CN115424433B - Method for describing following behavior of networked vehicles in multi-vehicle type hybrid traffic - Google Patents
Method for describing following behavior of networked vehicles in multi-vehicle type hybrid traffic Download PDFInfo
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
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- G08G1/00—Traffic control systems for road vehicles
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Abstract
The application provides a method for describing following behavior of a networked vehicle in multi-vehicle type hybrid traffic, and belongs to the technical field of intelligent traffic information. The method comprises the following steps of obtaining the motion parameters of the following vehicles and the leading vehicles of the observation road section at the moment t and the moment t+Deltat in the network connection scene; calculating the speed difference and the position difference of the following vehicle and the leading vehicle of the observation road section at the moment t and the average speed of the traffic flow at the moment t according to the acquired motion parameters; according to the combination type of the following vehicle pair of the observation road section at the moment t, calculating the influence of the leading vehicle on the vehicle type factor of the following vehicle; calculating the expected following distance of the following vehicle at the moment t according to the acquired motion parameters and the influence of the leading vehicle at the moment t on the vehicle type factors of the following vehicle; and calculating the acceleration of the following vehicle at the time t+T according to the data obtained in the steps, so as to describe the motion state of the following vehicle. The application simulates and analyzes the dynamic operation rule of the traffic system and provides theoretical basis for traffic management and control.
Description
Technical Field
The application belongs to the technical field of intelligent traffic information, and particularly relates to a method for describing following behavior of a networked vehicle in multi-vehicle type hybrid traffic.
Background
The traffic system is continuously developed towards the direction of intellectualization and networking, and the networking technology plays an extremely important role in various fields of the traffic system. On the other hand, because of large vehicle volume and poor performance, psychological stress is caused to surrounding drivers. For novel mixed traffic, the vehicle type factors and the network connection factors can jointly influence the dynamic evolution characteristics of traffic, and the interaction relationship between vehicles is more complex. Therefore, the novel hybrid traffic network vehicle following behavior mixed by multiple vehicles is depicted and described, so that theoretical basis is provided for traffic management and control, and the method has important significance.
The prior art CN109978260a discloses a method for predicting the following behavior of a network-connected vehicle under mixed traffic, which determines the following state of the target network-connected vehicle by considering the direct influence of the running state of a lead vehicle on the target network-connected vehicle and the direct influence of the running state of the network-connected vehicle within a communicable range on the target network-connected vehicle, wherein the running state includes speed, position and acceleration. The method can also be used for describing and describing the following behavior of the internet-connected vehicle, however, the method is not fully considered for the following behavior difference of the internet-connected vehicle under the common influence of the internet-connected vehicle and the vehicle type factors.
Disclosure of Invention
In view of the above, the application aims to provide a method for describing the following behavior of a networked vehicle in multi-vehicle type hybrid traffic, which solves the problems that the joint influence of the vehicle type and the networked factor in the novel hybrid traffic is rarely comprehensively considered at present, and how to describe the following behavior of the networked vehicle by taking the networked heterogeneity and the vehicle type heterogeneity as cut-in points is explored.
To achieve the above object, the present application is provided as follows: the method for describing the following behavior of the networked vehicle in the mixed traffic of multiple vehicle types comprises the following steps:
acquiring motion parameters of the following vehicles and the leading vehicles of the observation road section at the time t and the time t+Deltat under the network scene; the motion parameters comprise the speed v of the following car at the moment t i (t) and position x i Speed v of lead vehicle at time (t) and t i+1 (t) and position x i+1 Speed v of following car at time t+Deltat i (t+△t)；
Calculating the speed difference and the position difference of the following vehicle and the leading vehicle of the observation road section at the moment t and the average speed of the traffic flow of the observation road section at the moment t according to the acquired motion parameters;
calculating the influence of the lead vehicle at the time t on the vehicle type factor of the following vehicle according to the combination type of the following vehicle of the observation road section at the time t;
calculating the expected following distance of the following vehicle at the moment t according to the acquired motion parameters and the influence of the leading vehicle at the moment t on the vehicle type factors of the following vehicle;
calculating the stimulus lambda of the position difference of the t-moment observation road section following vehicle and the lead vehicle to the following vehicle driver according to the position difference of the t-moment observation road section following vehicle and the lead vehicle and the expected following distance of the following vehicle 1 ；
Calculating the stimulus lambda of the speed difference of the t-moment observation road section following vehicle and the lead vehicle to the following vehicle driver according to the speed difference of the t-moment observation road section following vehicle and the lead vehicle 2 ；
Observing the speed v of the following car of the road section according to the time t i (t) and calculating the average speed of the traffic flow the stimulus lambda of the average speed of the traffic flow of the observation road section at the moment t to the following car driver 3 ；
According to the position difference of the following car and the leading car of the observation road section at the moment t, the following car driver is stimulated by lambda 1 The speed difference between the following car and the leading car of the observation road section at the moment t stimulates lambda of the following car driver 2 And the stimulus lambda of the average speed of the traffic flow of the observation road section at the moment t to the following car driver 3 And calculating the acceleration of the following vehicle at the time t+T so as to describe the motion state of the following vehicle.
Further, the speed difference and the position difference between the following car and the leading car of the observation road section at the time t are shown as follows:
wherein:
v i (t) represents the speed of the following car of the observation road section at the moment t;
x i (t) represents the position of the observation road section following the car at the moment t;
v i+1 (t) represents the speed of the lead vehicle of the observation road section at the moment t;
x i+1 (t) represents the position of the lead vehicle of the observation road section at the moment t;
△x i (t) represents the position difference between the following car and the leading car of the observation road section at the moment t;
△v i and (t) represents the speed difference between the following car and the leading car of the observation road section at the moment t.
Further, the average speed of the traffic flow of the section of the observation at the moment tThe specific calculation formula is as follows:
in the method, in the process of the application,
n represents the total number of vehicles observing the road section traffic flow at the moment t;
v j the speed of the j-th vehicle of the observation section at time t is represented, wherein j=1, 2,3, …, N.
Further, the following vehicle pair combination type comprises one type of a large vehicle following large vehicle (H-H), a small vehicle following large vehicle (C-H), a large vehicle following small vehicle (H-C) or a small vehicle following small vehicle (C-C).
Further, the influence of the lead vehicle at the time t on the vehicle type factor of the following vehicle is shown as follows:
in the method, in the process of the application,
α HH representing a correction coefficient of a large vehicle following a large vehicle (H-H) scene;
α CH representing a correction coefficient in a scene that a small vehicle follows a large vehicle (C-H);
α HC representing a correction coefficient of a large vehicle following a small vehicle (H-C) scene;
α CC representing a correction coefficient in a small car-following small car (C-C) scene;
ξ i+1 representing the influence coefficient of the vehicle type;
the vehicle type of the leading vehicle is represented, when the value is 1, the vehicle is represented as a large vehicle, and when the value is 0, the vehicle is represented as a small vehicle;
the vehicle type of the following vehicle is represented, when the value is 1, the vehicle is a large vehicle, and when the value is 0, the vehicle is a small vehicle;
γ c,i representing the leading vehicle versus the following vehicleThe influence of the vehicle model factor is a constant.
Further, the expected following distance of the following vehicle at the time t is shown as the following specific calculation formula:
in the method, in the process of the application,
v i (t) represents the speed of the following car of the observation road section at the moment t;
v i+1 (t) represents the speed of the lead vehicle of the observation road section at the moment t;
Δt represents the reaction time of the driver with the car;
a i,max indicating a maximum deceleration of the following vehicle;
a i+1,max indicating the maximum deceleration of the lead vehicle;
m represents a preset value;
mu represents a network connection influence coefficient;
l i+1 representing the length of the lead vehicle;
d 3 representing a vehicle safety distance when stationary;
v i and (t+Deltat) represents the speed of the following car of the observation road section at the moment t+Deltat.
Further, the t+T moment follows the acceleration a of the car i (t+T), the specific calculation formula is as follows:
a i (t+T)＝λ 1 +λ 2 -λ 3 ，
wherein:
λ 1 the stimulus of the position difference of the following car and the leading car of the observation road section at the moment t to the following car driver is shown;
λ 2 the stimulus of the speed difference of the following car and the leading car of the observation road section at the moment t to the following car driver is shown;
λ 3 the stimulus of the average speed of the observed road section traffic flow to the following driver at the time t is shown.
Further, the following car and the leading car of the t-moment observation road sectionIs a stimulus lambda to the driver of the following car 1 The specific calculation formula is as follows:
λ 1 ＝C 1 ξ i+1 [(△x i (t)-h i+1,i (t)]μ，
in the method, in the process of the application,
C 1 representing a preset value;
ξ i+1 representing the influence coefficient of the vehicle type;
△x i (t) represents the position difference between the following car and the leading car of the observation road section at the moment t;
h i+1,i (t) represents the desired following distance of the following vehicle at the time t;
mu represents a network connection influence coefficient;
further, the speed difference between the following car and the leading car of the t-moment observation road section stimulates lambda of the following car driver 2 The specific calculation formula is as follows:
λ 2 ＝C 2 μ△v i (t)，
in the method, in the process of the application,
C 2 representing a preset value;
mu represents a network connection influence coefficient;
△v i (t) represents the speed difference between the following car and the leading car of the observation road section at the moment t;
further, the average speed of the traffic flow of the observation road section at the moment t stimulates lambda of the following car driver 3 The specific calculation formula is as follows:
in the method, in the process of the application,
C 3 is a preset value;
v i (t) represents the speed of the following car of the observation road section at the moment t;
vehicle level indicating observation road section at time tAverage speed.
Advantageous effects
The method fully considers the single car information and the car flow information acquired in the network environment and the composition of the car types in the mixed traffic, takes the network heterogeneity and the car type heterogeneity as cut-in points, and realizes the accurate depiction of the network car following behavior under the condition of different car following combination types. The application can describe and describe the network vehicle following behavior of different vehicle following pair combination types, thereby simulating and analyzing the dynamic operation rule of the traffic system and providing theoretical basis for traffic management and control.
Drawings
Fig. 1 is a flow chart of a method for describing following behavior of a networked vehicle in mixed traffic of multiple vehicles in an embodiment.
Detailed Description
In order to make the technical scheme, advantages and objects of the present application more clear, the technical scheme of the embodiment of the present application will be clearly and completely described below with reference to the accompanying drawings of the embodiment of the present application. It will be apparent that the described embodiments are some, but not all, embodiments of the application. All other embodiments, which can be obtained by a person skilled in the art without creative efforts, based on the described embodiments of the present application belong to the protection scope of the present application.
The application is further described below with reference to the drawings and examples.
Examples
As shown in fig. 1, the embodiment provides a method for describing following behavior of a networked vehicle in mixed traffic of multiple vehicles, which includes the following steps:
and 1) calculating the speed difference and the position difference of the following car and the leading car and the average speed of the traffic flow of the observation road section at the moment t under the networking scene.
The method specifically comprises the following steps:
s1.1, acquiring the speed v of the following car of the observation road section at the moment t under the networking scene i (t) and position x i (t)，Observing speed v of road section leading vehicle at time t i+1 (t) and position x i+1 (t)；
S1.2, calculating the speed difference and the position difference of the following car and the leading car of the observation road section at the moment t, wherein the specific calculation formula is as follows:
wherein:
v i (t) represents the speed of the following car of the observation road section at the moment t;
x i (t) represents the position of the observation road section following the car at the moment t;
v i+1 (t) represents the speed of the lead vehicle of the observation road section at the moment t;
x i+1 (t) represents the position of the lead vehicle of the observation road section at the moment t;
△x i (t) represents the position difference between the following car and the leading car of the observation road section at the moment t;
△v i and (t) represents the speed difference between the following car and the leading car of the observation road section at the moment t.
S1.3 calculating the average speed of the traffic flow of the observation road section at the moment t
In the method, in the process of the application,
n represents the total number of vehicles observing the road section traffic flow at the moment t;
v j the speed of the j-th vehicle of the observation section at time t is represented, wherein j=1, 2,3, …, N.
And 2) calculating the influence of the lead vehicle at the moment t on the vehicle type factor of the following vehicle according to the combination type of the following vehicle pair of the observation road section at the moment t.
The method specifically comprises the following steps:
s2.1, determining a following vehicle pair combination type, wherein the following vehicle pair combination type comprises one type of a large vehicle following large vehicle (H-H), a small vehicle following large vehicle (C-H), a large vehicle following small vehicle (H-C) or a small vehicle following small vehicle (C-C). S2.2, calculating the influence of the lead vehicle at the t moment on the vehicle type factor of the following vehicle, wherein the specific calculation formula is as follows:
in the method, in the process of the application,
α HH representing a correction coefficient of a large vehicle following a large vehicle (H-H) scene;
α CH representing a correction coefficient in a scene that a small vehicle follows a large vehicle (C-H);
α HC representing a correction coefficient of a large vehicle following a small vehicle (H-C) scene;
α CC representing a correction coefficient in a small car-following small car (C-C) scene;
ξ i+1 representing the influence coefficient of the vehicle type, wherein the value range is 1-1.7, the smaller value in the value range is taken by the small vehicle, the larger value in the value range is taken by the large vehicle, and the value of the small vehicle is smaller than the value of the large vehicle;
the vehicle type of the leading vehicle is represented, when the value is 1, the vehicle is represented as a large vehicle, and when the value is 0, the vehicle is represented as a small vehicle;
the vehicle type of the following vehicle is represented, when the value is 1, the vehicle is a large vehicle, and when the value is 0, the vehicle is a small vehicle;
γ c the influence of the lead vehicle on the vehicle type factor of the following vehicle is expressed and is a constant for correcting the expected following distance of the following vehicle.
And 3) calculating the expected following distance of the following vehicle at the moment t according to the influence of the speed of the following vehicle and the leading vehicle on the vehicle type factor of the following vehicle at the observation road section at the moment t.
S3.1, obtaining the speed v of the following car of the observation road section at the time t+Deltat under the networking scene i (t+△t)；
S3.2, calculating expected following distance h of the following vehicle at time t i+1,i (t) the specific calculation formula is as follows:
in the method, in the process of the application,
v i (t) represents the speed of the following car of the observation road section at the moment t;
v i+1 (t) represents the speed of the lead vehicle of the observation road section at the moment t;
Δt represents the reaction time of the driver with the car;
a i,max indicating a maximum deceleration of the following vehicle;
a i+1,max indicating the maximum deceleration of the lead vehicle;
m represents a preset value, and the value of the value can be modified according to specific conditions;
mu represents a network connection influence coefficient, and the value of the mu can be modified according to specific conditions;
l i+1 representing the length of the lead vehicle;
d 3 representing a vehicle safety distance when stationary;
v i and (t+Deltat) represents the speed of the following car of the observation road section at the moment t+Deltat.
And 4) calculating the acceleration of the following vehicle at the time t+T according to the data obtained in the step, so as to describe the motion state of the following vehicle.
The method specifically comprises the following steps:
s4.1, calculating stimulus lambda of the position difference of the following car and the leading car of the observation road section at the moment t to the following car driver 1 The specific calculation formula is as follows:
λ 1 ＝C 1 ξ i+1 [(△x i (t)-h i+1,i (t)]μ
in the method, in the process of the application,
C 1 representing a preset value, wherein the value can be modified according to specific conditions;
ξ i+1 representing the influence coefficient of the vehicle type, wherein the value range is 1-1.7, the smaller value in the value range is taken by the small vehicle, the larger value in the value range is taken by the large vehicle, and the value of the small vehicle is smaller than the value of the large vehicle;
△x i (t) represents the position difference between the following car and the leading car of the observation road section at the moment t;
h i+1,i (t) represents the desired following distance of the following vehicle at the time t;
mu represents a network connection influence coefficient, and the value of the mu can be modified according to specific conditions;
s4.2, calculating stimulus lambda of speed difference of the following car and the leading car of the observation road section at the moment t to the following car driver 2 The specific calculation formula is as follows:
λ 2 ＝C 2 μ△v i (t)
in the method, in the process of the application,
C 2 representing a preset value, wherein the value can be modified according to specific conditions;
mu represents a network connection influence coefficient, and the value of the mu can be modified according to specific conditions;
△v i (t) represents the speed difference between the following car and the leading car of the observation road section at the moment t;
s4.3 calculating the stimulus lambda of the average speed of the traffic flow of the observation road section at the moment t to the following car driver 3 The specific calculation formula is as follows:
in the method, in the process of the application,
C 3 the value of the preset value can be modified according to specific conditions;
v i (t) represents the speed of the following car of the observation road section at the moment t;
the average speed of the traffic flow of the observation road section at the moment t is represented;
s4.4 calculating the acceleration a of the following car at the next time t+T i (t+T), the specific calculation formula is as follows:
a i (t+T)＝λ 1 +λ 2 -λ 3
i.e.
In summary, the method for describing the following behavior of the internet-connected vehicle in the multi-vehicle type hybrid traffic fully considers the single vehicle information and the vehicle flow information acquired in the internet-connected environment and the composition of the vehicle types in the hybrid traffic, and realizes the accurate description of the following behavior of the internet-connected vehicle under the condition of different following vehicle combination types by taking the internet-connected heterogeneity and the vehicle type heterogeneity as cut-in points. The application can describe and describe the network vehicle following behavior of different vehicle following pair combination types, thereby simulating and analyzing the dynamic operation rule of the traffic system and providing theoretical basis for traffic management and control.
Finally, it is noted that the above embodiments are only for illustrating the technical solution of the present application and not for limiting the same, and although the present application has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solution of the present application may be modified or substituted without departing from the spirit and scope of the technical solution, and the present application is intended to be covered in the scope of the present application.
Claims (7)
1. A method for describing following behavior of a networked vehicle in multi-vehicle type hybrid traffic is characterized by comprising the following steps of: the method comprises the following steps:
acquiring motion parameters of the following vehicles and the leading vehicles of the observation road section at the moment t and the moment t+delta t in the network scene; the motion parameters comprise the speed v of the following car at the moment t i (t) and position x i (t)、Speed v of lead car at time t i+1 (t) and position x i+1 Speed v of following car at time t+Deltat i (t+Δt)；
Calculating the speed difference and the position difference of the following vehicle and the leading vehicle of the observation road section at the moment t and the average speed of the traffic flow of the observation road section at the moment t according to the acquired motion parameters;
calculating the influence of the lead vehicle at the time t on the vehicle type factor of the following vehicle according to the combination type of the following vehicle of the observation road section at the time t;
the influence of the lead vehicle at the time t on the vehicle type factor of the following vehicle is shown as follows:
in the method, in the process of the application,
α HH representing a correction coefficient of a large-sized vehicle in a H-H scene of the large-sized vehicle;
α CH representing a correction coefficient of a small-sized vehicle in a C-H scene following a large-sized vehicle;
α HC representing a correction coefficient of a large-sized vehicle in a H-C scene following a small-sized vehicle;
α CC representing a correction coefficient of the small car in a C-C scene of the small car;
ξ i+1 representing the influence coefficient of the vehicle type;
the vehicle type of the leading vehicle is represented, when the value is 1, the vehicle is represented as a large vehicle, and when the value is 0, the vehicle is represented as a small vehicle;
the vehicle type of the following vehicle is represented, when the value is 1, the vehicle is a large vehicle, and when the value is 0, the vehicle is a small vehicle;
γ c the influence of the leading vehicle at the time t on the vehicle type factor of the following vehicle is expressed as oneA constant;
calculating the expected following distance of the following vehicle at the moment t according to the acquired motion parameters and the influence of the leading vehicle at the moment t on the vehicle type factors of the following vehicle;
the expected following distance of the following vehicle at the time t is shown as follows:
in the method, in the process of the application,
v i (t) represents the speed of the following car of the observation road section at the moment t;
v i+1 (t) represents the speed of the lead vehicle of the observation road section at the moment t;
Δt represents the reaction time of the driver with the car;
a i,max indicating a maximum deceleration of the following vehicle;
a i+1,max indicating the maximum deceleration of the lead vehicle;
m represents a preset value;
mu represents a network connection influence coefficient;
l i+1 representing the length of the lead vehicle;
d 3 representing a vehicle safety distance when stationary;
v i (t+Δt) represents the speed of the following vehicle of the observation road section at the time t+Δt;
calculating the stimulus lambda of the position difference of the t-moment observation road section following vehicle and the lead vehicle to the following vehicle driver according to the position difference of the t-moment observation road section following vehicle and the lead vehicle and the expected following distance of the following vehicle 1 ；
Calculating the stimulus lambda of the speed difference of the t-moment observation road section following vehicle and the lead vehicle to the following vehicle driver according to the speed difference of the t-moment observation road section following vehicle and the lead vehicle 2 ；
Observing the speed v of the following car of the road section according to the time t i (t) and calculating the average speed of the traffic flow the stimulus lambda of the average speed of the traffic flow of the observation road section at the moment t to the following car driver 3 ；
According to the position difference of the following car and the leading car of the observation road section at the moment t, the following car driver is stimulated by lambda 1 The speed difference between the following car and the leading car of the observation road section at the moment t stimulates lambda of the following car driver 2 And the stimulus lambda of the average speed of the traffic flow of the observation road section at the moment t to the following car driver 3 Calculating acceleration of the following vehicle at the time t+T so as to describe the motion state of the following vehicle;
the time t+T is equal to the acceleration a of the car i (t+T), the specific calculation formula is as follows:
a i (t+T)＝λ 1 +λ 2 -λ 3 ，
wherein:
λ 1 the stimulus of the position difference of the following car and the leading car of the observation road section at the moment t to the following car driver is shown;
λ 2 the stimulus of the speed difference of the following car and the leading car of the observation road section at the moment t to the following car driver is shown;
λ 3 the stimulus of the average speed of the observed road section traffic flow to the following driver at the time t is shown.
2. The method for describing the following behavior of the networked vehicle in the mixed traffic of multiple vehicles according to claim 1, wherein the method comprises the following steps of: the speed difference and the position difference of the following car and the leading car of the observation road section at the moment t are shown as follows:
wherein:
v i (t) represents the speed of the following car of the observation road section at the moment t;
x i (t) represents the position of the observation road section following the car at the moment t;
v i+1 (t) represents the speed of the lead vehicle of the observation road section at the moment t;
x i+1 (t) represents the position of the lead vehicle of the observation road section at the moment t;
Δx i (t) represents the position difference between the following car and the leading car of the observation road section at the moment t;
Δv i and (t) represents the speed difference between the following car and the leading car of the observation road section at the moment t.
3. The method for describing the following behavior of the networked vehicle in the mixed traffic of multiple vehicles according to claim 2, wherein the method comprises the following steps of: the average speed of the traffic flow of the road section is observed at the moment tThe specific calculation formula is as follows:
in the method, in the process of the application,
n represents the total number of vehicles observing the road section traffic flow at the moment t;
v j the speed of the j-th vehicle of the observation road section at time t is indicated, where j=1, 2, 3.
4. The method for describing following behavior of a multi-vehicle type hybrid vehicle in-traffic internet-connected vehicle according to claim 3, wherein the method comprises the following steps of: the following vehicle pair combination type comprises one type of a large vehicle following large vehicle H-H, a small vehicle following large vehicle C-H, a large vehicle following small vehicle H-C or a small vehicle following small vehicle C-C.
5. The method for describing the following behavior of the networked vehicle in the mixed traffic of multiple vehicles according to claim 4, wherein the following behavior describing method is characterized by comprising the following steps of: the position difference of the following car and the front guide car of the observation road section at the moment t stimulates lambda of the driver of the following car 1 The specific calculation formula is as follows:
λ 1 ＝C 1 ξ i+1 [(Δx i (t)-h i+1,i (t)]μ，
in the method, in the process of the application,
C 1 representing a preset value;
ξ i+1 representing the influence coefficient of the vehicle type;
Δx i (t) represents the position difference between the following car and the leading car of the observation road section at the moment t;
h i+1,i (t) represents the desired following distance of the following vehicle at the time t;
mu represents the network connection influence coefficient.
6. The method for describing the following behavior of the networked vehicle in the mixed traffic of multiple vehicles according to claim 4, wherein the following behavior describing method is characterized by comprising the following steps of: the speed difference between the following car and the leading car of the observation road section at the moment t stimulates lambda of the following car driver 2 The specific calculation formula is as follows:
λ 2 ＝C 2 μΔv i (t)，
in the method, in the process of the application,
C 2 representing a preset value;
mu represents a network connection influence coefficient;
Δv i and (t) represents the speed difference between the following car and the leading car of the observation road section at the moment t.
7. The method for describing the following behavior of the networked vehicle in the mixed traffic of multiple vehicles according to claim 4, wherein the following behavior describing method is characterized by comprising the following steps of: the average speed of the traffic flow of the observation road section at the moment t stimulates lambda of the following car driver 3 The specific calculation formula is as follows:
in the method, in the process of the application,
C 3 is a preset value;
v i (t) represents the speed of the following car of the observation road section at the moment t;
and the average speed of the traffic flow of the observation road section at the time t is shown.
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