CN115862348A - Signalized intersection dynamic queuing length sensing and traffic signal control optimization algorithm, system and device based on vehicle-road cooperation - Google Patents
Signalized intersection dynamic queuing length sensing and traffic signal control optimization algorithm, system and device based on vehicle-road cooperation Download PDFInfo
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Abstract
The invention relates to the technical field of intelligent traffic association, in particular to an algorithm, a system and a device for sensing the dynamic queuing length of a signalized intersection and controlling and optimizing traffic signals based on vehicle-road cooperation. The signalized intersection dynamic queuing length perception and traffic signal control optimization algorithm based on vehicle-road cooperation comprises the following steps: under the state that the current queuing length of each phase of the intersection is obtained, calculating the minimum green light time required for emptying the queuing vehicles matched with the current queuing length of each phase of the intersection; forming an optimal green light ratio adjusting strategy in a state that the minimum green light time required by emptying the queued vehicles does not match the current green light timing; and updating the current green light timing according to the optimal green signal ratio adjusting strategy.
Description
Technical Field
The invention relates to the technical field of intelligent traffic association, in particular to an algorithm, a system and a device for sensing the dynamic queuing length of a signalized intersection and controlling and optimizing traffic signals based on vehicle-road cooperation.
Background
The urban arterial road is used as a framework of a traffic network, and bears the access functions of long-distance rapid traffic and commuting traffic, and the congestion phenomenon is the most frequent and serious. The traffic jam of the urban signal control main road is reflected by independent attributes of road sections, and is reflected by mutual influence and mutual association among the road sections, and obvious space-time characteristics are provided among the road sections under the condition of jam, particularly queue overflow. With the acceleration of the urbanization process, the quantity of motor vehicles kept is continuously increased, the problem between road resources and traffic requirements is increasingly prominent, the saturated traffic state becomes a common phenomenon, and traffic jam becomes the focus of attention of all circles of society.
In order to realize intelligent traffic management, firstly, road state data must be acquired, and in the prior art, a fixed vehicle detector such as a geomagnetic vehicle detector is generally adopted to acquire road conditions. However, the fixed vehicle detector cannot dynamically monitor the queuing length of the signalized intersection, so that the problem that the traffic signal control optimization method based on the estimation of the queuing length of the vehicle detector is not strong in adaptability is caused, and the queuing overflow event that the green light time is wasted or the green light time is too short often occurs.
Disclosure of Invention
Aiming at the defects of the prior art, the application provides a signalized intersection dynamic queuing length perception and traffic signal control optimization algorithm, system and device based on vehicle-road cooperation. Aiming at calculating the dynamic queuing length based on a vehicle-road cooperative system according to the traffic flow sensing data of each entrance road and the timing scheme of a traffic signal control system; calculating the minimum green light time required by the emptying of the queued vehicles according to the actual queuing length of each entrance lane at the signalized intersection; and comparing the minimum green time with the green time of the current timing scheme, judging whether the green time is increased or not, and calculating the green time required to be increased so as to reduce the occurrence of secondary parking of the queued vehicles to the maximum extent and maximize the passing efficiency of the signalized intersection. In particular, the amount of the solvent to be used,
on one hand, the invention provides a signalized intersection dynamic queuing length perception and traffic signal control optimization algorithm based on vehicle-road cooperation, which is characterized by comprising the following steps:
under the state that the current queuing length of each phase of the intersection is obtained, calculating the minimum green light time required for emptying the queuing vehicles matched with the current queuing length of each phase of the intersection;
forming an optimal green light ratio adjusting strategy in a state that the minimum green light time required by emptying the queued vehicles does not match the current green light timing;
and updating the current green light timing according to the optimal green signal ratio adjusting strategy.
Preferably, the signalized intersection dynamic queuing length sensing and traffic signal control optimization algorithm based on vehicle-road cooperation is provided, wherein: the calculation of the minimum green time required for emptying the queued vehicles matched with the current queuing length of each phase of the intersection under the condition of acquiring the current queuing length of each phase of the intersection specifically comprises the following steps,
the method for calculating the minimum green light time required by emptying the queued vehicles comprises the following steps:
g′ i,k,p the minimum green light time required for emptying the p phase queuing vehicle in the kth signal period of the ith intersection;
q i,k,p queuing length of the p phase of the kth signal period at the turn-on time of a green light at the ith intersection;
s i,k,p the vehicle driving rate after the p phase green light of the kth signal period of the ith intersection is started;
d i,k,p the arrival rate of the vehicle entering after the p phase green light of the kth signal period of the ith intersection is started.
Preferably, the signalized intersection dynamic queuing length sensing and traffic signal control optimization algorithm based on vehicle-road cooperation is provided, wherein: the step of forming the optimal green signal ratio adjustment strategy in the state that the minimum green light time required by emptying the queued vehicles does not match the current green light time specifically comprises the following steps:
acquiring queuing length data of each signal period of each intersection in each phase, and forming a state space according to the queuing length data;
acquiring action set data of each signal period and each phase of each intersection, and forming a working space according to the action set data;
acquiring average delay of the intersection, and forming a reward function according to the average delay;
forming a crossing traffic control optimization model according to the state space, the working space and the reward function;
and forming an optimal green signal ratio adjusting strategy according to the intersection traffic control optimization model.
Preferably, the signalized intersection dynamic queuing length sensing and traffic signal control optimization algorithm based on vehicle-road cooperation is provided, wherein: the state space is s i,k ＝[q i,k,1 ,q i,k,2 ,…,q i,k,P ]Wherein q is i,k,p Queuing length of the kth signal period p phase at the first intersection;
the working space is as follows: a is i,k ＝{a i,k,1 ,a i,k,2 ,…,a i,k,P }；a i,k,p Set of actions for the p-th phase of the k-th signal cycle at the ith intersection, a i,k,p = { extend the time of green light, the time of green light is invariable, shorten the time of green light };
the average delay of the intersection is taken to form the reward function:
wherein, T i,k,p The cycle duration of the p phase of the kth signal cycle of the ith intersection is obtained;
λ i,k,p (n) selecting motion a from motion space for the kth phase of the kth signal cycle of the ith intersection i,k Taking the nth action a i,k,p (1) The green signal ratio of the second time period,
g′ i,k,p (n) selecting motion a from motion space for the kth phase of the kth signal cycle of the ith intersection i,k Taking the nth action a i,k,p (n) the subsequent green light time period, g 'if the action is to prolong the green light time' i,k,p (n)＝g i,k,p (n) + Δ t, g 'if the operation is to shorten the green time' i,k,p (n)＝g i,k,p (n)-Δt；
x i,k,p (n) selecting motion a from motion space for the kth phase of the kth signal cycle of the ith intersection i,k Taking the nth action a i,k,p (ii) the degree of saturation after (n),
q i,k,p the maximum value of the queuing length of the p phase lane in the kth signal period of the ith intersection is obtained;
s ik,p and queuing the saturation flow rate of the lane with the maximum length for the p phase of the kth signal period of the ith intersection.
Gamma belongs to [0, 1) is a discount factor used for endowing different weights to delay rewards obtained by different synchronization numbers;
r i,k (j) Is a reward function.
Preferably, the signalized intersection dynamic queuing length sensing and traffic signal control optimization algorithm based on vehicle-road cooperation is provided, wherein: the step of forming an optimal split-green ratio adjustment strategy according to the intersection traffic control optimization model specifically comprises the following steps:
Q π* ＝max π* Q(s i,k (0),a i,k (1),a i,k (2),…,a i,k (n))
π * and adjusting the strategy for determining the optimal split ratio.
On the other hand, the present application further provides a signalized intersection dynamic queuing length sensing and traffic signal control optimization system based on vehicle-road coordination, wherein, the system comprises:
a collecting unit: collecting the current queuing conditions of the intersection in each phase and forming the current queuing length of each phase of the intersection for uploading;
the calculation unit is used for calculating the minimum green light time required for emptying the queuing vehicles matched with the current queuing length of each phase of the intersection under the state of acquiring the current queuing length of each phase of the intersection;
the adjusting unit is used for forming an optimal green signal ratio adjusting strategy in the state that the minimum green light time required by emptying the queued vehicles does not match the current green light timing;
and the updating unit is used for updating the current green light timing according to the optimal green signal ratio adjusting strategy.
Preferably, the signalized intersection dynamic queuing length sensing and traffic signal control optimizing system based on vehicle-road cooperation is described above, wherein: the adjusting unit specifically comprises:
the state space forming device is used for acquiring queuing length data of each signal period of each intersection and forming a state space according to the queuing length data;
the working space forming device is used for acquiring action set data of each signal period and each phase of each intersection and forming a working space according to the action set data;
the reward function forming device is used for obtaining the average delay of the intersection and forming a reward function according to the average delay;
the adjustment strategy forming device forms an intersection traffic control optimization model according to the state space, the working space and the reward function;
and forming an optimal green signal ratio adjusting strategy according to the intersection traffic control optimization model.
In another aspect, the present application further provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the aforementioned signalized intersection dynamic queuing length sensing and traffic signal control optimization algorithm based on vehicle-road coordination when executing the computer program.
Finally, the present application further provides a computer program product, which includes computer readable code or a readable storage medium carrying computer readable code, when the computer readable code is executed in a processor of an electronic device, the processor in the electronic device executes an algorithm for implementing the above-mentioned signalized intersection dynamic queue length sensing and traffic signal control optimization algorithm based on vehicle-road coordination.
Compared with the prior art, the invention has the beneficial effects that:
the embodiment calculates the dynamic queuing length based on the vehicle-road cooperative system according to the traffic flow sensing data of each entrance road and the timing scheme of the traffic signal control system; calculating the minimum green light time required by the emptying of the queued vehicles according to the actual queuing length of each entrance lane at the signalized intersection; and comparing the minimum green time with the green time of the current timing scheme, judging whether the green time is increased or not, and calculating the green time required to be increased so as to reduce the occurrence of secondary parking of the queued vehicles to the maximum extent and maximize the passing efficiency of the signalized intersection. The method does not depend on the arrangement position and the number of the vehicle detectors, and has strong adaptability; the manual light control on the traffic police in the morning and evening peak can be reduced or replaced, and the labor is saved.
Drawings
Fig. 1 is a schematic flow chart of a signalized intersection dynamic queuing length sensing and traffic signal control optimization algorithm based on vehicle-road coordination according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of a signalized intersection dynamic queuing length sensing and traffic signal control optimization algorithm based on vehicle-road coordination according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
On one hand, as shown in fig. 1, the invention provides a signalized intersection dynamic queuing length sensing and traffic signal control optimization algorithm based on vehicle-road cooperation, wherein the algorithm comprises the following steps:
step S110, under the state that the current queuing length of each phase of the intersection is obtained, calculating the minimum green light time required for emptying the queuing vehicles matched with the current queuing length of each phase of the intersection;
step S120, placing the vehicle in lineForming an optimal green signal ratio adjusting strategy in a state that the minimum green light time required by the air is not matched with the current green light timing; schematically, a signal lamp timing scheme of the intersection is obtained in real time through a cloud control platform of the vehicle-road cooperative system, wherein the scheme comprises green lamp time lengths of different phases of the intersection at different moments, namely g i,k ＝[g i,k,1 ,g i,k,2 ,...,g i,k,P ]，g i,k,p The green light duration of the P phase of the kth signal period of the ith intersection is P = 1.
Comparing the minimum green light time calculated by each phase of the intersection with the green light time of the current timing scheme, wherein the p phase of the kth signal period of the ith intersection meets the minimum green light time g 'required by emptying of the queued vehicles' i,k,p The green light time length of the p phase of the kth signal period of the ith intersection is g i,k,p If, if
g′ i,k,p ≤g i,k,p Keeping the current timing scheme unchanged; otherwise, step S120 is performed.
And step S130, updating the current green light timing according to the optimal green signal ratio adjusting strategy.
The embodiment calculates the dynamic queuing length based on the vehicle-road cooperative system according to the traffic flow sensing data of each entrance road and the timing scheme of the traffic signal control system; calculating the minimum green light time required by the emptying of the queued vehicles according to the actual queuing length of each entrance lane at the signalized intersection; and comparing the minimum green time with the green time of the current timing scheme, judging whether the green time is increased or not, and calculating the green time required to be increased so as to reduce the occurrence of secondary parking of the queued vehicles to the maximum extent and maximize the passing efficiency of the signalized intersection. The method does not depend on the arrangement position and the number of the vehicle detectors, and has strong adaptability; the manual light control on the traffic police in the morning and evening peak can be reduced or replaced, and the labor is saved.
As a further preferred embodiment, the signalized intersection dynamic queuing length sensing and traffic signal control optimization algorithm based on vehicle-road coordination is described above, wherein: step S110, under the state of obtaining the current queuing length of each phase of the intersection, calculating the minimum green light time required for forming the queuing vehicle emptying matched with the current queuing length of each phase of the intersection specifically comprises,
the method for calculating the minimum green light time required by emptying the queued vehicles comprises the following steps:
g′ i,k,p the minimum green light time required for emptying the No. p phase queuing vehicle in the No. i signal period;
q i,k,p queuing length of the p phase of the kth signal period at the turn-on time of a green light at the ith intersection;
s i,k,p the vehicle driving rate after the p phase green light of the kth signal period of the ith intersection is started;
d i,k,p the arrival rate of the driving vehicle after the p phase green light is started in the kth signal period of the ith intersection.
Further, the signalized intersection dynamic queuing length sensing and traffic signal control optimization algorithm based on vehicle-road cooperation is provided, wherein: step S120, forming an optimal split-green ratio adjustment strategy in a state where the minimum split-green time required for emptying the queued vehicle does not match the current split-green time specifically includes: as shown in figure 2 of the drawings, in which,
step S1201, obtaining queuing length data of each signal period and each phase of each intersection, and forming a state space according to the queuing length data; the state space is si,k ＝[q i,k,1 ,q i,k,2 ,...,q i,k,P ]Wherein q is i,k,p Queuing length of the kth signal period and the pth phase of the ith intersection;
step S1202, acquiring action set data of each phase of each signal period of each intersection, and forming a working space according to the action set data; the working space is as follows: ai,k ＝{a i,k,1 ,a i,k,2 ,...,a i,k,P }；a i,k,p for the ith intersectionSet of actions for the p-th phase of k signal cycles, a i,k,p = { extend the time of green light, the time of green light is invariable, shorten the time of green light };
step S1203, obtaining average delay of the intersection, and forming a reward function according to the average delay; the reward function is:
wherein, T i,k,p The cycle duration of the p phase of the kth signal cycle of the ith intersection is set;
λ i,k,p (n) selecting motion a from motion space for the kth phase of the kth signal cycle of the ith intersection i,k Taking the nth action a i,k,p (1) The green signal ratio of the second time period,
g′ i,k,p (n) selecting motion a from motion space for the kth phase of the kth signal cycle of the ith intersection i,k Taking the nth action a i,k,p (n) the subsequent green light time period, g 'if the action is to prolong the green light time' i,k,p (n)＝g i,k,p (n) + Δ t, g 'if the operation is to shorten the green time' i,k,p (n)＝g i,k,p (n)-Δt；
x i,k,p (n) selecting motion a from motion space for the kth phase of the kth signal cycle of the ith intersection i,k Taking the nth action a i,k,p (ii) the degree of saturation after (n),
q i,k,p the maximum value of the queuing length of the p phase lane in the kth signal period of the ith intersection is obtained;
s i,k,p and queuing the saturation flow rate of the lane with the maximum length for the p phase of the kth signal period of the ith intersection.
Gamma is an element [0, 1) which is a discount factor and is used for endowing different weights to delay rewards obtained by different synchronization numbers;
r i,k (j) Is a reward function.
And S1204, forming an intersection traffic control optimization model according to the state space, the working space and the reward function, wherein the intersection traffic control model is formed by combining the state space, the working space and the reward function based on Markov decision.
Step S1205, forming an optimal green signal ratio adjustment strategy according to the intersection traffic control optimization model, specifically comprising:
Q π* ＝max π* Q(s i,k (0),a i,k (1),a i,k (2),...,a i,k (n))
π * and adjusting the strategy for determining the optimal split ratio.
One embodiment is illustrated:
assuming an initial state s before signal control optimization i,k (0) Selecting an action a from the action space i,k (1) After execution the state space becomes s i,k (1) To obtain a delay reward r i,k (0)，
d i,k,p (1) -selecting motion a from motion space for kth phase of kth signal period of ith intersection i,k Take the 1 st action a i,k,p (1) Later delay; d i,k,p (0) -the kth signal period of the ith intersection is the p-th phase initial state s i,k (0) Delay of (d); k is a radical of formula p The value is determined by the p phase traffic flow, the phase weight with large flow is set to be larger, and the phase weight with small flow is set to be smaller; p =1,.. P, P is the phase number of the kth signal cycle at the ith intersection
To delay d i,k,p (1) For example, the calculation formula is as follows
Two components are adopted.
In the formula:
T i,k,p the cycle duration of the p phase of the kth signal cycle of the ith intersection is obtained;
λ i,k,p (1) Selecting motion a from motion space for the p phase of the kth signal period of the ith intersection i,k Take the 1 st action a i,k,p (1) Rear green ratio, λ i,k,p (1)＝g′ i,k,p (1)/T i,k,p ，g′ i,k,p (1) Selecting motion a from motion space for the p phase of the kth signal period of the ith intersection i,k Take the 1 st action a i,k,p (1) The subsequent green light time is g 'if the action is to prolong the green light time' i,k,p (1)＝g i,k,p (1) + Δ t, if the operation is to shorten the green time, g' i,k,p (1)＝g i,k,p (1)-Δt；
x i,k,p (1) Selecting motion a from motion space for the p phase of the kth signal period of the ith intersection i,k Take the 1 st action a i,k,p (1) Rear saturation, x i,k,p (1)＝q i,k,p /(s i,k,p ×λ i,k,p (1))，q i,k,p The maximum value of the queuing length of the p phase lane in the kth signal period of the ith intersection is obtained; s is i,k,p And queuing the saturation flow rate of the lane with the maximum length for the kth phase of the ith signal period at the ith intersection.
By analogy, a series of actions are passed through in the action space i,k (1),a i,k (2) Say } after execution, the state space becomes s i,k (n), the delay reward earned.
Example two
On the other hand, the invention provides a signalized intersection dynamic queuing length sensing and traffic signal control optimization system based on vehicle-road cooperation, wherein the signalized intersection dynamic queuing length sensing and traffic signal control optimization system comprises:
the acquisition unit: collecting the current queuing conditions of the intersection in each phase and forming the current queuing length of each phase of the intersection for uploading; the acquisition unit can be a millimeter wave radar, a radar vision integrated machine and the like, the millimeter wave radar and the radar vision integrated machine acquire the traffic flow and the queuing length of different phases of the signalized intersection at different moments, particularly the queuing length of the different phases of the intersection at the green light starting moment, so that the number of vehicles passing through the intersection during the green light period of each phase of the signalized intersection can be known;
the calculation unit is used for calculating the minimum green light time required for emptying the queuing vehicles matched with the current queuing length of each phase of the intersection under the state of acquiring the current queuing length of each phase of the intersection;
the adjusting unit is used for forming an optimal green signal ratio adjusting strategy in the state that the minimum green light time required by emptying the queued vehicles does not match the current green light timing;
and the updating unit is used for updating the current green light timing according to the optimal green signal ratio adjusting strategy.
As a further preferred embodiment, the signalized intersection dynamic queuing length sensing and traffic signal control optimization algorithm based on vehicle-road coordination is described above, wherein: the adjusting unit specifically comprises:
the state space forming device is used for acquiring queuing length data of each signal period of each intersection and forming a state space according to the queuing length data;
the working space forming device is used for acquiring action set data of each signal period and each phase of each intersection and forming a working space according to the action set data;
the reward function forming device is used for calculating the average delay of the intersection to form a reward function;
the adjustment strategy forming device forms an intersection traffic control optimization model according to the state space, the working space and the reward function;
and forming an optimal green signal ratio adjusting strategy according to the intersection traffic control optimization model.
The working principle of the signalized intersection dynamic queuing length sensing and traffic signal control optimization system based on vehicle-road coordination is the same as that of the signalized intersection dynamic queuing length sensing and traffic signal control optimization method based on vehicle-road coordination provided in the first embodiment, and details are not repeated here.
EXAMPLE III
The embodiment of the application provides an electronic device, and the electronic device can be integrated with a control device based on a game running environment. Fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application. As shown in fig. 3, the present embodiment provides an electronic device 400, which includes: one or more processors 420; a storage 410 for storing one or more programs that, when executed by the one or more processors 420, cause the one or more processors 420 to perform:
under the state that the current queuing length of each phase of the intersection is obtained, calculating the minimum green light time required for emptying the queuing vehicles matched with the current queuing length of each phase of the intersection;
forming an optimal green light ratio adjusting strategy in a state that the minimum green light time required by emptying the queued vehicles does not match the current green light timing;
and updating the current green light timing according to the optimal green signal ratio adjusting strategy.
As shown in fig. 3, the electronic device 400 includes a processor 420, a storage device 410, an input device 430, and an output device 440; the number of the processors 420 in the electronic device may be one or more, and one processor 420 is taken as an example in fig. 3; the processor 420, the storage device 410, the input device 430, and the output device 440 in the electronic device may be connected by a bus or other means, and are exemplified by a bus 450 in fig. 3.
The storage device 410 is a computer-readable storage medium, and can be used for storing software programs, computer executable programs, and module units, such as program instructions corresponding to the control method based on the game execution environment in the embodiment of the present application.
The storage device 410 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the terminal, and the like. Further, the storage 410 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some examples, storage 410 may further include memory located remotely from processor 420, which may be connected via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The input device 430 may be used to receive input numbers, character information, or voice information, and to generate key signal inputs related to user settings and function control of the electronic device. The output device 440 may include a display screen, speakers, etc.
As shown in fig. 3, the electronic device 400 includes a processor 420, a storage device 410, an input device 430, and an output device 440; the number of the processors 420 in the electronic device may be one or more, and one processor 420 is taken as an example in fig. 3; the processor 420, the storage device 410, the input device 430, and the output device 440 in the electronic device may be connected by a bus or other means, and are exemplified by a bus 450 in fig. 3.
The storage device 410 is a computer-readable storage medium, and can be used for storing software programs, computer executable programs, and module units, such as program instructions corresponding to the control method based on the game execution environment in the embodiment of the present application.
The storage device 410 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the terminal, and the like. Further, the storage 410 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some examples, storage 410 may further include memory located remotely from processor 420, which may be connected via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The input device 430 may be used to receive input numbers, character information, or voice information, and to generate key signal inputs related to user settings and function control of the electronic device. The output device 440 may include a display screen, speakers, etc.
Example four
In some embodiments, the methods described above may be implemented as a computer program product. The computer program product may include a computer-readable storage medium having computer-readable program instructions embodied thereon for carrying out various aspects of the present disclosure. Specifically, the method comprises the following steps:
under the state that the current queuing length of each phase of the intersection is obtained, calculating the minimum green light time required for emptying the queuing vehicles matched with the current queuing length of each phase of the intersection;
forming an optimal green light ratio adjusting strategy in a state that the minimum green light time required by emptying the queued vehicles does not match the current green light timing;
and updating the current green light timing according to the optimal green signal ratio adjusting strategy.
The computer-readable storage medium described above may be a tangible device that can hold and store the instructions for use by the instruction execution device. The computer readable storage medium may be, for example, but not limited to, an electronic memory device, a magnetic memory device, an optical memory device, an electromagnetic memory device, a semiconductor memory device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a Static Random Access Memory (SRAM), a portable compact disc read-only memory (CD-ROM), a Digital Versatile Disc (DVD), a memory stick, a floppy disk, a mechanical coding device, such as punch cards or in-groove projection structures having instructions stored thereon, and any suitable combination of the foregoing. Computer-readable storage media as used herein is not to be construed as transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission medium (e.g., optical pulses through a fiber optic cable), or electrical signals transmitted through electrical wires.
The computer-readable program instructions described herein may be downloaded from a computer-readable storage medium to a respective computing/processing device, or to an external computer or external storage device over a network, such as the internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. The network adapter card or network interface in each computing/processing device receives computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in the respective computing/processing device.
The computer program instructions for carrying out operations of the present disclosure may be assembly instructions, instruction Set Architecture (ISA) instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including an object oriented programming language, as well as conventional procedural programming languages. The computer-readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider). In some embodiments, aspects of the disclosure are implemented by personalizing an electronic circuit, such as a programmable logic circuit, a Field Programmable Gate Array (FPGA), or a Programmable Logic Array (PLA), with state information of computer-readable program instructions, which can execute the computer-readable program instructions.
These computer-readable program instructions may be provided to a processing unit of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processing unit of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer-readable program instructions may also be stored in a computer-readable storage medium that can direct a computer, programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer-readable medium storing the instructions comprises an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.
The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer, other programmable apparatus or other devices implement the functions/acts specified in the flowchart and/or block diagram block or blocks.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
Having described embodiments of the present disclosure, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen in order to best explain the principles of the embodiments, the practical application, or technical improvements to the technology in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.
Claims (9)
1. A signalized intersection dynamic queuing length perception and traffic signal control optimization algorithm based on vehicle-road cooperation is characterized by comprising the following steps:
under the state that the current queuing length of each phase of the intersection is obtained, calculating the minimum green light time required for emptying the queuing vehicles matched with the current queuing length of each phase of the intersection;
forming an optimal green signal ratio adjusting strategy in the state that the minimum green light time required by emptying the queued vehicles is not matched with the current green light time;
and updating the current green light timing according to the optimal green signal ratio adjusting strategy.
2. The signalized intersection dynamic queuing length sensing and traffic signal control optimization algorithm based on vehicle-road coordination according to claim 1, characterized in that: the calculation of the minimum green light time required for emptying the queuing vehicles matched with the current queuing length of each phase of the intersection under the state of acquiring the current queuing length of each phase of the intersection specifically comprises the following steps,
the method for calculating the minimum green light time required by emptying the queued vehicles comprises the following steps:
g′ i,k,p the minimum green light time required for emptying the p phase queuing vehicle in the kth signal period of the ith intersection;
q i,k,p queuing length of the p phase of the kth signal period at the turn-on time of a green light at the ith intersection;
s i,k,p the vehicle driving rate after the p phase green light of the kth signal period of the ith intersection is started;
d i,k,p the arrival rate of the vehicle entering after the p phase green light of the kth signal period of the ith intersection is started.
3. The signalized intersection dynamic queuing length sensing and traffic signal control optimization algorithm based on vehicle-road coordination according to claim 1, characterized in that: the forming of the optimal split-green ratio adjustment strategy in the state that the minimum split-green time required for emptying the queued vehicles does not match the current split-green time specifically comprises:
acquiring queuing length data of each signal period of each intersection in each phase, and forming a state space according to the queuing length data;
acquiring action set data of each signal period and each phase of each intersection, and forming a working space according to the action set data;
acquiring average delay of the intersection, and forming a reward function according to the average delay;
forming a crossing traffic control optimization model according to the state space, the working space and the reward function;
and forming an optimal green signal ratio adjusting strategy according to the intersection traffic control optimization model.
4. The signalized intersection dynamic queuing length sensing and traffic signal control optimization algorithm based on vehicle-road coordination according to claim 3, characterized in that:
the state space is s i,k ＝[q i,k,1 ,q i,k,2 ,…,q i,k,P ]Wherein q is i,k,p Queuing length of the kth signal period and the pth phase of the ith intersection;
the working space is as follows: a is i,k ＝{a i,k,1 ,a i,k,2 ,…,a i,k,P }；a i,k,p Set of actions for the p-th phase of the k-th signal cycle at the ith intersection, a i,k,p = { extend the time of green light, the time of green light is invariable, shorten the time of green light };
the average delay of the intersection is taken to form the reward function:
wherein, T i,k,p The cycle duration of the p phase of the kth signal cycle of the ith intersection is obtained;
λ i,k,p (n) selecting motion a from motion space for the kth phase of the kth signal cycle of the ith intersection i,k Taking the nth action a i,k,p (1) The green signal ratio of the second time period,
g′ i,k,p (n) selecting motion a from motion space for the kth phase of the kth signal cycle of the ith intersection i,k Taking the nth action a i,k,p (n) the subsequent green light time period, g 'if the action is to prolong the green light time' i,k,p (n)＝g i,k,p (n) + Δ t, g 'if the operation is to shorten the green time' i,k,p (n)＝g i,k,p (n)-Δt；
x i,k,p (n) selecting motion a from motion space for the kth phase of the kth signal cycle of the ith intersection i,k Taking the nth action a i,k,p (ii) the degree of saturation after (n),
q i,k,p the maximum value of the queuing length of the p phase lane in the kth signal period of the ith intersection is obtained;
s i,k,p queuing length for the p phase of the kth signal period of the ith intersectionA maximum lane saturation flow rate;
gamma belongs to [0, 1) as a discount factor;
r i,k (j) Is a reward function.
5. The signalized intersection dynamic queuing length sensing and traffic signal control optimization algorithm based on vehicle-road coordination according to claim 4, characterized in that: the step of forming an optimal split-green ratio adjustment strategy according to the intersection traffic control optimization model specifically comprises the following steps:
Q π* ＝max π* Q(s i,k (0),a i,k (1),a i,k (2),…,a i,k (n))
π * and adjusting the strategy for determining the optimal split ratio.
6. A signalized intersection dynamic queuing length perception and traffic signal control optimization system based on vehicle-road cooperation is characterized by comprising:
a collecting unit: collecting the current queuing conditions of the intersection in each phase and forming the current queuing length of each phase of the intersection for uploading;
the calculation unit is used for calculating the minimum green light time required by emptying the queued vehicles matched with the current queuing length of each phase of the intersection under the condition of acquiring the current queuing length of each phase of the intersection;
the adjusting unit is used for forming an optimal green signal ratio adjusting strategy in the state that the minimum green light time required by emptying the queued vehicles does not match the current green light timing;
and the updating unit is used for updating the current green light timing according to the optimal green signal ratio adjusting strategy.
7. The signalized intersection dynamic queuing length sensing and traffic signal control optimization system based on vehicle-road coordination according to claim 6, wherein: the adjusting unit specifically comprises:
the state space forming device is used for acquiring queuing length data of each signal period of each intersection and forming a state space according to the queuing length data;
the working space forming device is used for acquiring action set data of each signal period of each intersection and each phase, and forming a working space according to the action set data;
the reward function forming device is used for acquiring the average delay of the intersection and forming a reward function according to the average delay;
the adjustment strategy forming device forms an intersection traffic control optimization model according to the state space, the working space and the reward function;
and forming an optimal green signal ratio adjusting strategy according to the intersection traffic control optimization model.
8. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the signalized intersection dynamic queue length sensing and traffic signal control optimization algorithm based on vehicle-to-vehicle coordination according to any one of claims 1 to 5 when executing the computer program.
9. A computer program product comprising computer readable code or a readable storage medium carrying computer readable code which, when run in a processor of an electronic device, the processor in the electronic device executes an algorithm for implementing the intersection dynamic queue length awareness and traffic signal control optimization based on vehicle-to-road coordination according to any one of claims 1 to 5.
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