CN111341152B - Network-connected automobile green passing system and method considering waiting queue and safe collision avoidance - Google Patents

Network-connected automobile green passing system and method considering waiting queue and safe collision avoidance Download PDF

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CN111341152B
CN111341152B CN202010138765.7A CN202010138765A CN111341152B CN 111341152 B CN111341152 B CN 111341152B CN 202010138765 A CN202010138765 A CN 202010138765A CN 111341152 B CN111341152 B CN 111341152B
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vehicle
queue
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CN111341152A (en
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殷国栋
董昊轩
庄伟超
徐利伟
梁晋豪
王法安
刘赢
刘昊吉
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Southeast University
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    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • 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
    • G08G1/065—Traffic control systems for road vehicles by counting the vehicles in a section of the road or in a parking area, i.e. comparing incoming count with outgoing count
    • 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
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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Abstract

The invention relates to a green traffic system and a green traffic method of a networked automobile considering the influence of a waiting queue and safe collision avoidance, wherein the green traffic method mainly comprises a green traffic system architecture, a traffic information acquisition method, a waiting queue traffic time estimation method based on an intelligent driver following model and a kinematics model, an automobile green traffic speed optimization method based on dynamic programming and a collision avoidance control method based on vehicle distance maintenance; the method utilizes the existing mature technical conditions to realize safe, energy-saving and efficient traffic control of the automobiles at the urban congested intersection under the condition that the intelligent internet automobile technology is not popularized on a large scale, and provides an effective and reliable solution for the technologies of economical driving, green traffic, efficient traffic at the intersection and the like of the automobiles.

Description

Network-connected automobile green passing system and method considering waiting queue and safe collision avoidance
Technical Field
The invention relates to a green traffic system and method of a networked automobile considering a waiting queue and safe collision avoidance, and belongs to the field of intelligent traffic.
Background
With the development of the fields of automobile electronics, network communication, intelligent control and the like, automobiles and traffic are organically integrated into a whole, an intelligent traffic system is favorably constructed, the new mode and new state development of the automobiles and traffic services are promoted, and the method has important significance for improving traffic efficiency, saving resources, reducing pollution, reducing accident rate and improving traffic management.
The intersection queue to be driven influences the change of the subsequent automobile movement speed, and the movement speed is the key of the safe, energy-saving and efficient control of the automobile; under the condition of low popularity of the existing intelligent networked automobile technology (including the intelligent networked automobile technology, which means information interaction and sharing between automobiles and everything, such as vehicle-to-vehicle communication V2V, vehicle-to-road communication V2I, vehicle-to-person communication V2P, vehicle network communication V2N and the like; and the automobile autonomous driving technology), the existing means is utilized to reasonably estimate the waiting queue passing time, and the estimated passing time is applied to the economic driving speed optimization of the automobiles, so that the method has important significance for the application of advanced control technologies such as automobile energy-saving driving, green passing, crossing efficient passing and the like, and effectively improves traffic safety, automobile energy-saving level and traffic passing efficiency.
Disclosure of Invention
The invention provides a green traffic system and a green traffic method of an internet automobile considering a waiting queue and safe collision avoidance, which fully consider the actual situation and the prior art level, acquire the optimized green traffic speed and integrate a collision avoidance control method to ensure the driving safety of the automobile.
The technical scheme adopted by the invention for solving the technical problems is as follows:
a green traffic system of a networked automobile considering a queue to be driven and safe collision avoidance comprises a control area, a traffic control area and a traffic control area, wherein the control area is an area which is a certain range away from a stop line of an intersection;
the system also comprises a plurality of controlled automobiles, wherein the controlled automobiles are automobiles which are to drive into or are in a control area, and are communicated with the signal lamp controller through V2I communication;
the system also comprises a queue to be driven, wherein the queue to be driven is a queue formed by cars waiting to pass at a stop line at an intersection when signal lamps are red;
arranging a plurality of first geomagnetic coils at the edge of the control area, namely, the first geomagnetic coils are far away from the intersection stop line;
laying a plurality of second magnetic coils at the stop line of the intersection;
as a further preferred aspect of the present invention, firstly, defining the time of the phase timing of the signal lamp as the current state of the signal lamp and the time required for switching to the next state;
when the signal lamp is a red lamp, firstly, the number of cars waiting to run at a stop line of the intersection and the phase timing information of the signal are obtained, and the length of a control area is optimized;
then, calculating the acceleration or deceleration of the automobiles in the queue to be driven by using an intelligent driver following model, calculating the length and the speed change track of the queue to be driven based on an automobile kinematic model, and estimating the passing time of the queue to be driven;
then, an automobile model containing energy and dynamics is applied, multiple constraints and multiple targets are considered, a speed optimization problem containing automobile and traffic constraints is designed, and a dynamic planning algorithm is adopted to calculate the green passing speed of the automobile;
finally, the optimized speed is sent to the controlled automobile by V2I communication, the automobile runs according to the speed after entering a control area, and meanwhile, a collision avoidance strategy is executed to ensure safe passing;
as a further preferred aspect of the present invention, the method specifically comprises the following steps:
initialization: setting a control area range D, initializing the number N of controlled automobiles to be 0, initializing a first geomagnetic coil count N1, initializing a second geomagnetic coil count N2 to be 0, initializing the time t to be 0, and initializing a controller calculating unit;
the first step is as follows: acquiring traffic information, namely embedding a geomagnetic coil in a road in advance at a position which is D away from a parking line at an intersection, and automatically counting when an automobile passes through the geomagnetic coil and outputting the count to a signal lamp controller; the position of a controlled automobile is acquired through a vehicle-mounted GPS, the phase timing of a signal lamp is directly read from a signal lamp controller, and the information is transmitted to the signal lamp controller in real time;
the second step is that: estimating the passing time of the queue to be passed, namely randomizing the parameters of the automobiles to be passed by adopting uniform distribution, correcting an intelligent driver following model by utilizing added starting delay judgment factors, maximum acceleration constraints and minimum braking deceleration constraints, calculating the acceleration or deceleration of each automobile in the queue to be passed, and estimating the passing time of the queue to be passed by utilizing an automobile kinematics model;
the third step: optimizing economical driving speed, setting minimum speed constraint for ensuring passing efficiency, meeting the maximum speed constraint of road speed limit, ensuring acceleration or deceleration constraint of automobile comfort, establishing an automobile model, solving the optimization problem by adopting a dynamic programming algorithm with energy consumption of an automobile in a control area as an optimization target, and outputting green passing speed for ensuring safety, energy conservation and high efficiency of the automobile;
the fourth step: broadcasting the green passing speed, namely broadcasting the optimized green passing speed to the controlled automobile by using a V2I communication network, wherein the controlled automobile in the control area can run according to the speed;
the fifth step: safe collision avoidance control, wherein a vehicle distance keeping strategy of a controlled vehicle and a waiting queue tail vehicle is designed to avoid collision;
and (4) ending: when the controlled automobile drives away from the intersection stop line, ending the control of the controlled automobile;
as a further preferred aspect of the present invention, the traffic information acquisition in the first step specifically includes:
when the first geomagnetic coil detects that the front wheel and the rear wheel of the automobile pass through the first geomagnetic coil at the same time, the number of the automobiles is counted and added by 1, when the second geomagnetic coil detects that the front wheel and the rear wheel of the automobile pass through the second geomagnetic coil at the same time, the difference between the number of the automobiles to be driven and the number of the automobiles to be driven in the control area is N1-N2;
n1 counts and keeps when the first geomagnetic coil detects that only the front wheel of the automobile passes through, and the static length of the queue to be driven is set as the length D of the control area; the second ground magnetic coil detects that only the front wheel of the automobile passes through the N2 count keeping;
the position information of the controlled automobile is acquired through a vehicle-mounted GPS, and is transmitted to a crossing signal lamp controller in real time through V2I communication, and the controlled automobile and the signal lamp controller are both provided with V2I communication terminals, so that the interactive transmission of information can be realized; the phase timing information of the signal lamp is read from the inner part of the signal lamp;
as a further preferred embodiment of the present invention, the specific steps of estimating the transit time of the queue to be traveled in the second step are as follows:
defining the maximum length of the vehicle body of the controlled vehicle as LmaxThe minimum length of the car body is LminThe maximum static head distance of the automobile is HmaxThe minimum static head distance of the automobile is HminThe maximum starting time delay of the automobile is ZmaxThe minimum starting delay of the automobile is ZminThe maximum movement time interval of the automobile is dhmaxThe minimum movement time interval of the automobile is dhminThe number of the cars waiting for driving at the intersection is N, and the length of the jth car is LjThe head distance of the jth vehicle is HjThe starting delay of the jth vehicle is ZjThe movement time interval of the jth vehicle is dhjThe random uniform distribution function is rand (), and the kronecker product is
Figure GDA0003030817720000031
j is an automobile mark in the control area, the head car is 1, the tail car is N, and then the automobile parameters based on random uniform distribution are as follows:
Figure GDA0003030817720000032
definition sjIs the jth vehicle position, vjIs the jth vehicle speed, ajAcceleration/deceleration of the jth vehicle, d is ideal following distance, amaxFor maximum acceleration of the vehicle, aminAnd is the maximum deceleration of the automobile, v is the ideal speed,
Figure GDA0003030817720000034
as an acceleration factor, KjTo activate the delay determining factor, t is the current time,
the vehicle acceleration/deceleration based on the modified intelligent driver following model is as follows:
Figure GDA0003030817720000033
wherein:
Figure GDA0003030817720000041
in the above formula, max () represents taking the maximum function, min () represents taking the minimum function,
definition of SjStopping for the jth vehicle from the intersectionInitial position of stop wire, DqjTo the initial length of the queue for the jth vehicle to go, DqThe initial total length of the queue to be queued.
Then the jth vehicle is away from the initial position S of the intersection stop linejComprises the following steps:
Figure GDA0003030817720000042
taking the jth vehicle as a tail vehicle and the initial length D of the queue to be drivenqjComprises the following steps:
Dqj＝Sj+0.5Lj
queue initial quiescent length DqThe length of the tail vehicle is determined as follows:
Dq＝DqN+0.5LN
in the above formula, DqNIs the length from the 1 st vehicle to the Nth vehicle, i.e. the length from the 1 st vehicle to the queue tail vehicle, LNIs the length of the Nth vehicle in the queue, namely the length of the tail vehicle in the queue;
establishing a time discretization problem, defining discrete time interval as delta t, and time for changing signal lamp from current state to next state as tsThe fixed timing of the signal is tinThe time for turning signal light to green light is tgrThe time for which the signal lamp keeps red is treThe traffic light state is P (P ═ 0 indicates red light, P ═ 1 indicates green light), and v indicates green lightmaxFor the highest vehicle speed that is limited by the road,
by adopting a discretization calculation method, the motion speed v of the jth vehicle at the kth stepjComprises the following steps:
Figure GDA0003030817720000043
t is obtained from the signal time definitionre＝tgr＝tsThen the jth vehicle running length d at the kth stepqjComprises the following steps:
Figure GDA0003030817720000051
whether the queue passes through the intersection is determined according to whether the tail car passes through the intersection, and the movement length of the whole queue is determined by the tail carq(k)＝dqN(k) From which the queue transit time t can be calculatedqComprises the following steps:
Figure GDA0003030817720000052
as a further preferred aspect of the present invention, the third step of optimizing the green passage vehicle speed specifically comprises:
defining g as gravity acceleration, m as automobile mass, f as friction resistance coefficient, theta as road gradient, CDIs the air resistance coefficient, rho is the air density, d is the driving distance, delta is the conversion coefficient of the rotational inertia of the automobile, F is the traction force, wherein the positive value is the driving force, the negative value is the braking force, and x is [ d v ]]TThe state quantity is represented by a quantity of state,
the particle model is adopted to describe the automobile longitudinal dynamics model:
Figure GDA0003030817720000053
define the instantaneous fuel consumption rate of the automobile as
Figure GDA0003030817720000054
Defining the oil consumption coefficient of the automobile as alpha0、α1、α2、α3，β0，β1，β2Wherein the automobile oil consumption coefficient is obtained through tests,
then the model of the instantaneous oil consumption of the automobile is as follows:
Figure GDA0003030817720000055
defining the oil consumption of the automobile as J, the control quantity of the optimization problem as u, and the initial speed as vsTerminal vehicle speed vpMinimum vehicle speed vminMaximum vehicle speed vmaxThe optimization problem length is N, and the maximum driving force is FdMaximum braking force of FbWherein the maximum driving force and the maximum braking force are determined by road adhesion and braking comfort,
the optimization problem is then as follows:
Figure GDA0003030817720000056
satisfies the following conditions:
Figure GDA0003030817720000061
x(0)＝[vs，0]
x(N)＝[vp，D]
v(k)∈[vmin，vmax]
u(k)∈[Fb(k)，Fd(k)]
defining a terminal cost function of a dynamic programming algorithm as follows:
Figure GDA0003030817720000062
wherein argmin () represents the control quantity and state quantity functions when taking the minimum value,
the dynamic programming reverse iteration cost function is defined as:
Figure GDA0003030817720000063
the optimal green passing speed meeting the requirements can be obtained by solving the equation;
as a further preferable aspect of the present invention, the fourth step of the green passage vehicle speed broadcast includes:
the optimal green passing speed is sent to the controlled automobile by using the signal lamp controller V2I communication terminal and the controlled automobile V2I communication terminal;
as a further preferable aspect of the present invention, the safe collision avoidance control in the fifth step includes:
the collision avoidance control algorithm is arranged in the vehicle, the distance between the collision avoidance control algorithm and the tail vehicle of the front queue waiting to be driven is obtained through a radar, the collision avoidance control algorithm is kept in a safe distance, and the defined deceleration for ensuring comfort braking is atThe maximum deceleration for road adhesion is
Figure GDA0003030817720000064
dsMinimum following distance, d, to meet road adhesioncIn order to meet the minimum following distance of the braking comfort, delta d is the distance between the controlled automobiles and the tail of the queue to be driven,
Figure GDA0003030817720000065
as the coefficient of the road surface adhesion,
the safe collision avoidance control is as follows:
Figure GDA0003030817720000066
wherein:
Figure GDA0003030817720000067
Figure GDA0003030817720000071
the speed generated by the safety collision avoidance control is the final driving speed of the controlled automobile.
Through the technical scheme, compared with the prior art, the invention has the following beneficial effects:
1. the method fully considers the situation that the intelligent networked automobile is not popularized yet, is difficult to accurately acquire all information in traffic and realize the situation that the automobile is controlled independently, establishes a green traffic system architecture aiming at a typical urban traffic scene, accurately estimates the traffic time of a queue to be driven, optimizes the traffic speed which is beneficial to the safety, energy conservation and high efficiency of the automobile, integrates a collision avoidance control method, and ensures the safety, energy conservation and high efficiency traffic control of the automobile;
2. the control method is integrated in the signal lamp controller, information interaction is carried out between the signal lamp controller and the controlled automobile through V2I communication, used equipment (the signal lamp controller, the geomagnetic coil, the V2I terminal and the like) are mature and reliable products, and the designed control method is effective;
3. the invention adopts a random method, reasonably randomizes automobile performance parameters such as automobile body length, static head distance, movement time distance, starting time delay and the like within a reasonable limit, wherein the parameters are different due to the difference of drivers and automobile types, and the randomizing method can improve the applicability of the invention in different traffic scenes;
4. the method adopts a classical automobile kinematics model and an intelligent driver following model, and improves the calculation accuracy of the queue static length, the dynamic length, the passing time and the passing speed by means of random parameters and acceleration/deceleration, so that the method is suitable for common urban traffic scenes, and simultaneously ensures that the estimation accuracy meets the use requirement;
5. the invention adopts a dynamic programming algorithm, can realize multi-target optimization of safe driving, minimum energy consumption, shortest passing time and the like under the conditions of multiple constraints of vehicle speed, acceleration/deceleration, road adhesion and the like, and outputs the vehicle speed meeting the requirements.
Drawings
The invention is further illustrated with reference to the following figures and examples.
FIG. 1 is a green traffic system architecture of networked automobiles considering queues to be driven and safe collision avoidance according to a preferred embodiment of the present invention;
FIG. 2 is a flow chart of a green traffic control method of the networked automobile considering a waiting queue and safe collision avoidance according to the preferred embodiment of the invention;
fig. 3 is a simulation result of the green traffic control method of the internet-connected vehicle in consideration of the waiting queue and the safe collision avoidance according to the preferred embodiment of the present invention, wherein 3a is a vehicle speed variation graph and 3b is a vehicle position variation graph.
Detailed Description
The present invention will now be described in further detail with reference to the accompanying drawings. These drawings are simplified schematic views illustrating only the basic structure of the present invention in a schematic manner, and thus show only the constitution related to the present invention.
The intersection waiting queue can influence the change of the subsequent automobile movement speed, and the popularization degree of the existing intelligent network connection automobile technology is low, so that the method has important significance for effectively improving the traffic safety, the automobile energy-saving level and the traffic passing efficiency on the premise of reasonable existing means.
Example 1:
fig. 1 shows that the networked automobile green traffic system considering the waiting queue and safe collision avoidance provided by the present application includes a control area, which is an area within a certain range from a stop line at an intersection;
the system also comprises a plurality of controlled automobiles, wherein the controlled automobiles are defined to be automobiles which are about to drive into or are in a control area form, and are communicated with the signal lamp controller through V2I communication, namely the controlled automobiles can communicate with the signal lamp controller through V2I communication to transmit information;
the system also comprises a waiting queue, wherein the waiting queue is defined as a queue formed by cars waiting to pass at a stop line at an intersection when the signal lamps are red lamps;
arranging a plurality of first geomagnetic coils at the edge of the control area, namely the first geomagnetic coils are far away from the intersection stop line, and the first geomagnetic coils are used for detecting the edge of the control area;
and laying a plurality of second magnetic coils on the intersection stop line to detect the position of the intersection stop line.
Example 2:
when the signal lamp is a red lamp, a queue to be driven exists in a set control area of the intersection, the speed of a controlled automobile to be driven into the control area is influenced, in order to avoid time waste caused by over actuation and rapid parking, after the controlled automobile is driven into the control area, on the basis of the architecture of the embodiment 1, a signal lamp controller is received to drive through a green passing speed sent by V2I communication, and the safe, energy-saving and efficient driving is carried out in the control area by combining a safe collision avoidance method installed in the controlled automobile until the controlled automobile drives through an intersection stop line;
in brief, firstly, defining the signal lamp phase timing as the current state of the signal lamp and the time required for switching to the next state;
when the signal lamp is a red lamp, firstly, information such as the number of cars waiting to run at a stop line of the intersection, the phase timing of the signal and the like is obtained, and the length of a control area (namely the length of an optimization problem) is optimized; then, calculating the acceleration or deceleration of the automobiles in the queue to be driven by using an intelligent driver following model, calculating the length and the speed change track of the queue to be driven based on an automobile kinematic model, and estimating the passing time of the queue to be driven; then, an automobile model containing energy and dynamics is applied, multiple constraints and multiple targets are considered, a speed optimization problem containing automobile and traffic constraints is designed, and a dynamic planning algorithm is adopted to calculate the green passing speed of the automobile; and finally, the optimized speed is sent to the controlled automobile by V2I communication, the automobile runs according to the speed after entering a control area, and meanwhile, a collision avoidance strategy is executed, so that the safe passing is ensured.
The green passage method is specifically stated as follows:
the method specifically comprises the following steps shown in figure 2:
initialization: setting a control area range D to be 500m, initializing the number N of controlled automobiles to be 0, initializing a first geomagnetic coil count N1, initializing a second geomagnetic coil count N2 to be 0, initializing an initialization time t to be 0, and initializing a controller calculation unit;
the first step is as follows: acquiring traffic information, namely embedding a geomagnetic coil in a road in advance at a position which is D away from a parking line at an intersection, and automatically counting when an automobile passes through the geomagnetic coil and outputting the count to a signal lamp controller; the position of a controlled automobile is acquired through a vehicle-mounted GPS, the phase timing of a signal lamp is directly read from a signal lamp controller, and the information is transmitted to the signal lamp controller in real time;
the method comprises the following specific steps:
when the first geomagnetic coil detects that the front wheel and the rear wheel of the automobile pass through the first geomagnetic coil at the same time, the number of the automobiles is counted and added by 1, when the second geomagnetic coil detects that the front wheel and the rear wheel of the automobile pass through the second geomagnetic coil at the same time, the difference between the number of the automobiles to be driven and the number of the automobiles to be driven in the control area is N1-N2;
n1 counts and keeps when the first geomagnetic coil detects that only the front wheel of the automobile passes through, and the static length of the queue to be driven is set as the length D of the control area; the second ground magnetic coil detects that only the front wheel of the automobile passes through the N2 count keeping;
the position information of the controlled automobile is acquired through a vehicle-mounted GPS, and is transmitted to a crossing signal lamp controller in real time through V2I communication, and the controlled automobile and the signal lamp controller are both provided with V2I communication terminals, so that the interactive transmission of information can be realized; the signal lamp phase timing information is generated in the signal controller and sent to the signal lamp, and only internal reading is needed;
the second step is that: and estimating the passing time of the queue to be passed, namely randomizing the parameters of the automobiles to be passed by adopting uniform distribution, correcting the acceleration or deceleration of each automobile in the queue to be passed by using an intelligent driver following model by adding a starting delay judgment factor, a maximum acceleration constraint and a minimum braking deceleration constraint, and estimating the passing time of the queue to be passed by using an automobile kinematics model.
The method comprises the following specific steps:
specifically, the maximum length of the vehicle body is defined as Lmax5.5m, the minimum length of the car body is Lmin3.5m, the maximum static head distance of the vehicle is Hmax3m, the minimum static head distance of the vehicle is Hmin3m, the maximum starting time delay of the vehicle is Zmax2s, the minimum starting delay of the vehicle is ZminWhen the distance between the vehicles is 0.5m, the number of the vehicles waiting for driving at the intersection is N-9, and the length of the jth vehicle is LjThe head distance of the jth vehicle is HjThe starting delay of the jth vehicle is ZjThe acceleration or deceleration delay constant of the jth vehicle is taujThe kronecker product is
Figure GDA0003030817720000091
σ and μ are gaussian function parameters, j is a vehicle mark in the control area, the head vehicle is 1, the tail vehicle is N-5,
the vehicle parameters based on random uniform distribution are:
Figure GDA0003030817720000092
definition sjIs the jth vehicle position, vjIs the jth vehicle speed, ajAcceleration/deceleration of the jth vehicle, d is ideal following distance, amax＝3m/s2For maximum acceleration of the vehicle, amin＝-4m/s2For the maximum deceleration of the vehicle, v is 20m/s, which is the ideal vehicle speed,
Figure GDA0003030817720000093
as an acceleration factor, KjTo activate the delay determining factor, t is the current time,
the vehicle acceleration/deceleration based on the modified intelligent driver following model is as follows:
Figure GDA0003030817720000101
wherein:
Figure GDA0003030817720000102
in the above formula, max () represents taking the maximum function, min () represents taking the minimum function,
definition of SjFor the jth vehicle from the initial position of the intersection stop line, DqjTo the initial length of the queue for the jth vehicle to go, DqThe initial total length of the queue to be queued.
Then the jth vehicle is away from the initial position S of the intersection stop linejComprises the following steps:
Figure GDA0003030817720000103
taking the jth vehicle as a tail vehicle and the initial length D of the queue to be drivenqjComprises the following steps:
Dqj＝Sj+0.5Lj
queue to be queued initial quiescent length DqThe length of the tail vehicle is determined as follows:
Dq＝DqN+0.5LN
in the above formula, DqNIs the length from the 1 st vehicle to the Nth vehicle, i.e. the length from the 1 st vehicle to the queue tail vehicle, LNIs the length of the Nth vehicle in the queue, namely the length of the tail vehicle in the queue;
calculating to obtain the static length of the queue to be queued as Dq＝56.5m。
Establishing a time discretization problem, defining discrete time interval as delta t, and time for changing signal lamp from current state to next state as tsWhen the signal is fixed, t is 45sin45s, the time for turning signal lamp to green is tgrAt 5s, the signal lamp remains red for a time treSignal light state P5 s, where P0 denotes red light, P1 denotes green light, vmaxWhen the maximum speed of the vehicle is 20m/s and the discretization calculation method is adopted, the motion speed v of the jth vehicle in the kth stepjComprises the following steps:
Figure GDA0003030817720000111
t is obtained from the signal time definitionre＝tgr＝tsThen the jth vehicle running length d at the kth stepqjComprises the following steps:
Figure GDA0003030817720000112
whether the queue to be driven passes the intersection is determined according to whether the tail car passes, and the movement length of the whole queue to be driven is determined by the tail carq(k)＝dqN(k) Therefore, the passage time t of the queue to be driven can be calculatedqComprises the following steps:
Figure GDA0003030817720000113
the estimated queue transit time was calculated to be 65.3 s.
The third step: optimizing economical driving speed, setting minimum speed constraint for ensuring passing efficiency, meeting the maximum speed constraint of road speed limit, ensuring acceleration or deceleration constraint of automobile comfort, establishing an automobile model, solving the optimization problem by adopting a dynamic programming algorithm with energy consumption of an automobile in a control area as an optimization target, and outputting green passing speed for ensuring safety, energy conservation and high efficiency of the automobile;
the method comprises the following specific steps:
definition g ═ 9.8m · s-2The gravity acceleration is, m is 1421kg, the controlled vehicle mass, f is 0.016, the friction resistance coefficient, θ is 0, the road gradient, CD0.3 is the air resistance coefficient, ρ ρ ρ 1.206 is the air density, d is the distance traveled, δ 1.022 is the vehicle moment of inertia conversion coefficient, F is the tractive effort, where positive values are the driving force, negative values are the braking force, and x is [ d v ]]TThe state quantity is represented by a quantity of state,
the particle model is adopted to describe the automobile longitudinal dynamics model:
Figure GDA0003030817720000114
define the instantaneous fuel consumption rate of the automobile as
Figure GDA0003030817720000115
Defining the oil consumption coefficient of the automobile as alpha0＝0.1569mL·s-1、α1＝2.45×10-2mL·m-1α2＝-7.415×10-4mL·s·m-2、α3＝5.975×10-4mL·s2·m-3，β0＝7.224×10- 2mL·s·m-1，β1＝9.681×10-2mL·s2·m-2，β2＝1.075×10-3mL·s3·m-3And the coefficients are obtained through experiments, and then the instantaneous oil consumption model of the automobile is as follows:
then the model of the instantaneous oil consumption of the automobile is as follows:
Figure GDA0003030817720000121
defining the oil consumption of the automobile as J, the control quantity of the optimization problem as u, and the initial speed as vsTerminal vehicle speed vpMinimum vehicle speed vminMaximum vehicle speed vmaxThe optimization problem length is N, and the maximum driving force is FdMaximum braking force of FbWherein the maximum driving force and the maximum braking force are determined by road adhesion and braking comfort,
the optimization problem is then as follows:
Figure GDA0003030817720000122
satisfies the following conditions:
Figure GDA0003030817720000123
x(0)＝[15，0]
x(N)＝[13，500]
v(k)∈[5，20]
u(k)∈[Fb(k)，Fd(k)]
defining a terminal cost function of a dynamic programming algorithm as follows:
Figure GDA0003030817720000124
wherein argmin () represents the control quantity and state quantity functions when taking the minimum value,
the dynamic programming reverse iteration cost function is defined as:
Figure GDA0003030817720000125
the optimal green passing speed meeting the requirements can be obtained by solving the equation;
the fourth step: broadcasting the green passing speed, namely broadcasting the optimized green passing speed to the controlled automobile by using a V2I communication network, wherein the controlled automobile in the control area can run according to the speed;
the method comprises the following specific steps:
the optimal green passing speed is sent to the controlled automobile by using the signal lamp controller V2I communication terminal and the controlled automobile V2I communication terminal;
the fifth step: safe collision avoidance control, wherein a vehicle distance keeping strategy of a controlled vehicle and a waiting queue tail vehicle is designed to avoid collision;
the method comprises the following specific steps:
the collision avoidance control algorithm is arranged in a controlled automobile, the distance between the collision avoidance control algorithm and the tail automobile of the front queue waiting to be driven is obtained through a radar, the collision avoidance control algorithm is kept in a safe distance, and the defined deceleration for ensuring comfort braking is at＝1.5m/s-2The maximum deceleration for road adhesion is
Figure GDA0003030817720000131
dsMinimum following distance, d, to meet road adhesioncIn order to meet the minimum following distance of the braking comfort, delta d is the distance between the controlled automobiles and the tail of the queue to be driven,
Figure GDA0003030817720000132
as the coefficient of the road surface adhesion,
the safe collision avoidance control is as follows:
Figure GDA0003030817720000133
wherein:
Figure GDA0003030817720000134
Figure GDA0003030817720000135
the speed generated by the safety collision avoidance control is the final driving speed of the controlled automobile;
and (4) ending: and when the controlled automobile drives away from the intersection stop line, ending the control of the controlled automobile.
In the green traffic method, a signal lamp controller is used for information acquisition, method calculation and data storage, the signal lamp controller is a traditional intersection signal lamp control device and is generally installed near an intersection, relevant algorithms of the fourth step, the fifth step and the sixth step in the green traffic method are strictly executed by combining information such as signal lamp phase timing and the number of cars to be driven, and optimal vehicle speed is stored and output, so that the whole method is completed.
The simulation result is shown in fig. 3, where 3a is a vehicle speed change graph and 3b is a vehicle position change graph, compared with the conventional method, the controlled vehicle can pass through the intersection in a non-stop state, and keeps a safe distance from the tail car of the queue to be driven, and the controlled vehicle can follow the train and immediately pass through the queue after passing through the intersection. The oil consumption in the whole process of the traditional method is 62.4ml, the oil consumption in the method designed by the invention is 55.2ml, and the energy-saving effect is improved by 16.6%.
It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
The meaning of "and/or" as used herein is intended to include both the individual components or both.
The term "connected" as used herein may mean either a direct connection between components or an indirect connection between components via other components.
In light of the foregoing description of the preferred embodiment of the present invention, many modifications and variations will be apparent to those skilled in the art without departing from the spirit and scope of the invention. The technical scope of the present invention is not limited to the content of the specification, and must be determined according to the scope of the claims.

Claims (5)

1. A green traffic method of an internet automobile considering a waiting queue and safe collision avoidance is characterized by comprising the following steps: firstly, defining the signal lamp phase timing as the current state of the signal lamp and the time required for switching to the next state;
when the signal lamp is a red lamp, firstly, the number of cars waiting to run at a stop line of the intersection and the phase timing information of the signal are obtained, and the length of a control area is optimized;
then, calculating the acceleration or deceleration of the automobiles in the queue to be driven by using an intelligent driver following model, calculating the length and the speed change track of the queue to be driven based on an automobile kinematic model, and estimating the passing time of the queue to be driven;
then, an automobile model containing energy and dynamics is applied, multiple constraints and multiple targets are considered, a speed optimization problem containing automobile and traffic constraints is designed, and a dynamic planning algorithm is adopted to calculate the green passing speed of the automobile;
finally, the optimized speed is sent to the controlled automobile by V2I communication, the automobile runs according to the speed after entering a control area, and meanwhile, a collision avoidance strategy is executed to ensure safe passing;
the method specifically comprises the following steps:
initialization: setting a control area range D, initializing the number N of controlled automobiles to be 0, initializing a first geomagnetic coil count N1, initializing a second geomagnetic coil count N2 to be 0, initializing the time t to be 0, and initializing a controller calculating unit;
the first step is as follows: acquiring traffic information, namely embedding a geomagnetic coil in a road in advance at a position which is D away from a parking line at an intersection, and automatically counting when an automobile passes through the geomagnetic coil and outputting the count to a signal lamp controller; the position of a controlled automobile is acquired through a vehicle-mounted GPS, the phase timing of a signal lamp is directly read from a signal lamp controller, and the information is transmitted to the signal lamp controller in real time;
the second step is that: estimating the passing time of the queue to be passed, namely randomizing the parameters of the automobiles to be passed by adopting uniform distribution, correcting an intelligent driver following model by utilizing added starting delay judgment factors, maximum acceleration constraints and minimum braking deceleration constraints, calculating the acceleration or deceleration of each automobile in the queue to be passed, and estimating the passing time of the queue to be passed by utilizing an automobile kinematics model;
the third step: optimizing economical driving speed, setting minimum speed constraint for ensuring passing efficiency, meeting the maximum speed constraint of road speed limit, ensuring acceleration or deceleration constraint of automobile comfort, establishing an automobile model, solving the optimization problem by adopting a dynamic programming algorithm with energy consumption of an automobile in a control area as an optimization target, and outputting green passing speed for ensuring safety, energy conservation and high efficiency of the automobile;
the fourth step: broadcasting the green passing speed, namely broadcasting the optimized green passing speed to the controlled automobile by using a V2I communication network, wherein the controlled automobile in the control area can run according to the speed;
the fifth step: safe collision avoidance control, wherein a vehicle distance keeping strategy of a controlled vehicle and a waiting queue tail vehicle is designed to avoid collision;
and (4) ending: when the controlled automobile drives away from the intersection stop line, ending the control of the controlled automobile;
the first step of traffic information acquisition comprises the following specific steps:
when the first geomagnetic coil detects that the front wheel and the rear wheel of the automobile pass through the first geomagnetic coil at the same time, the number of the automobiles is counted and added by 1, when the second geomagnetic coil detects that the front wheel and the rear wheel of the automobile pass through the second geomagnetic coil at the same time, the difference between the number of the automobiles to be driven and the number of the automobiles to be driven in the control area is N1-N2;
n1 counts and keeps when the first geomagnetic coil detects that only the front wheel of the automobile passes through, and the static length of the queue to be driven is set as the length D of the control area; the second ground magnetic coil detects that only the front wheel of the automobile passes through the N2 count keeping;
the position information of the controlled automobile is acquired through a vehicle-mounted GPS, and is transmitted to a crossing signal lamp controller in real time through V2I communication, and the controlled automobile and the signal lamp controller are both provided with V2I communication terminals, so that the interactive transmission of information can be realized; the phase timing information of the signal lamp is read from the inner part of the signal lamp; the specific steps of the estimation of the waiting queue passing time in the second step are as follows:
defining the maximum length of the vehicle body of the controlled vehicle as LmaxThe minimum length of the car body is LminThe maximum static head distance of the automobile is HmaxThe minimum static head distance of the automobile is HminThe maximum starting time delay of the automobile is ZmaxThe minimum starting delay of the automobile is ZminThe maximum movement time interval of the automobile is dhmaxThe minimum movement time interval of the automobile is dhminThe number of the cars waiting for driving at the intersection is N, and the length of the jth car is LjThe head distance of the jth vehicle is HjThe starting delay of the jth vehicle is ZjThe movement time interval of the jth vehicle is dhjThe random uniform distribution function is rand (), and the kronecker product is
Figure FDA0003030817710000021
j is an automobile mark in the control area, the head car is 1, the tail car is N, and then the automobile parameters based on random uniform distribution are as follows:
Figure FDA0003030817710000022
definition sjIs the jth vehicle position, vjIs the jth vehicle speed, ajAcceleration/deceleration of the jth vehicle, d is ideal following distance, amaxFor maximum acceleration of the vehicle, aminAnd is the maximum deceleration of the automobile, v is the ideal speed,
Figure FDA0003030817710000024
as an acceleration factor, KjTo activate the delay determining factor, t is the current time,
the vehicle acceleration/deceleration based on the modified intelligent driver following model is as follows:
Figure FDA0003030817710000023
wherein:
Figure FDA0003030817710000031
in the above formula, max () represents taking the maximum function, min () represents taking the minimum function,
definition of SjFor the jth vehicle from the initial position of the intersection stop line, DqjTo the initial length of the queue for the jth vehicle to go, DqThe initial total length of the queue to be queued;
then the jth vehicle is away from the initial position S of the intersection stop linejComprises the following steps:
Figure FDA0003030817710000032
taking the jth vehicle as a tail vehicle and the initial length D of the queue to be drivenqjComprises the following steps:
Dqj＝Sj+0.5Lj
queue initial quiescent length DqThe length of the tail vehicle is determined as follows:
Dq＝DqN+0.5LN
in the above formula, DqNIs the length from the 1 st vehicle to the Nth vehicle, i.e. the length from the 1 st vehicle to the queue tail vehicle, LNIs the length of the Nth vehicle in the queue, namely the length of the tail vehicle in the queue;
establishing a time discretization problem, defining discrete time interval as delta t, and time for changing signal lamp from current state to next state as tsThe fixed timing of the signal is tinThe time for turning signal light to green light is tgrThe time for which the signal lamp keeps red is treThe signal lamp state is P, where P ═ 0 denotes red, P ═ 1 denotes green, and v denotes redmaxFor the highest vehicle speed that is limited by the road,
by adopting a discretization calculation method, the motion speed v of the jth vehicle at the kth stepjComprises the following steps:
Figure FDA0003030817710000033
t is obtained from the signal time definitionre＝tgr＝tsThen the jth vehicle running length d at the kth stepqjComprises the following steps:
Figure FDA0003030817710000041
whether the queue passes through the intersection is determined according to whether the tail car passes through the intersection, and the movement length of the whole queue is determined by the tail carq(k)＝dqN(k) From which the queue transit time t can be calculatedqComprises the following steps:
Figure FDA0003030817710000042
2. the green traffic method of the networked automobiles considering the queues to be walked and the safe collision avoidance according to claim 1, which is characterized in that: in the third step, the green passing vehicle speed optimization comprises the following specific steps:
defining g as gravity acceleration, m as automobile mass, f as friction resistance coefficient, theta as road gradient, CDIs the air resistance coefficient, rho is the air density, d is the driving distance, delta is the conversion coefficient of the rotational inertia of the automobile, F is the traction force, wherein the positive value is the driving force, the negative value is the braking force, and x is [ d v ]]TThe state quantity is represented by a quantity of state,
the particle model is adopted to describe the automobile longitudinal dynamics model:
Figure FDA0003030817710000043
define the instantaneous fuel consumption rate of the automobile as
Figure FDA0003030817710000044
Defining the oil consumption coefficient of the automobile as alpha0、α1、α2、α3，β0，β1，β2Wherein the automobile oil consumption coefficient is obtained through tests,
then the model of the instantaneous oil consumption of the automobile is as follows:
Figure FDA0003030817710000045
defining the oil consumption of the automobile as J, the control quantity of the optimization problem as u, and the initial speed as vsTerminal vehicle speed vpMinimum vehicle speed vminMaximum vehicle speed vmaxThe optimization problem length is N, and the maximum driving force is FdMaximum braking force of FbWherein the maximum driving force and the maximum braking force are determined by road adhesion and braking comfort,
the optimization problem is then as follows:
Figure FDA0003030817710000046
satisfies the following conditions:
Figure FDA0003030817710000051
x(0)＝[vs，0]
Figure FDA0003030817710000055
v(k)∈[vmin，vmax]
u(k)∈[Fb(k)，Fd(k)]
defining a terminal cost function of a dynamic programming algorithm as follows:
Figure FDA0003030817710000052
wherein argmin () represents the control quantity and state quantity functions when taking the minimum value,
the dynamic programming reverse iteration cost function is defined as:
Figure FDA0003030817710000053
by solving the equation, the optimal green passing speed meeting the requirement can be obtained.
3. The green traffic method of the networked automobiles considering the queues to be walked and the safe collision avoidance according to claim 2, characterized in that: the fourth step is that the green passing vehicle speed broadcasting comprises the following specific steps:
and sending the optimal green passing speed to the controlled automobile by using the signal lamp controller V2I communication terminal and the controlled automobile V2I communication terminal.
4. The green traffic method of the networked automobiles considering the queues to be walked and the safe collision avoidance according to claim 3, wherein: the fifth step is that the safe collision avoidance control comprises the following specific steps:
the collision avoidance control algorithm is arranged in the vehicle, the distance between the collision avoidance control algorithm and the tail vehicle of the front queue waiting to be driven is obtained through a radar, the collision avoidance control algorithm is kept in a safe distance, and the defined deceleration for ensuring comfort braking is atThe maximum deceleration for road adhesion is
Figure FDA0003030817710000056
dsMinimum following distance, d, to meet road adhesioncIn order to meet the minimum following distance of the braking comfort, delta d is the distance between the controlled automobiles and the tail of the queue to be driven,
Figure FDA0003030817710000057
as the coefficient of the road surface adhesion,
the safe collision avoidance control is as follows:
Figure FDA0003030817710000054
wherein:
Figure FDA0003030817710000061
Figure FDA0003030817710000062
the speed generated by the safety collision avoidance control is the final driving speed of the controlled automobile.
5. A system for considering the waiting queue and the green traffic method of the networked automobiles for safe collision avoidance based on any one of claims 1 to 4 is characterized in that: the system comprises a control area which is an area within a certain range from a stop line at an intersection;
the system also comprises a plurality of controlled automobiles, wherein the controlled automobiles are automobiles which are to drive into or are in a control area, and are communicated with the signal lamp controller through V2I communication;
the system also comprises a queue to be driven, wherein the queue to be driven is a queue formed by cars waiting to pass at a stop line at an intersection when signal lamps are red;
arranging a plurality of first geomagnetic coils at the edge of the control area, namely, the first geomagnetic coils are far away from the intersection stop line;
and laying a plurality of second ground magnetic coils at the intersection stop line.
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