and method for predicting intersection time of vehicle passing traffic signal lamp in real time |
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102568218A (en) * | 2011-12-09 | 2012-07-11 | 东南大学 | Method for determining safe running speed on expressway under crosswind |
| US20150120177A1 (en) * | 2013-10-29 | 2015-04-30 | Honeywell International Inc. | System and method for maintaining aircraft separation based on distance or time |
| US9297722B2 (en) * | 2009-07-22 | 2016-03-29 | Meidensha Corporation | Driver'S aid device and driver'S aid system |
| CN107618512A (en) * | 2017-08-23 | 2018-01-23 | 清华大学 | Driving behavior safe evaluation method based on people's car environment multi-data source |
| CN110962927A (en) * | 2018-09-29 | 2020-04-07 | 比亚迪股份有限公司 | Turning control method and device, computer readable storage medium and unmanned aerial vehicle |
| CN112115610A (en) * | 2020-09-18 | 2020-12-22 | 长安大学 | System and method for evaluating side-turning and side-slipping risks of trucks on road sharp and steep curve sections |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102723001B (en) * | 2012-06-08 | 2014-02-19 | 长安大学 | Implementation method of speed feedback sign system for bend steering vehicle speed safety state prewarning |
-
2021
- 2021-04-20 CN CN202110423620.6A patent/CN113538896B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9297722B2 (en) * | 2009-07-22 | 2016-03-29 | Meidensha Corporation | Driver'S aid device and driver'S aid system |
| CN102568218A (en) * | 2011-12-09 | 2012-07-11 | 东南大学 | Method for determining safe running speed on expressway under crosswind |
| US20150120177A1 (en) * | 2013-10-29 | 2015-04-30 | Honeywell International Inc. | System and method for maintaining aircraft separation based on distance or time |
| CN107618512A (en) * | 2017-08-23 | 2018-01-23 | 清华大学 | Driving behavior safe evaluation method based on people's car environment multi-data source |
| CN110962927A (en) * | 2018-09-29 | 2020-04-07 | 比亚迪股份有限公司 | Turning control method and device, computer readable storage medium and unmanned aerial vehicle |
| CN112115610A (en) * | 2020-09-18 | 2020-12-22 | 长安大学 | System and method for evaluating side-turning and side-slipping risks of trucks on road sharp and steep curve sections |
Non-Patent Citations (2)
| Title |
|---|
| Advisory Speed Estimation for an Improved V2X Communications Awareness in Winding Roads;Juan Aznar-Poveda et.al;《 2020 22nd International Conference on Transparent Optical Networks (ICTON)》;20200922;第61-65页 * |
| 横风作用下复杂路段汽车运行安全的概率评估;田林 等;《武汉理工大学学报》;20140731;第1-4页 * |
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