A multi-vehicle collaborative modeling method for the tunnel entrance area based on a car-following model

Abstract

The present invention discloses a multi-vehicle collaborative modeling method for the tunnel entrance area based on a car-following model, comprising the following steps: S1: Define the tunnel entrance area; S2: Determine the collaborative range of the following vehicles; S3: Determine the optimized speed function of the following vehicles in the tunnel entrance area; S4: Determine the car-following model of the vehicles in the tunnel entrance area; S5: Establish a multi-vehicle collaborative model for the tunnel entrance area. According to the characteristics of the tunnel entrance area, the present invention respectively determines the optimized speed functions for the approach section and the entrance section of the tunnel entrance area, making the proposed multi-vehicle collaborative model more targeted. The present invention also considers the influence of the information of multiple leading vehicles in the tunnel entrance area on the following vehicles, including the relative speed information between the leading vehicles and between the leading vehicle and the following vehicle, and also considers the relative speed between the following vehicle and its following vehicle, which can make the multi-vehicle collaborative model established by the present invention have higher stability.

Description

Technical Field

[0001] The present invention relates to the technical field of multi-vehicle collaborative modeling methods in the tunnel entrance area, and particularly relates to a multi-vehicle collaborative modeling method in the tunnel entrance area based on a car-following model Background Art

[0002] Tunnels can be spatially divided into four parts: the entrance section, the transition section, the middle section, and the exit section. In the spatial distribution of tunnel accidents, the accident rate of the tunnel entrance section is significantly higher than that of other sections. In fact, the poor vehicle collaboration effect is an important reason for traffic accidents in this area. And the car-following behavior of vehicles is a common phenomenon in traffic. It is not only an important influencing factor for vehicles to drive collaboratively, but also an important manifestation of the vehicle collaboration effect. At the same time, in the tunnel entrance area, due to its unique traffic condition constraints, the car-following behavior of vehicles will be more prominent in this area. Therefore, in the tunnel entrance area, starting from the car-following behavior of vehicles and based on the car-following theory, designing a car-following model for this area and then establishing a multi-vehicle collaborative model for this area is a necessary and reasonable technical route, which is of great significance for solving the problem of poor vehicle-vehicle collaboration effect existing in this area

[0003] By consulting relevant patents and papers, it is found that there are few patents that study the multi-vehicle collaborative model in this area based on the car-following model. Patent CN113112817A discloses a tunnel vehicle positioning and warning system and method based on vehicle networking and car-following behavior, which can realize the real-time analysis of the running conditions of connected and non-connected vehicles under the condition of no GNSS signal. However, this method mainly focuses on the acquisition and processing of vehicle position and speed information, lacking the analysis of the mutual influence between vehicles. Therefore, it is not applicable to the establishment of the multi-vehicle collaborative model in this area. Patent CN113468675A discloses a tunnel entrance traffic environment modeling method, vehicle-mounted equipment and storage medium, which can obtain the total potential field force and total potential field force model of the tunnel entrance traffic environment through the potential field theory. However, this method focuses more on the comprehensive influence of the environmental conditions in the tunnel entrance area on vehicle driving, ignoring the dynamic mutual influence process between vehicles and vehicles, and cannot establish the multi-vehicle collaborative model in this area Summary of the Invention

[0004] The purpose of the present invention is to provide a multi-vehicle collaborative modeling method in the tunnel entrance area based on a car-following model to solve the problem that the poor vehicle collaborative driving effect in this area easily leads to traffic accidents in this area

[0005] To achieve the above purpose, the present invention provides the following technical solutions: A multi-vehicle collaborative modeling method in the tunnel entrance area based on a car-following model, including the following steps:

[0006] S1: Define the tunnel entrance area, and divide the tunnel area into an entrance approach section, an entrance section, a transition section, and a non-entrance area in sequence according to the vehicle driving direction;

[0007] S2: Determine the cooperation range of the following vehicle, that is, the number of leading vehicles that the following vehicle cooperates with is m and the number of following vehicles is k;

[0008] S3: Determine the optimized speed function of the following vehicle in the tunnel entrance area;

[0009] S4: Determine the vehicle following model in the tunnel entrance area;

[0010] S5: Establish a multi-vehicle cooperation model in the tunnel entrance area.

[0011] To further improve the model accuracy, in S1, the entrance approach section is a distance from 200 meters before the tunnel entrance to the tunnel entrance; the entrance section is a distance from the tunnel entrance to 50 meters after the tunnel entrance; the transition section is a distance from 50 meters after the tunnel entrance to 200 meters; the non-entrance area is the tunnel section after the transition section.

[0012] To further improve the model accuracy, the cooperation range of the following vehicle in S2 is specifically: centered on the following vehicle, according to its influence by different leading vehicles and its influence on different following vehicles, the first m leading vehicles and the last k following vehicles are included in the cooperation range.

[0013] To further improve the model accuracy, the optimized speed function of the following vehicle in S3 includes an entrance approach section optimized speed function, an entrance section optimized speed function, and a transition section optimized speed function;

[0014] The entrance approach section optimized speed function adopts the following expression:

[0015] V(Δx n ,v n+1 )=V1+V2tanh[C1(Δx n (t)-l c )-C2]

[0016] Where, Δx n represents the distance between the nth vehicle and the leading vehicle; v n+1 represents the driving speed of the vehicle in front of the nth vehicle; V1, V2, C1, and C2 are constants and are fixed parameters of the optimized speed function; l c represents the length of the vehicle; tanh is the hyperbolic tangent function;

[0017] The entrance section optimized speed function is the same as the transition section optimized speed function, and both adopt the following expression:

[0018]

[0019] V(Δx n , v n+1 ) = V max [S(Δx n ) - S(Δx s )] + [1 - S(Δx n )]v n+1 (t)

[0020] Among them, S(Δx) represents the sensitivity of the optimal speed to the spatial headway distance, so S(Δx) ∈ [0, 1]; Δx s is the safe driving distance; μ ∈ (0, 1) is an adjustable parameter.

[0021] To further improve the model accuracy, the vehicle following model in S4 adopts the following expression:

[0022]

[0023] Among them, the parameter a is the sensitivity coefficient of the following vehicle, and b is the speed difference coefficient of the leading vehicle; x n (t) is the position of the nth vehicle at time t, v n (t) is the speed of the nth vehicle at time t; Δx n = x n+1 - x n represents the distance between the (n + 1)th vehicle and the nth vehicle at time t, and Δv n = v n+1 - v n represents the speed difference between the (n + 1)th vehicle and the nth vehicle at time t; m represents the number of vehicles in front that the following vehicle can perceive, and β l ≥0, α l ≤1 represents the sensitivity of the following vehicle to the lth vehicle in front, and the calculation process is as follows:

[0024]

[0025]

[0026] Among them, both β and α are constants, and since the influence of the leading vehicle on the following vehicle decreases as the number of vehicles between them increases, so β l > β l+1 , α l > α l+1 .

[0027] To further improve the model accuracy, the multi - vehicle cooperation model in S5 adopts the following expression:

[0028]

[0029] Among them, the parameter c is the cooperation coefficient between the following vehicle and the leading vehicle, and d is the cooperation coefficient between the following vehicle and the rear vehicle; k represents the number of rear vehicles that the following vehicle can sense, and γ l ≥0, δ l ≤1 respectively represent the sensitivity of the driver to the l-th vehicle in the front and rear. The calculation process is as follows:

[0030]

[0031]

[0032] Beneficial effects:

[0033] One beneficial effect of the present invention is that according to the characteristics of the tunnel entrance area, the optimized speed functions of the introduction section and the entrance section of the tunnel entrance area are respectively determined, making the proposed multi-vehicle cooperation model more targeted.

[0034] Another beneficial effect of the present invention is that it considers the influence of multi-leading vehicle information in the tunnel entrance area on the following vehicle, including the relative speed information between the leading vehicles and between the leading vehicle and the following vehicle, and also considers the relative speed between the following vehicle and its rear vehicle, which can make the multi-vehicle cooperation model established by the present invention more stable. Description of the drawings

[0035] Figure 1 is the flowchart of the multi-vehicle cooperation modeling method for the tunnel entrance area based on the car-following model;

[0036] Figure 2 is the schematic diagram of the sectionalization of the tunnel entrance area;

[0037] Figure 3 is the schematic diagram of the cooperation range of the following vehicle. Specific implementation manners

[0038] In order to make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to the embodiments.

[0039] Embodiment 1: As Figures 1 to 3 shown, this embodiment provides a multi-vehicle cooperation modeling method for the tunnel entrance area based on the car-following model to solve the problem of poor vehicle cooperation driving effect in this area.

[0040] The objective of the present invention is achieved through the following technical solutions:

[0041] A multi-vehicle cooperation modeling method for the tunnel entrance area based on the car-following model includes the following steps:

[0042] Step 1, define the tunnel entrance area

[0043] In the tunnel area, it can be sequentially divided into an approach section, an entrance section, a transition section, and a non-entrance area according to the driving direction of the vehicle. The approach section is a distance from 200 meters before the tunnel entrance to the tunnel entrance; the entrance section is a distance from the tunnel entrance to 50 meters after the tunnel entrance; the transition section is a distance from 50 meters after the tunnel entrance to 200 meters; the non-entrance area is the tunnel section after the transition section. The tunnel entrance area of the present invention refers to the spatial area composed of the approach section, the entrance section, and the transition section, as Figure 1 shown.

[0044] Step 2, determine the cooperation range of the following vehicle

[0045] According to the vehicle following theory, the driving situation of the leading vehicle will have a decisive impact on the following behavior of the following vehicle. In the present invention, for the tunnel entrance area, as the number of vehicles between the leading vehicle and the following vehicle increases, its impact on the following behavior of the following vehicle becomes smaller. At the same time, the following vehicle will also become the leading vehicle of the vehicle behind it, affecting the following behavior of the vehicle behind. Therefore, a vehicle can both be a following vehicle, and can also be the leading vehicle of other vehicles, and can also be the following vehicle of other vehicles. When determining the cooperation range of the following vehicle in the present invention, taking the following vehicle as the center, according to the influence of the following vehicle by different leading vehicles and its own influence on different following vehicles, the leading vehicles and following vehicles within a certain range are included in the cooperation range, as Figure 2 shown. In the figure, n represents the serial number of the following vehicle, m represents the number of leading vehicles that the following vehicle can perceive, and k represents the number of following vehicles that the following vehicle can perceive.

[0046] Step 3, determine the optimal speed function of the following vehicle in the tunnel entrance area

[0047] In the tunnel entrance area, due to the influence of the special environmental conditions in this area and the differences in driving conditions in the approach section and the entrance section of the tunnel, the vehicle following behavior will change significantly. According to the following model theory, the optimal speed function of the following vehicle is an important part of the following model and has an important impact on the following model of the vehicle. Therefore, the existence of the above differences will inevitably be reflected in the optimal speed function of the vehicle following model, and it is necessary to design different optimal speed functions for the approach section and the entrance section of the tunnel.

[0048] For the approach section of the tunnel, the vehicles driving in this stage are driving in a normal manner, and the optimal speed function in this stage adopts the following expression:

[0049] V(Δx n ,v n+1 )=V1+V2tanh[C1(Δx n (t)-l c )-C2]

[0050] The Δx here n represents the distance between the nth vehicle and the vehicle in front; v n+1 represents the driving speed of the vehicle in front of the nth vehicle; the leading vehicles V1, V2, C1 and C2 represent the parameters of the optimal speed function; lc represents the length of the vehicle; tanh is the hyperbolic tangent function.

[0051] For the entrance section of the tunnel, during this stage, the vehicles in motion are subject to the constraints of the tunnel's environmental conditions and traffic rules, which will result in a longer reaction time and more aggressive driving behavior for the drivers. Therefore, the following expression is adopted for the optimal speed function at this stage:

[0052]

[0053] V(Δx n ,v n+1 ) = V max [S(Δx n ) - S(Δx s )] + [1 - S(Δx n )]v n+1 (t)

[0054] In the formula, S(Δx) represents the sensitivity of the optimal speed to the spatial headway distance, so S(Δx) ∈ [0, 1]; Δx s is the safe driving distance; μ ∈ (0, 1) is an adjustable parameter. Among them, the optimal speed function in the transition section is the same as that in the entrance section, and both adopt the above formula.

[0055] Step 4, determine the vehicle following model in the tunnel entrance area

[0056] In the tunnel entrance area, due to the changes in environmental conditions and driving rules, the driver's vigilance will be improved. The driver needs more information about the vehicle in front to control the following state of the vehicle. At the same time, in order to realize the coordinated driving of multiple vehicles, it is necessary to incorporate the driving information of multiple vehicles in front on the basis of the traditional following model. At the same time, the driver will not only consider the information between the vehicle in front and the vehicle in front, but also consider the relative speed information between the vehicle in front and the vehicle he is driving. Based on the above analysis, the present invention proposes the following vehicle following model in the tunnel entrance area:

[0057]

[0058] In the formula, the parameter a is the sensitivity coefficient of the following vehicle, and b is the speed difference coefficient of the vehicle in front. x n (t) is the position of the nth vehicle at time t, v n (t) is the speed of the nth vehicle at time t. Δx n = x n+1 - xn Denote the spacing between the (n + 1)-th vehicle and the n-th vehicle at time t as Δv n = v n+1 - v n which represents the speed difference between the (n + 1)-th vehicle and the n-th vehicle at time t. m represents the number of vehicles in front that the following vehicle can sense, and β l ≥ 0, α l ≤ 1 represents the sensitivity of the following vehicle to the l-th vehicle in front, and the calculation process is as follows:

[0059]

[0060]

[0061] where β, α = 2, 3, 4,... and are all constants. As described in Step 2, the influence of the leading vehicle on the following vehicle decreases as the number of intervening vehicles between them increases. Therefore, β l > β l+1 、α l > α l+1 .

[0062] Step 5, establish a multi-vehicle cooperation model for the tunnel entrance area

[0063] The car-following model described in Step 4 fully considers the influence of the leading vehicle's information on the driving behavior of the following vehicle and is the basis for establishing the multi-vehicle cooperative driving model described in the present invention. During the multi-vehicle cooperative driving process, not only the relative position and relative speed information between the leading vehicles need to be considered to determine the car-following behavior of the vehicle itself, but also the relative information between the following vehicle and each leading vehicle needs to be considered. Based on this, on the basis of the car-following model described in Step 4, the present invention establishes the following multi-vehicle cooperation model by introducing the relative speed information of the following vehicle with its front and rear vehicles:

[0064]

[0065] In the formula, the parameter c is the cooperation coefficient between the following vehicle and the leading vehicle, and d is the cooperation coefficient between the following vehicle and the following vehicle. k represents the number of vehicles behind that the following vehicle can sense, and γ l ≥ 0, δ l ≤ 1 respectively represent the sensitivity of the driver to the l-th vehicle in front and behind, and the calculation process is as follows:

[0066]

[0067]

[0068] The above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and all of them should be covered by the scope of the claims of the present invention.

Claims

1. A multi-vehicle collaborative modeling method for the tunnel entrance area based on a car-following model, characterized in that It includes the following steps: S1: Define the tunnel entrance area, and divide the tunnel area into an approach section, an entrance section, a transition section, and a non-entrance area in sequence according to the vehicle driving direction; S2: Determine the cooperation range of following vehicles, that is, the number of leading vehicles that the following vehicles cooperate with is m, and the number of following vehicles is k; S3: Determine the optimized speed function of following vehicles in the tunnel entrance area; The optimized speed function of following vehicles in S3 includes an approach section optimized speed function, an entrance section optimized speed function, and a transition section optimized speed function; The approach section optimized speed function adopts the following expression: V(Δx n ,v n+1 ) = V1 + V2tanh[C1(Δx n (t) - l c ) - C2] where, Δx n represents the distance between the nth vehicle and the vehicle in front; v n+1 represents the driving speed of the vehicle in front of the nth vehicle; V1, V2, C1, and C2 are constants and are fixed parameters of the optimal speed function; l c represents the length of the vehicle; tanh is the hyperbolic tangent function; The entrance section optimized speed function is the same as the transition section optimized speed function, and both adopt the following expression: Among them, S(Δx) represents the sensitivity of the optimal speed to the spatial headway distance, so S(Δx) ∈ [0, 1]; Δx s is the safe driving distance; μ ∈ (0, 1) is an adjustable parameter; S4: Determine the vehicle following model in the tunnel entrance area; The vehicle following model in S4 adopts the following expression: Among them, parameter a is the sensitivity coefficient of the following vehicle, and b is the speed difference coefficient of the leading vehicle; x n (t) is the position of the nth vehicle at time t, and v n (t) is the speed of the nth vehicle at time t; Δx n = x n+1 - x n represents the distance between the (n + 1)th vehicle and the nth vehicle at time t, and Δv n = v n+1 - v n represents the speed difference between the (n + 1)th vehicle and the nth vehicle at time t; m represents the number of vehicles in front that the following vehicle can perceive, and β l ≥ 0, α l ≤ 1 represents the sensitivity of the following vehicle to the lth vehicle in front. The calculation process is as follows: where both β and α are constants, and since the influence of the leading vehicle on the following vehicle decreases as the number of intervening vehicles between the two increases, so β l > β l+1 , α l > α l+1 ; S5: Establish a multi-vehicle cooperation model in the tunnel entrance area; The multi-vehicle cooperation model in S5 adopts the following expression: Among them, the parameter c is the cooperation coefficient between the following vehicle and the leading vehicle, and d is the cooperation coefficient between the following vehicle and the following vehicle; k represents the number of following vehicles that the following vehicle can sense, and γ l ≥0, δ l ≤1 respectively represent the sensitivity of the driver to the l-th vehicle in the front and the back. The calculation process is as follows:

2. The multi-vehicle collaborative modeling method for the tunnel entrance area based on the car-following model according to claim 1, wherein In S1, the approach section is a distance from 200 meters before the tunnel entrance to the tunnel entrance; The entrance section is a distance from the tunnel entrance to 50 meters after the tunnel entrance; The transition section is a distance from 50 meters after the tunnel entrance to 200 meters; the non-entrance area is the tunnel section after the transition section.

3. The multi-vehicle collaborative modeling method for the tunnel entrance area based on the car-following model according to claim 2, wherein The cooperation range of following vehicles in S2 is specifically: taking the following vehicle as the center, according to its influence by different leading vehicles and its influence on different following vehicles, the first m vehicles and the last k vehicles are included in the cooperation range.

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