Road path dynamic control method based on risk optimization

Abstract

The invention discloses a road path dynamic control method based on risk optimization. The method comprises the steps of 1, conflict risk calculation; 2, collision risk calculation; 3, limiting risks of lane lines; 4, risk fusion; and 5, calculating the optimal driving path of the vehicle. The risk is divided into three types of conflict risk, collision risk and marking limit risk, the risk size is combined with the risk occurrence probability, a risk fusion mechanism is constructed, the risk optimal point is calculated and fitted into a line, a driving track with the minimum risk is provided for the vehicle, and the risk risk is improved. And the safety and the passing efficiency of the road are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent traffic control, and in particular to a road path dynamic control method based on risk optimization. Background Art

[0002] In modern society, with the rapid increase in the number of vehicles, road traffic faces unprecedented challenges. Especially during peak hours in the morning and evening, the density of vehicles on the road increases significantly, and various risk factors also increase. These risk factors include but are not limited to conflict risk, collision risk and line restriction risk, which may accumulate rapidly in a short period of time, leading to traffic accidents and seriously affecting road traffic safety and traffic efficiency.

[0003] Existing research often focuses on the analysis of a single risk factor, such as conflict risk or collision risk, and rarely considers these risk factors in combination. This separate research approach ignores the interactions and influences between different risk factors, resulting in an incomplete and inaccurate assessment and control of road traffic risks. Many field theory-based methods have been introduced to intuitively express the magnitude of risk in the driving environment. However, this method directly expresses the magnitude of the risk without deeply calculating the probability of the risk actually occurring. At this point, the risk assessment model may show a risk area with high field strength, which intuitively gives people a sense of high risk. However, even if the field strength is large, if the probability of the risk occurring is actually low, then this high-risk area may not be as dangerous as it seems. In other words, a risk area with high field strength does not always mean a high probability of collision, because the actual probability of collision also depends on many other factors, such as the dynamic behavior of the vehicle and the complexity of the traffic environment.

[0004] In addition, existing traffic management methods often rely on traditional road markings to guide vehicles, which lack flexibility and adaptability. On roads with heavy traffic and high vehicle density, fixed marking restrictions often fail to meet actual traffic needs, leading to traffic congestion and safety hazards. Summary of the invention

[0005] The present invention overcomes the shortcomings of the prior art and proposes a road path dynamic control method based on risk optimization, in order to provide vehicles with a driving trajectory with the lowest risk, thereby improving road safety and traffic efficiency.

[0006] In order to achieve the above-mentioned object of the invention, the present invention adopts the following technical scheme:

[0007] The present invention provides a method for dynamic control of a road path based on risk optimization, which comprises the following steps:

[0008] Step 1: Establish a rectangular coordinate system of the road by taking the endpoint on the road boundary as the origin, the driving direction of the vehicle on the road as the x-axis, and the axis perpendicular to the driving direction of the vehicle as the y-axis;

[0009] The road is numbered from the inside to the outside according to the number of lanes, and the lane lines are marked as ,in, represents the bth lane line, and n represents the total number of lanes;

[0010] The ordinates of the n+1 lane lines are recorded as ;in, Indicates the bth lane line The vertical coordinate of the b lane line The vertical coordinate and the b+1th lane line The vertical coordinate Any coordinate between the ordinates is marked as any coordinate of lane b. ;

[0011] The risk factors on the road are divided into three categories: conflict risk, collision risk and lane line restriction risk;

[0012] Define any vehicle i and vehicle j, and , using the intelligent roadside detector set on the road to obtain the angle between vehicle i and vehicle j ; Get the size of the vehicle, and Represent the length and width of vehicle i respectively; get the coordinates of the midpoint of each vehicle, and Represent the midpoint coordinates of vehicle i and vehicle j respectively, and calculate the distance between vehicle i and vehicle j ; Get the steering angle of each vehicle, Indicates the steering angle of vehicle i; obtains the speed of vehicle i ; Get the speed difference between vehicle i and vehicle j ; Get the acceleration difference between vehicle i and vehicle j ; and count the total number of vehicles on the road c;

[0013] Step 2: Calculate the virtual volume of vehicle i ;

[0014] Step 3: Calculate the collision risk of vehicle i ;

[0015] Step 4: Calculate any coordinate on the road Risk of conflict ;

[0016] Step 5: Calculate any coordinate on the road Collision risk ;

[0017] Step 6: Divide the road into n+1 lanes to get n lanes, and calculate any coordinate on each lane The restricted risk of the lane line at the location, and the restricted risk of the lane line on each road constitutes the restricted risk of any coordinate on the road Lane restriction risk ;

[0018] Step 7: Calculate any coordinate on the road according to formula (30) Total risk ;

[0019] (30)

[0020] In formula (30), m represents the risk dimension index;

[0021] Step 8: Based on total risk , calculate the coordinates of the risk optimal point on the road, which is used to fit the optimal driving path of the vehicle.

[0022] The method for dynamic control of a road path based on risk optimization described in the present invention is also characterized in that step 2 includes the following steps:

[0023] Step 2.1: Calculate the directional effectiveness factor of vehicle i according to formula (1): ;

[0024] (1)

[0025] In formula (1), represents the underlying risk factor;

[0026] Step 2.2: Calculate the virtual volume of vehicle i according to formula (2): ;

[0027] (2)

[0028] In formula (2), represents the vehicle volume conversion factor, Represents the velocity influence weight factor in the virtual volume.

[0029] Further, step 3 includes the following steps:

[0030] Step 3.1: Calculate the steering angle of the left boundary of vehicle i according to formula (3): ;

[0031] (3)

[0032] In formula (3), A constant representing the uncertainty of the steering angle, and Indicates the left and right fluctuation range thresholds related to the steering angle;

[0033] Step 3.2: Calculate the radius of the left boundary of vehicle i according to formula (4): ;

[0034] (4)

[0035] Step 3.3: Calculate the steering angle of the right boundary of vehicle i according to formula (5): ;

[0036] (5)

[0037] Step 3.4: Calculate the radius of the left boundary of vehicle i according to formula (6): ;

[0038] (6)

[0039] Step 3.5: Calculate the path driving area of ​​vehicle i according to formula (7): ;

[0040] (7)

[0041] Step 3.6: Calculate the estimated left driving area of ​​vehicle i according to formula (8): ;

[0042] (8)

[0043] Step 3.7: Calculate the right estimated driving area of ​​vehicle i according to formula (9): ;

[0044] (9)

[0045] Step 3.8: Calculate the safe operating area of ​​vehicle i according to formula (10): ;

[0046] (10)

[0047] Step 3.9: Calculate the safe operating area of ​​vehicle j according to the process from step 3.1 to step 3.8 ;

[0048] Step 3.10: Calculate the intersection of the conflict areas of vehicle i and vehicle j according to formula (11): ;

[0049] (11)

[0050] Step 3.11: Calculate the collision probability of vehicle i according to formula (12): ;

[0051] (12)

[0052] In formula (12), represents the maximum intersection of the conflict areas of vehicle i and other vehicles;

[0053] Step 3.12: Calculate the collision risk field strength of vehicle i according to formula (13): ;

[0054] (13)

[0055] In formula (13), Indicates the impact weight factor of the conflict risk size, The speed impact weighting factor in conflict risk; is the virtual volume of vehicle j, The modulus represents the relative distance;

[0056] Step 3.13: Calculate the collision risk of vehicle i according to formula (14): ;

[0057] (14).

[0058] Further, step 4 includes the following steps:

[0059] Step 4.1: Calculate the coordinates of vehicle i on the road according to formula (15): Horizontal risk attenuation factor ;

[0060] (15)

[0061] In formula (15), It indicates the influence of the relative distance between other vehicles and vehicle i on the longitudinal risk. represents the speed of vehicle i The extent of impact on vertical risk;

[0062] Step 4.2: Calculate the coordinates of vehicle i on the road according to formula (16): Longitudinal risk attenuation factor ;

[0063] (16)

[0064] In formula (16), It indicates the influence of the relative distance between other vehicles and vehicle i on the lateral risk. represents the speed of vehicle i The degree of impact on horizontal risks;

[0065] Step 4.3: Calculate the coordinates of vehicle i on the road according to formula (17): The risk decay function at ;

[0066] (17)

[0067] Step 4.4: Calculate any coordinate on the road according to formula (18) Risk of conflict ;

[0068] (18).

[0069] Further, step 5 includes the following steps:

[0070] Step 5.1: Calculate the vehicle i in the time interval according to formula (19) Driving length within ;

[0071] (19)

[0072] Step 5.2: Calculate the vehicle i in the time interval according to formula (20) Driving range within ;

[0073] ϕ i ( D t) = [ x i , x i + L i ( D t) ] (20)

[0074] Step 5.3: Calculate the time interval of vehicle j according to the process from step 5.1 to step 5.2. Driving range within ϕ j ( D t) = [ x j , x j + L j ( D t) ] ;

[0075] Step 5.4: Calculate the time interval between vehicle i and vehicle j according to formula (21): Intersection of inner driving areas ;

[0076] (twenty one)

[0077] Step 5.5: Calculate the collision probability of vehicle i according to formula (22): ;

[0078] (twenty two)

[0079] In formula (22), Indicates that vehicle i and other vehicles are The maximum length of the travel area within the time period;

[0080] Step 5.6: Calculate the collision risk field strength of vehicle i according to formula (23): ;

[0081] (twenty three)

[0082] In formula (23), Indicates the impact weight factor of the collision risk. Indicates the acceleration impact weight factor in collision risk;

[0083] Step 5.7: Calculate the collision risk of vehicle i according to formula (24): ;

[0084] (twenty four)

[0085] Step 5.8: Calculate any coordinate on the road according to formula (25) Collision risk ;

[0086] (25).

[0087] Further, step 6 includes the following steps:

[0088] Step 6.1: Calculate the line limit risk according to formula (26) ;

[0089] (26)

[0090] In formula (26), represents a fixed risk value for road markings;

[0091] Step 6.2: Calculate any coordinate on the bth lane according to formula (27): The attenuation factor of the lane line restriction risk at ;

[0092] (27)

[0093] In formula (27), represents the risk diffusion weight of the marking line;

[0094] Step 6.3: Calculate any coordinate on the bth lane according to formula (28): The attenuation function of the lane line restriction risk at ;

[0095] (28)

[0096] Step 6.4: Calculate any coordinate on the bth lane according to formula (29): Lane markings limit risk ;

[0097] (29)

[0098] Step 6.5: Follow the process from step 6.1 to step 6.4 to calculate the coordinates of any lane. The lane line at each location limits the risk and constitutes the risk on the entire road .

[0099] Further, step 8 includes the following steps:

[0100] Step 8.1: Calculate any coordinate on the road according to formula (31): Total risk Gradient ;

[0101] (31)

[0102] Step 8.2: Define the number of iterations as ,initialization ;

[0103] Step 8.3, randomly select another coordinate on the road as the first The coordinates of the iteration ,in, , ;

[0104] Step 8.4: Calculate the The coordinates of the iteration ;

[0105] (32)

[0106] In formula (32), Indicates The step size of the iteration, Representing coordinates Total risk The gradient of

[0107] Step 8.5: When equation (33) holds, As the coordinates of the risk optimum;

[0108] (33)

[0109] In formula (33), represents the convergence threshold;

[0110] Step 8.6, after assigning k+1 to k, return to step 8.4 until the number of risk optimal point coordinates reaches p, obtain the coordinates of all risk optimal points and perform second-order polynomial fitting to obtain the curve equation with the minimum risk, which is the optimal driving path for vehicles on the road.

[0111] The electronic device of the present invention includes a memory and a processor, wherein the memory is used to store a program that supports the processor to execute the road path dynamic control method, and the processor is configured to execute the program stored in the memory.

[0112] The present invention provides a computer-readable storage medium, wherein a computer program is stored on the computer-readable storage medium, and the computer program executes the steps of the road path dynamic control method when the computer program is executed by a processor.

[0113] Compared with the prior art, the beneficial technical effects of the present invention are embodied in:

[0114] 1. The present invention divides risks into three types: conflict risk, collision risk and marking restriction risk, and combines the size of the risk with the probability of the risk occurring, thereby providing a comprehensive risk assessment model that is more in line with actual traffic scenarios, making the risk assessment results more comprehensive and accurate, thereby more truly reflecting the risk situations that may be encountered during road driving.

[0115] 2. The present invention proposes the concept of risk dimension index and constructs a risk fusion mechanism. In this way, the present invention can reveal the coupling relationship and interaction mechanism between different risk factors, so that risk assessment does not only stay in a single dimension, but forms a multi-dimensional and three-dimensional risk assessment system. This fusion mechanism makes risk assessment more in line with the actual situation and provides more scientific decision-making support for traffic management and road safety.

[0116] 3. The present invention takes into account the effective factor of the vehicle's direction and constructs a virtual volume index based on it. The introduction of virtual volume provides drivers with a more intuitive risk perception, which helps to improve driving safety and reduce the occurrence of traffic accidents.

[0117] 4. The present invention calculates the optimal risk point and fits it into a line, providing the vehicle with a driving trajectory with the lowest risk. This method not only considers the risk minimization of a single vehicle, but also considers the optimization of the entire traffic flow, so that the vehicle can travel on the optimal path while ensuring safety, thereby improving the safety and traffic efficiency of the road. BRIEF DESCRIPTION OF THE DRAWINGS

[0118] Figure 1 It is the overall flow chart of the present invention;

[0119] Figure 2 This is a cycle graph for calculating the optimal path points of the present invention. DETAILED DESCRIPTION

[0120] In this embodiment, Figure 1 As shown in the figure, a road path dynamic control method based on risk optimization is to divide the risk into three types: conflict risk, collision risk and line restriction risk, and combine the size of the risk with the probability of risk occurrence, and construct a risk fusion mechanism, calculate the optimal risk point, and fit it into a line, so as to provide the vehicle with the lowest risk driving trajectory. Specifically, the following steps are included:

[0121] Step 1: Establish a rectangular coordinate system of the road by taking the endpoint on the road boundary as the origin, the driving direction of the vehicle on the road as the x-axis, and the axis perpendicular to the driving direction of the vehicle as the y-axis;

[0122] The road is numbered from the inside to the outside according to the number of lanes, and the lane lines are marked as ,in, represents the bth lane line, and n represents the total number of lanes;

[0123] The ordinates of the n+1 lane lines are recorded as ;in, Indicates the bth lane line The vertical coordinate of the b lane line The vertical coordinate and the b+1th lane line The vertical coordinate Any coordinate between the ordinates is marked as any coordinate of lane b. ;

[0124] The risk factors on the road are divided into three categories: conflict risk, collision risk and lane line restriction risk;

[0125] Define any vehicle i and vehicle j, and , using the intelligent roadside detector set on the road to obtain the angle between vehicle i and vehicle j ; Get the size of the vehicle, and Represent the length and width of vehicle i respectively; get the coordinates of the midpoint of each vehicle, and Represent the midpoint coordinates of vehicle i and vehicle j respectively, and calculate the distance between vehicle i and vehicle j ; Get the steering angle of each vehicle, Indicates the steering angle of vehicle i; obtains the speed of vehicle i ; Get the speed difference between vehicle i and vehicle j ; Get the acceleration difference between vehicle i and vehicle j ; and count the total number of vehicles on the road c;

[0126] Step 2: Virtual volume calculation;

[0127] Step 2.1: Calculate the directional effectiveness factor of vehicle i according to formula (1): ;

[0128] (1)

[0129] In formula (1), represents the underlying risk factor;

[0130] Step 2.2: Calculate the virtual volume of vehicle i according to formula (2): ;

[0131] (2)

[0132] In formula (2), represents the vehicle volume conversion factor, Represents the velocity influence weight factor in the virtual volume;

[0133] Step 3: Calculate the conflict risk;

[0134] The conflict risk concerns the potential for conflicts with other vehicles or traffic participants that may occur when the vehicle attempts to change lanes. This risk can be calculated by considering the product of the conflict risk field strength and the probability of conflict occurrence.

[0135] Step 3.1: Calculate the steering angle of the left boundary of vehicle i according to formula (3): ;

[0136] (3)

[0137] In formula (3), A constant representing the uncertainty of the steering angle, and Indicates the left and right fluctuation range thresholds related to the steering angle;

[0138] Step 3.2: Calculate the radius of the left boundary of vehicle i according to formula (4): ;

[0139] (4)

[0140] Step 3.3: Calculate the steering angle of the right boundary of vehicle i according to formula (5): ;

[0141] (5)

[0142] Step 3.4: Calculate the radius of the left boundary of vehicle i according to formula (6): ;

[0143] (6)

[0144] Step 3.5: Calculate the path driving area of ​​vehicle i according to formula (7): ;

[0145] (7)

[0146] Step 3.6: Calculate the estimated left driving area of ​​vehicle i according to formula (8): ;

[0147] (8)

[0148] Step 3.7: Calculate the right estimated driving area of ​​vehicle i according to formula (9): ;

[0149] (9)

[0150] Step 3.8: Calculate the safe operating area of ​​vehicle i according to formula (10): ;

[0151] (10)

[0152] Step 3.9: Calculate the safe operating area of ​​vehicle j according to the process from step 3.1 to step 3.8 ;

[0153] Step 3.10: Calculate the intersection of the conflict areas of vehicle i and vehicle j according to formula (11): ;

[0154] (11)

[0155] Step 3.11: Calculate the collision probability of vehicle i according to formula (12): ;

[0156] (12)

[0157] In formula (12), represents the maximum intersection of the conflict areas of vehicle i and other vehicles;

[0158] Intuitively, the conflict level between vehicle i and vehicle j is related to the overlap of the trajectory distribution between the two vehicles. The overlap of the spatial trajectories of the two vehicles indicates the possibility of conflict between the two vehicles. When the trajectory distribution between the two vehicles does not overlap, the estimated conflict probability is 0, and the conflict risk field strength is also 0. The conflict probability increases with the increase of the overlap of the geometric spatial trajectories of the two vehicles.

[0159] Step 3.12: Calculate the collision risk field strength of vehicle i according to formula (13): ;

[0160] (13)

[0161] In formula (13), Indicates the impact weight factor of the conflict risk size, The speed impact weighting factor in conflict risk; is the virtual volume of vehicle j, The modulus represents the relative distance;

[0162] Step 3.13: Calculate the collision risk of vehicle i according to formula (14): ;

[0163] (14)

[0164] Step 3.14: Calculate the coordinates of vehicle i on the road according to formula (15): Horizontal risk attenuation factor ;

[0165] (15)

[0166] In formula (15), It indicates the influence of the relative distance between other vehicles and vehicle i on the longitudinal risk. represents the speed of vehicle i The extent of impact on vertical risk;

[0167] Step 3.15: Calculate the coordinates of vehicle i on the road according to formula (16): Longitudinal risk attenuation factor ;

[0168] (16)

[0169] In formula (16), It indicates the influence of the relative distance between other vehicles and vehicle i on the lateral risk. represents the speed of vehicle i The degree of impact on horizontal risks;

[0170] Step 3.16: Calculate the coordinates of vehicle i on the road according to formula (17): The risk decay function at ;

[0171] (17)

[0172] Step 3.17: Calculate any coordinate on the road according to formula (18) Risk of conflict ;

[0173] (18)

[0174] Step 4: Collision risk;

[0175] Step 4.1: Calculate the vehicle i in the time interval according to formula (19) Driving length within ;

[0176] (19)

[0177] Step 4.2: Calculate the vehicle i in the time interval according to formula (20) Driving range within ;

[0178] ϕ i ( D t) = [ x i , x i + L i ( D t) ] (20)

[0179] Step 4.3: Calculate the time interval of vehicle j according to the process from step 4.1 to step 4.2. Driving range within ϕ j ( D t) = [ x j , x j + L j ( D t) ] ;

[0180] Step 4.4: Calculate the time interval between vehicle i and vehicle j according to formula (21): Intersection of inner driving areas ;

[0181] (twenty one)

[0182] Step 4.5: Calculate the collision probability of vehicle i according to formula (22): ;

[0183] (twenty two)

[0184] In formula (22), Indicates that vehicle i and other vehicles are The maximum length of the travel area within the time period;

[0185] Step 4.6: Calculate the collision risk field strength of vehicle i according to formula (23): ;

[0186] (twenty three)

[0187] In formula (23), Indicates the impact weight factor of the collision risk. Indicates the acceleration impact weight factor in collision risk;

[0188] Step 4.7: Calculate the collision risk of vehicle i according to formula (24): ;

[0189] (twenty four)

[0190] Step 4.8: Calculate any coordinate on the road according to formula (25) Collision risk ;

[0191] (25)

[0192] Step 5: Divide the road into n+1 lanes to obtain n lanes, and calculate any coordinate on each lane The restricted risk of the lane line at the location, and the restricted risk of the lane line on each road constitutes the restricted risk of any coordinate on the road Lane restriction risk ;

[0193] In the traffic system, road markings define the physical boundaries and rules of vehicle driving with their fixedness. Their existence is constant and unchanging. Since these markings stipulate the path that vehicles should maintain, any behavior of driving on these road markings will generate different degrees of marking restriction risks. Given the invariance of road markings, we believe that as long as these markings exist, the occurrence of marking restriction risks is certain, and its probability of occurrence is 1.

[0194] Step 5.1: Calculate the line limit risk according to formula (26) ;

[0195] (26)

[0196] In formula (26), represents a fixed risk value for road markings;

[0197] Step 5.2: Calculate any coordinate on the bth lane according to formula (27): The attenuation factor of the lane line restriction risk at ;

[0198] (27)

[0199] In formula (27), represents the risk diffusion weight of the marking line;

[0200] Step 5.3: Calculate any coordinate on the bth lane according to formula (28): The attenuation function of the lane line restriction risk at ;

[0201] (28)

[0202] Step 5.4: Calculate any coordinate on the bth lane according to formula (29): Lane markings limit risk ;

[0203] (29)

[0204] Step 5.5: Follow the process from step 5.1 to step 5.4 to calculate the coordinates of any lane. The lane line at each location limits the risk and constitutes the risk on the entire road ;

[0205] Step 6: Calculate any coordinate on the road according to formula (30) Total risk ;

[0206] (30)

[0207] In formula (30), m represents the risk dimension index; m = 1 means that the risk is in one-dimensional space (linear superposition), that is, all risk factors are considered equally; m = 2 means that the risk is in two-dimensional space (square superposition), that is, the risk assessment is more affected by risk factors that are close or have a greater direct impact; m = ∞ means that the risk assessment only considers the most direct and adjacent risk sources, ignoring all other risk factors. By carefully selecting the value of m, the formula can provide a comprehensive risk assessment under various risk interweaving conditions according to different traffic environments and driving scenarios, ensuring that the vehicle can take the most appropriate action.

[0208] Step 7: Calculate the optimal driving path for the vehicle; Figure 2 As shown, it is a cycle diagram for calculating the optimal path points for vehicle travel;

[0209] Step 7.1: Calculate any coordinate on the road according to formula (31): Total risk Gradient ;

[0210] (31)

[0211] Step 7.2: Define the number of iterations as ,initialization ;

[0212] Step 7.3, randomly select another coordinate on the road as the first The coordinates of the iteration ,in, , ;

[0213] Step 7.4: Calculate the The coordinates of the iteration ;

[0214] (32)

[0215] In formula (32), Indicates The step size of the iteration, Representing coordinates Total risk The gradient of

[0216] Step 7.5: When equation (33) holds, As the coordinates of the risk optimum;

[0217] (33)

[0218] In formula (33), represents the convergence threshold;

[0219] Step 7.6, after assigning k+1 to k, return to step 7.4 until the number of risk optimal point coordinates reaches p, obtain the coordinates of all risk optimal points and perform second-order polynomial fitting to obtain the curve equation with the minimum risk, which is the optimal driving path for vehicles on the road.

[0220] In this embodiment, an electronic device includes a memory and a processor, wherein the memory is used to store a program that supports the processor to execute the above method, and the processor is configured to execute the program stored in the memory.

[0221] In this embodiment, a computer-readable storage medium stores a computer program on the computer-readable storage medium, and the computer program executes the steps of the above method when executed by a processor.

Claims

1. A road path dynamic control method based on risk optimization, characterized in that: The following steps are involved: Step 1: Establish a rectangular coordinate system of the road by taking the endpoint on the road boundary as the origin, the driving direction of the vehicle on the road as the x-axis, and the axis perpendicular to the driving direction of the vehicle as the y-axis; The roads are numbered from the inside to the outside according to the number of lanes, and the lane lines are marked as ,in, represents the bth lane line, and n represents the total number of lanes; The ordinates of the n+1 lane lines are recorded as ;in, Indicates the bth lane line The vertical coordinate of the b lane line The vertical coordinate and the b+1th lane line The vertical coordinate Any coordinate between the ordinates is marked as any coordinate of lane b. ; The risk factors on the road are divided into three categories: conflict risk, collision risk and lane line restriction risk; Define any vehicle i and vehicle j, and , using the intelligent roadside detector set on the road to obtain the angle between vehicle i and vehicle j ; Get the size of the vehicle, and Represent the length and width of vehicle i respectively; get the coordinates of the midpoint of each vehicle, and Represent the midpoint coordinates of vehicle i and vehicle j respectively, and calculate the distance between vehicle i and vehicle j ; Get the steering angle of each vehicle, Indicates the steering angle of vehicle i; obtains the speed of vehicle i ; Get the speed difference between vehicle i and vehicle j ; Get the acceleration difference between vehicle i and vehicle j ; and count the total number of vehicles on the road c; Step 2: Calculate the virtual volume of vehicle i ; Step 3: Calculate the collision risk of vehicle i ; Step 4: Calculate any coordinate on the road Risk of conflict ; Step 5: Calculate any coordinate on the road Collision risk ; Step 6: Divide the road into n+1 lanes to get n lanes, and calculate any coordinate on each lane The restricted risk of the lane line at the location, and the restricted risk of the lane line on each road constitutes the restricted risk of any coordinate on the road Lane restriction risk ; Step 7: Calculate any coordinate on the road according to formula (30) Total risk ; (30) In formula (30), m represents the risk dimension index; Step 8: Based on total risk , calculate the coordinates of the risk optimal point on the road, which is used to fit the optimal driving path of the vehicle.

2. A road path dynamic control method based on risk optimization according to claim 1, characterized in that: Step 2 includes the following steps: Step 2.1: Calculate the directional effectiveness factor of vehicle i according to formula (1): ; (1) In formula (1), represents the underlying risk factor; Step 2.2: Calculate the virtual volume of vehicle i according to formula (2): ; (2) In formula (2), represents the vehicle volume conversion factor, Represents the velocity influence weight factor in the virtual volume.

3. The method for dynamic control of road paths based on risk optimization according to claim 2, characterized in that: Step 3 includes the following steps: Step 3.1: Calculate the steering angle of the left boundary of vehicle i according to formula (3): ; (3) In formula (3), A constant representing the uncertainty of the steering angle, and Indicates the left and right fluctuation range thresholds related to the steering angle; Step 3.2: Calculate the radius of the left boundary of vehicle i according to formula (4): ; (4) Step 3.3: Calculate the steering angle of the right boundary of vehicle i according to formula (5): ; (5) Step 3.4: Calculate the radius of the left boundary of vehicle i according to formula (6): ; (6) Step 3.5: Calculate the path driving area of ​​vehicle i according to formula (7): ; (7) Step 3.6: Calculate the estimated left driving area of ​​vehicle i according to formula (8): ; (8) Step 3.7: Calculate the right estimated driving area of ​​vehicle i according to formula (9): ; (9) Step 3.8: Calculate the safe operating area of ​​vehicle i according to formula (10): ; (10) Step 3.9: Calculate the safe operating area of ​​vehicle j according to the process from step 3.1 to step 3.8 ; Step 3.10: Calculate the intersection of the conflict areas of vehicle i and vehicle j according to formula (11): ; (11) Step 3.11: Calculate the collision probability of vehicle i according to formula (12): ; (12) In formula (12), represents the maximum intersection of the conflict areas of vehicle i and other vehicles; Step 3.12: Calculate the collision risk field strength of vehicle i according to formula (13): ; (13) In formula (13), Indicates the impact weight factor of the conflict risk size, The speed impact weighting factor in conflict risk; is the virtual volume of vehicle j, The modulus represents the relative distance; Step 3.13: Calculate the collision risk of vehicle i according to formula (14): ; (14)。 4. The method for dynamic control of road paths based on risk optimization according to claim 3 is characterized in that: Step 4 includes the following steps: Step 4.1: Calculate the coordinates of vehicle i on the road according to formula (15): Horizontal risk attenuation factor ; (15) In formula (15), It indicates the influence of the relative distance between other vehicles and vehicle i on the longitudinal risk. represents the speed of vehicle i The extent of impact on vertical risk; Step 4.2: Calculate the coordinates of vehicle i on the road according to formula (16): Longitudinal risk attenuation factor ; (16) In formula (16), It indicates the influence of the relative distance between other vehicles and vehicle i on the lateral risk. represents the speed of vehicle i The degree of impact on horizontal risks; Step 4.3: Calculate the coordinates of vehicle i on the road according to formula (17): The risk decay function at ; (17) Step 4.4: Calculate any coordinate on the road according to formula (18) Risk of conflict ; (18)。 5. The method for dynamic control of road paths based on risk optimization according to claim 4, characterized in that: Step 5 includes the following steps: Step 5.1: Calculate the vehicle i in the time interval according to formula (19) Driving length within ; (19) Step 5.2: Calculate the vehicle i in the time interval according to formula (20) Driving range within ; (20) Step 5.3: Calculate the time interval of vehicle j according to the process from step 5.1 to step 5.

2. Driving range within ; Step 5.4: Calculate the time interval between vehicle i and vehicle j according to formula (21): Intersection of inner driving areas ; (21) Step 5.5: Calculate the collision probability of vehicle i according to formula (22): ; (22) In formula (22), Indicates that vehicle i and other vehicles are The maximum length of the travel area within the time period; Step 5.6: Calculate the collision risk field strength of vehicle i according to formula (23): ; (23) In formula (23), Indicates the impact weight factor of the collision risk. Indicates the acceleration impact weight factor in collision risk; Step 5.7: Calculate the collision risk of vehicle i according to formula (24): ; (24) Step 5.8: Calculate any coordinate on the road according to formula (25) Collision risk ; (25)。 6. A road path dynamic control method based on risk optimization according to claim 5, characterized in that: Step 6 includes the following steps: Step 6.1: Calculate the line limit risk according to formula (26) ; (26) In formula (26), represents a fixed risk value for road markings; Step 6.2: Calculate any coordinate on the bth lane according to formula (27): The attenuation factor of the lane line restriction risk at ; (27) In formula (27), represents the risk diffusion weight of the marking line; Step 6.3: Calculate any coordinate on the bth lane according to formula (28): The attenuation function of the lane line restriction risk at ; (28) Step 6.4: Calculate any coordinate on the bth lane according to formula (29): Lane markings limit risk ; (29) Step 6.5: Follow the process from step 6.1 to step 6.4 to calculate the coordinates of any lane. The lane line at each location limits the risk and constitutes the risk on the entire road .

7. The method for dynamic control of road paths based on risk optimization according to claim 6, characterized in that: Step 8 includes the following steps: Step 8.1: Calculate any coordinate on the road according to formula (31): Total risk Gradient ; (31) Step 8.2: Define the number of iterations as ,initialization ; Step 8.3, randomly select another coordinate on the road as the first The coordinates of the iteration ,in, , ; Step 8.4: Calculate the The coordinates of the iteration ; (32) In formula (32), Indicates The step size of the iteration, Representing coordinates Total risk The gradient of Step 8.5: When equation (33) holds, As the coordinates of the risk optimum; (33) In formula (33), represents the convergence threshold; Step 8.6, after assigning k+1 to k, return to step 8.4 until the number of risk optimal point coordinates reaches p, obtain the coordinates of all risk optimal points and perform second-order polynomial fitting to obtain the curve equation with the minimum risk, which is the optimal driving path for vehicles on the road.

8. An electronic device, comprising a memory and a processor, characterized in that: The memory is used to store a program that supports the processor to execute the road path dynamic control method according to any one of claims 1 to 7, and the processor is configured to execute the program stored in the memory.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the road path dynamic control method according to any one of claims 1 to 7 are executed.

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