JP2023524574A - A Unified Quantification Method for Driving Risk Comprehensively Considering Each Element of People, Vehicles, and Roads - Google Patents

Abstract

obtaining an initial driving safety field model of driving risk according to the principle of energy transfer; decomposing the initial driving safety field model into longitudinal and lateral directions; creating a safety field model; calculating a field force Fji by the vehicle j with respect to any position point i in the traffic environment where the vehicle j is located; and a step of recognizing the driving risk affected by the influence of j. This method is based on the fact that driving risk depends on the comprehensive interaction between each element that affects driving safety. proposed a modeling concept.

Description

TECHNICAL FIELD The present invention relates to the technical field of smart car use, and more particularly to a unified quantification method for driving risk that comprehensively considers people-vehicle-road factors.

Quantifying driving risks is the basis for developing driving safety support technology and autonomous driving technology. Conventional research usually uses parameters describing crashes to quantify driving risk, and there are mainly accident analysis-based risk assessment methods, vehicle kinematics-based assessment methods, and artificial potential energy field-based risk assessment methods. Research on automotive smart safety technology has already entered a high-growth period. Overall, the assessment of driving risk consisted of 1) an assessment of risk in the longitudinal direction of the vehicle and a one-dimensional driving risk assessment of risk in the longitudinal direction, and 2) consideration of both the longitudinal and lateral dimensions of the vehicle. Two categories of two-dimensional driving risk assessments can be distinguished.

Chinese and foreign scholars have already done a lot of research on driving risk assessment, but there are still many shortcomings. Usually, as a method of evaluating the driving risk of the vehicle traveling visual angle, a risk evaluation model is constructed by vehicle kinematics and dynamics theory based on the vehicle state information and the relative motion relationship information between the two vehicles. On the other hand, a new method represented by an artificial potential energy field was adopted. Both methods have their own advantages, but they both have common deficiencies, namely, they do not consider all risk factors, have a single application scenario, and are difficult to handle in a complex and changing traffic environment. Therefore, the same smart car requires multiple independent risk assessment models, and it ignores the effects of the driver's own physiological and psychological characteristics, road and traffic environment factors, etc. on driving risk. , Human-vehicle-road risk generation mechanism has not been sufficiently researched, so the practical application of the conventional method is greatly restricted.

In order to address the above issues, in order to improve the scientific, time-sensitive and accurate driving risk assessment, from the viewpoint that traffic accidents are abnormal energy transfer, vehicles are driven based on kinetic energy while the vehicle is running. It is necessary to propose a driving risk description method based on quantum field theory by constructing an initial driving safety field model of the risk to the outside world and analyzing the mutual influence relationship between each element in the traffic environment. In this method, driving risk is quantitatively described from the viewpoint of traffic management, taking into account the driving visual angle of the vehicle. Analyze the impact on the vehicle and propose to form a comprehensive driving risk unified form that simultaneously considers the interaction between the attributes of the vehicle itself and the traffic flow. construct a driving safety field model.

SUMMARY OF THE INVENTION It is an object of the present invention to provide a unified method for quantifying driving risk that comprehensively considers the factors of people, vehicles, and roads in order to solve or reduce at least one of the above-mentioned drawbacks of the prior art. .

In order to achieve the above object, the present invention
According to the energy transfer principle, obtaining an initial driving safety field model of the driving risk represented by equation (3); decomposing the initial driving safety field model into longitudinal and lateral directions to obtain vehicle j information and traffic environment information; and a step of creating a first unified driving safety field model expressed by equation (69) or a second unified driving safety field model expressed by equation (74) based on the traffic environment in which vehicle j is located. calculating a field force F _ji by the vehicle j for the position point i; and based on said field force F _ji recognizing the driving risk to which the point i is affected by the vehicle j;

where x _ji represents the longitudinal distance from any point i in the environment of vehicle j, y _ji represents the lateral distance of vehicle j from point i, and r ₀ represents the represents the distance between vehicles, r _max represents the maximum distance between vehicles in free flow, r _min represents the minimum distance between vehicles in free flow, i.e., the center of mass of vehicle j and said position point i and E _j is the sum of the kinetic energy E _j,0 determined by the speed v _j of vehicle j and the relative kinetic energy determined by multiple traffic environment factors, and E _j,fac is the kinetic energy Energy E represents the relative kinetic energy determined by _j,0 and traffic environment factors, which include road surface friction coefficient, road curvature, road slope, environmental visibility, lane and road speed limit rules, and vehicle j's When any one of the speed and traffic environment factors is ignored, the kinetic energy value corresponding to that factor is 0, and _kx is the speed of vehicle j and the longitudinal gradient adjustment coefficient of each traffic environment factor. k _x,fac represents the speed of vehicle j and the longitudinal gradient adjustment coefficient of each traffic environment element, and k _y is the product of the speed of vehicle j and the lateral gradient adjustment coefficient of each traffic environment element and _ky,fac represents the speed of vehicle j and the lateral gradient adjustment coefficient of each traffic environment element, and when any of the speed of vehicle j and the traffic environment element is ignored, Provided is a unified quantification method for driving risk that comprehensively considers each element of people-vehicle-road with a corresponding slope adjustment coefficient value of 1.

The present invention has the following advantages by adopting the above technical solutions. 1. The present invention proposes a driving safety field modeling method that can accurately reflect the interaction relationship between vehicles in the road traffic environment, considering the influence of driving risk caused by each element of the road traffic environment, such as people, vehicles, and roads. In addition to organically combining vertical and horizontal risks during vehicle driving in the form of a field, the vertical and horizontal risks are not only converted from the discrete form in the conventional method to a continuous form, but also visualized in the form of a risk distribution map. can be displayed. 2. The present invention improves the accuracy of the description of inter-relationships between vehicles while ensuring continuity of risk distribution. 3. The present invention provides a driving risk quantification method, which can identify driving risks in advance and take corresponding safety measures to prevent traffic accidents from occurring.

1 is a schematic diagram of the relationship between field force and potential energy in a traffic environment; FIG. It is an elliptical constraint principle diagram. FIG. 3 is a schematic diagram of a state in which a vehicle j normally travels in a lane; FIG. 3 is a schematic diagram of a state in which a vehicle j runs on lane 3;

The present invention will now be described in detail with reference to the drawings and examples.

Based on the driving risk field model below and the relationship between the field force F _ji and the potential energy U _ji in the traffic environment shown in FIG. By analyzing the impact of driving risk on driving risk, we can confirm the mechanism of driving risk, identify driving risk in advance, take corresponding safety measures, and provide a method of quantifying driving risk to prevent traffic accidents. intended to

As is well known to those skilled in the art, driving risks do not normally exist in isolation, but generally occur between vehicles and between the vehicles themselves and the traffic environment. In order to assess the safety state of the traffic environment, in the embodiment of the present invention, the risk is expressed in the field, the driving risk is defined as the field interaction between each study object, and the human perception of the risk in the traffic environment. Specifically, the risk between two objects in a traffic environment is shown in the field as follows.

In equations (1) and (2), j represents a field source, i represents a point in the traffic environment, U _ji represents the potential energy field due to the field source at i point, and in the traffic environment, U _ji is a function of field source j's self-attribute M _j , velocity v _j and distance r _ji between field source j and point i, and F _ji is the gradient of the potential energy field U _ji , i.e. is the field force, the negative sign represents the direction of descent along the gradient of the field, and the field force received F _ji is large.

In an embodiment of the present invention, the field that describes the risk in the traffic environment is called the "driving safety field", and if r represents the distance of point i from vehicle j in the traffic environment, then the distance of point i from vehicle j is The larger is, the smaller the received field force F _ji and the smaller the potential energy U _ji . Compared to the electric field method, when modeling for the driving safety field, the model can quantify the driving risk under certain conditions. However, physical electric fields are not particularly suitable for describing driving risk. For example, in an electric field, the potential energy at infinity is 0, and charged particle A is not affected by charged particle B at infinity. and the distance between charged particles A and B is infinitesimal, the electric field force between them is infinite. Of course, these two phenomena have no corresponding scenario in traffic. Therefore, for the above problem, embodiments of the present invention provide a new modeling for the driving safety field.

FIG. 1 shows the relationship between field force and potential energy. In FIG. 1, a curve in the coordinate system represents the field force F _ji exerted by a vehicle j on any position point i in the environment, and the induced risk range has a boundary, between point i and vehicle j If the distance r _ji exceeds r _max , ie r _ji ≧r _max , point i is unaffected by vehicle j, ie F _ji =0. On the other hand, the potential energy U _ji at a certain position of point i also satisfies U _ji =0, which is a scenario in which the distance between vehicles in a traffic environment is sufficiently large and the driver's actions are not affected by other vehicles (e.g., free flow scenario), and as the distance r _ji between point i and vehicle j decreases (i.e., r _ji <r _max ), the field force F _ji and potential energy U _ji begin to increase, Moreover, the smaller the r _ji , the greater the field force F _ji and the potential energy U _ji . However, if the distance r _ji between point i and vehicle j is less than r _min , i.e., r _ji <r _min , the field force F _ji will not increase, which means that in a traffic environment a collision accident occurs. It corresponds to the scenario that occurred. In an embodiment of the present invention, both the coordinates of the midpoint i and the vehicle j are calculated as their geometric centers, and the distance between the point i and the vehicle j is 0, since the traffic participants have a given appearance size. does not become For ease of analysis, the field force F _ji for which r _ji is less than r _min is set to a constant maximum value F _max .

A method for quantifying driving risk according to an embodiment of the present invention includes several aspects as follows.
(1) Risk quantification method for the vehicle itself (1.1) Risk from the traffic management perspective In the embodiment of the present invention, the initial driving safety field model is simply modified according to Fig. 1 to form a new initial driving safety field model. , that is, formula (3) is obtained.

where E _j,0 represents the kinetic energy of vehicle j. If r _ji ε[0,r _min ) then the value of F _ji is equal to E _j,0 . r ₀ is the driver's gaze range for risk and is related to the driver's following distance. r _max is the free-stream vehicle separation and represents the maximum impact range of the risk, also called the maximum vehicle-to-vehicle separation in the free stream. r _min represents the minimum distance between the vehicles in free flow, ie the distance between the centroid of vehicle j and said position point i in the event of a collision.

When the driver runs behind the vehicle in front, it is limited by the current situation of the traffic environment. As can be seen, the driver's inter-vehicle distance r ₀ is shown as equation (4).

where the overall sharpness of the driver is γ, γ∈[−0.03,0] s ² /m, the average reaction time is τ, τ=1 s, and l is effective is the length of the vehicle, l=6 m, and v is the velocity of the traffic flow.

According to the road traffic manual, at free flow speed, the maximum value q _max of traffic flow satisfies the following equation (5).
q _max =3100−54v _f (5)

where v _f is the free stream flow velocity, so the vehicle spacing r _max in the free stream is given as equation (6).

As can be seen from FIG. 1 and equation (3), r _min is related to the values of r _max and r ₀ and follows equation (7).

F _ji is a given value within r _ji ε(0,r _min )∪(r _max ,+∞) and is relevant to changes in r _ji only if r _ji ε[r _min ,r _max ] Therefore, in this embodiment, analysis is mainly performed on the interval r _ji ε[r _min , r _max ].

If a vehicle j is in free motion at constant velocity in an unbounded environment, the driving risk posed by the vehicle j in the environment is isotropic satisfy sex. Thus, the driving safety field field force F _ji,0 is shown as equation (8).

where x _ji represents the longitudinal distance between vehicle j and some point i in the environment, and y _ji represents the lateral distance between vehicle j and point i.

The change in gradient of field force F _ji,0 in the generated driving safety field is given by equation (9).

If the mass and velocity of vehicle j are known, the field forces produced by vehicle j at each position in the road traffic environment can be calculated from equation (9). In an open road traffic environment, the driving safety field is only and inversely related to distance, the closer to the vehicle the greater the force of the driving safety field experienced.

In the actual road traffic environment, the motion of the vehicle is directional, so the risk that the vehicle poses to the outside world is not isotropic. Normally, regardless of whether it is based on human subjective sensation or objective collision probability, the positive direction of motion poses a greater risk to the outside world than the negative direction during vehicle motion. Such a phenomenon is analogous to the wave Doppler shift effect. The view that vehicle j poses a greater risk to the environment in the positive direction of motion than in the negative direction may be described as the degree of gradient descent of the driving safety field field force being related to the direction of motion of the vehicle, i.e. , the field force gradient drop in the driving safety field slows down as vehicle j approaches point i. Setting the longitudinal and lateral gradient adjustment factors yields equation (10).

where k _x,0 represents the longitudinal grade adjustment factor for the speed of vehicle j, and k _y,0 is the lateral grade adjustment factor for the speed of vehicle j. Of course, the parameters k _x,0 and k _y,0 directly affect the distribution of the driving safety field. The "longitudinal direction" described in the specification corresponds to x, and the "horizontal direction" corresponds to y. "Forward" is the direction in which vehicle j travels in the direction indicated by the lane centerline.

If vehicle j is traveling in the positive direction of x, k _x,0 and k _y,0 are defined as follows according to the Doppler shift principle.

where _xj is the x-coordinate of vehicle j, _vj is the x-direction velocity of vehicle j, and point i, which may be another vehicle or another point, represents a given point in the environment. , then x _i is the given coordinate of the point i in the x direction and v _i =0; conversely, if i represents a vehicle, then x _i is the x coordinate of the vehicle and v _i is its motion speed, v _max is the propagation speed of risk, and the risk given by a moving object to the outside world is usually related to the attributes of the moving object itself.

(1.2) Risks from vehicle driving visual angle Traffic perturbations occur when a vehicle is driving in a traffic environment. be. Therefore, according to the equation (8), the risk of the vehicle j to the vehicle i in the traffic environment from the driver's angle is described by the driving safety field as shown in the equation (15).

It is clear from Equation (17) that although the formula for calculating the longitudinal gradient adjustment coefficient is the same from the traffic control visual angle and the vehicle driving visual angle, v _i constantly changes at the vehicle driving visual angle. , whose value is different from the gradient adjustment factor for the traffic control viewing angle.

Similarly, the effect of a particular car j on the overall traffic flow in the traffic environment may be analyzed from the traffic flow angle. If the mean velocity of the car flow in the traffic flow is denoted by , then equation (11) may be rewritten as:

(1.3) Overall driving risk As can be seen from the analysis in (1.1) and (1.2), when observing a particular vehicle from either a traffic management angle or a vehicle driving angle, both There are certain restrictions. For this reason, in the embodiment of the present invention, driving risk is quantitatively described mainly from the vehicle driving visual angle, and the driving risk is quantitatively described from the traffic management visual angle. The expression form of the driving risk is unified as Equation (20).

In the formula, _Ej represents the risk source element of vehicle j while it is running, _kx represents the vertical trend of risk occurring while vehicle j is running, and _ky represents the risk factor occurring while vehicle j is running. Represents the trend of change in the horizontal direction.

Note that if i represents a particular target (e.g., vehicle i, rider i, pedestrian i, stationary obstacle i, etc.), F _ji represents the safety field force corresponding to the risk that vehicle j poses to i, and k The parameter v _i in _x is the actual velocity of target i.

(2) Analysis and quantification of risk restraints of road traffic facilities and driver behavior In order to enhance driving safety, road traffic facilities and regulations require that one vehicle be forcibly stopped so that the trajectories of vehicles cross each other. facilities that reduce driving risk by slowing vehicles by warning or increasing the right-of-way for other vehicles, traffic flows traveling in the same or opposite directions and control driving risk by guiding the direction of motion of the vehicle.

(2.1) Effects of road traffic facilities on traffic risk (2.1.1) Longitudinal restraint of traffic lights , two states during which the red signal is turned off and the green signal is turned on. Chinese standard GB 14886-2016 stipulates that the yellow light duration of a traffic light should be 3s-5s, and if the vehicle is far enough away from the intersection when the yellow light is on, the parking line There is at least 3s before deceleration to . Vehicles that have sufficient time to decelerate to the parking line will then experience the equivalent restraint resistance F _sj due to the red light of the traffic light.

(2.1.2) Longitudinal Restriction of Crosswalks By networking the road traffic environment, vehicles can easily obtain information on the traffic environment. Regarded as a facility to limit driving speed and reduce driving risk. Before crossing the pedestrian crossing, the closer the vehicle is to the pedestrian crossing, the greater the resistance to traffic regulation. _According to Chinese traffic regulations, the speed at which a vehicle crosses the crosswalk must not exceed 30 km/h. Define to receive F _cj .

(2.1.3) Longitudinal restraint of road traffic speed limit signs Road speed limit signs have the role of restraining the running of vehicles only by speed. It poses less risk than two other types of violations: ignoring traffic lights and not slowing down before crossings. If v _l,m of the lane is the minimum speed limit of the lane and v _l,h is the maximum speed limit of the lane, the equivalent restraint resistance F _lj that vehicle j receives from the road traffic speed limit marking is:

(2.1.4) Lateral Constraints of Road Traffic Marking Lines Road traffic marking lines play a role of driving guidance and action restraint for drivers. Traffic marking lines include lane lines and pedestrian crossing lines, and lane lines laterally influence the behavior of drivers and further influence the driving process of vehicles. The lane does not directly affect the driving risk of the vehicle, and the vehicle does not cross the road traffic marking line directly to cause traffic accidents. Road traffic marking lines are generally considered to be capable of generating virtual lateral restraint forces (such as lane keeping) while the vehicle is in motion. Therefore, the restraining force _Fmj applied to the vehicle by the road traffic marking line is defined as in Equation (32).

where _km is a constant factor and may be calibrated with the return lateral acceleration of the vehicle at various vehicle speeds, _kmy is the lateral slope adjustment factor, which is related to driver behavior and r _max,m is the influence range of the road traffic marking line, let r _max,m =0.5l _w , indicating that the vehicle is not affected by the traffic marking line when traveling on the lane centerline.

(2.2) Risk quantification method of driver behavior (2.2.1) Normal driving behavior of drivers It is indicated as binding on the conduct of a person. If the driver and traffic environment factors are not taken into account, the risk given by the vehicle to the outside world is assumed to be isotropic. 2, where A ₁ A ₂ and B ₁ B ₂ are the major and minor axes of the ellipse, respectively, and A ₁ A ₂ =2A ₁ j=2jA ₂ =2A _j , B ₁ B ₂ = 2B ₁ j=2jB ₂ =2B _j . Also, the ellipse shown in FIG. 2 is one contour line of the risk field that the vehicle j occurs in the environment.

In order to ensure that drivers always comply with the rules while driving and to ensure safe driving as much as possible, drivers usually keep a certain headway while driving a vehicle and also observe traffic rules. , stipulates that the vehicle must not change lanes continuously, and at the same time, together with the geometrical dimensions of the vehicle, the lengths of the semi-major and semi-minor axes of the ellipse in Figure 2 are as follows: set like
A _j =r _max +l ₁ (33)
_Bj = _lw + _l2 + _lcj (34)

where A _j is the semi-major axis of the ellipse, l ₁ is half the vehicle length, B _j is the semi-minor axis of the ellipse, and l _w is one times the lane width (usually l _w = 3.5 m), l ₂ is half the vehicle width, and l _cj is the distance between the vehicle and the lane centerline. Note that the major axis of the ellipse is a function related to vehicle speed, _and the lower the vehicle speed, the smaller the major axis. Define _w .

Due to the lateral restraint action of the lane, a clear difference appeared in the longitudinal and lateral risk distributions during vehicle travel. The ellipse shown in Fig. 2 is obtained by compressing the isotropic circular distribution, taking into consideration the safe inter-vehicle time, vehicle flow speed, etc. in the vertical direction and the influence of lane restrictions in the lateral direction. 2, an elliptical risk distribution with dynamically changing long and short axes is formed. When laterally compressed, the outer circle contours are compressed to the inner elliptical contours, and B' ₁ B' ₂ is shortened to B ₁ B ₂ , but the two field force contours represent the same risk values. is. Therefore, the following equation is obtained when the risk of occurrence of vehicle j is distributed along the blue contour line.

(2.2.2) Violation by Drivers The impact of road traffic facilities on driving safety is reflected in the constraint on driving risk. Intentionally or unintentionally breaking the restraint that is given to Therefore, the embodiment of the present invention analyzes the motion state of the vehicle under the longitudinal speed limit and the lateral position limit to determine whether the driver's behavior is prone to violations.

(2.2.2.1) Longitudinal speed limit The risk induced by a perturbation of the traffic environment by a vehicle is related to the speed of the vehicle itself and the average speed of the flow of vehicles, similar to Equation (20), the vehicle The violation risk that a vehicle poses to the road traffic environment when exceeding the maximum speed limit or below the road minimum speed limit may be expressed as equation (41).

For longitudinal infringements, according to equation (22), the driving safety field field force F _ji corresponding to the driving risk imparted to the outside world while driving is:

(2.2.2.2) Lateral Position Limitation The role of road traffic marking lines is to constrain and reduce the vehicle's impact on the traffic environment by constraining the lateral movement of the vehicle. As shown in FIG. 3, when a vehicle travels stably in a lane formed by lanes 2 and 3, the elliptical restraint effect on vehicle j caused by lanes 2 and 3 is expressed by equation (33) in the vertical and horizontal directions, respectively. ) and equation (34). However, if the vehicle is on a certain road marking line for a long time, as shown in FIG. The elliptical constraint action of the road traffic marking line on vehicle j is caused by lanes 2 and 4, the longitudinal semi-major axis of the ellipse still following equation (33), but the transverse semi-minor axis of the ellipse following equation (46).

B _j =l _w +l ₂ +l _jc (46)
where l _jc is the distance from the centerline of vehicle j.

(3) Risk quantification method of road traffic environment elements (3.1) Road surface friction coefficient (3.1.1) Effect of road surface friction coefficient on braking distance ABS system at the front to promote China's policy regulation The number of vehicles equipped with this system is increasing year by year, and it is becoming more and more popular. By controlling the braking force of the brakes on the front and rear axles, it is possible to equalize the synchronous friction coefficient and the road surface friction coefficient. The minimum braking distances for vehicles are:

where m is the mass of the vehicle, g is the acceleration of gravity, b is the distance of the rear axle of the vehicle from the center of the vehicle, and a is the distance of the front axle of the vehicle from the center of the vehicle; f is the rolling resistance coefficient, Ψ is the rear drive axle moment distribution coefficient, for front-wheel drive vehicles, Ψ=0, while for rear-wheel drive vehicles, Ψ=1, L is the wheelbase of the vehicle, A is the wind-swept area of the vehicle, ρ is the density of the air, usually ρ=1.2258Ns ² m ⁻⁴ , and C _D is the air resistance coefficient of the vehicle. , C _lf and C _lr are the front and rear air lift coefficients of the vehicle, respectively.

Also, if the vehicle must decelerate below the maximum road speed limit after the road surface friction has decreased, and vehicle j travels in the positive direction of x, the total driving risk that vehicle j poses to the outside world is is as follows.

(3.2) Curvature of Road In designing a road, it is inevitable that the road bends on a plane or has undulations in its longitudinal section, so there are a large number of curves with large curvatures. When the vehicle passes through a curve, if the vehicle speed v _j >v _d there is a risk due to the curvature of the road, and if v _j >v _j,lim the road can provide sufficient lateral force to the vehicle. As a result, the vehicle will skid. Therefore, when v _j ∈ [v _d , v _j,lim ], the field force F _jc of the driving safety field of the driving risk due to road curvature is expressed by Equation (56), The risk source increment E _j,c after

In steering, the vehicle always tends to move away from the steering center, and the lateral force exerted by the ground on the tires exerts a centripetal force on the steering of the vehicle, enabling stable running of the vehicle. If the vehicle speed is too high or if the steering radius is too small and the ground makes it difficult to provide sufficient centripetal force to the vehicle, the vehicle will enter a dangerous situation such as skidding. Thus, when steering, the vehicle poses a greater risk on the side to which the centrifugal force is directed than on the other side. Assuming that the steering angle δ _j of the wheels of the vehicle j is positive in the counterclockwise direction, the longitudinal gradient adjustment coefficient k _x,c defining the road curvature is expressed by Equation (58), and the lateral gradient adjustment coefficient k _{y and c} are represented by equation (59), and each parameter acquisition method in the equation can be calculated from the theory of vehicle dynamics.

where _vd represents the design speed of the road, φ represents the coefficient of friction of the road surface, _FjZ represents the vertical support force exerted by the ground on vehicle j, and _FjY represents the lateral friction exerted by the road surface on vehicle j. _yi represents the x-coordinate of point i and _yj represents the y-coordinate of vehicle j.

When considering the steering process of the vehicle after considering the direct risk and the perturbation risk due to the vehicle, the total driving risk given by the vehicle j to the outside world is expressed as Equation (60).

(3.3) Road Inclination Driving risks due to road inclination are mainly the interaction process between vehicles when going uphill, and the conversion of gravitational potential energy into kinetic energy when going downhill. It appears in the deterioration of the braking performance. In the uphill section, the driving safety field field force F _ji corresponding to the driving risk to the outside world while driving is shown as equation (61).

On downhill sections, the risk is that the energy carried by the vehicle has gravitational potential energy in addition to its own kinetic energy, i.e. the risk increases as the value of the energy carried by the energy source increases. Assuming that the gradient of the slope is i _r , the conversion amount E _j,s of the gravitational potential energy when the vehicle j travels downhill is given by Equation (63). can be determined based on the properties and kinematics of

Thus, the field force F _js of the driving safety field of driving risk due to slope is shown as equation (64).

The driving safety field field force F _ji corresponding to the driving risk that the vehicle poses to the outside world when traveling downhill is:

Clearly, equation (65) is applicable to both uphill and downhill scenarios, if the vehicle is going uphill, the value of Fj _,s is 0, and if the vehicle is traveling downhill, If so, F _js is calculated by equation (64).

(3.4) Environmental Visibility When encountering bad weather such as heavy rain, dense fog, ice and snow, the friction coefficient of the road may decrease, and the driver's visibility is also strongly affected (industrial cameras, etc.). Sensors for smart driving are also interfered with or affected). Bad weather makes drivers more nervous and poses driving risks. When driving in the rain, the driver's field of vision is easily affected. , Due to the limited range of wiper water, the rain adheres to the windshield and rearview mirror, which reduces the driver's visibility and visual perception range. As a result, it becomes difficult to maintain a safe distance from other vehicles. easy to decline. Therefore, changes in environmental visibility due to weather have a very large impact on driving safety, and the force field of the driving safety field, which corresponds to the driving risk posed to the traffic environment by a vehicle traveling with constant environmental visibility, is given by Eq. (66 ).

where the ambient visibility longitudinal slope adjustment factor k _x,e and the ambient visibility lateral slope adjustment factor k _y,e are related to driver behavior, vehicle state and environmental conditions. If we only consider the effect of environmental visibility, the effect of environmental visibility on the lateral direction of the vehicle is small.

In the vehicle longitudinal direction, the value of k _{x ,e satisfies}

where k _j,e is a constant and relates to the driver's actual visual acuity, let k _j,e =1 and for a driver with good vision, the visibility in a good traffic environment is Typically D ₀ =500 m and the current environment visibility D _e adjusts its value in real time according to weather conditions.

(4) Comprehensive human-vehicle-road risk quantification method How five types of traffic environment factors affect the risk that a vehicle poses to the outside world: direct risk and perturbation risk that a vehicle poses to the outside world, road surface conditions, road curvature, road slope, and environmental visibility We examined the effects of normal driving behavior and illegal driving behavior under traffic rules on vehicle risks. This study examines the restraining effects of four types of traffic facilities (traffic lights, pedestrian crossings, road traffic speed limit markings, and road traffic marking lines) and traffic environment elements represented by road boundaries on vehicle motion.

(4.1) Unified driving safety field model (4.1.1) Field forces Based on the original framework of comprehensive driving risk modeling, the overall framework for shaping the risks that vehicles pose to the outside world. is shown as follows.

(4.1.2) Potential Energy A direct force description of how a point in a traffic environment is affected by multiple vehicles has limitations. In this embodiment, a complete driving safety field system is constructed to describe interaction relationships among people, vehicles, and roads in the road traffic environment, and quantified description of driving risks is realized.

In the driving safety field, at point P (P∈[r _min ,r _max ] ₎ , the potential energy that the vehicle obtains under the influence of the field source is , equal to the work to move r _ji ≧r _max . Therefore, the potential energy U _jp at point P is:

Thus, if the potential energy U _ji of field source j experienced by vehicle i is in the form of a Cartesian coordinate system, the following equations are obtained.

The gradient change of potential energy is as follows.

Specific examples are provided below.
It is possible to judge the degree of risk that the i-car receives from the virtual acceleration obtained by Newton's second law, and take measures such as warning or active braking for each grade. For example, when _ai > 3m/s ² , vehicle i emits an alarm sound, when _ai > 5m/s ² , vehicle i applies slight braking, and when _ai > 8m/s ² , vehicle i performs emergency braking.

運転リスクの発生メカニズムは、運転安全に影響する各要素間の総合的な相互作用にあり、運転リスクに影響を与える要素は、上記の実施例に記載の様々な要素だけではない。本発明の実施例の研究目的は、特定のシナリオにおいて運転リスクに影響を与える新たな要素が出現した場合に、本発明の実施例によって提案された統一的なモデリング構想の枠組みで対応する数学モデルを構築することができる統一的なモデリング構想を提供することである。

The driving risk generation mechanism lies in the comprehensive interaction among the elements that affect driving safety, and the elements that affect driving risk are not limited to the various elements described in the above examples. The research purpose of the embodiment of the present invention is to find a corresponding mathematical model in the framework of the unified modeling concept proposed by the embodiment of the present invention when new factors affecting driving risk appear in a specific scenario. It is to provide a unified modeling concept that can build

It should be noted that the above examples are only used to describe the technical solution of the present invention and are not intended to limit it. As is obvious to those skilled in the art, the technical solutions described in each of the above embodiments can be modified, and some of their technical features can be equally replaced. These modifications or replacements do not make the essence of the corresponding technical solution depart from the spirit and scope of the technical solution of each embodiment of the present invention.

Claims (9)

A unified quantification method for driving risk that comprehensively considers each element of people, vehicles, and roads,
obtaining an initial driving safety field model of driving risk given by equation (3) according to the energy transfer principle;
decomposing the initial driving safety field model into longitudinal and lateral directions to create a first unified driving safety field model represented by equation (69) based on vehicle j information and traffic environment information;
calculating the field force F _ji by the vehicle j for any position point i in the traffic environment in which the vehicle j is located;
recognizing the driving risk to which point i is subject to the influence of vehicle j based on said field forces _Fji ;

where x _ji represents the longitudinal distance from any point i in the environment of vehicle j, y _ji represents the lateral distance of vehicle j from point i, and r ₀ represents the represents the following distance, r _max represents the maximum separation of the vehicles in the free stream, r _min represents the minimum separation of the vehicles in the free stream, and E _j is the kinetic energy E _j,0 determined by the velocity v _j of the vehicle j. and the relative kinetic energy determined by a plurality of traffic environment factors, E _j,fac represents the kinetic energy E _j,0 and the relative kinetic energy determined by the traffic environment factors, the traffic environment factors being the road surface Kinetic energy corresponding to any of the speed of vehicle j and traffic environment factors, including friction coefficient, road curvature, road inclination, environment visibility, lane and road speed limit rules, if the factor is ignored is 0, _kx is the product of the speed of vehicle j and the longitudinal gradient adjustment coefficient of each traffic environment element, and kx _,fac is the speed of vehicle j and the longitudinal gradient adjustment factor of each traffic environment element. _ky is the product of the speed of vehicle j and the lateral slope adjustment coefficient of each traffic environment element; ky _,fac represents the speed of vehicle j and the lateral slope adjustment coefficient of each traffic environment element; , the speed of the vehicle j and the traffic environment factor, the value of the slope adjustment factor corresponding to the factor is 1 if the factor is ignored. obtaining an initial driving safety field model of driving risk given by equation (3) according to the energy transfer principle;
decomposing the initial driving safety field model into longitudinal and lateral directions to create a second unified driving safety field model represented by equation (74) based on vehicle j information and traffic environment information;
calculating the potential energy U _ji by the vehicle j for any position point i of the environment in which the vehicle j is located;
recognizing the driving risk to which point i is subject to the influence of vehicle j based on said potential energy _Uji ;

where x _ji represents the longitudinal distance from any point i in the environment of vehicle j, y _ji represents the lateral distance of vehicle j from point i, and r ₀ represents the represents the following distance, r _max represents the maximum separation of the vehicles in the free stream, r _min represents the minimum separation of the vehicles in the free stream, and E _j is the kinetic energy E _j,0 determined by the velocity v _j of the vehicle j. and the relative kinetic energy determined by a plurality of traffic environment factors, E _j,fac represents the kinetic energy E _j,0 and the relative kinetic energy determined by the traffic environment factors, the traffic environment factors being the road surface Kinetic energy corresponding to any of the speed of vehicle j and traffic environment factors, including friction coefficient, road curvature, road inclination, environment visibility, lane and road speed limit rules, if the factor is ignored is 0, _kx is the product of the speed of vehicle j and the longitudinal gradient adjustment coefficient of each traffic environment element, and kx _,fac is the speed of vehicle j and the longitudinal gradient adjustment factor of each traffic environment element. _ky is the product of the speed of vehicle j and the lateral slope adjustment coefficient of each traffic environment element; ky _,fac represents the speed of vehicle j and the lateral slope adjustment coefficient of each traffic environment element; , the speed of the vehicle j and the traffic environment element are ignored, the value of the gradient adjustment coefficient corresponding to the element is 1. A unified quantification method for comprehensively considered driving risk.

The relative kinetic energy E _{j,c determined} by the road curvature is given by Eq. The longitudinal gradient adjustment factor k _x,c is shown as equation (58), the road curvature lateral gradient adjustment factor k _y,c is shown as equation (59),

The relative kinetic energy _Ej,s determined by the road slope i _r is shown as equation (63), wherein the longitudinal gradient adjustment factor k _x,s of the road slope i _r and the lateral slope adjustment factor k x,s of the road slope i _r k _y,s are both 1,

The relative kinetic energy determined by the environment visibility is 0, the environment visibility longitudinal slope adjustment factor k _x,e is shown as equation (67), and the environment visibility lateral slope adjustment factor k _{y, e} is shown as equation (68),

where D _e represents the current environment visibility, D ₀ represents the visibility of the driver in a good traffic environment, and k _j,e represents a constant relating to the actual visual acuity of the driver. 3. The unified quantifying method of driving risk according to claim 1 or 2, which comprehensively considers each element of people-vehicle-road. The relative kinetic energy determined by the lane is zero, the lane pitch adjustment factor k _x,d is given as equation (36), and the lane side slope adjustment factor k _y,d is given by equation (37) shown as

where _l1 is half the vehicle length, _lw is one lane width, _l2 is half the vehicle width, and _lcj is the distance between the vehicle and the lane centerline. 3. The unified quantifying method of driving risk according to claim 1 or 2, wherein the driving risk is a distance, and the factors of people, vehicles, and roads are taken into consideration comprehensively. The relative kinetic energy E _jl determined by the road speed limit rule is shown as equation (42), the longitudinal gradient adjustment factor k _x,l of the road speed limit rule is shown as equation (43), and the road speed limit The lateral slope adjustment factor k _y,l of the rule is shown as equation (44),

where _mj represents the mass of vehicle j, _vl represents the road speed limit value, vl _,m represents the road minimum speed limit, vl _,h represents the road maximum speed limit, v _j,max represents the maximum speed at which vehicle j can travel, l ₁ is half the vehicle length, l _w is one lane width, l ₂ is half the vehicle width, l _cj is the distance between the vehicle and the lane centerline, according to claim 1 or 2, wherein the unified quantification method of driving risk comprehensively considers each element of people-vehicle-road. A unified quantification method for driving risk that comprehensively considers each element of people, vehicles, and roads,
Create an initial driving safety field model shown by the following formula,

where F _ji represents the risk field force by vehicle j for any position point i in the traffic environment in which vehicle j is located, and F _max is the maximum risk field force corresponding to vehicle j's velocity v _j . where E _j,0 represents the kinetic energy determined by the velocity of vehicle j, r _ji represents the distance between the center of mass of vehicle j and said position point i, r ₀ represents the driver's gaze radius for risk where r _min represents the distance between the center of mass of vehicle j and said position point i in the event of a collision, r _max represents the distance between the vehicles in free flow,
For r _min ≤ r _ji ≤ r _max , to determine the risk field force F _ji by vehicle j for any location point i of the traffic environment in which vehicle j is located, a first unified formula create a driving risk field model,

Or, if r _min ≦r _ji ≦r _max , to determine the risk potential energy U _ji by vehicle j for any location point i of the traffic environment in which vehicle j is located, a second unity given by create a realistic driving risk field model,

where x _ji represents the longitudinal distance between the center of mass of the vehicle j and the location point i, y _ji represents the lateral distance between the center of mass of the vehicle j and the location point i, and E _j is the motion is the sum of the energy E _j,0 and the relative kinetic energy determined based on a plurality of traffic environment factors, which are road surface friction coefficient, road curvature, road slope, environment visibility, lane and road speed limit rule, if the speed of vehicle j or any element of said traffic environment factors is ignored, then the value of kinetic energy corresponding to said speed or factor is 0 and k _x is the speed of vehicle j is the product of the longitudinal adjustment factor and the longitudinal adjustment factor of each said traffic environment element, _ky is the product of the lateral adjustment factor of the speed of vehicle j and the lateral adjustment factor of each said traffic environment element; if any factor of the speed of vehicle j or said traffic environment factor is ignored, the value of the longitudinal adjustment factor or lateral adjustment factor corresponding to said velocity or factor is 1;
For the risk at any position point i of the traffic environment or the risk of a vehicle at any position point i of the traffic environment, the risk to said position point i by all other vehicles within the r _max radius or the sum of the potential energies of risks to said position point i by all other vehicles within the r _max radius range.

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