CN112767715A - Intersection traffic signal lamp and intelligent networked automobile cooperative control method - Google Patents

Intersection traffic signal lamp and intelligent networked automobile cooperative control method Download PDF

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CN112767715A
CN112767715A CN202011590023.4A CN202011590023A CN112767715A CN 112767715 A CN112767715 A CN 112767715A CN 202011590023 A CN202011590023 A CN 202011590023A CN 112767715 A CN112767715 A CN 112767715A
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time
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CN112767715B (en
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钱立军
陈健
吴冰
宣亮
陈晨
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Hefei University of Technology
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    • G—PHYSICS
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    • G08G1/00—Traffic control systems for road vehicles
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    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/07—Controlling traffic signals
    • G08G1/08—Controlling traffic signals according to detected number or speed of vehicles
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    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/07—Controlling traffic signals
    • G08G1/081—Plural intersections under common control
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Abstract

The invention discloses a cooperative control method of a crossroad traffic signal lamp and an intelligent networked automobile, which comprises the following steps: acquiring intelligent networking automobile information in a communication range of an intersection; establishing an arrival time optimization model of the vehicle arriving at the intersection, and solving the optimal arrival time of the vehicle arriving at the intersection by using the vehicle information; sequencing all vehicles arriving at the intersection to obtain a sequence of the vehicles passing through the intersection in sequence; establishing a signal lamp optimization model, and solving by using vehicle information, optimal arrival time and a sequence of vehicles passing through an intersection to obtain an optimal signal lamp state; establishing a speed track optimization model of the vehicle, and solving by using vehicle information and the optimal signal lamp state to obtain an optimal speed track; and realizing cooperative control of the signal lamp and the vehicle by using the optimal signal lamp state and the optimal vehicle speed track. The invention can comprehensively improve the traffic capacity of the intersection and the fuel economy of the vehicle by cooperatively controlling the traffic signal lamp of the intersection and the intelligent networked automobile.

Description

Intersection traffic signal lamp and intelligent networked automobile cooperative control method
Technical Field
The invention relates to the field of intelligent traffic systems, in particular to a cooperative control method of intersection traffic lights and an intelligent networked automobile.
Background
With the increase of the number of vehicles in the world, urban traffic, particularly intersections, face the problems of traffic jam, environmental pollution, frequent traffic accidents and the like, and huge social and economic losses are caused. Meanwhile, traffic jam causes frequent acceleration and deceleration and idling of vehicles, and fuel consumption and emission pollution are aggravated. In recent years, the development of intelligent networking technology has provided a new opportunity to solve the above problems, and vehicles approaching an intersection can acquire signal light states, adjacent vehicle information and front road information through vehicle-vehicle communication (V2V) and vehicle-infrastructure communication (V2I), thereby optimizing their own speed trajectory. In addition, the traffic signal controller may also acquire information about vehicles approaching the intersection to optimize the signal light conditions.
The current intersection control is mostly focused on single signal lamp or vehicle speed track optimization control research, however, the intersection is taken as a system, the signal lamp and the vehicle are taken as two key elements which are mutually influenced, and the single optimization of one element cannot achieve the overall optimization, for example, in a high traffic flow scene, the intersection passing efficiency can be deteriorated due to the fact that only the vehicle speed track is optimized. In addition, the optimization target of the current intersection control is mostly focused on improving the traffic capacity of the intersection, but as the number of vehicles on the road increases, the problems of oil resource shortage and environmental pollution caused by vehicle fuel consumption become more and more serious, and how to reduce the vehicle fuel consumption while ensuring the traffic efficiency of the intersection is a major problem for the current intersection control.
Disclosure of Invention
The invention aims to overcome the defects in the prior art, and provides a cooperative control method of a traffic signal lamp of an intersection and an intelligent networked automobile, so that the traffic efficiency of the intersection can be ensured, and the fuel consumption of vehicles can be reduced, thereby relieving the problems of traffic jam, environmental pollution, resource shortage and the like faced by the current urban traffic and realizing green sustainable development.
The invention adopts the following technical scheme for solving the technical problems:
the invention discloses a cooperative control method of a crossroad traffic signal lamp and an intelligent networked automobile, which is characterized by comprising the following steps of:
step 1: acquiring intelligent networking automobile information in a communication range of an intersection; the intelligent networking automobile information comprises: the current speed, the lane and the distance between the current position and the stop line;
step 2: establishing an arrival time optimization model of the vehicle arriving at the intersection with the aim of minimizing the travel time and the fuel consumption of a single vehicle, so that the optimal arrival time of the vehicle arriving at the intersection is solved by utilizing the intelligent networked automobile information;
and step 3: sequencing all vehicles arriving at the intersection according to the intelligent network connection automobile information to obtain a sequence of the vehicles passing through the intersection in sequence;
and 4, step 4: establishing a signal lamp optimization model aiming at minimizing the travel time and fuel consumption of all vehicles at the intersection, so that the optimal signal lamp state is obtained by utilizing the intelligent network connection automobile information, the optimal arrival time and the sequence of vehicles passing through the intersection in sequence;
and 5: establishing a speed track optimization model of the vehicle, and solving by using the intelligent networked automobile information and the optimal signal lamp state to obtain an optimal speed track;
step 6: and realizing cooperative control of the signal lamp and the vehicle by using the optimal signal lamp state and the optimal vehicle speed track.
The invention relates to a cooperative control method of a crossroad traffic signal lamp and an intelligent networked automobile, which is characterized in that an arrival time optimization model of a vehicle arriving at the crossroad in the step 2 is shown as the formula (1):
Figure BDA0002868672380000021
in the formula (1), ω is a weight coefficient indicating the specific gravity of the travel time and the fuel consumption,
Figure BDA0002868672380000022
the travel time for a vehicle i on lane L to reach the intersection,
Figure BDA0002868672380000023
the fuel consumption of a vehicle i on a lane L reaching the intersection is shown, i is the vehicle serial number, and L is the lane number.
The driving working conditions of the vehicle i on the lane L to reach the intersection are divided into acceleration passing through the intersection, constant speed passing through the intersection and deceleration passing through the intersection;
when accelerating through the intersection, the travel time of the vehicle is calculated by using the formula (2)
Figure BDA0002868672380000024
Figure BDA0002868672380000025
In the formula (2), the reaction mixture is,
Figure BDA0002868672380000026
the distance of the vehicle i on the lane L from the stop line at the intersection,
Figure BDA0002868672380000027
is the speed of the vehicle i in the lane L,
Figure BDA0002868672380000028
is the acceleration, v, of the vehicle i on the lane LtarA vehicle target speed;
when the uniform speed passes through the intersection, the travel time of the vehicle is calculated by the formula (3)
Figure BDA0002868672380000029
Figure BDA00028686723800000210
When the vehicle is decelerated and passes through the intersection, the travel time of the vehicle is calculated by the formula (4)
Figure BDA00028686723800000211
Figure BDA00028686723800000212
The signal lamp optimization model in the step 4 is as shown in formula (5):
Figure BDA0002868672380000031
in the formula (5), N is the total number of vehicles at the intersection, j is the position of the vehicle in the sequence R passing through the intersection, and τjIdle time of a vehicle with j in a sequence R passing through an intersection, ejThe energy consumption of the vehicle at j in the sequence R passing through the intersection due to parking and idling is shown.
The idle time tau of the vehicle with j in the sequence R of passing intersectionsjCalculated from equation (6):
τj＝tj,new-tj,opt (6)
in the formula (6), tj,optFor the optimal arrival time, t, of a vehicle with j in the sequence R passing through the intersectionj,newThe vehicle arrival time calculated according to the running condition of a front vehicle j-1 for a vehicle with j in a sequence R passing through the intersection is as follows:
Figure BDA0002868672380000032
in the formula (7), tj-1,newThe vehicle arrival time p calculated according to the running condition of the front vehicle j-2 for the vehicle with j-1 in the sequence R passing through the intersectionj-1The time for the vehicle with the position j-1 in the sequence R passing through the intersection to pass through the intersection is C, the time required by signal lamp phase switching is zero when the current vehicle j-1 is in the same lane.
Energy consumption e caused by parking and idling of the vehicle with j in the sequence R of passing intersectionsjCalculated from equation (8):
Figure BDA0002868672380000033
in the formula (8), KjIs the energy consumption rate at idle of a vehicle with j in a sequence R passing through an intersection, BjThe energy loss due to parking is caused by a vehicle at j in the sequence R passing through the intersection.
The speed trajectory optimization model of the vehicle in the step 5 is shown as equation (9) to equation (11):
Figure BDA0002868672380000034
Figure BDA0002868672380000035
Figure BDA0002868672380000036
in the formula (9) -formula (11), ω is1，ω2，ω3And ω4Is four weight coefficients, T is the prediction time length, and T is the expression timeThe variable of (a) is selected,
Figure BDA0002868672380000037
the distance traveled by vehicle i in lane L at time k + T-1,
Figure BDA0002868672380000038
the distance traveled by vehicle i in lane L at time k,
Figure BDA0002868672380000041
the fuel consumed by the vehicle i in the lane L at the time t,
Figure BDA0002868672380000042
the speed, v, of a vehicle i on a lane L at time ttar(t) is the target vehicle speed of the vehicle i on the lane L at time t,
Figure BDA0002868672380000043
acceleration, v, of a vehicle i on a lane L at time tminAnd vmaxFor road minimum and maximum speed limits, aminAnd amaxThe minimum and maximum values of the vehicle acceleration,
Figure BDA0002868672380000044
is the distance between the vehicle i on the lane L and the front vehicle i-1, and comprises:
Figure BDA0002868672380000045
in the formula (12), S0For front and rear vehicle safety distance, thThe time interval of the vehicle head is the time interval,
Figure BDA0002868672380000046
is the speed of vehicle i-1 on lane L at time t,
Figure BDA0002868672380000047
the distance traveled by vehicle i in lane L at time t,
Figure BDA0002868672380000048
is the distance traveled by vehicle i-1 in lane L at time t.
Compared with the prior art, the invention has the beneficial effects that:
1. under the intelligent networking environment, through establishing signal lamp optimization model and vehicle speed orbit optimization model, realized the cooperative control of intersection traffic signal lamp with the vehicle, compare in single signal lamp or vehicle orbit optimization control, cooperative control's whole optimization effect is better to the current efficiency at intersection and the fuel economy of vehicle have effectively been promoted.
2. In the optimization target of the cooperative control of the traffic signal lamp and the vehicle, the traffic capacity of the intersection is considered, and the fuel consumption of the vehicle is considered, so that the performance of the intersection is comprehensively improved.
Drawings
FIG. 1 is a schematic diagram of the cooperative control of traffic signal lamps at crossroads and intelligent networked automobiles of the present invention;
FIG. 2 is a flow chart of the cooperative control of the traffic signal lamp at the intersection and the intelligent networked automobile of the invention;
FIG. 3a illustrates two scenarios of the present invention wherein a vehicle accelerates through an intersection;
FIG. 3b illustrates two scenarios of the present invention where the vehicle is decelerating through an intersection;
FIG. 4a is a graph of vehicle travel time simulation test results at a single lane intersection in accordance with the present invention;
FIG. 4b is a graph of the results of a vehicle fuel consumption simulation test at a single lane intersection in accordance with the present invention.
Detailed Description
In this embodiment, a method for cooperatively controlling a traffic signal lamp at an intersection and an intelligent networked automobile includes, as shown in fig. 2, the following steps:
step 1: acquiring intelligent networking automobile information in a communication range of an intersection; the intelligent networking automobile information comprises: the current speed, the lane and the distance between the current position and the stop line;
as shown in fig. 1, the roadside unit obtains intelligent networked automobile information within the communication range of the intersection through dedicated short-range communication (DSRC), 5G communication, V2I communication such as a camera and a radar and sensor technology, and is used for optimizing the arrival time and the signal lamp state of the automobile.
Step 2: establishing an arrival time optimization model of the vehicle arriving at the intersection with the aim of minimizing the travel time and the fuel consumption of a single vehicle as a target, wherein the model is shown as a formula (1), so that the optimal arrival time of the vehicle arriving at the intersection is solved by utilizing the intelligent networked automobile information;
Figure BDA0002868672380000051
in the formula (1), ω is a weight coefficient indicating the specific gravity of the travel time and the fuel consumption,
Figure BDA0002868672380000052
the travel time for a vehicle i on lane L to reach the intersection,
Figure BDA0002868672380000053
the fuel consumption of a vehicle i on a lane L reaching the intersection is shown, i is the vehicle serial number, and L is the lane number.
From the perspective of a vehicle, assuming that the vehicle accelerates or decelerates at a constant acceleration, the way the vehicle reaches an intersection can be divided into three conditions: 1) accelerating to reach the intersection; 2) reaching the intersection at a constant speed at the current speed; 3) the speed is reduced to reach the intersection. When the vehicle arrives at the intersection with acceleration or deceleration, two cases can be distinguished. Case 1: when the vehicle is relatively close to the intersection, the vehicle accelerates or decelerates through the intersection at a constant acceleration. Case 2: when the vehicle is far enough away from the intersection, the vehicle can accelerate or decelerate to the target speed, and then pass through the intersection at the constant speed of the target speed. Fig. 3a shows two cases where the vehicle accelerates through the intersection, and fig. 3b shows two cases where the vehicle decelerates through the intersection.
When accelerating through the intersection, the travel time of the vehicle is calculated by using the formula (2)
Figure BDA0002868672380000054
Figure BDA0002868672380000055
In the formula (2), the reaction mixture is,
Figure BDA0002868672380000056
the distance of the vehicle i on the lane L from the stop line at the intersection,
Figure BDA0002868672380000057
is the speed of the vehicle i in the lane L,
Figure BDA0002868672380000058
is the acceleration, v, of the vehicle i on the lane LtarA vehicle target speed;
when the uniform speed passes through the intersection, the travel time of the vehicle is calculated by the formula (3)
Figure BDA0002868672380000059
Figure BDA00028686723800000510
When the vehicle is decelerated and passes through the intersection, the travel time of the vehicle is calculated by the formula (4)
Figure BDA00028686723800000511
Figure BDA00028686723800000512
The fuel consumption of the vehicle reaching the intersection can be calculated by a vehicle fuel consumption model, for example, a hybrid vehicle, as shown in the following equation (5) -equation (7):
Figure BDA0002868672380000061
Figure BDA0002868672380000062
Figure BDA0002868672380000063
in the formulae (5) to (7),
Figure BDA0002868672380000069
CD，ρa，
Figure BDA0002868672380000064
f, theta are respectively the mass, the air resistance coefficient, the air density, the windward area, the rolling resistance coefficient and the road surface gradient of the vehicle i on the lane L, g is the gravity acceleration,
Figure BDA0002868672380000065
the power consumed for the vehicle i in the lane L,
Figure BDA0002868672380000066
for the efficiency of the braking energy recovery of the vehicle i on the lane L,
Figure BDA0002868672380000067
in order to improve the transmission efficiency of the vehicle i on the lane L,
Figure BDA0002868672380000068
the calorific value of the fuel of the vehicle i on the lane L, and beta is a coefficient representing the acceleration or deceleration state of the vehicle.
One method for solving the optimal arrival time of the vehicle is as follows: and obtaining the allowable vehicle speed range V according to the road speed limit, discretizing the allowable vehicle speed range V, and calculating the travel time and the fuel consumption of the vehicle by taking the vehicle speed as the final target vehicle speed reaching the intersection for each speed value V epsilon V. For example, assuming that the road allowable maximum speed is 20m/s, the allowable minimum speed is 4m/s, and the discrete step size is set to 2m/s, the allowable speed range V of the vehicle is [4,6,8,10,12,14,16,18,20 ]. When the target vehicle speed of the selected vehicle is any one of the allowable vehicle speed ranges, such as 8m/s, the travel time and the fuel consumption of the vehicle reaching the intersection at the target vehicle speed can be calculated, so that the vehicle reaching time with the minimum optimization objective function is the optimal reaching time.
And step 3: sequencing all vehicles arriving at the intersection according to the intelligent network connection automobile information to obtain a sequence of the vehicles passing through the intersection in sequence;
taking a single-lane intersection as an example, assuming that the intersection only has two lanes, the lane 1 has three vehicles, and the vehicles 1, 2 and 3 are respectively arranged from near to far away from the intersection; there are two vehicles in the lane 2, and the vehicles 4 and 5 are respectively located from near to far from the intersection, the first vehicle passing through the intersection is the first vehicle (vehicle 1 or vehicle 4) on the lane 1 or 2, and the second vehicle passing through the intersection is the second vehicle (vehicle 2 or vehicle 5) on the same lane or the first vehicle (vehicle 4 or vehicle 1) on the other lane. The above process is repeated until all vehicles have passed through the intersection, whereby a sequence of all possible vehicles passing through the intersection in sequence is obtained.
And 4, step 4: establishing a signal lamp optimization model aiming at minimizing the travel time and fuel consumption of all vehicles at the intersection, so that the optimal signal lamp state is obtained by utilizing the intelligent network connection automobile information, the optimal arrival time and the sequence of vehicles passing through the intersection in sequence;
considering the traffic behavior constraint of vehicles at the intersection, not every vehicle can reach the intersection at the optimal arrival time, so the traffic signal optimization is converted into finding an optimal vehicle passing sequence, and the combination of the idle time and the energy consumption of all vehicles is optimal. The signal lamp optimization model in the step 4 is shown as the formula (8):
Figure BDA0002868672380000071
in the formula (8), N is the total number of vehicles at the intersection, j is the position of the vehicle in the sequence R of passing the intersection, the sequence R of passing the vehicle through the intersection is obtained from the step 3, and τjIdle time of a vehicle with j in a sequence R passing through an intersection, ejThe energy consumption of the vehicle at j in the sequence R passing through the intersection due to parking and idling is shown.
The time for the vehicle to reach the intersection needs to be recalculated according to the arrival time of the preceding vehicle. The vehicle has 2 cases through the intersection: 1) the previous vehicle passing through the intersection is a vehicle on the same lane; 2) the former vehicle passing through the intersection is a vehicle on a different lane. For the two situations, when the optimal arrival time of the vehicle is greater than the sum of the arrival time of the front vehicle, the time of the front vehicle passing through the intersection and the signal lamp switching time, the arrival time of the vehicle is not changed, otherwise, the arrival time of the vehicle is the sum of the arrival time of the front vehicle, the time of the front vehicle passing through the intersection and the signal lamp switching time.
Idle time τ of vehicle with j in sequence R passing through intersectionjCalculated from equation (9):
τj＝tj,new-tj,opt (9)
in the formula (9), tj,optFor the optimal arrival time, t, of a vehicle with j in the sequence R passing through the intersectionj,newThe vehicle arrival time calculated according to the running condition of a front vehicle j-1 for a vehicle with j in a sequence R passing through the intersection is as follows:
Figure BDA0002868672380000072
in the formula (10), tj-1,newThe vehicle arrival time p calculated according to the running condition of the front vehicle j-2 for the vehicle with j-1 in the sequence R passing through the intersectionj-1To pass through an intersectionThe time when the vehicle with the position j-1 in the sequence R passes through the intersection is C, the time required by signal lamp phase switching is zero when the current vehicle j-1 is in the same lane.
The energy consumption of a vehicle passing through an intersection can be divided into two parts: energy consumption due to vehicle parking and energy consumption due to vehicle idling. Energy consumption e due to parking and idling of a vehicle with j in the sequence R passing through an intersectionjCalculated from equation (11):
Figure BDA0002868672380000073
in the formula (11), KjIs the energy consumption rate at idle of a vehicle with j in a sequence R passing through an intersection, BjThe energy loss due to parking is caused by a vehicle at j in the sequence R passing through the intersection.
One method of solving for the optimal signal lamp state is as follows: the method comprises the steps of obtaining a sequence R of vehicles passing through an intersection in sequence, starting from a first vehicle in the sequence, regarding each vehicle in the sequence as a stage when passing through the intersection, calculating idle time and energy consumption when reaching the intersection, selecting a front vehicle with the minimum sum of the idle time and the energy consumption as a decision point when each vehicle can pass through the intersection under two conditions (according to whether the front vehicles are in the same lane), calculating the next stage until the last vehicle passes through the intersection, calculating the minimum idle time and the energy consumption, obtaining the sequence when the optimal vehicle passes through the intersection and the vehicle arrival time by reverse pushing, and obtaining the optimal signal lamp state by integrating the arrival time of the vehicles in each lane.
And 5: establishing a speed track optimization model of the vehicle as shown in the formula (12) -formula (14), and solving by using intelligent networked automobile information and an optimal signal lamp state to obtain an optimal speed track;
Figure BDA0002868672380000081
Figure BDA0002868672380000082
Figure BDA0002868672380000083
in the formula (12) -formula (14), ω1，ω2，ω3And ω4Four weight coefficients, T is the prediction duration, T is a variable representing time,
Figure BDA0002868672380000084
the distance traveled by vehicle i in lane L at time k + T-1,
Figure BDA0002868672380000085
the distance traveled by vehicle i in lane L at time k,
Figure BDA0002868672380000086
the fuel consumed by the vehicle i in the lane L at the time t,
Figure BDA0002868672380000087
the speed, v, of a vehicle i on a lane L at time ttar(t) is the target vehicle speed of the vehicle i on the lane L at time t,
Figure BDA0002868672380000088
acceleration, v, of a vehicle i on a lane L at time tminAnd vmaxFor road minimum and maximum speed limits, aminAnd amaxThe minimum and maximum values of the vehicle acceleration,
Figure BDA0002868672380000089
is the distance between the vehicle i on the lane L and the front vehicle i-1, and comprises:
Figure BDA00028686723800000810
in the formula (15), S0For front and rear vehicle safety distance, thThe time interval of the vehicle head is the time interval,
Figure BDA00028686723800000811
is the speed of vehicle i-1 on lane L at time t,
Figure BDA00028686723800000812
the distance traveled by vehicle i in lane L at time t,
Figure BDA00028686723800000813
is the distance traveled by vehicle i-1 in lane L at time t.
The intelligent networked automobile acquires information such as the position, the speed, the acceleration and the like of a front automobile through a radar, an ultrasonic sensor or a V2V communication technology, and is used for calculating the distance between the intelligent networked automobile and the front automobile, so that the automobile collision is avoided; and obtaining the optimal signal lamp state through the V2I communication technology to calculate the target vehicle speed, thereby avoiding red light parking. In addition, the vehicle speed track optimization target also considers the fuel economy, the maneuverability and the riding comfort of the vehicle.
Because the vehicle speed track is optimized into an optimal control problem with a plurality of constraints, the optimal control problem can be solved through model predictive control, a pseudo-spectrum method and other optimal control methods.
Step 6: and realizing cooperative control of the signal lamp and the vehicle by using the optimal signal lamp state and the optimal vehicle speed track.
The following is a specific example:
a single-lane intersection model is built in a VISSIM (traffic simulation software), a signal lamp optimization control algorithm and a vehicle speed track optimization algorithm are programmed in an MATLAB, the length of a road is set to be 300m, the maximum allowable speed of the road is 20m/s, the minimum allowable speed of the road is 0m/s, the simulation time is set to be 1200s, and the simulation time step length is 0.5 s. FIG. 4a is a diagram showing the results of a simulation test of the travel time of a vehicle at a single-lane intersection according to the present invention, and FIG. 4b is a diagram showing the results of a simulation test of the fuel consumption of a vehicle at a single-lane intersection according to the present invention. As can be seen from fig. 4a and 4b, compared with the vehicle speed trajectory optimization method using the timing signal lamps, the method provided by the invention can effectively improve the traffic capacity of the intersection, which can reach 27% at most, and reduce the fuel consumption of the vehicle, which can reach 24% at most.

Claims (7)

1. A cooperative control method for a crossroad traffic signal lamp and an intelligent networked automobile is characterized by comprising the following steps:
step 1: acquiring intelligent networking automobile information in a communication range of an intersection; the intelligent networking automobile information comprises: the current speed, the lane and the distance between the current position and the stop line;
step 2: establishing an arrival time optimization model of the vehicle arriving at the intersection with the aim of minimizing the travel time and the fuel consumption of a single vehicle, so that the optimal arrival time of the vehicle arriving at the intersection is solved by utilizing the intelligent networked automobile information;
and step 3: sequencing all vehicles arriving at the intersection according to the intelligent network connection automobile information to obtain a sequence of the vehicles passing through the intersection in sequence;
and 4, step 4: establishing a signal lamp optimization model aiming at minimizing the travel time and fuel consumption of all vehicles at the intersection, so that the optimal signal lamp state is obtained by utilizing the intelligent network connection automobile information, the optimal arrival time and the sequence of vehicles passing through the intersection in sequence;
and 5: establishing a speed track optimization model of the vehicle, and solving by using the intelligent networked automobile information and the optimal signal lamp state to obtain an optimal speed track;
step 6: and realizing cooperative control of the signal lamp and the vehicle by using the optimal signal lamp state and the optimal vehicle speed track.
2. The cooperative control method of the intersection traffic signal lamp and the intelligent networked automobile according to claim 1, wherein the arrival time optimization model of the vehicle at the intersection in the step 2 is represented by the following formula (1):
Figure FDA0002868672370000011
in the formula (1), ω is a weight coefficient indicating the specific gravity of the travel time and the fuel consumption,
Figure FDA0002868672370000012
the travel time for a vehicle i on lane L to reach the intersection,
Figure FDA0002868672370000013
the fuel consumption of a vehicle i on a lane L reaching the intersection is shown, i is the vehicle serial number, and L is the lane number.
3. The cooperative control method of the intersection traffic signal lamp and the intelligent networked automobile as claimed in claim 2, wherein the driving conditions of the vehicle i on the lane L reaching the intersection are divided into accelerating crossing the intersection, passing the intersection at a constant speed and decelerating crossing the intersection;
when accelerating through the intersection, the travel time of the vehicle is calculated by using the formula (2)
Figure FDA0002868672370000014
Figure FDA0002868672370000015
In the formula (2), the reaction mixture is,
Figure FDA0002868672370000016
the distance of the vehicle i on the lane L from the stop line at the intersection,
Figure FDA0002868672370000017
is the speed of the vehicle i in the lane L,
Figure FDA0002868672370000018
is the acceleration, v, of the vehicle i on the lane LtarA vehicle target speed;
when the uniform speed passes through the intersection, the travel time of the vehicle is calculated by the formula (3)
Figure FDA0002868672370000021
Figure FDA0002868672370000022
When the vehicle is decelerated and passes through the intersection, the travel time of the vehicle is calculated by the formula (4)
Figure FDA0002868672370000023
Figure FDA0002868672370000024
4. The cooperative control method of the intersection traffic signal lamp and the intelligent networked automobile according to claim 1, wherein the signal lamp optimization model in the step 4 is represented by formula (5):
Figure FDA0002868672370000025
in the formula (5), N is the total number of vehicles at the intersection, j is the position of the vehicle in the sequence R passing through the intersection, and τjIdle time of a vehicle with j in a sequence R passing through an intersection, ejThe energy consumption of the vehicle at j in the sequence R passing through the intersection due to parking and idling is shown.
5. The crossroad traffic signal lamp and intelligence of claim 4The cooperative control method of the networked automobile is characterized in that the idle time tau of the vehicle with the position j in the sequence R of passing intersections isjCalculated from equation (6):
τj＝tj,new-tj,opt (6)
in the formula (6), tj,optFor the optimal arrival time, t, of a vehicle with j in the sequence R passing through the intersectionj,newThe vehicle arrival time calculated according to the running condition of a front vehicle j-1 for a vehicle with j in a sequence R passing through the intersection is as follows:
Figure FDA0002868672370000026
in the formula (7), tj-1,newThe vehicle arrival time p calculated according to the running condition of the front vehicle j-2 for the vehicle with j-1 in the sequence R passing through the intersectionj-1The time for the vehicle with the position j-1 in the sequence R passing through the intersection to pass through the intersection is C, the time required by signal lamp phase switching is zero when the current vehicle j-1 is in the same lane.
6. The cooperative control method of intersection traffic signal lamps and intelligent networked automobiles as claimed in claim 4, wherein the energy consumption e of the vehicle with j in the sequence R passing through the intersection due to parking and idling is characterized in thatjCalculated from equation (8):
Figure FDA0002868672370000027
in the formula (8), KjIs the energy consumption rate at idle of a vehicle with j in a sequence R passing through an intersection, BjThe energy loss due to parking is caused by a vehicle at j in the sequence R passing through the intersection.
7. The cooperative control method of the intersection traffic signal lamp and the intelligent networked automobile as claimed in claim 1, wherein the velocity trajectory optimization model of the vehicle in the step 5 is as shown in the formula (9) to the formula (11):
Figure FDA0002868672370000031
Figure FDA0002868672370000032
Figure FDA0002868672370000033
in the formula (9) -formula (11), ω is1，ω2，ω3And ω4Four weight coefficients, T is the prediction duration, T is a variable representing time,
Figure FDA0002868672370000034
the distance traveled by vehicle i in lane L at time k + T-1,
Figure FDA0002868672370000035
the distance traveled by vehicle i in lane L at time k,
Figure FDA0002868672370000036
the fuel consumed by the vehicle i in the lane L at the time t,
Figure FDA0002868672370000037
the speed, v, of a vehicle i on a lane L at time ttar(t) is the target vehicle speed of the vehicle i on the lane L at time t,
Figure FDA0002868672370000038
acceleration, v, of a vehicle i on a lane L at time tminAnd vmaxFor road minimum and maximum speed limits, aminAnd amaxThe minimum and maximum values of the vehicle acceleration,
Figure FDA0002868672370000039
is the distance between the vehicle i on the lane L and the front vehicle i-1, and comprises:
Figure FDA00028686723700000310
in the formula (12), S0For front and rear vehicle safety distance, thThe time interval of the vehicle head is the time interval,
Figure FDA00028686723700000311
is the speed of vehicle i-1 on lane L at time t,
Figure FDA00028686723700000312
the distance traveled by vehicle i in lane L at time t,
Figure FDA00028686723700000313
is the distance traveled by vehicle i-1 in lane L at time t.
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