A method for establishing a safe potential field car-following model for intelligent vehicles based on road longitudinal sections

Abstract

The present invention discloses a method for establishing a safe potential field following model for intelligent vehicles based on a road longitudinal section, and the steps are as follows: obtaining the geometric linear information of the road longitudinal section, the information of the autonomous driving vehicle and the information of the vehicle ahead in the traffic flow; establishing the physical and mechanical functions of the autonomous driving vehicle on the road longitudinal section linear shape; constructing the potential field model of the vehicle ahead in the two-dimensional plane of the road longitudinal section according to the safety potential field theory; obtaining the speed and acceleration of the autonomous driving vehicle and the vehicle ahead with different road longitudinal section linear shapes through the physical and mechanical functions and superimposing the vehicle potential fields, and finally establishing a safe potential field following model for the autonomous driving vehicle. The present invention can effectively evaluate the risk of autonomous driving vehicles following driving under different road longitudinal section linear conditions, and conduct safety hazard inspections for the promotion of autonomous driving vehicles and the actual operation of existing road infrastructure.

Description

Technical Field

[0001] The invention belongs to the technical field of road safety evaluation, and in particular relates to a method for establishing a safety potential field following model of an intelligent vehicle based on a road longitudinal section. Background Art

[0002] In a complex traffic system, facing a changing road traffic environment, vehicles on the road make different driving behavior responses based on the traffic information they receive. The difference in driving behavior of different vehicles is usually the main factor affecting road traffic safety and road traffic efficiency. During the driving process, vehicles mainly choose different driving behaviors based on their own expected speed and the safe distance between them and surrounding vehicles. Among them, car following and lane changing are two basic driving behaviors during vehicle driving. Therefore, the car following model and lane changing model in traditional traffic flow theory are to achieve a detailed description of vehicle car following and lane changing behaviors by analyzing the longitudinal and lateral interactions of vehicles during road driving. During the driving process of an autonomous vehicle, the autonomous vehicle makes the choice of car following or lane changing based on its own expected speed and the information of surrounding vehicles (position, speed, etc.). Compared with the car following behavior of a driver-driven vehicle, its car following behavior process is more complicated, the running trajectory of surrounding vehicles has a more significant impact, and its safety research significance is more obvious. In recent years, the development of autonomous driving has provided new opportunities and challenges for traffic management and control. Self-driving cars can achieve information exchange between vehicles and complete car-following behavior through on-board sensors, controllers, and actuators. However, considering the changes in relevant road linear conditions and environment, as well as the interaction between intelligent networked vehicles and traffic flow, the safety of self-driving vehicles on the road is also the research object of many scholars.

[0003] At present, there are relatively few studies on the following behavior of autonomous driving vehicles based on road alignment at home and abroad. In order to make autonomous driving vehicles more adaptable to road alignment and passengers have a more comfortable riding experience, it is necessary to make the road alignment more adaptable to the following behavior of autonomous driving vehicles. The research of this project will have a far-reaching impact on the future implementation of autonomous driving. Summary of the invention

[0004] The present invention provides a method for establishing a smart vehicle safety potential field following model based on road longitudinal sections, which is helpful to evaluate the driving risk of the following behavior of an autonomous driving vehicle under different road longitudinal section linear conditions, provides a theoretical reference for the design and optimization of the early warning function of a conditional autonomous driving system, and conducts safety hazard inspections for function testing of the conditional autonomous driving system and actual operation in existing road infrastructure.

[0005] In order to solve the above technical problems, the present invention adopts the following technical solutions:

[0006] A method for establishing a safe potential field following model for an intelligent vehicle based on a road longitudinal section, for the following behavior of an autonomous driving vehicle, based on the road longitudinal section linear condition combined with the vehicle potential field, performs the following steps to construct an autonomous driving vehicle following model under the conditions of a convex vertical curve road longitudinal section linear condition or a concave vertical curve road longitudinal section linear condition combined with the vehicle potential field:

[0007] Step A: Acquire driving condition information of the autonomous driving vehicle in the following behavior under the current road longitudinal profile alignment condition, including road longitudinal profile alignment information, front vehicle information, and autonomous driving vehicle information;

[0008] Step B: Based on the road longitudinal section alignment information, determine whether the current road longitudinal section alignment condition is a convex vertical curve or a concave vertical curve, and then construct a two-dimensional space coordinate system corresponding to the convex vertical curve or the concave vertical curve, and depict the autonomous driving vehicle information and the front vehicle information on the coordinate system;

[0009] Step C: Based on the current road longitudinal profile conditions and combined with the driving condition information of the autonomous driving vehicle in the car-following behavior, a physical and mechanical model of the autonomous driving vehicle's car-following behavior is established, thereby obtaining the combined acceleration of the autonomous driving vehicle in the straight line direction with the vehicle in front of it under the current road longitudinal profile conditions;

[0010] Step D: Based on the vehicle safety potential field theory and the distance between the autonomous driving vehicle and the vehicle ahead in the two-dimensional space coordinate system, a vehicle potential field model of the vehicle ahead is constructed;

[0011] Step E: Based on the current expected acceleration of the vehicle, combined with the combined acceleration of the autonomous driving vehicle in the straight direction with the vehicle in front of it under the current road longitudinal profile conditions, and the vehicle potential field model of the vehicle in front, a following model of the autonomous driving vehicle combined with the vehicle potential field under the longitudinal profile conditions of a convex vertical curve road or a concave vertical curve road is constructed.

[0012] As a preferred technical solution of the present invention, in step A, the road longitudinal section linear information includes the longitudinal slope size on both sides of the road longitudinal section slope change point; the front vehicle information includes the traction size of the front vehicle and the position of the front vehicle; the automatic driving vehicle information includes the traction size of the automatic driving vehicle, the position of the automatic driving vehicle, and the distance between the center of mass of the automatic driving vehicle and the center of mass of the front vehicle.

[0013] As a preferred technical solution of the present invention, in step B, based on the road longitudinal section linear information, the following steps are specifically performed to establish a two-dimensional space coordinate system, and to depict the autonomous driving vehicle information and the front vehicle information on the coordinate system:

[0014] Step B1: Based on the road longitudinal section linear information, that is, the longitudinal slopes on both sides of the road longitudinal section slope change point, the linear condition of the road longitudinal section where the autonomous driving vehicle is currently located is obtained as a convex vertical curve or a concave vertical curve, and a two-dimensional space coordinate system is established for the convex vertical curve of the road longitudinal section or the concave vertical curve of the road longitudinal section. The two-dimensional space coordinate system corresponding to the convex vertical curve takes the starting point of the vertical curve as the coordinate origin; in the two-dimensional space coordinate system of the concave vertical curve, the starting point of the vertical curve is (0, R)

[0015] Where R is the radius of the vertical curve;

[0016] Step B2: Based on the two-dimensional spatial coordinate system of the linear condition of the current road longitudinal section, the front vehicle information including the front vehicle position is depicted on the coordinate axis; the autonomous driving vehicle information includes the position of the autonomous driving vehicle and the straight-line distance between the center of mass of the autonomous driving vehicle and the center of mass of the front vehicle.

[0017] As a preferred technical solution of the present invention, in step C, based on the current road longitudinal section linear condition and combined with the driving condition information of the autonomous driving vehicle in the car-following behavior, the following steps are specifically performed to establish a physical and mechanical model of the current autonomous driving vehicle's car-following behavior, and then obtain the combined acceleration of the autonomous driving vehicle in the straight line direction with the vehicle in front of it under the current road longitudinal section linear condition:

[0018] Step C1: When the linear condition of the current road longitudinal section is a convex vertical curve, execute steps C1.1-C1.2 to establish a physical and mechanical model of the autonomous driving vehicle, and then obtain the combined acceleration of the autonomous driving vehicle in the straight line direction with the vehicle in front of it when the linear condition of the current road longitudinal section is a convex vertical curve:

[0019] Step C1.1: Based on the mechanical balance of the two-dimensional space plane, the physical mechanical model of the autonomous driving vehicle is constructed through the following mechanical function expression to obtain the acceleration a of the autonomous driving vehicle B in the driving direction: B :

[0020] F1±M B gsinθ=M B a B

[0021]

[0022] Where F1 is the traction of the autonomous vehicle B; M B is the gravity of the autonomous vehicle B; a B is the acceleration of the autonomous driving vehicle B in the driving direction; θ is the angle between the gravity direction of the autonomous driving vehicle B and the line connecting the center of mass of the autonomous driving vehicle B and the center of the vertical curve;

[0023] Through the following mechanical function expression, the physical mechanical model of the front vehicle is constructed to obtain the acceleration a of the front vehicle A in the driving direction: A :

[0024] F1′±M A gsinμ=M A a A

[0025]

[0026] Where F1′ is the traction of the vehicle A in front; M A is the gravity of the vehicle A in front; a A is the acceleration of the front vehicle A in the driving direction; μ is the angle between the gravity direction of the front vehicle and the line connecting the center of mass of the front vehicle and the center of the vertical curve;

[0027] Step C1.2: Based on the acceleration a of the autonomous driving vehicle in its direction of travel B , combined with the position of the autonomous driving vehicle and the vehicle ahead, the total acceleration a of the autonomous driving vehicle in the direction of the straight-line distance between it and the vehicle ahead is obtained when the longitudinal section of the road ahead is a convex vertical curve 合 :

[0028] when hour:

[0029]

[0030] when hour:

[0031]

[0032] In the formula, is the angle between the driving direction of the autonomous driving vehicle B and the line connecting the center of mass of the autonomous driving vehicle and the vehicle in front;

[0033] Step C2: When the linear condition of the current road longitudinal section is a concave vertical curve, execute steps C2.1-C2.2 to establish a physical and mechanical model of the autonomous driving vehicle, and then obtain the combined acceleration of the autonomous driving vehicle in the straight line direction with the vehicle in front of it when the linear condition of the current road longitudinal section is a concave vertical curve:

[0034] Step C2.1: Based on the mechanical balance requirements of the two-dimensional space plane, the physical mechanical model of the autonomous driving vehicle is constructed through the following mechanical function expression to obtain the acceleration a of the autonomous driving vehicle B in the driving direction: B ′:

[0035] F1±M B gsinθ=M B a B

[0036]

[0037] Where F1 is the traction of the autonomous vehicle B; M B is the gravity of the autonomous vehicle B; a B is the acceleration of the autonomous driving vehicle B in the driving direction; θ is the angle between the center of mass of the autonomous driving vehicle and the center of the vertical curve in the direction of gravity of the autonomous driving vehicle;

[0038] Through the following mechanical function expression, the physical mechanical model of the front vehicle is constructed to obtain the acceleration a of the front vehicle A in the driving direction: A :

[0039] F1′±M A gsinμ=M A a A

[0040]

[0041] Where F1′ is the traction of the vehicle A in front; M A is the gravity of the vehicle A in front; a A is the acceleration of the front vehicle A in the driving direction; μ is the angle between the gravity direction of the front vehicle and the line connecting the center of mass of the front vehicle and the center of the vertical curve;

[0042] Step C2.2: Based on the acceleration a′ of the autonomous driving vehicle in the driving direction B , combined with the position of the autonomous driving vehicle and the vehicle ahead, the total acceleration a of the autonomous driving vehicle in the straight-line distance direction from the vehicle ahead is obtained when the longitudinal section of the road ahead is a concave vertical curve 合 ′:

[0043] when hour:

[0044]

[0045] when hour:

[0046]

[0047] In the formula, It is the angle between the driving direction of the autonomous driving vehicle B and the line connecting the center of mass of the autonomous driving vehicle and the vehicle in front.

[0048] As a preferred technical solution of the present invention, in the step D, the following steps are performed to construct a vehicle potential field model of the vehicle ahead;

[0049] Step D1: Based on the distance between two points in the two-dimensional space coordinate system, the distance between the autonomous driving vehicle and the vehicle in front in the two-dimensional space is constructed by the following formula;

[0050]

[0051]

[0052] Where |k′| is the distance between the autonomous driving vehicle and the vehicle in front, (x0, y0) is the position coordinate of the center of mass of the autonomous driving vehicle in the two-dimensional space coordinate system, a is a preset parameter related to speed; τ is the preset critical threshold of the safety distance corresponding to the vertical curve linear condition; v is the speed of the autonomous driving vehicle; σ is the steering angle when the vehicle in front turns; (x * ,y * ) is the corresponding deflection value of the original coordinates (x, y) of the position of the center of mass of the front vehicle in the two-dimensional space coordinate system after turning;

[0053] Step D2: The distance between the autonomous driving vehicle and the vehicle in front in the two-dimensional space is combined with the safety potential field theory to construct a vehicle potential field model of the vehicle in front, as shown below:

[0054]

[0055] In the formula, λ and β1 are preset coefficients; M A is the mass of the vehicle A in front; a A is the acceleration of the front vehicle A in the direction of travel; It is the angle between the line connecting the two vehicle centroids and the driving direction of the autonomous driving vehicle.

[0056] As a preferred technical solution of the present invention, in step E, based on the current vehicle expected acceleration, combined with the acceleration of the autonomous driving vehicle in the straight direction with the vehicle in front of it under the current road longitudinal profile conditions, and the vehicle potential field model of the vehicle in front, the following steps are specifically performed to construct an autonomous driving vehicle following model combined with the vehicle potential field under the convex vertical curve road longitudinal profile conditions or the concave vertical curve road longitudinal profile conditions:

[0057] Step E1: Based on the potential field model of the vehicle ahead, obtain the field force F of the potential field of the vehicle ahead that the autonomous driving vehicle is subjected to AB , as shown below:

[0058]

[0059] in,

[0060] In the formula, β2 is the preset coefficient, v B is the speed of the autonomous vehicle B.

[0061] Step E2: Based on the field force of the potential field of the vehicle in front of the autonomous driving vehicle, obtain the field force F of the autonomous driving vehicle B AB The acceleration a generated by the action AB , as shown below:

[0062]

[0063] Step E3: Based on the field force F of the autonomous driving vehicle B AB The acceleration a generated by the action AB , combined with the total acceleration of the autonomous driving vehicle in the straight line direction with the vehicle in front of it under the current road longitudinal section line condition, the acceleration of the autonomous driving vehicle in the driving direction is obtained:

[0064]

[0065]

[0066] Where: a 合 is the total acceleration of the autonomous driving vehicle in the straight line direction with the vehicle in front of it under the condition of a convex vertical curve; a 合 ′ is the total acceleration of the autonomous driving vehicle in the concave vertical curve and the vehicle in front of it in the straight line direction; is the angle between the driving direction of the autonomous driving vehicle B and the line connecting the center of mass of the autonomous driving vehicle and the vehicle in front; is the angle between the driving direction of the front vehicle and the line connecting the centers of mass of the two vehicles; d AB is the distance between the center of mass of the autonomous driving vehicle and the vehicle in front; g is the reduction coefficient of the acceleration generated by the potential field force as the distance changes, a 场 is the acceleration of the autonomous driving vehicle in the driving direction when the current road longitudinal section line condition is a convex vertical curve; a 场 ′ is the acceleration of the autonomous driving vehicle in the driving direction when the current road longitudinal section alignment condition is a concave vertical curve;

[0067] Step E4: In summary, an autonomous driving vehicle following model combined with a vehicle potential field under the longitudinal profile alignment condition of a convex vertical curve road or the longitudinal profile alignment condition of a concave vertical curve road is constructed, and the formula is as follows:

[0068]

[0069] Where a1 = a max tanh[δ(v0 (a) -v B )],

[0070] Where a1 is the expected acceleration of the autonomous vehicle; a maxis the maximum acceleration allowed by the autonomous vehicle; δ is the coefficient value of the difference between the current speed of the vehicle and the expected speed; v0 (a) is the expected speed of the autonomous vehicle under the current acceleration condition, v B For self-driving vehicles.

[0071] A device for establishing a method for establishing a safe potential field following model of an intelligent vehicle based on a road longitudinal section includes a memory and a processor, wherein the memory stores a computer program, and is characterized in that the method for establishing a safe potential field following model of an intelligent vehicle based on a road longitudinal section is implemented when the processor executes the computer program.

[0072] A computer-readable storage medium having a computer program stored thereon, characterized in that when the computer program is executed by a processor, the method for establishing a safe potential field following model of an intelligent vehicle based on a road longitudinal section is implemented.

[0073] The beneficial effects of the present invention are as follows: the present invention provides a method for establishing a safety potential field following model for intelligent vehicles based on a road longitudinal section. Starting from the perspective of the impact of traffic flow conditions and road conditions on vehicle safety in traffic flow, the following behavior of a single autonomous driving vehicle on a single lane at a road longitudinal section is considered in combination with the safety potential field theory, and the physical and mechanical functions of the autonomous driving vehicle are established. The potential field model of the autonomous driving vehicle under the safety potential field theory is used to evaluate the speed and acceleration of the following behavior of the autonomous driving vehicle, thereby obtaining a complete autonomous driving vehicle following model under the safety potential field theory, providing a theoretical reference for the safety issues of autonomous driving vehicles in actual road scenarios. At the same time, the following risk of autonomous driving vehicles is obtained by using the method disclosed in the present invention to conduct safety hazard inspections for the promotion of autonomous driving vehicles and the actual operation of existing road infrastructure. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] Figure 1 It is a flow chart of a method for establishing a safe potential field car-following model of an intelligent vehicle based on a road longitudinal section according to the present invention;

[0075] Figure 2 It is a schematic diagram of the physical mechanical functions of the car-following behavior of the autonomous driving vehicle of the present invention under the condition of a convex vertical curve in the longitudinal section of the road;

[0076] Figure 3 It is a schematic diagram of the physical and mechanical functions of the following behavior of the autonomous driving vehicle of the present invention under the condition of a concave vertical curve in the longitudinal section of the road. DETAILED DESCRIPTION

[0077] The present invention will be further described below in conjunction with the accompanying drawings. The following embodiments may enable those skilled in the art to more fully understand the present invention, but are not intended to limit the present invention in any way.

[0078] This embodiment proposes a method for establishing a safety potential field following model for intelligent vehicles based on road longitudinal sections. It studies the following model of autonomous driving vehicles under two classic longitudinal section linear conditions. The following model is helpful to evaluate the driving risk of following behavior of autonomous driving vehicles under different road longitudinal section linear conditions, provide theoretical reference for the design and optimization of the early warning function of the conditional autonomous driving system, and conduct safety hazard inspection for the function testing of the conditional autonomous driving system and the actual operation of the existing road infrastructure.

[0079] like Figure 1 As shown, a method for establishing a safe potential field following model for an intelligent vehicle based on a road longitudinal section is provided. For the following behavior of an autonomous driving vehicle, the following steps are performed based on the road longitudinal section linear conditions combined with the vehicle potential field to construct an autonomous driving vehicle following model under the convex vertical curve road longitudinal section linear conditions or the concave vertical curve road longitudinal section linear conditions combined with the vehicle potential field.

[0080] Step A: Obtain driving condition information of the autonomous driving vehicle in the following behavior under the current road longitudinal profile conditions, including road longitudinal profile information, front vehicle information, and autonomous driving vehicle information.

[0081] In step A, the road longitudinal section linear information includes the longitudinal slope size on both sides of the road longitudinal section slope change point, that is, the longitudinal slope value; the front vehicle information includes the traction size of the front vehicle, the position of the front vehicle, and the distance between the front vehicle and the starting point of the ramp; the autonomous driving vehicle information includes the traction size of the autonomous driving vehicle, the position of the autonomous driving vehicle, and the distance between the center of mass of the autonomous driving vehicle and the center of mass of the front vehicle. The front vehicle in this embodiment is a vehicle that is in the same lane as the autonomous driving vehicle and is located in front of the autonomous driving vehicle in the driving direction. Ignoring the wheel size and only considering the center of mass position of the vehicle shape, the center of gravity and the center of mass coincide.

[0082] Step B: Based on the road longitudinal section alignment information, determine whether the current road longitudinal section alignment condition is a convex vertical curve or a concave vertical curve, and then construct a two-dimensional space coordinate system corresponding to the convex vertical curve or the concave vertical curve, and depict the autonomous driving vehicle information and the vehicle ahead information on the coordinate system. That is, the autonomous driving vehicle information and the vehicle ahead information are marked in real time on the coordinate system.

[0083] In the step B, based on the road longitudinal section linear information, the following steps are specifically performed to establish a two-dimensional space coordinate system, and to depict the autonomous driving vehicle information and the front vehicle information on the coordinate system:

[0084] Step B1: Based on the road longitudinal section linear information, that is, the longitudinal slopes on both sides of the road longitudinal section slope change point, the linear condition of the road longitudinal section where the autonomous driving vehicle is currently located is obtained as a convex vertical curve or a concave vertical curve, and the radius of the road longitudinal section vertical curve, and a two-dimensional space coordinate system is established for the convex vertical curve of the road longitudinal section or the concave vertical curve of the road longitudinal section. The two-dimensional space coordinate system corresponding to the convex vertical curve takes the starting point of the vertical curve as the coordinate origin, such as Figure 2 As shown; in the two-dimensional space coordinate system of the concave vertical curve, the starting point of the vertical curve is (0, R), where R is the radius of the vertical curve, and 0 is the horizontal coordinate of the starting point of the concave vertical curve, such as Figure 3 As shown. And the distance information between the center of mass of the two vehicles is obtained through the sensors on the autonomous driving vehicle.

[0085] Step B2: Based on the two-dimensional spatial coordinate system of the linear condition of the current road longitudinal section, the front vehicle information including the front vehicle position is depicted on the coordinate axis; the autonomous driving vehicle information includes the position of the autonomous driving vehicle and the straight-line distance between the center of mass of the autonomous driving vehicle and the center of mass of the front vehicle. In the figure, vehicle A is the front vehicle, vehicle B is the autonomous driving vehicle, and d AB is the straight-line distance between the front vehicle and the center of mass of the autonomous driving vehicle.

[0086] Step C: Based on the current road longitudinal profile alignment conditions and combined with the driving condition information of the autonomous driving vehicle in the following behavior, a physical and mechanical model of the autonomous driving vehicle's following behavior is established, thereby obtaining the combined acceleration of the autonomous driving vehicle in the straight line direction with the vehicle in front of it under the current road longitudinal profile alignment conditions.

[0087] In step C, based on the current road longitudinal profile alignment conditions and combined with the driving condition information of the autonomous driving vehicle in the following behavior, the following steps are specifically performed to establish a physical and mechanical model of the current autonomous driving vehicle's following behavior, and then obtain the combined acceleration of the autonomous driving vehicle in a straight line direction with the vehicle in front of it under the current road longitudinal profile alignment conditions.

[0088] Step C1: When the linear condition of the current road longitudinal section is a convex vertical curve, execute steps C1.1-C1.2 to establish a physical and mechanical model of the autonomous driving vehicle, and then obtain the combined acceleration of the autonomous driving vehicle in the straight line direction with the vehicle in front of it when the linear condition of the current road longitudinal section is a convex vertical curve:

[0089] Step C1.1: Based on the mechanical balance of the two-dimensional space plane, the autonomous driving vehicle B is subjected to traction in the driving direction. The physical mechanical model of the autonomous driving vehicle is constructed through the following mechanical function expression to obtain the acceleration a of the autonomous driving vehicle B in the driving direction: B :

[0090] F1±M Bgsinθ=M B a B

[0091]

[0092] Where F1 is the traction of the autonomous vehicle B; M B is the gravity of the autonomous vehicle B; a B is the acceleration of the autonomous driving vehicle B in the driving direction; θ is the angle between the gravity direction of the autonomous driving vehicle B and the line connecting the center of mass of the autonomous driving vehicle B and the center of the vertical curve;

[0093] When the linear condition of the current road longitudinal section is a convex vertical curve, in this embodiment, the convex vertical curve road is approximated as a part of a circle, and the radius of the circle is the radius of the convex vertical curve road. Then, on both sides of the highest point of the road, the physical and mechanical model of the autonomous driving vehicle is as follows:

[0094] For an autonomous vehicle, when the autonomous vehicle is on the left side of the highest point of the road, the acceleration a of the autonomous vehicle B in the driving direction is B for: When the autonomous vehicle is on the right side of the highest point of the road, the acceleration a of the autonomous vehicle B in the direction of travel is B for: When the autonomous vehicle is at the highest point of the road, θ is 0, then

[0095] The front vehicle is subject to traction in the driving direction. The physical and mechanical model of the front vehicle is constructed through the following mechanical function expression to obtain the acceleration a of the front vehicle A in the driving direction. A :

[0096] F1′±M A gsinμ=M A a A

[0097]

[0098] Where F1′ is the traction of the vehicle A in front; M A is the gravity of the vehicle A in front; a A is the acceleration of the front vehicle A in the driving direction; μ is the angle between the gravity direction of the front vehicle and the line connecting the center of mass of the front vehicle and the center of the vertical curve;

[0099] In this embodiment, the physical and mechanical model of the vehicle in front is as follows:

[0100] For the vehicle ahead, when the vehicle ahead is on the left side of the highest point of the road, the acceleration a of the vehicle ahead in the direction of travel is A : When the front vehicle A is on the right side of the highest point of the road, the acceleration a of the front vehicle A in the direction of travel B for: When the front vehicle A is at the highest point of the road, θ is 0, then

[0101] Step C1.2: Based on the acceleration a of the autonomous driving vehicle in its direction of travel B , combined with the position of the autonomous driving vehicle and the vehicle ahead, the total acceleration a of the autonomous driving vehicle in the direction of the straight-line distance between it and the vehicle ahead is obtained when the longitudinal section of the road ahead is a convex vertical curve 合 , which can be divided into the following two situations:

[0102] when hour:

[0103]

[0104] when hour:

[0105]

[0106] In the formula, It is the angle between the driving direction of the autonomous driving vehicle B and the line connecting the center of mass of the autonomous driving vehicle and the vehicle in front.

[0107] Step C2: When the linear condition of the current road longitudinal section is a concave vertical curve, execute steps C2.1-C2.2 to establish a physical and mechanical model of the autonomous driving vehicle, and then obtain the combined acceleration of the autonomous driving vehicle in the straight line direction with the vehicle in front of it when the linear condition of the current road longitudinal section is a concave vertical curve:

[0108] Step C2.1: Based on the mechanical balance requirements of the two-dimensional space plane, the autonomous driving vehicle B is subjected to traction in the driving direction. The physical mechanical model of the autonomous driving vehicle is constructed through the following mechanical function expression to obtain the acceleration a of the autonomous driving vehicle B in the driving direction: B ′:

[0109] F1±M B gsinθ=M B a B

[0110]

[0111] Where F1 is the traction of the autonomous vehicle B; M B is the gravity of the autonomous vehicle B; a Bis the acceleration of the autonomous driving vehicle B in the driving direction; θ is the angle between the center of mass of the autonomous driving vehicle and the center of the vertical curve in the direction of gravity of the autonomous driving vehicle;

[0112] When the linear condition of the current road longitudinal section is a concave vertical curve, in this embodiment, the concave vertical curve road is approximated as a part of a circle, and the radius of the circle is the radius of the concave vertical curve road. Then, on both sides of the highest point of the road, the physical and mechanical model of the autonomous driving vehicle is as follows:

[0113] For an autonomous vehicle, when the autonomous vehicle is on the left side of the highest point of the road, the acceleration a of the autonomous vehicle B in the driving direction is B for: When the autonomous vehicle is on the right side of the highest point of the road, the acceleration a of the autonomous vehicle B in the direction of travel is B for: When the autonomous vehicle is at the highest point of the road, θ is 0, then

[0114] The front vehicle is subject to traction in the driving direction. The physical and mechanical model of the front vehicle is constructed through the following mechanical function expression to obtain the acceleration a of the front vehicle A in the driving direction. A :

[0115] F1′±M A gsinμ=M A a A

[0116]

[0117] Where F1′ is the traction of the vehicle A in front; M A is the gravity of the vehicle A in front; a A is the acceleration of the front vehicle A in the driving direction; μ is the angle between the gravity direction of the front vehicle and the line connecting the center of mass of the front vehicle and the center of the vertical curve;

[0118] In this embodiment, the physical and mechanical model of the vehicle in front is as follows:

[0119] For the vehicle ahead, when the vehicle ahead is on the left side of the highest point of the road, the acceleration a of the vehicle ahead in the direction of travel is A : When the front vehicle A is on the right side of the highest point of the road, the acceleration a of the front vehicle A in the direction of travel B for: When the front vehicle A is at the highest point of the road, θ is 0, then

[0120] Step C2.2: Based on the acceleration a′ of the autonomous driving vehicle in the driving directionB , combined with the position of the autonomous driving vehicle and the vehicle ahead, the total acceleration a of the autonomous driving vehicle in the straight-line distance direction from the vehicle ahead is obtained when the longitudinal section of the road ahead is a concave vertical curve 合 ′:

[0121] when hour:

[0122]

[0123] when hour:

[0124]

[0125] In the formula, It is the angle between the driving direction of the autonomous driving vehicle B and the line connecting the center of mass of the autonomous driving vehicle and the vehicle in front.

[0126] Road traffic is composed of basic elements such as people, vehicles, roads, and environment. The total safety potential field of the road is the superposition of the safety potential fields of many traffic elements. Therefore, the potential field strength of the total safety potential field in a common scene is E total The calculation is as follows:

[0127] |E total |=ω L |E L |+ω S |E S |+ω V |E V |

[0128] Where: E L E is the potential field strength of the road longitudinal section linear field; S is the road boundary potential field strength; E V is the potential field strength of the vehicle potential field; ω L ,ω S ,ω V They correspond to the weights of the potential field strength of the road line field, the potential field strength of the road boundary field, and the potential field strength of the vehicle potential field.

[0129] Since only the longitudinal section alignment conditions are considered, in the ideal state of the following model, the autonomous driving vehicle B will not deviate from the center line of the road when driving in the center of a single-lane road and only the longitudinal section alignment of the road is considered, so the influence of the road boundary field can be ignored; in addition, this scheme starts from the perspective of the impact of traffic flow conditions and road conditions on the safety of vehicles in traffic flow, and combines the safety potential field theory to consider the following behavior of a single autonomous driving vehicle in a single lane at the longitudinal section of the road. Therefore, the following model of the autonomous driving vehicle in the scenario of this scheme is affected by the superposition of the longitudinal section alignment conditions of the road and the potential field of the vehicle ahead.

[0130] Step D: Based on the vehicle safety potential field theory and the distance between the autonomous driving vehicle and the vehicle ahead in the two-dimensional space coordinate system, a vehicle potential field model of the vehicle ahead is constructed;

[0131] In the step D, the following steps are performed to construct a vehicle potential field model of the vehicle ahead;

[0132] Step D1: Based on the distance between two points in the two-dimensional space coordinate system, the distance between the autonomous driving vehicle and the vehicle in front in the two-dimensional space is constructed by the following formula;

[0133]

[0134]

[0135] Where |k′| is the distance between the autonomous driving vehicle and the vehicle in front, (x0, y0) is the position coordinate of the center of mass of the autonomous driving vehicle in the two-dimensional space coordinate system, a is a preset parameter related to speed; τ is the preset critical threshold of the safety distance corresponding to the vertical curve linear condition; v is the speed of the autonomous driving vehicle; σ is the steering angle when the vehicle in front turns; (x * ,y * ) is the corresponding deflection value of the original coordinates (x, y) of the position of the center of mass of the front vehicle in the two-dimensional space coordinate system after turning;

[0136] Assume that the position coordinates of the center of mass of the autonomous driving vehicle B in the longitudinal section of the two-dimensional space coordinate system are (x0, y0). In the following scenario, the distance k from the two-dimensional plane space point to the vehicle has the following relationship. The conventional distance calculation formula is:

[0137]

[0138] According to the formula from the above-mentioned spatial point to the center of mass of the autonomous driving vehicle, the following motion of the autonomous driving vehicle is considered in the two-dimensional plane of the longitudinal section of the road. Therefore, the changes in the coordinates of the mass point will occur when the vehicle climbs and descends, and the velocity components and acceleration components generated in the horizontal and vertical directions are considered. In order to better describe the changes in the degree of risk faced by the autonomous driving vehicle B when approaching the vehicle in front, the distance correction is performed on the actual two-dimensional space.

[0139] Step D2: The distance between the autonomous driving vehicle and the vehicle in front in the two-dimensional space is combined with the safety potential field theory to construct a vehicle potential field model of the vehicle in front, as shown below:

[0140]

[0141] In the formula, λ and β1 are preset coefficients; M A is the mass of the vehicle A in front; aA is the acceleration of the front vehicle A in the direction of travel; It is the angle between the line connecting the two vehicle centroids and the driving direction of the autonomous driving vehicle.

[0142] Due to the influence of the potential fields of other vehicles around, the vehicle potential field formed by the front vehicle has the following effect on the autonomous driving vehicle: when the front vehicle is a certain distance away from the autonomous driving vehicle, the vehicle potential field of the front vehicle will act on the autonomous driving vehicle. Therefore, the strength of the potential field will gradually decrease with the increase of distance. When the front vehicle is a certain distance away from the autonomous driving vehicle, the strength of the potential field is approximately 0.

[0143] Step E: Based on the current expected acceleration of the vehicle, combined with the combined acceleration of the autonomous driving vehicle in the straight direction with the vehicle in front of it under the current road longitudinal profile conditions, and the vehicle potential field model of the vehicle in front, a following model of the autonomous driving vehicle combined with the vehicle potential field under the longitudinal profile conditions of a convex vertical curve road or a concave vertical curve road is constructed.

[0144] In step E, based on the current vehicle expected acceleration, combined with the acceleration of the autonomous driving vehicle in the straight direction with the vehicle in front of it under the current road longitudinal profile alignment condition, and the vehicle potential field model of the vehicle in front, the following steps are specifically performed to construct an autonomous driving vehicle following model combined with the vehicle potential field under the convex vertical curve road longitudinal profile alignment condition or the concave vertical curve road longitudinal profile alignment condition:

[0145] Step E1: Based on the potential field model of the vehicle ahead, obtain the field force F of the potential field of the vehicle ahead that the autonomous driving vehicle is subjected to AB , as shown below:

[0146]

[0147] in,

[0148] In the formula, β2 is the preset coefficient, v B is the speed of the autonomous vehicle B.

[0149] Step E2: Based on the field force of the potential field of the vehicle in front of the autonomous driving vehicle, obtain the field force F of the autonomous driving vehicle B AB The acceleration a generated by the action AB , as shown below:

[0150]

[0151] Step E3: Based on the field force F of the autonomous driving vehicle B AB The acceleration a generated by the action AB, combined with the total acceleration of the autonomous driving vehicle in the straight line direction with the vehicle in front of it under the current road longitudinal profile conditions, the acceleration of the autonomous driving vehicle in the driving direction is obtained, that is, the vector sum in the driving direction of the autonomous driving vehicle B:

[0152]

[0153]

[0154] Where: a 合 is the total acceleration of the autonomous driving vehicle in the straight line direction with the vehicle in front of it under the condition of a convex vertical curve; a 合 ′ is the total acceleration of the autonomous driving vehicle in the concave vertical curve and the vehicle in front of it in the straight line direction; is the angle between the driving direction of the autonomous driving vehicle B and the line connecting the center of mass of the autonomous driving vehicle and the vehicle in front; is the angle between the driving direction of the front vehicle and the line connecting the centers of mass of the two vehicles; d AB is the straight-line distance between the center of mass of the autonomous driving vehicle and the vehicle in front; g is the reduction coefficient of the acceleration generated by the potential field force as the distance changes, a 场 is the acceleration of the autonomous driving vehicle in the driving direction when the current road longitudinal section line condition is a convex vertical curve; a 场 ′ is the acceleration of the autonomous driving vehicle in the driving direction when the current road longitudinal section alignment condition is a concave vertical curve;

[0155] Step E4: In summary, an autonomous driving vehicle following model combined with a vehicle potential field under the longitudinal profile alignment condition of a convex vertical curve road or the longitudinal profile alignment condition of a concave vertical curve road is constructed, and the formula is as follows:

[0156]

[0157] Where a1 = a max tanh[δ(v0 (a) -v B )],

[0158] Where a1 is the expected acceleration of the autonomous vehicle; a max is the maximum acceleration allowed by the autonomous vehicle; δ is the coefficient value of the difference between the current speed of the vehicle and the expected speed; v0 (a) is the expected speed of the autonomous vehicle under the current acceleration condition, v B For self-driving vehicles.

[0159] The autonomous driving vehicle following model combined with the vehicle potential field under the longitudinal section alignment condition of the convex vertical curve road is:

[0160]

[0161] The autonomous driving vehicle following model combined with the vehicle potential field under the longitudinal section alignment condition of the concave vertical curve road is:

[0162]

[0163] Since the force generated by the safety potential field is a short-range force, that is, the force only works at a short distance, when the front and rear vehicles are far apart in the following state, that is, when the potential field strength is approximately 0, the acceleration and deceleration of vehicles on regular roads are mainly expressed by the relationship between the current speed of the vehicle and the expected speed as follows:

[0164] a1=a max tanh[δ(v0 (a) -v B )]

[0165] Combined with the road longitudinal section alignment conditions, without the potential field force of the vehicle in front, the autonomous driving vehicle following model under the convex vertical curve road longitudinal section alignment conditions is:

[0166] The following model of the autonomous driving vehicle under the longitudinal section alignment condition of the concave vertical curve road is:

[0167] A device for establishing a method for establishing a safe potential field following model of an intelligent vehicle based on a road longitudinal section includes a memory and a processor, wherein the memory stores a computer program, and is characterized in that the method for establishing a safe potential field following model of an intelligent vehicle based on a road longitudinal section is implemented when the processor executes the computer program.

[0168] A computer-readable storage medium having a computer program stored thereon, characterized in that when the computer program is executed by a processor, the method for establishing a safe potential field following model of an intelligent vehicle based on a road longitudinal section is implemented.

[0169] The present invention designs a method for establishing a safety potential field following model for intelligent vehicles based on road longitudinal sections. Starting from the perspective of the impact of traffic flow conditions and road conditions on vehicle safety in traffic flow, the following behavior of a single autonomous driving vehicle on a single lane at a road longitudinal section is considered in combination with the safety potential field theory, and the physical and mechanical functions of the autonomous driving vehicle are established. The potential field model of the autonomous driving vehicle under the safety potential field theory is used to evaluate the speed and acceleration of the following behavior of the autonomous driving vehicle, and then a complete autonomous driving vehicle following model under the safety potential field theory is obtained, providing a theoretical reference for the safety issues of autonomous driving vehicles in actual road scenarios. At the same time, the following risk of autonomous driving vehicles is obtained by using the method disclosed in the present invention to conduct safety hazard inspections for the promotion of autonomous driving vehicles and the actual operation of existing road infrastructure.

[0170] The above are only preferred embodiments of the present invention, but do not limit the patent scope of the present invention. Although the present invention is described in detail with reference to the above embodiments, those skilled in the art can still modify the technical solutions recorded in the above embodiments, or replace some of the technical features with equivalent ones. Any equivalent structure made by using the contents of the present invention specification and drawings, directly or indirectly used in other related technical fields, is also within the scope of patent protection of the present invention.

Claims

1. A method for establishing a safe potential field car-following model for intelligent vehicles based on road longitudinal sections, characterized by: For the following behavior of the autonomous driving vehicle, based on the road longitudinal profile conditions combined with the vehicle potential field, the following steps are performed to construct an autonomous driving vehicle following model under the convex vertical curve road longitudinal profile conditions or the concave vertical curve road longitudinal profile conditions combined with the vehicle potential field: Step A: Acquire driving condition information of the autonomous driving vehicle in the following behavior under the current road longitudinal profile alignment condition, including road longitudinal profile alignment information, front vehicle information, and autonomous driving vehicle information; Step B: Based on the road longitudinal section alignment information, determine whether the current road longitudinal section alignment condition is a convex vertical curve or a concave vertical curve, and then construct a two-dimensional space coordinate system corresponding to the convex vertical curve or the concave vertical curve, and depict the autonomous driving vehicle information and the front vehicle information on the coordinate system; Step C: Based on the current road longitudinal profile conditions and combined with the driving condition information of the autonomous driving vehicle in the car-following behavior, a physical and mechanical model of the autonomous driving vehicle's car-following behavior is established, thereby obtaining the combined acceleration of the autonomous driving vehicle in the straight line direction with the vehicle in front of it under the current road longitudinal profile conditions; Step D: Based on the vehicle safety potential field theory and the distance between the autonomous driving vehicle and the vehicle ahead in the two-dimensional space coordinate system, a vehicle potential field model of the vehicle ahead is constructed; Step E: Based on the current expected acceleration of the vehicle, combined with the combined acceleration of the autonomous driving vehicle in the straight direction with the vehicle in front of it under the current road longitudinal profile conditions, and the vehicle potential field model of the vehicle in front, a following model of the autonomous driving vehicle combined with the vehicle potential field under the longitudinal profile conditions of a convex vertical curve road or a concave vertical curve road is constructed.

2. The method for establishing a safe potential field car-following model for intelligent vehicles based on a road longitudinal section according to claim 1, characterized in that: In step A, the road longitudinal section linear information includes the longitudinal slope size on both sides of the road longitudinal section slope change point; the front vehicle information includes the traction size of the front vehicle and the position of the front vehicle; the automatic driving vehicle information includes the traction size of the automatic driving vehicle, the position of the automatic driving vehicle, and the distance between the center of mass of the automatic driving vehicle and the center of mass of the front vehicle.

3. The method for establishing a safe potential field car-following model for intelligent vehicles based on a road longitudinal section according to claim 1, characterized in that: In the step B, based on the road longitudinal section linear information, the following steps are specifically performed to establish a two-dimensional space coordinate system, and to depict the autonomous driving vehicle information and the front vehicle information on the coordinate system: Step B1: Based on the road longitudinal section linear information, that is, the longitudinal slopes on both sides of the road longitudinal section slope change point, the linear condition of the road longitudinal section where the autonomous driving vehicle is currently located is obtained as a convex vertical curve or a concave vertical curve, and a two-dimensional space coordinate system is established for the convex vertical curve of the road longitudinal section or the concave vertical curve of the road longitudinal section. The two-dimensional space coordinate system corresponding to the convex vertical curve takes the starting point of the vertical curve as the coordinate origin; In the two-dimensional space coordinate system of the concave vertical curve, the starting point of the vertical curve is (0, R), where R is the radius of the vertical curve; Step B2: Based on the two-dimensional spatial coordinate system of the linear condition of the current road longitudinal section, the front vehicle information including the front vehicle position is depicted on the coordinate axis; the autonomous driving vehicle information includes the position of the autonomous driving vehicle and the straight-line distance between the center of mass of the autonomous driving vehicle and the center of mass of the front vehicle.

4. The method for establishing a safe potential field car-following model for intelligent vehicles based on a road longitudinal section according to claim 2, characterized in that: In step C, based on the current road longitudinal profile linear condition and combined with the driving condition information of the autonomous driving vehicle in the car-following behavior, the following steps are specifically performed to establish a physical and mechanical model of the current autonomous driving vehicle's car-following behavior, thereby obtaining the combined acceleration of the autonomous driving vehicle in the straight line direction with the vehicle in front of it under the current road longitudinal profile linear condition: Step C1: When the linear condition of the current road longitudinal section is a convex vertical curve, execute steps C1.1-C1.2 to establish a physical and mechanical model of the autonomous driving vehicle, and then obtain the combined acceleration of the autonomous driving vehicle in the straight line direction with the vehicle in front of it when the linear condition of the current road longitudinal section is a convex vertical curve: Step C1.1: Based on the mechanical balance of the two-dimensional space plane, the physical mechanical model of the autonomous driving vehicle is constructed through the following mechanical function expression to obtain the acceleration a of the autonomous driving vehicle B in the driving direction: B : F1±M B gsinθ=M B a B Where F1 is the traction of the autonomous vehicle B; M B is the gravity of the autonomous vehicle B; a B is the acceleration of the autonomous driving vehicle B in the driving direction; θ is the angle between the gravity direction of the autonomous driving vehicle B and the line connecting the center of mass of the autonomous driving vehicle B and the center of the vertical curve; Through the following mechanical function expression, the physical mechanical model of the front vehicle is constructed to obtain the acceleration a of the front vehicle A in the driving direction: A : F1′±M A gsinμ=M A a A Where F1′ is the traction of the vehicle A in front; M A is the gravity of the vehicle A in front; a A is the acceleration of the front vehicle A in the driving direction; μ is the angle between the gravity direction of the front vehicle and the line connecting the center of mass of the front vehicle and the center of the vertical curve; Step C1.2: Based on the acceleration a of the autonomous driving vehicle in its direction of travel B , combined with the position of the autonomous driving vehicle and the vehicle ahead, the total acceleration a of the autonomous driving vehicle in the direction of the straight-line distance between it and the vehicle ahead is obtained when the longitudinal section of the road ahead is a convex vertical curve 合 : when hour: when hour: In the formula, is the angle between the driving direction of the autonomous driving vehicle B and the line connecting the center of mass of the autonomous driving vehicle and the vehicle in front; Step C2: When the linear condition of the current road longitudinal section is a concave vertical curve, execute steps C2.1-C2.2 to establish a physical and mechanical model of the autonomous driving vehicle, and then obtain the combined acceleration of the autonomous driving vehicle in the straight line direction with the vehicle in front of it when the linear condition of the current road longitudinal section is a concave vertical curve: Step C2.1: Based on the mechanical balance requirements of the two-dimensional space plane, the physical mechanical model of the autonomous driving vehicle is constructed through the following mechanical function expression to obtain the acceleration a of the autonomous driving vehicle B in the driving direction: B ′: F1±M B gsinθ=M B a B Where F1 is the traction of the autonomous vehicle B; M B is the gravity of the autonomous vehicle B; a B is the acceleration of the autonomous driving vehicle B in the driving direction; θ is the angle between the center of mass of the autonomous driving vehicle and the center of the vertical curve in the direction of gravity of the autonomous driving vehicle; Through the following mechanical function expression, the physical mechanical model of the front vehicle is constructed to obtain the acceleration a of the front vehicle A in the driving direction: A : F1′±M A gsinμ=M A a A Where F1′ is the traction of the vehicle A in front; M A is the gravity of the vehicle A in front; a A is the acceleration of the front vehicle A in the driving direction; μ is the angle between the gravity direction of the front vehicle and the line connecting the center of mass of the front vehicle and the center of the vertical curve; Step C2.2: Based on the acceleration a′ of the autonomous driving vehicle in the driving direction B , combined with the position of the autonomous driving vehicle and the vehicle ahead, the total acceleration a of the autonomous driving vehicle in the straight-line distance direction from the vehicle ahead is obtained when the longitudinal section of the road ahead is a concave vertical curve 合 ′: when hour: when hour: In the formula, It is the angle between the driving direction of the autonomous driving vehicle B and the line connecting the center of mass of the autonomous driving vehicle and the vehicle in front.

5. The method for establishing a safe potential field car-following model for intelligent vehicles based on a road longitudinal section according to claim 1, characterized in that: In the step D, the following steps are performed to construct a vehicle potential field model of the vehicle ahead; Step D1: Based on the distance between two points in the two-dimensional space coordinate system, the distance between the autonomous driving vehicle and the vehicle in front in the two-dimensional space is constructed by the following formula; Where |k′| is the distance between the autonomous driving vehicle and the vehicle in front, (x0, y0) is the position coordinate of the center of mass of the autonomous driving vehicle in the two-dimensional space coordinate system, a is a preset parameter related to speed; τ is the preset critical threshold of the safety distance corresponding to the vertical curve linear condition; v is the speed of the autonomous driving vehicle; σ is the steering angle when the vehicle in front turns; (x * ,y * ) is the corresponding deflection value of the original coordinates (x, y) of the position of the center of mass of the front vehicle in the two-dimensional space coordinate system after turning; Step D2: The distance between the autonomous driving vehicle and the vehicle in front in the two-dimensional space is combined with the safety potential field theory to construct a vehicle potential field model of the vehicle in front, as shown below: In the formula, λ and β1 are preset coefficients; M A is the mass of the vehicle A in front; a A is the acceleration of the front vehicle A in the direction of travel; It is the angle between the line connecting the two vehicle centroids and the driving direction of the autonomous driving vehicle.

6. The method for establishing a safe potential field car-following model for intelligent vehicles based on a road longitudinal section according to claim 5, characterized in that: In step E, based on the current vehicle expected acceleration, combined with the acceleration of the autonomous driving vehicle in the straight direction with the vehicle in front of it under the current road longitudinal profile alignment condition, and the vehicle potential field model of the vehicle in front, the following steps are specifically performed to construct an autonomous driving vehicle following model combined with the vehicle potential field under the convex vertical curve road longitudinal profile alignment condition or the concave vertical curve road longitudinal profile alignment condition: Step E1: Based on the potential field model of the vehicle ahead, obtain the field force F of the potential field of the vehicle ahead that the autonomous driving vehicle is subjected to AB , as shown below: in, In the formula, β2 is the preset coefficient, v B is the speed of the autonomous vehicle B; Step E2: Based on the field force of the potential field of the vehicle in front of the autonomous driving vehicle, obtain the field force F of the autonomous driving vehicle B AB The acceleration a generated by the action AB , as shown below: Step E3: Based on the field force F of the autonomous driving vehicle B AB The acceleration a generated by the action AB , combined with the total acceleration of the autonomous driving vehicle in the straight line direction with the vehicle in front of it under the current road longitudinal section line condition, the acceleration of the autonomous driving vehicle in the driving direction is obtained: Where: a 合 is the total acceleration of the autonomous driving vehicle in the straight line direction with the vehicle in front of it under the condition of a convex vertical curve; a 合 ′ is the total acceleration of the autonomous driving vehicle in the concave vertical curve and the vehicle in front of it in the straight line direction; is the angle between the driving direction of the autonomous driving vehicle B and the line connecting the center of mass of the autonomous driving vehicle and the vehicle in front; is the angle between the driving direction of the front vehicle and the line connecting the centers of mass of the two vehicles; d AB is the distance between the center of mass of the autonomous driving vehicle and the vehicle in front; g is the reduction coefficient of the acceleration generated by the potential field force as the distance changes, a 场 is the acceleration of the autonomous driving vehicle in the driving direction when the current road longitudinal section line condition is a convex vertical curve; a 场 ′ is the acceleration of the autonomous driving vehicle in the driving direction when the current road longitudinal section alignment condition is a concave vertical curve; Step E4: In summary, an autonomous driving vehicle following model combined with a vehicle potential field under the longitudinal profile alignment condition of a convex vertical curve road or the longitudinal profile alignment condition of a concave vertical curve road is constructed, and the formula is as follows: Where a1 = a max tanh[δ(v0 (a) -v B )], Where a1 is the expected acceleration of the autonomous vehicle; a max is the maximum acceleration allowed by the autonomous vehicle; δ is the coefficient value of the difference between the current speed of the vehicle and the expected speed; v0 (a) is the expected speed of the autonomous vehicle under the current acceleration condition, v B is the current speed of the autonomous vehicle.

7. A device for establishing a method for establishing a safety potential field following model of an intelligent vehicle based on a road longitudinal section, comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the method for establishing a safe potential field following model for an intelligent vehicle based on a road longitudinal section as described in any one of claims 1 to 6 is implemented.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for establishing a safe potential field following model for an intelligent vehicle based on a road longitudinal section as described in any one of claims 1 to 6 is implemented.

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