Ecological driving method considering credit control uncertainty

Abstract

The invention provides an ecological driving method considering credit control uncertainty, which belongs to the technical field of ecological driving and comprises the following steps: 1) establishing a vehicle decision control model; 2) obtaining the probability that the traffic signal is a green light in a control time domain; 3) calculating the feasible time period; and 4) solving the vehicle decision control model. Compared with the prior art, on the basis of the opportunity constraint model predictive control theory, the uncertainty of the traffic signals is fused into the vehicle decision control model, the application range of the ecological driving technology is expanded, landing application of the ecological driving technology is promoted, and environmental pollution and energy consumption of a traffic system are effectively reduced.

Description

Technical Field

[0001] The present invention belongs to the technical field of eco-driving, and in particular relates to an eco-driving method taking into account signal control uncertainty. Background Art

[0002] Eco-driving is a driving style that aims to save energy, reduce emissions, reduce fuel consumption and improve driving safety. It reduces negative impacts on the environment by optimizing driving behavior and vehicle energy consumption management. At intersections, vehicles can communicate with intersection lights through vehicle networking technology to obtain signal phase and timing data (SPaT) to achieve precise speed guidance, ensure passing when the light is green, and reduce unnecessary idling waiting. These strategies not only help improve fuel efficiency, but also alleviate intersection congestion and promote the overall sustainable development of road traffic.

[0003] Signal control uncertainty usually refers to the uncertainty of traffic signal control, which is specifically manifested in the uncertainty of the opening time and duration of the green light phase. Signal control uncertainty is particularly obvious at intersections controlled by inductive traffic signals. The essence of inductive traffic signal control is a control strategy that dynamically adjusts signal timing based on real-time traffic flow. The arrival of vehicles is monitored by inductive coils or other detection equipment installed under the road surface. When a vehicle is detected passing by, the signal control system will combine the current traffic conditions to determine whether to give priority to vehicles in that direction. Compared with timed traffic signal control, inductive traffic signal control has greater flexibility and responsiveness, and can significantly optimize the traffic efficiency of intersections.

[0004] However, most of the existing eco-driving technologies assume that traffic signals are completely deterministic and that complete signal phase and timing data (SPaT) can be obtained. Therefore, they are not suitable for sensing traffic signal control intersections, and thus cannot be applied on a large scale. This shortcoming seriously restricts further energy conservation and emission reduction of the traffic system. Therefore, the existing technology has defects and needs targeted invention improvements. Summary of the invention

[0005] The object of the present invention is to provide an eco-driving method taking into account the uncertainty of signal control, such as Figure 1 As shown, it is characterized in that it includes the following steps:

[0006] S1) Establishing a vehicle decision-making control model based on model predictive control theory;

[0007] S2) Based on the existing technology, obtain the probability that the traffic signal is green in the control time domain;

[0008] S3) calculating the feasible time period based on the green light probability of the traffic signal;

[0009] S4) Solve the vehicle decision control model.

[0010] Furthermore, in S1, the mathematical formula of the vehicle decision control model is as follows:

[0011]

[0012] St

[0013] ξ k+1 =Aξ k +Bu k

[0014]

[0015] u min ≤u k ≤u max

[0016] in,

[0017] System Dynamics Cost Function constraint

[0018] Where k is the index of the control step; K is the total number of control steps;

[0019] uk is the control quantity; ξ k is the state vector; is the expectation of the state vector;

[0020] is the matrix transpose operator;

[0021] Q is the weight matrix of the state vector; r is the weight of the control quantity; A is the state matrix; B is the control matrix;

[0022] is the minimum value of the state vector; is the maximum value of the state vector; u min is the minimum value of the control amount; u max is the maximum value of the control amount;

[0023] s k is the vehicle position; v k is the vehicle speed; k is the acceleration;

[0024] △τ is the length of adjacent control steps; v d is the expected speed; q v is the speed weight;

[0025] is the minimum value of the vehicle position; is the maximum value of the vehicle position;

[0026] v max It is the speed limit of the road;

[0027] -inf means negative infinity; inf means positive infinity; -inf and inf mean no constraints;

[0028] t0 is the initial control step, i.e. the initial time;

[0029] G(t0) represents the state of the traffic signal at time t0; G(t0)=1 represents that at time t0, the state of the traffic signal is green; G(t0)=0 represents that at time t0, the state of the traffic signal is not green;

[0030] K pass is a feasible time period;

[0031] s stop is the location of the traffic light; s k and stop The schematic diagram is as follows Figure 2 As shown;

[0032] a min is the minimum value of acceleration; a max is the maximum value of acceleration.

[0033] Furthermore, in S2, the control time domain refers to the control time domain T of the vehicle decision control model in S1, and the calculation formula is:

[0034] T=K△T

[0035] Assume that within the range T, the traffic signal switches the light color only once, such as Figure 3 As shown; the probability that the traffic signal is green at the kth step is It is a set value or obtained through existing technology.

[0036] Furthermore, in S3, the feasible time period is calculated, which specifically includes the following steps:

[0037] S31) Calculate the switching probability of the traffic signal at the kth step Schematic diagram as Figure 4 As shown, the calculation formula

[0038] as follows:

[0039]

[0040] in, represents the probability of a green light in the kth step; represents the probability that the light is red after the kth step;

[0041] represents the probability that the light is red in the kth step; represents the probability that the light is green after the kth step.

[0042] S32) Calculate the switching probability F(k) of the traffic signal in the kth step, and the calculation formula is as follows:

[0043]

[0044] S33) Define the feasible time period K pass , the mathematical expression is as follows:

[0045]

[0046] Among them, k sw K pass The upper or lower limit of . This means that when G(t0) = 1, from step 0 to step k sw The control step in the step corresponds to the green light phase, so it is feasible, and from the kth sw The control steps from step 0 to step K correspond to the red light phase, so it is not feasible. Similarly, when G(t0) = 0, the control steps from step 0 to step k correspond to the red light phase, so it is not feasible. sw The control step within the step corresponds to the red light phase, so it is not feasible, and the control step from the kth sw The control steps from step to step K correspond to the green light phase and are therefore feasible.

[0047] S34) User-defined risk factor γ, meaning as follows:

[0048] γ represents the K pass The vehicle in the intersection can pass smoothly; further, when G(t0) = 1, the formula is used to express “at K pass The probability that the vehicle can successfully pass through the intersection is at least γ”, which is F(k sw )≤1-γ;

[0049] When G(t0) = 0, the formula is expressed as “at K pass The probability that the vehicle can successfully pass through the intersection is at least γ”, which is F(k sw )≥γ.

[0050] S35) Calculate k sw , the calculation formula is as follows:

[0051]

[0052] Among them, F -1 is the inverse function of F.

[0053] Furthermore, in S4, an open source solver (such as OSQP) can be called to solve the vehicle decision control model. The specific calling method can be found in the official website user manual and will not be repeated here.

[0054] Compared with the prior art, the present invention has the following beneficial effects:

[0055] The innovation of the invention lies in that a vehicle decision control model that takes into account the uncertainty of signal control is innovatively established based on the theory of chance-constrained model predictive control, thereby expanding the scope of application of eco-driving technology. The superiority of the present invention lies in that the eco-driving method provided by the present invention is not only applicable to intersections controlled by traffic signals with fixed timing, but also to signal control uncertain environments, such as intersections controlled by inductive traffic signals. Therefore, the present invention effectively promotes the implementation of eco-driving technology. The threshold of the present invention lies in that the present invention applies advanced V2X technology, and at the same time requires in-depth understanding and flexible application of mathematical theories such as model predictive control and chance constraints, so the present invention has a high threshold. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 The present invention provides a technical roadmap for an eco-driving method that takes signal control uncertainty into consideration.

[0057] Figure 2 For k and stop Schematic diagram of .

[0058] Figure 3 This is a schematic diagram of light color switching.

[0059] Figure 4 is the switching probability of the traffic signal at the kth step Schematic diagram of the calculation. DETAILED DESCRIPTION

[0060] The following will be described in more detail with reference to the accompanying drawings, in which a preferred embodiment of the present invention is shown. It should be understood that those skilled in the art can modify the present invention described herein while still achieving the beneficial effects of the present invention. Therefore, the following description should be understood as being widely known to those skilled in the art and not as a limitation to the present invention.

[0061] like Figure 1 As shown, an eco-driving method considering signal control uncertainty specifically includes the following steps:

[0062] Step 1

[0063] Based on the model predictive control theory, a vehicle decision control model is established, and the mathematical formula is expressed as follows:

[0064]

[0065] St

[0066] ξ k+1 =Aξ k +Bu k

[0067]

[0068] u min ≤u k ≤u max

[0069] in,

[0070] System Dynamics Cost Function constraint

[0071] Where k is the index of the control step; K is the total number of control steps;

[0072] u k is the control quantity; k is the state vector; is the expectation of the state vector;

[0073] is the matrix transpose operator;

[0074] Q is the weight matrix of the state vector; r is the weight of the control quantity; A is the state matrix; B is the control matrix;

[0075] is the minimum value of the state vector; is the maximum value of the state vector; u min is the minimum value of the control amount; u max is the maximum value of the control amount;

[0076] s k is the vehicle position; v k is the vehicle speed; k is the acceleration; △τ is the length of the adjacent control step; v d is the expected speed; q v is the speed weight;

[0077] is the minimum value of the vehicle position; is the maximum value of the vehicle position; v max It is the speed limit of the road;

[0078] -inf means negative infinity; inf means positive infinity; -inf and inf mean no constraints;

[0079] t0 is the initial control step, i.e. the initial time; G(t0) represents the state of the traffic signal at time t0; G(t0) = 1 represents that at time t0, the state of the traffic signal is green;

[0080] G(t0)=0 means that at time t0, the state of the traffic signal is not green;

[0081] K pass is the feasible time period; s stop is the location of the traffic light; s k and stop The schematic diagram is as follows Figure 2 As shown; a min is the minimum value of acceleration; a max is the maximum value of acceleration.

[0082] Step 2

[0083] Based on the existing technology, the probability of the traffic signal being green in the control time domain is obtained.

[0084] The control time domain refers to the control time domain T of the vehicle decision control model in S1, and the calculation formula is:

[0085] T=K△τ

[0086] Assume that within the range T, the traffic signal switches the light color only once, such as Figure 3 As shown; the probability that the traffic signal is green at the kth step It is a set value or obtained through existing technology.

[0087] Step 3

[0088] Based on the green light probability of traffic signals, the feasible time period is calculated. The specific steps are as follows:

[0089] (1) Calculate the switching probability of the traffic signal at the kth step Schematic diagram as Figure 4 As shown, the calculation formula is as follows:

[0090]

[0091] in,

[0092]

[0093] represents the probability of a green light in the kth step; represents the probability that the light is red after the kth step; represents the probability that the light is red in the kth step; represents the probability that the light is green after the kth step.

[0094] (2) Calculate the switching probability F(k) of the traffic signal in the kth step. The calculation formula is as follows:

[0095]

[0096] (3) Define the feasible time period K pass , the mathematical expression is as follows:

[0097]

[0098] Among them, k sw K pass The upper or lower limit of . This means that when G(t0) = 1, from step 0 to step k sw The control step in the step corresponds to the green light phase, so it is feasible, and from the kth sw The control steps from step 0 to step K correspond to the red light phase, so it is not feasible. Similarly, when G(t0) = 0, the control steps from step 0 to step k correspond to the red light phase, so it is not feasible. sw The control step within the step corresponds to the red light phase, so it is not feasible, and the control step from the kth sw The control steps from step to step K correspond to the green light phase and are therefore feasible.

[0099] (4) User-defined risk factor γ, meaning as follows:

[0100] γ represents the K pass The vehicle in the intersection can pass smoothly; further, when G(t0) = 1, the formula is used to express “at K pass The probability that the vehicle can successfully pass through the intersection is at least γ”, which is F(k sw )≤1-γ; when G(t0)=0, the formula is used to express “at K pass The probability that the vehicle can successfully pass through the intersection is at least γ”, which is F(k sw )≥γ.

[0101] (5) Calculate k sw , the calculation formula is as follows:

[0102]

[0103] Among them, F -1 is the inverse function of F.

[0104] Step 4

[0105] Solve the vehicle decision control model.

[0106] Open source solvers (such as OSQP) can be called to solve the vehicle decision control model. The specific calling method can be found in the official website user manual and will not be repeated here.

[0107] The above is only a preferred embodiment of the present invention and does not limit the present invention in any way. Any technician in the relevant technical field, without departing from the scope of the technical solution of the present invention, makes any form of equivalent replacement or modification to the technical solution and technical content disclosed in the present invention, which does not depart from the content of the technical solution of the present invention and still falls within the protection scope of the present invention.

Claims

1. An eco-driving method considering signal control uncertainty, characterized in that: The steps include: S1) Establishing a vehicle decision control model; S2) obtaining the probability that the traffic signal is green in the control time domain; S3) calculating the feasible time period; S4) Solve the vehicle decision control model.

2. The ecological driving method considering signal control uncertainty according to claim 1, characterized in that: In S1, the mathematical formula of the vehicle decision control model is as follows: st ξ k+1 =Aξ k +Bu k in min in k in max in, System Dynamics Cost Function constraint Where k is the index of the control step; K is the total number of control steps; u k is the control quantity; k is the state vector; is the expectation of the state vector; is the matrix transpose operator; Q is the weight matrix of the state vector; r is the weight of the control quantity; A is the state matrix; B is the control matrix; is the minimum value of the state vector; is the maximum value of the state vector; u min is the minimum value of the control amount; u max is the maximum value of the control amount; s k is the vehicle position; v k is the vehicle speed; k is the acceleration; Δτ is the length of adjacent control steps; v d is the expected speed; q v is the speed weight; is the minimum value of the vehicle position; is the maximum value of the vehicle position; max It is the speed limit of the road; -inf means negative infinity; inf means positive infinity; -inf and inf mean no constraints; 0 is the initial control step, i.e. the initial moment; G(t0) represents the state of the traffic signal at time t0; G(t0)=1 means that at time t0, the state of the traffic signal is green; G(t0)=0 means that at time t0, the state of the traffic signal is not green; K pass is a feasible time period; s stop is the location of the traffic light; a min is the minimum value of acceleration; a max is the maximum value of acceleration.

3. The ecological driving method considering signal control uncertainty according to claim 2, characterized in that: In S2, the control time domain is the control time domain T of the vehicle decision control model in S1, and the calculation formula is: T=KΔτ Assuming that within the range T, the traffic signal only switches light color once, obtain the probability that the traffic signal is green at the kth step and express it as 4. The ecological driving method considering signal control uncertainty according to claim 3, characterized in that: In S3, calculating the feasible time period specifically includes the following steps: S31) Calculate the switching probability of the traffic signal at the kth step The calculation formula is as follows: in, represents the probability of a green light in the kth step; represents the probability that the light is red after the kth step; represents the probability that the light is red in the kth step; represents the probability that the light is green after the kth step; S32) Calculate the switching probability F(k) of the traffic signal in the kth step, and the calculation formula is as follows: S33) Define the feasible time period K pass , the mathematical expression is as follows: Among them, k sw K pass upper or lower limit. S34) User-defined risk factor γ Among them, γ represents the pass The vehicle in the intersection can pass smoothly; then, when G(t0) = 1, the formula is expressed as "at K pass The probability that the vehicle can successfully pass through the intersection is at least γ”, which is F(k sw )≤1-γ; when G(t0)=0, it is expressed by the formula "at K pass The probability that the vehicle can successfully pass through the intersection is at least γ”, which is F(k sw ) ≥ γ; S35) Calculate k sw , the calculation formula is as follows: Among them, F -1 is the inverse function of F.

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