CN115424460B - Road green wave optimization method and system - Google Patents
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Abstract
The application relates to a road green wave optimization method and system, and relates to the field of intelligent traffic. The method comprises the steps of determining a green wave scene and obtaining a green wave road optimization control strategy table; dividing green wave time periods, including obtaining date types of calculation dates; acquiring an operation scheme, and determining a scheme corresponding to the minimum saturation as a coordination period scheme; generating a coordination phase, including obtaining phase parameters of the coordination period scheme; calculating intersection timing, and acquiring a configured scheduling plan and a time period; determining a green wave period, and determining an optimization period with the smallest deviation from the common period as a green wave coordination period; determining the green wave band speed, and calculating the tertile of each road section data as a coordination band speed value; and generating a green wave scheme, and adjusting the phase difference according to the original phase difference of the green wave road. According to the road green wave optimization method and system, the phase difference of a plurality of road sections in the intersection phase timing and the area is calculated according to the intersection traffic flow and the road section vehicle speed, the vehicle traffic capacity is improved, and the area traffic pressure is relieved.
Description
Technical Field
The application relates to the field of intelligent traffic, in particular to a road green wave optimization method and system.
Background
Currently, a green wave road refers to that on a specified traffic route, after the speed of a road section is specified, a signal controller correspondingly adjusts the green light starting time of each crossing through which a traffic flow passes according to the distance of the road section, so as to ensure that the traffic flow just encounters a green light when reaching each crossing. The green wave traffic reduces the stopping of vehicles at intersections and improves the average driving speed and the traffic capacity. However, at present, due to different sizes of traffic flows passing through different time environments and continuous increase of the quantity of the reserved motor vehicles along with urban development, the green light starting time and the phase release time of each intersection are required to be adjusted by an indefinite person according to the traffic flows, and the situation that the traffic flows cannot be flexibly dealt with is not achieved.
In addition, in order to improve the traffic capacity of the whole road in the area, the intersecting roads of a plurality of roads in the area are required to realize a green wave effect, so that the effect of relieving the traffic pressure in the area is achieved. Based on the problems, the invention needs to design an optimization method of the green wave road, which not only can reduce the manual workload, but also can rapidly and flexibly calculate the scheme according to the traffic flow and the road section speed of different time dimensions.
Therefore, it is desirable to provide a road green wave optimization method and system, which calculate the phase timing of an intersection and the phase difference of a plurality of road sections in an area according to the traffic flow of the intersection and the vehicle speed of the road sections, improve the traffic capacity of the vehicle, and relieve the traffic pressure of the area.
Disclosure of Invention
According to a first aspect of some embodiments of the present application, a road green wave optimization method is provided, and is applied to a platform (e.g., a cloud control platform, etc.), where the method may include determining a green wave scene, and acquiring a green wave road optimization control policy table; dividing green wave time periods, including obtaining date types of calculation dates; acquiring an operation scheme, and determining a scheme corresponding to the minimum saturation as a coordination period scheme; generating a coordination phase, including obtaining phase parameters of the coordination period scheme; calculating intersection timing, and acquiring a configured scheduling plan and a time period; determining a green wave period, and determining an optimization period with the smallest deviation from the common period as a green wave coordination period; determining the green wave band speed, and calculating the tertile of each road section data as a coordination band speed value; and generating a green wave scheme, and adjusting the phase difference according to the original phase difference of the green wave road.
In some embodiments, the determining a green wave scene, and obtaining a green wave road optimization control policy table specifically includes obtaining a green wave road list to be optimized, including green wave road optimization priority and green wave road key intersections; acquiring green wave road parameter data to be optimized, wherein the parameter data comprise associated intersections, intersection sequences, intersection intervals and intersections; obtaining at least two green wave road groups, wherein each green wave road group comprises green wave roads with the same intersection, and then optimizing the green wave roads of each green wave road group respectively.
In some embodiments, the dividing the green wave period specifically includes:
s301 obtaining a date type of a calculated date, wherein the date type is the previous day when calculating the previous day;
s302, acquiring all key intersections in each green wave road group;
s303. obtaining the lane reference flow of each lane of all the key intersections of the date type in s302 every 5 minutes, and calculating the sum of the reference flows of each lane of the date type in 24 hours as follows:
s304. decimate data F i＝1....288 Generating an initial remainder set ass305. find maximum data F i And its sequence number i;
s306. set the data comparison threshold αF of the present group i Generating a first set of dataThe corresponding remainder set is
s307. F i The data is compared from the beginning to the two sides, namely the data F is in the sequence number i bit i Respectively with forward sequence number i-1 data F i-1 And backward sequence number i+1 bit data F i+1 Comparing to determine deviation beta;
s308. determining beta and threshold value alpha F i A relationship;
s309. if β is less than or equal to αF i Sequence number i-1 bit data F i-1 And sequence number i+1 bit data F i+1 And sequence number i bit data F i Belongs to a group, updates the data set of the group intoThe corresponding remainder set is +.>s310. continue to compare bit data F of sequence number i-2 i-2 And sequence number i+2 bit data F i+2 And sequence number i bit data F i The deviation beta of (2);
s311. If beta is not more than alpha F i Updating the set of data sets toThe corresponding remainder set is
s312. continue to compare the sequence number i-m bit data F i-m And sequence number i+u bit data F i+u And sequence number i bit data F i The deviation beta of (2);
s313. if beta is not more than alpha F i Updating the set of data sets toThe corresponding remainder set is +.>Wherein, i-m and i+u in the remainder set represent the data set to be put into after being sequentially and circularly compared;
s314. if beta>αF i Sequence number i-m bit data F i-m And sequence number i+u bit data F i+u And sequence number i bit data F i Not belonging to one group, i.e. the first set of data sets has the result shown in s311, the first set of data sets has a maximum value of F i ；
s315. in remainder setContinuing to select the maximum value, i.e. serial number z-bit data F z Generate a second set of data->The corresponding remainder set is +.>Wherein z is used to represent the data location of the maximum in the dataset;
s316. data F in serial number z z For starting point to compare data to two sides, i.e. with serial number z bit data F z Respectively with the forward sequence number z-1 bit data F z-1 And backward sequence number z+1 bit data F z+1 Comparing to determine deviation beta;
s317. judge the comparison sequence number z-1 bit data F before and after the sequence number z z-1 And sequence number z+1 bit data F z+1 Whether or not in remainder set D R In the remainder set D R In the corresponding direction search is continued, if not in the remainder set D R The corresponding direction search is ended;
s318. repeating s309-s317, determining the second set of data sets asThe maximum value of the second group of data sets is F z The corresponding remainder set is +.>The i-m and i+u in the remainder set are used for indicating whether the data set is needed to be put into after the sequential cyclic comparison;
s319. repeating s309-s318 until remainder set D R No residual data in the data D, x groups of data D are generated according to the original data sequence number 1 ，D 2 ..D x Reordering, namely:
comparing the data number of each group of data sets, when a certain group of data sets D x When the number of data in the data set D is less than gamma x Merging into D x At D 1、2...x A previous or subsequent set of data sets in the data set ordering;
s320. and->Representing the data sets of the previous group and the next group, respectively, judging +.> Is of a size of (2); when->Will D x DataIntegration and->A data set; when (when)Will D x Data sets are combined to->A data set; when->Comparison and judgment->And D x Sum of absolute difference values of all data of data set and MAXD x And->The sum of absolute difference values of all data of the data set is D x Merging into a dataset with a smaller sum of absolute differences;
s321. from the repartitioned dataset:
performing data set analysis;
s322. outputting a 24-hour period division result in the date type:
(0、g*15/60)、(g*15/60、d*15/60)、(d*15/60、z*15/60、)......((j+1)*15/60、24:00)。
In some embodiments, the dividing the green wave period specifically includes:
s401, acquiring a configuration scheme of a green wave road in a present period, and performing period scheme matching on the green wave road divided by an update period;
s402. according to the time interval dividing result, respectively obtaining at least two schemes of each intersection in the time interval under the date type;
s403. obtaining 5 minutes reference flow and Σf of each lane of each intersection b-5 ；
s404. calculate the hourly traffic capacity C of each scenario obtained in s402 h ；
s405. calculate the saturation Σf for each scheme b-5 /C h ；
s406. determining at least two saturation Σf b-5 /C h The scheme corresponding to the minimum value in the system is an intersection coordination period scheme.
In some embodiments, the generating the coordination phase specifically includes:
s501. acquiring the coordination phase of the green wave road in the existing period, and performing coordination phase matching on the green wave road divided by the updated period based on the period scheme;
s502, acquiring the internal steering relation of all intersections of the green wave road, if the acquisition is successful, exiting the current green wave road optimization if the acquisition is unsuccessful;
s503, acquiring association relations between the upstream road section, the downstream road section and the intersection of the green wave road, if the acquisition succeeds, exiting the current green wave road optimization if the acquisition fails;
S504, respectively obtaining forward and reverse coordinated flow directions of each intersection of the green wave road according to the association relation between the upstream intersection and the downstream intersection of the green wave road;
s505. judging the direction of the road passing through the upstream road section, the connection road junction and the downstream road section to obtain the association relation between the two road sections and the connection road junction, judging the direction of the connection road junction of the starting road section and the ending road section, and judging the steering lane of the road junction from the steering starting direction of the road junction to the steering ending direction of the road junction;
s506, acquiring phase parameters according to the forward and reverse steering lanes of s505, and acquiring the phase of the current steering lane of the current period scheme at the intersection, and if at least two phases exist, arranging the at least two phases according to the phase sequence to serve as a coordination phase;
in some embodiments, the calculating the intersection timing, obtaining the configured scheduling plan and the configured time period specifically includes:
s601. acquiring a scheduling plan and a time period of a green wave road in a present time period, and acquiring initial timing parameters of each intersection;
s602, according to the dispatching plan and the time period, obtaining the sum Sigma f of the reference flow of each lane every 5 minutes in the time period of each intersection b-5 Performing timing optimization on the successfully acquired intersections, and configuring initial timing parameters for the unobtainable intersections;
s603. will Σf b-5 Converting the small flow rate to the intersectionT i The length of the hour period after the period division is the same;
s604, obtaining intersection lane canalization information, phase sequence of the time period scheme, lane traffic capacity and period duration T 0 ；
s605. calculating the flow ratio of each lane in the periodWherein f h C is the traffic lane hour flow x A configuration value for a lane hour saturation flow rate;
s606. determining the maximum flow ratio y of each phase of the current time period scheme i ＝max[y x ]Wherein i represents a phase number, and if the same lane exists in a plurality of phases, the same lane in different phases is assigned the same value;
s607. calculate the sum of the maximum flow ratios of each phase of the intersection Y = Σy i ；
s608. calculate the green light loss time l= Σ (L) of the time period scheme i +I i -A i ) Wherein the signal loss time of phase i is L i Green light interval time I i Yellow light time A i )
S609, judging Y value interval, if Y is less than 0.7, the period durationIf Y is more than or equal to 0.7 and less than 1, the period duration C 0 ＝1.23Le (2.46-0.02L)*Y The method comprises the steps of carrying out a first treatment on the surface of the If 1 is less than or equal to Y, exiting;
s610. judging the period duration;
s611. if C 0 ≤T 0 +30&C 0 < = 180, then C 0 ＝C 0 ；
s612. if C 0 ≤T 0 +30&C 0 > 180, then C 0 ＝180；
s613 if C 0 ＞T 0 +30&C 0 < = 180, then C 0 ＝T 0 +30；
s614 if C 0 ＞T 0 +30&C 0 > 180, then C 0 ＝180；
s615. calculating effective green light time length G of period e ＝C 0 -L；
s616. calculating the ratio of the sum of the flow ratios of the phase flow ratios
s617 calculating the effective green light time of each phase
s618. calculate green time Gl of each phase display i ＝Max(g ei 、g min )+L i -A i Wherein g min The minimum green light duration of all phases associated with the current period, max is the maximum value;
s619 calculating the optimization period C 0 ＝∑(GL i +I i )。
In some embodiments, the determining a green wave period and determining an optimization period with the smallest deviation from the common period as a green wave coordination period specifically includes:
s701. obtain all key crossing optimization period C of green wave road group i ；
s702. determining the common period as MaxC i ；
s703. judging the optimization period of each intersectionMaxC i Difference of (2) to determine->MaxC i The green wave coordination period C of the crossing corresponding to the minimum difference value of the optimization period of the crossing co ；
s704. calculating green light time length of each phase of each crossing matching green wave coordination period
In some embodiments, the determining the green band speed, calculating the tertile of each road segment data as the coordinated band speed value specifically includes:
s801. obtaining the velocity v of forward and reverse coordinated flow direction in N continuous same date type current calculation periods at each road opening along the green wave road i ；
s802. calculating the tertile of each road opening speed value;
s803. determine that each third quartile is the coordinated band speed value of the forward and reverse directions of the intersection.
In some embodiments, the generating a green wave scheme adjusts the phase difference according to the original phase difference of the green wave road, and specifically includes: s901. according to each green wave road group, calculating the original phase difference of each green wave road of each group;
s902. according to the optimized priority order of green wave road groups, adjusting the phase difference of the crossing;
s903 generating two arrays including a first array (1) of unadjusted phase difference green wave road arrays and a second array (2) of adjusted phase difference green wave road arrays;
A. acquiring a green wave road with the minimum optimization priority order from a first array (1), finishing adjustment if no data exists, and continuing to circularly adjust if the data exists;
B. acquiring a green wave road with the highest optimization priority order in a second array (2), if no data exists, putting the green wave road acquired by the A into the second array (2), and deleting the green wave road in the first array (1), wherein the phase difference of each intersection of the green wave road is unchanged; if the data exists, judging whether the green wave road obtained in the step (2) and the green wave road obtained in the step (1) have associated intersections, if at least two intersections with higher road grades exist, determining the intersections with higher road grades as reference intersections, adjusting the phase differences of all intersections of the green wave road obtained in the step (1), and transferring the adjusted green wave road from the first array (1) to the second array (2); the adjusting the phase difference includes:
the phase difference of the intersection in the green wave road of the second array (2) is t 0 The phase difference in the green wave road acquired in the first array (1) is t 1 The phase difference deviation is t 0 -t 1 The phase difference after the adjustment of other intersections of the green wave road obtained in the first array (1) is [ t ] i -(t 1 -t 0 )]modC i ；
s904 repeating the above s903 until there is no data of green wave road in the first array (1).
In some embodiments, the calculating the green wave road phase difference specifically includes:
s1001. obtaining green wave road parameters including green wave road number, intersection number, and key intersections, wherein each green wave road is provided with at most one key intersection; width w of crossing i Forward distance l of crossing i→i+1 Reverse distance l of crossing i→i-1 Wherein i=1..n, n is the number of intersections;
s1002. obtain timing parameters of intersection i, and forward coordinate phase green light time t i|f Reverse coordination phase green light duration t i|r Forward and reverse coordination phase green light turn-on time difference delta t i|fr ；
s1003. obtain the forward direction coordination belt speed V of intersection i i→i+1 Reverse coordination belt speed V i→i-1 ；
s1004. obtain the forward coordinated phase difference O of intersection i i|f And a reversed coordinated phase difference O i|r ＝O i|f +Δt i|fr ；
s1005. obtain period C of intersection i i ；
S1006, acquiring current coordination types, including bidirectional coordination, forward coordination and reverse coordination;
s1007. calculating the bidirectional coordination phase of intersection i and intersection i+1, and when the type is bidirectional coordination, entering s1007-s1011:
A. Forward coordinated phase difference O of initial fixed intersection i i|f =0, reverse phase difference O i|r ＝Δt i|fr ；
B. Calculating the forward coordinated phase difference of intersection i+1Reverse coordinated phase difference O i+1|r ＝O i+1|f +Δt i+1|fr The method comprises the steps of carrying out a first treatment on the surface of the Wherein the phase difference of the intersection i+1 is respectively from 0 to C i+1 Performing cycle traversal;
C. judging whether the intersection i and the intersection i+1 form bidirectional green waves at the moment, if so, recording forward bandwidth q i→i+1|f Reverse bandwidth q i+1→i|r The method comprises the steps of carrying out a first treatment on the surface of the Comprises the steps of D-G:
D. judging whether the forward direction forms a coordination phase at the moment:[MC i+1 +O i+1|f 、MC i+1 +O i+1|f +t i+1|f ]wherein M is an integer greater than or equal to 0; presence of M makes->[MC i+1 +O i+1|f 、MC i+1 +O i+1|f +t i+1|f ]The overlapping part exists, namely the forward coordinated phase difference of the intersection i+1 is O i+1|f ，
E. Judging whether the reverse direction forms a coordination phase at the moment:[NC i +O i|r 、NC i +O i|r +t i|r ]wherein N is an integer greater than or equal to 0; the presence of N causes[NC i +O i|r 、NC i +O i|r +t i|r ]The coordinated phase difference of the reverse direction of the overlapped part, namely the intersection i+1 is O i+1|f ，/>Forward bandwidth at this time: wherein,
is a point that is in the overlap interval;
F. reverse bandwidth:
wherein,
is a point that is in the overlap interval;
G. when the intersection i and the intersection i+1 form a bidirectional green wave, namely D, E steps are satisfied simultaneously, calculating B=q i→i+1|r +q i+1→i|r Acquiring the forward coordinated phase difference of intersection i+1 corresponding to maxB as O i+1|f The phase difference is two-way coordination between the intersection i and the intersection i+1; if there are at least two values of maxB, the smaller value of forward and reverse bandwidth deviation is obtained, when
When a plurality of values still exist at the moment, determining the intersection i+1The forward coordinated phase difference is O i+1|f Is a smaller value of (2);
H. when the intersection i and the intersection i+1 cannot form a bidirectional green wave, namely the bidirectional coordination condition is not satisfied, the bidirectional green wave is determined to be forward coordination, and the coordination phase difference between the intersection i and the intersection i+1 is calculated to be [0 ],]；
I. Recording whether intersection i and intersection i+1 form bidirectional coordination or not, if not, recording 0, and if so, recording 1, wherein intersection i+1 is phase
Phase difference of intersection i is O i+1|f ；
S1008, repeating the above steps, calculating the coordinated phase difference between the intersection i+1 and the intersection i+2 until the last intersection completes calculation, and generating a final result list [0, O ] 2|f 、O 3|f 、...、O n|f ]；
s1009 calculating the phase difference of the intersection corrected relative to the first intersection as [0, O ] 2 、O 3 、...、O n ]，O 2 ＝O 2|f ，O 3 ＝(O 3|f +O 2|f )modC 3 ，O 4 ＝(O 4|f +O 3|f +O 2|f )modC 4 ，O n ＝(O n-1|f +...+O 3|f +O 2|f )modC n ；
S1010, obtaining whether key intersections exist, if not, the final coordination phase difference of all the intersections is s1008, and if so, modifying the final coordination phase difference, and if so, the final coordination phase difference Off of the key intersections k =0, the critical intersection phase difference correction amount is Δo=0-O k Calculating the final coordination phase difference of other intersections;
s1011 the final coordinated phase difference of all intersections is [0+ΔO, (O) 2 +ΔO)modC 2 、(O 3 +ΔO)modC 3 、...、(O n +ΔO)modC n ]；
When the bidirectional green wave coordination does not exist or the condition is met, calculating the coordination phase between the two intersections by using a forward coordination algorithm when the unidirectional coordination bandwidth is lower than a threshold value;
s1012. calculating the forward coordination phase of intersection i and intersection i+1, and entering s1012-s1015 when the type is forward coordination:
A. when the coordination is forward, the coordination phase difference between the intersection i and the intersection i+1 is calculated as [0 ],]；
B. The steps are repeated to calculate the coordinated phase difference between the intersection i+1 and the intersection i+2 until the last intersection is calculated,
generating a final result list [0 ],...、/>]；
S1013 calculating phase difference of the intersection corrected relative to the first intersection as [0, O ] 2 、O 3 、...、O n ]，
s1014. acquiring whether there is a key intersection, if there is no key intersection, the final coordination phase difference of all intersections is s1013, if there is a key intersection to modify the final coordination phase difference, the final coordination phase difference of the key intersection is Off k =0, the critical intersection phase difference correction amount is Δo=0-O k Calculating the final coordination phase difference of other intersections;
s1015. final coordinated phase difference of all intersections is [0+Δ O, O ] 2 +ΔO、O 3 +ΔO、...、O n +ΔO]；
When the two-way green wave coordination does not exist or the condition is met, calculating the coordination phase between the two intersections by using a forward coordination algorithm when the one-way coordination bandwidth is lower than a threshold value;
s1016. calculating the reverse coordination phase of the intersection i and the intersection i+1, and entering s1016-s1020 when the type is reverse coordination, wherein the intersection sequence is calculated after reordering according to the reverse order:
s1017. calculate the reverse coordination phase of intersection i and intersection i-1, where i=n, n-1,..1;
A. when the coordination is reverse coordination, the coordination phase difference between the intersection i and the intersection i-1 is [0 ],]；
B. Repeating the steps to calculate the coordinated phase difference between the intersection i-1 and the intersection i-2 until the last intersection is completed
Calculating, generating an initial reverse phase difference list of each intersection after the first circulation as [ O ] 1|r 、O 2|r 、...、O n|r ]；
s1018 calculating the corrected forward phase difference list of the intersection relative to the first intersection as [ O ] 1 、O 2 、O 3 、...、O n ]，
O 1 ＝0，
O 2 ＝(O 2|r -O 1|r -Δt 2|fr )modC 2 .......O n ＝[O n|r -(O n-1|r +...+O 3|r +O 2|r )-Δt n|fr ]modC n ；
s1019. acquiring whether there is a critical intersection, if there is no critical intersection, the final coordination phase difference of all intersections is s1017, if there is a critical intersection to modify the final coordination phase difference, the final coordination phase difference of the critical intersection is O k =0, the critical intersection phase difference correction amount is Δo=0-O k ；
s1020. calculating the final coordination phase difference of other intersections, wherein the final coordination phase difference of all intersections is [ 0+Delta O, O ] 2 +ΔO、O 3 +ΔO、...、O n +ΔO]In this case, the opposite directionA coordinated phase difference in the direction;
s1021. traffic signal phase difference of intersection n= (coordinated phase difference-length of coordinated phase from first phase start time) mod c n 。
According to a second aspect of some embodiments of the present application, there is provided a road green wave optimization system comprising a memory configured to store data and instructions; a processor in communication with a memory, wherein, when executing instructions in the memory, the processor is configured to: determining a green wave scene and acquiring a green wave road optimization control strategy table; dividing green wave time periods, including obtaining date types of calculation dates; acquiring an operation scheme, and determining a scheme corresponding to the minimum saturation as a coordination period scheme; generating a coordination phase, including obtaining phase parameters of the coordination period scheme; calculating intersection timing, and acquiring a configured scheduling plan and a time period; determining a green wave period, and determining an optimization period with the smallest deviation from the common period as a green wave coordination period; determining the green wave band speed, and calculating the tertile of each road section data as a coordination band speed value; and generating a green wave scheme, and adjusting the phase difference according to the original phase difference of the green wave road.
Therefore, according to the road green wave optimization method and the road green wave optimization system, the phase difference of a plurality of road sections in the intersection phase timing and the area is calculated according to the intersection traffic flow and the road section vehicle speed, the vehicle traffic capacity is improved, and the area traffic pressure is relieved.
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For a better understanding and to set forth of some embodiments of the present application, reference will now be made to the description of embodiments taken in conjunction with the accompanying drawings in which like reference numerals identify corresponding parts throughout.
Fig. 1 is an exemplary schematic diagram of a road green wave optimization system provided in accordance with some embodiments of the present application.
Fig. 2 is an exemplary flow chart of a road green wave optimization method provided in accordance with some embodiments of the present application.
Detailed Description
The following description with reference to the accompanying drawings is provided to facilitate a comprehensive understanding of the various embodiments of the present application defined by the claims and their equivalents. These embodiments include various specific details for ease of understanding, but these are to be considered exemplary only. Accordingly, those skilled in the art will appreciate that various changes and modifications may be made to the various embodiments described herein without departing from the scope and spirit of the present application. In addition, descriptions of well-known functions and constructions will be omitted herein for brevity and clarity of description.
The terms and phrases used in the following specification and claims are not limited to a literal sense, but rather are only used for the purpose of clarity and consistency in understanding the present application. Thus, it will be appreciated by those skilled in the art that the descriptions of the various embodiments of the present application are provided for illustration only and not for the purpose of limiting the application as defined by the appended claims and their equivalents.
The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which embodiments of the present application are shown, it being apparent that the embodiments described are only some, but not all, of the embodiments of the present application. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.
It is noted that the terminology used in the embodiments of the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the present application. As used in this application and the appended claims, the singular forms "a," "an," "the," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used in this application refers to and encompasses any or all possible combinations of one or more of the associated listed items. The expressions "first", "second", "said first" and "said second" are used for modifying the respective elements irrespective of order or importance, and are used merely for distinguishing one element from another element without limiting the respective elements.
Terminals according to some embodiments of the present application may be intelligent terminals, platforms, equipment, and/or electronic devices, etc.; the intelligent terminal may include a vehicle-mounted terminal or the like. The platform may include a cloud platform or the like, which may include a system platform composed of one or more electronic devices; the equipment may include intelligent networked vehicles (Intelligent Connected Vehicle, ICV); the electronic device may include one or a combination of several of a personal computer (PC, such as tablet, desktop, notebook, netbook, palmtop PDA), client device, virtual reality device (VR), augmented reality device (AR), mixed reality device (MR), XR device, renderer, smart phone, mobile phone, e-book reader, portable Multimedia Player (PMP), audio/video player (MP 3/MP 4), camera and wearable device, etc. According to some embodiments of the present application, the wearable device may include an accessory type (e.g., a watch, a ring, a bracelet, glasses, or a Head Mounted Device (HMD)), an integrated type (e.g., an electronic garment), a decorative type (e.g., a skin pad, a tattoo, or an in-built electronic device), etc., or a combination of several. In some embodiments of the present application, the electronic device may be flexible, not limited to the devices described above, or may be a combination of one or more of the various devices described above. In this application, the term "user" may indicate a person using an electronic device or a device using an electronic device (e.g., an artificial intelligence electronic device).
The embodiment of the application provides a road green wave optimization method and system. In order to facilitate understanding of the embodiments of the present application, the embodiments of the present application will be described in detail below with reference to the accompanying drawings.
Fig. 1 is an exemplary schematic diagram of a road green wave optimization system provided in accordance with some embodiments of the present application. As shown in fig. 1, the road green wave optimization system 100 may include a network 110, a control end 120, a user end 130, a server 140, and the like. Specifically, the control end 120 and the user end 130 establish communication through a network, for example, the control end 120 and the user end 130 may communicate in the same local area network (e.g., the network environment of the same router, etc.). Further, the control end 120 may be connected to the network 110 by a wired (e.g., a network cable, etc.) or a wireless (e.g., a cloud server, etc.), and the user end 130 may establish a communication connection with the network 110 by a wired or wireless (e.g., WIFI, etc.) or the like. In some embodiments, the client 130 may send vehicle real-time information, etc., to the control 120, server 140. Further, the control end 120 and the server 140 may feed back the green wave scheme, the road grade data, etc. to the user end 130. As an example, the server 140 and/or the control terminal 120 may acquire road class data based on the road side device, or acquire road trend information according to map data of the road side device, or the like.
According to some embodiments of the present application, the control end 120 and the user end 130 may be the same or different terminal devices. The terminal device may include, but is not limited to, an intelligent terminal, a cloud platform, a mobile terminal, a computer, and the like. In the intelligent traffic scenario, the control end 120 may include a cloud control platform, and the user end 130 may include a network-connected vehicle. In some embodiments, the control terminal 120 and the user terminal 130 may be integrated in one device, for example, an in-vehicle terminal or the like. In some embodiments, server 140 is one of the computers, with the advantages of faster operation, higher load, etc., than a conventional computer, and the corresponding price is higher. In a network environment, a server may provide computing or application services for other clients (e.g., terminals such as PCs, smartphones, ATMs, and the like, as well as large devices such as transportation systems). The server has high-speed CPU operation capability, long-time reliable operation, strong I/O external data throughput capability and better expansibility. Services that the server may provide include, but are not limited to, assuming the ability to respond to service requests, assuming services, securing services, and the like. The server has an extremely complex internal structure including an internal structure similar to a general computer, etc., as an electronic device, and the internal structure of the server may include a central processing unit (Central Processing Unit, CPU), a hard disk, a memory, a system bus, etc., as an example.
In some embodiments of the present application, the road green wave optimization system 100 may omit one or more elements, or may further include one or more other elements. As an example, the road green wave optimization system 100 may include a plurality of clients 130, such as a plurality of intelligent vehicles, and the like. For another example, the road green wave optimization system 100 can include one or more control terminals 120. As another example, the road green wave optimization system 100 may include a plurality of servers 140, or the like. In some embodiments, the road green wave optimization system 100 may include, but is not limited to, a system based on urban intelligent traffic scene processing. The network 110 may be any type of communication network that may include a computer network (e.g., a local area network (LAN, local Area Network) or wide area network (WAN, wide Area Network)), the internet, and/or a telephone network, among others, or a combination of several. In some embodiments, network 110 may be other types of wireless communication networks. The wireless communication may include microwave communication and/or satellite communication, etc. The wireless communication may include cellular communication, such as global system for mobile communications (GSM, global System for Mobile Communications), code division multiple access (CDMA, code Division Multiple Access), third generation mobile communications (3G,The 3rd Generation Telecommunication), fourth generation mobile communications (4G), fifth generation mobile communications (5G), sixth generation mobile communications (6G), long term evolution technology (LTE, long Term Evolution), long term evolution technology upgrades (LTE-a, LTE-Advanced), wideband code division multiple access (WCDMA, wideband Code Division Multiple Access), universal mobile telecommunications system (UMTS, universal Mobile Telecommunications System), wireless broadband (WiBro, wireless Broadband), and the like, or a combination of several. In some embodiments, the user terminal 130 may be other devices and/or electronic devices with equivalent functional modules, which may include one or a combination of several of intelligent internet connected vehicles (Intelligent Connected Vehicle, ICV), virtual reality devices (VR), renderers, personal computers (PCs, such as tablet computers, desktop computers, notebooks, netbooks, palmtop PDAs), smartphones, mobile phones, electronic book readers, portable Multimedia Players (PMPs), audio/video players (MP 3/MP 4), cameras, wearable devices, and the like.
In some embodiments, the WIFI may be other types of wireless communication technologies. According to some embodiments of the present application, the wireless communication may include wireless local area network (WiFi, wireless Fidelity), bluetooth low energy (BLE, bluetooth Low Energy), zigBee, near field communication (NFC, near Field Communication), magnetic security transmission, radio frequency and body area network (BAN, body Area Network), etc., or a combination of several. According to some embodiments of the present application, the wired communication may include a global navigation satellite system (Glonass/GNSS, global Navigation Satellite System), a global positioning system (GPS, global Position System), a beidou navigation satellite system or galileo (european global satellite navigation system), or the like. The wired communication may include universal serial bus (USB, universal Serial Bus), high-definition multimedia interface (HDMI, high-Definition Multimedia Interface), recommended standard 232 (RS-232,Recommend Standard 232), plain old telephone service (POTS, plain Old Telephone Service), etc., or a combination of several.
It should be noted that the description of the road green wave optimization system 100 is merely for convenience of description, and is not intended to limit the application to the scope of the illustrated embodiments. It will be understood by those skilled in the art that various changes in form and details may be made to the application areas of implementing the above-described methods and systems based on the principles of the present system without departing from such principles, and any combination of individual elements or connection of constituent subsystems with other elements may be possible. For example, the server 140 and/or the control terminal 120 may acquire map data, road class data, etc. through a roadside device, etc. Such variations are within the scope of the present application.
Fig. 2 is an exemplary flow chart of a road green wave optimization method provided in accordance with some embodiments of the present application. As depicted in fig. 2, the process 200 may be implemented by the road green wave optimization system 100. In some embodiments, the road green wave optimization method 200 may be initiated automatically or by instruction. The instructions may include system instructions, device instructions, user instructions, action instructions, etc., or a combination of the several.
At 201, a green wave scene is determined, and a green wave road optimization control strategy table is obtained. Operation 201 may be implemented by the control end 120 of the road green wave optimization system 100. In some embodiments, the control end 120 may determine a green wave scene and obtain a green wave road optimization control policy table. In some embodiments, the control end 120 and/or the server 140 may determine green wave scenes, etc. according to a green wave road optimization control strategy table.
As an example, the determining a green wave scene, and obtaining a green wave road optimization control policy table specifically includes obtaining a green wave road list to be optimized, including green wave road optimization priority and green wave road key intersections; acquiring green wave road parameter data to be optimized, wherein the parameter data comprise associated intersections, intersection sequences, intersection intervals and intersections; obtaining at least two green wave road groups, wherein each green wave road group comprises green wave roads with the same intersection, and then optimizing the green wave roads of each green wave road group respectively.
At 202, green wave time periods are divided, including obtaining a date type of the calculation date. Operation 202 may be implemented by the control end 120, the server 140 of the road green wave optimization system 100. In some embodiments, the control terminal 120 and/or the server 140 may divide the green wave period, including obtaining a date type of the calculation date.
As an example, the dividing the green wave period specifically includes:
s301 obtaining a date type of a calculated date, wherein the date type is the previous day when calculating the previous day;
s302, acquiring all key intersections in each green wave road group;
s303. obtaining the lane reference flow of each lane of all the key intersections of the date type in s302 every 5 minutes, and calculating the sum of the reference flows of each lane of the date type in 24 hours as follows:
s304. decimate data F i＝1....288 Generating an initial remainder set ass305. find maximum data F i And its sequence number i;
s306. set the data comparison threshold αF of the present group i Generating a first set of dataThe corresponding remainder set is
s307. F i The data is compared from the beginning to the two sides, namely the data F is in the sequence number i bit i Respectively with forward sequence number i-1 data F i-1 And backward sequence number i+1 bit data F i+1 Comparing to determine deviation beta;
s308. determining beta and threshold value alpha F i A relationship;
s309. if β is less than or equal to αF i Sequence number i-1 bit data F i-1 And sequence number i+1 bit data F i+1 And sequence number i bit data F i Belongs to a group, updates the data set of the group intoThe corresponding remainder set is +.>
s310. continue to compare bit data F of sequence number i-2 i-2 And sequence number i+2 bit data F i+2 And sequence number i bit data F i The deviation beta of (2);
s311. If beta is not more than alpha F i Updating the set of data sets toThe corresponding remainder set is
s312. continue to compare the sequence number i-m bit data F i-m And sequence number i+u bit data F i+u And sequence number i bit data F i The deviation beta of (2);
s313. if beta is not more than alpha F i Updating the set of data sets toThe corresponding remainder set is +.>Wherein, i-m and i+u in the remainder set represent the data set to be put into after being sequentially and circularly compared;
s314. if beta>αF i Sequence number i-m bit data F i-m And sequence number i+u bit data F i+u And sequence number i bit data F i Not belonging to one group, i.e. the first set of data sets has the result shown in s311, the first set of data sets has a maximum value of F i ；
s315. in remainder setContinuing to select the maximum value, i.e. serial number z-bit data F z Generate a second set of data->The corresponding remainder set is +.>Wherein z is used to represent the data location of the maximum in the dataset;
s316. data F in serial number z z For starting point to compare data to two sides, i.e. with serial number z bit data F z Respectively with the forward sequence number z-1 bit data F z-1 And backward sequence number z+1 bit data F z+1 Comparing to determine deviation beta;
s317. judge the comparison sequence number z-1 bit data F before and after the sequence number z z-1 And sequence number z+1 bit data F z+1 Whether or not in remainder set D R In the remainder set D R In the corresponding direction search is continued, if not in the remainder set D R The corresponding direction search is ended;
s318. repeating s309-s317, determining the second set of data sets asThe maximum value of the second group of data sets is F z The corresponding remainder set is +.>The i-m and i+u in the remainder set are used for indicating whether the data set is needed to be put into after the sequential cyclic comparison;
s319. repeating s309-s318 until remainder set D R No residual data in the data D, x groups of data D are generated according to the original data sequence number 1 ，D 2 ..D x Reordering, namely:
comparing the data number of each group of data sets, when a certain group of data sets D x When the number of data in the data set D is less than gamma x Merging into D x At D 1、2...x A previous or subsequent set of data sets in the data set ordering;
s320. and->Representing the data sets of the previous group and the next group, respectively, judging +.> Is of a size of (2); when->Will D x Data sets are combined to->A data set; when (when)Will D x Data sets are combined to->A data set; when->Comparison and judgment->And D x Sum of absolute difference values of all data of data set and MAXD x And->The sum of absolute difference values of all data of the data set is D x Merging into a dataset with a smaller sum of absolute differences;
s321. from the repartitioned dataset:
performing data set analysis;
s322. outputting a 24-hour period division result in the date type:
(0、g*15/60)、(g*15/60、d*15/60)、(d*15/60、z*15/60、)......((j+1)*15/60、24:00)。
at 203, an operating scheme is obtained, and a scheme corresponding to the minimum saturation is determined to be a coordinated time period scheme. Operation 203 may be implemented by the control end 120 of the road green wave optimization system 100, the server 140. In some embodiments, the control end 120 and/or the server 140 may acquire an operation scheme, and determine the scheme corresponding to the minimum saturation as the coordination period scheme.
As an example, the dividing the green wave period specifically includes:
s401, acquiring a configuration scheme of a green wave road in a present period, and performing period scheme matching on the green wave road divided by an update period;
s402. according to the time interval dividing result, respectively obtaining at least two schemes of each intersection in the time interval under the date type;
s403. obtaining 5 minutes reference flow and Σf of each lane of each intersection b-5 ；
s404. calculate the hourly traffic capacity C of each scenario obtained in s402 h ；
s405. calculate the saturation Σf for each scheme b-5 /C h ；
s406. determining at least two saturation Σf b-5 /C h The scheme corresponding to the minimum value in the system is an intersection coordination period scheme.
At 204, a coordination phase is generated, including obtaining phase parameters of the coordination period scheme. Operation 204 may be implemented by the server 140 and/or the control side 120 of the road green wave optimization system 100. In some embodiments, the server 140 and/or the control terminal 120 may generate a coordination phase including obtaining phase parameters of the coordination period scheme.
For example, the generating the coordination phase specifically includes:
s501. acquiring the coordination phase of the green wave road in the existing period, and performing coordination phase matching on the green wave road divided by the updated period based on the period scheme;
s502, acquiring the internal steering relation of all intersections of the green wave road, if the acquisition is successful, exiting the current green wave road optimization if the acquisition is unsuccessful;
s503, acquiring association relations between the upstream road section, the downstream road section and the intersection of the green wave road, if the acquisition succeeds, exiting the current green wave road optimization if the acquisition fails;
s504, respectively obtaining forward and reverse coordinated flow directions of each intersection of the green wave road according to the association relation between the upstream intersection and the downstream intersection of the green wave road;
s505. judging the direction of the road passing through the upstream road section, the connection road junction and the downstream road section to obtain the association relation between the two road sections and the connection road junction, judging the direction of the connection road junction of the starting road section and the ending road section, and judging the steering lane of the road junction from the steering starting direction of the road junction to the steering ending direction of the road junction;
S506, acquiring phase parameters according to the forward and reverse steering lanes of s505, and acquiring the phase of the current steering lane of the current period scheme at the intersection, and if at least two phases exist, arranging the at least two phases according to the phase sequence to serve as a coordination phase;
at 205, the intersection timing is calculated, and the configured scheduling plan and time period are obtained. Operation 205 may be implemented by the server 140 and/or the control end 120 of the road green wave optimization system 100. In some embodiments, the server 140 and/or the control terminal 120 may calculate intersection timing, obtain a configured scheduling plan and time period.
As an example, the calculating intersection timing, obtaining a configured scheduling plan and a time period specifically includes:
s601. acquiring a scheduling plan and a time period of a green wave road in a present time period, and acquiring initial timing parameters of each intersection;
s602, according to the dispatching plan and the time period, obtaining the sum Sigma f of the reference flow of each lane every 5 minutes in the time period of each intersection b-5 Performing timing optimization on the successfully acquired intersections, and configuring initial timing parameters for the unobtainable intersections;
s603. will Σf b-5 Converting the small flow rate to the intersectionT i The length of the hour period after the period division is the same;
s604, obtaining intersection lane canalization information, phase sequence of the time period scheme, lane traffic capacity and period duration T 0 ；
s605. calculating the flow ratio of each lane in the periodWherein f h C is the traffic lane hour flow x A configuration value for a lane hour saturation flow rate;
s606. determining the maximum flow ratio y of each phase of the current time period scheme i ＝max[y x ]Wherein i represents a phase number, and if the same lane exists in a plurality of phases, the same lane in different phases is assigned the same value;
s607. calculate the sum of the maximum flow ratios of each phase of the intersection Y = Σy i ；
s608. calculate the green light loss time l= Σ (L) of the time period scheme i +I i -A i ) Wherein the signal loss time of phase i is L i Green light interval time I i Yellow light time A i )
S609, judging Y value interval, if Y is less than 0.7, the period durationIf Y is more than or equal to 0.7 and less than 1, the period duration C 0 ＝1.23Le (2.46-0.02L)*Y The method comprises the steps of carrying out a first treatment on the surface of the If 1 is less than or equal to Y, exiting;
s610. judging the period duration;
s611. if C 0 ≤T 0 +30&C 0 < = 180, then C 0 ＝C 0 ；
s612. if C 0 ≤T 0 +30&C 0 > 180, then C 0 ＝180；
s613 if C 0 ＞T 0 +30&C 0 < = 180, then C 0 ＝T 0 +30；
s614 if C 0 ＞T 0 +30&C 0 > 180, then C 0 ＝180；
s615. calculating effective green light time length G of period e ＝C 0 -L；
s616. calculating the ratio of the sum of the flow ratios of the phase flow ratios
s617 calculating the effective green light time of each phase
s618. calculate green time Gl of each phase display i ＝Max(g ei 、g min )+L i -A i Wherein g min The minimum green light duration of all phases associated with the current period, max is the maximum value;
s619 calculating the optimization period C 0 ＝∑(GL i +I i )。
At 206, a green wave period is determined, and an optimization period with the smallest deviation from the common period is determined as a green wave coordination period. Operation 206 may be implemented by the server 140 and/or the control end 120 of the road green wave optimization system 100. In some embodiments, the server 140 and/or the control terminal 120 may determine a green wave period, and determine an optimization period with the smallest deviation from the common period as a green wave coordination period.
As an example, the determining the green wave period, determining the optimization period with the smallest deviation from the common period as the green wave coordination period specifically includes:
s701. obtain all key crossing optimization period C of green wave road group i ；
s702. determining the common period as MaxC i ；
s703. judging the optimization period of each intersectionMaxC i Difference of (2) to determine->MaxC i The green wave coordination period C of the crossing corresponding to the minimum difference value of the optimization period of the crossing co ；
s704. calculating green light time length of each phase of each crossing matching green wave coordination period
At 207, green band speed is determined and the tertile of each road segment data is calculated as a coordinated band speed value. Operation 207 may be implemented by the server 140 and/or the control terminal 120 of the road green wave optimization system 100. In some embodiments, the server 140 and/or the control terminal 120 may determine the green band speed and calculate the tertile of each road segment data as a coordinated band speed value.
As an example, the determining the green band speed, calculating the tertile of each road segment data as the coordination band speed value specifically includes:
s801. obtaining the velocity v of forward and reverse coordinated flow direction in N continuous same date type current calculation periods at each road opening along the green wave road i ；
s802. calculating the tertile of each road opening speed value;
s803. determine that each third quartile is the coordinated band speed value of the forward and reverse directions of the intersection. .
At 208, a green wave scheme is generated, and the phase difference is adjusted according to the green wave road original phase difference. Operation 208 may be implemented by the server 140 and/or the control end 120 of the road green wave optimization system 100. In some embodiments, the server 140 and/or the control terminal 120 may generate a green wave scheme to adjust the phase difference according to the green wave road original phase difference.
As an example, the green wave generation scheme adjusts the phase difference according to the original phase difference of the green wave road, and specifically includes:
s901. according to each green wave road group, calculating the original phase difference of each green wave road of each group;
s902. according to the optimized priority order of green wave road groups, adjusting the phase difference of the crossing;
s903 generating two arrays including a first array (1) of unadjusted phase difference green wave road arrays and a second array (2) of adjusted phase difference green wave road arrays;
C. Acquiring a green wave road with the minimum optimization priority order from a first array (1), finishing adjustment if no data exists, and continuing to circularly adjust if the data exists;
D. acquiring a green wave road with the highest optimization priority order in a second array (2), if no data exists, putting the green wave road acquired by the A into the second array (2), and deleting the green wave road in the first array (1), wherein the phase difference of each intersection of the green wave road is unchanged; if the data exists, judging whether the green wave road obtained in the step (2) and the green wave road obtained in the step (1) have associated intersections, if at least two intersections with higher road grades exist, determining the intersections with higher road grades as reference intersections, adjusting the phase differences of all intersections of the green wave road obtained in the step (1), and transferring the adjusted green wave road from the first array (1) to the second array (2); the adjusting the phase difference includes:
the phase difference of the intersection in the green wave road of the second array (2) is t 0 The phase difference in the green wave road acquired in the first array (1) is t 1 The phase difference deviation is t 0 -t 1 The phase difference after the adjustment of other intersections of the green wave road obtained in the first array (1) is [ t ] i -(t 1 -t 0 )]modC i ；
s904 repeating the above s903 until there is no data of green wave road in the first array (1).
According to some embodiments of the present application, the process 200 may further include calculating green wave road phase differences, and the like. As an example, the calculating green wave road phase difference specifically includes:
s1001. obtaining green wave road parameters including green wave road number, intersection number, and key intersections, wherein each green wave road is provided with at most one key intersection; width w of crossing i Forward distance l of crossing i→i+1 Reverse distance l of crossing i→i-1 Wherein i=1..n, n is the number of intersections;
s1002. obtain timing parameters of intersection i, and forward coordinate phase green light time t i|f Reverse coordination phase green light duration t i|r Forward and reverse coordination phase green light turn-on time difference delta t i|fr ；
s1003. obtain the forward direction coordination belt speed V of intersection i i→i+1 Reverse coordination belt speed V i→i-1 ；
s1004. obtain the forward coordinated phase difference O of intersection i i|f Reverse phase difference O i|r ＝O i|f +Δt i|fr ；
s1005. obtain period C of intersection i i ；
S1006, acquiring current coordination types, including bidirectional coordination, forward coordination and reverse coordination;
s1007. calculating the bidirectional coordination phase of intersection i and intersection i+1, and when the type is bidirectional coordination, entering s1007-s1011: J. forward coordinated phase difference O of initial fixed intersection i i|f =0, reverse phase difference O i|r ＝Δt i|fr The method comprises the steps of carrying out a first treatment on the surface of the K. Calculating the forward coordinated phase difference of intersection i+1Reverse coordinated phase difference O i+1|r ＝O i+1|f +Δt i+1|fr The method comprises the steps of carrying out a first treatment on the surface of the Wherein the phase difference of the intersection i+1 is respectively from 0 to C i+1 Performing cycle traversal;
l, judging whether the intersection i and the intersection i+1 form bidirectional green waves at the moment, if so, recording the forward bandwidth q i→i+1|f Reverse bandwidth q i+1→i|r The method comprises the steps of carrying out a first treatment on the surface of the Comprises the steps of D-G:
m, judging whether the forward direction forms a coordination phase at the moment:[MC i+1 +O i+1|f 、MC i+1 +O i+1|f +t i+1|f ]wherein M is an integer greater than or equal to 0; presence of M makes->[MC i+1 +O i+1|f 、MC i+1 +O i+1|f +t i+1|f ]The overlapping part exists, namely the forward coordinated phase difference of the intersection i+1 is O i+1|f ，
N, judging whether the reverse direction forms a coordination phase at the moment:[NC i +O i|r 、NC i +O i|r +t i|r ]wherein N is an integer greater than or equal to 0; the presence of N causes[NC i +O i|r 、NC i +O i|r +t i|r ]The coordinated phase difference of the reverse direction of the overlapped part, namely the intersection i+1 is O i+1|f ，/>Forward bandwidth at this time: wherein,
is a point that is in the overlap interval;
o, reverse bandwidth:
wherein,
is a point that is in the overlap interval;
p, when the road mouth i and the road mouth i+1 form a bidirectional green wave, namely D, E steps are simultaneously satisfied, calculating B=q i→i+1|r +q i+1→i|r Acquiring the forward coordinated phase difference of intersection i+1 corresponding to maxB as O i+1|f The phase difference is two-way coordination between the intersection i and the intersection i+1; if there are at least two values of maxB, the smaller value of forward and reverse bandwidth deviation is obtained, when
At this time there are still a plurality of valuesWhen the coordinated phase difference in the forward direction of the intersection i+1 is determined to be O i+1|f Is a smaller value of (2);
q, when the road mouth i and the road mouth i+1 cannot form bidirectional green waves, namely the bidirectional coordination condition is not satisfied, determining forward coordination, and calculating the coordination phase difference between the road mouth i and the road mouth i+1 as [0 ], ]；
R, recording whether intersection i and intersection i+1 form bidirectional coordination, if not, recording 0, if recording 1, and the phase difference of intersection i+1 relative to intersection i is O i+1|f ；
S1008, repeating the above steps, calculating the coordinated phase difference between the intersection i+1 and the intersection i+2 until the last intersection completes calculation, and generating a final result list [0, O ] 2|f 、O 3f 、...、O n|f ]；
s1009 calculating the phase difference of the intersection corrected relative to the first intersection as [0, O ] 2 、O 3 、...、O n ]，O 2 ＝O 2|f ，O 3 ＝(O 3|f +O 2|f )modC 3 ，O 4 ＝(O 4|f +O 3|f +O 2|f )modC 4 ，O n ＝(O n-1|f +...+O 3|f +O 2|f )modC n ；
S1010, obtaining whether key intersections exist, if not, the final coordination phase difference of all the intersections is s1008, and if so, modifying the final coordination phase difference, and if so, the final coordination phase difference Off of the key intersections k =0, the critical intersection phase difference correction amount is Δo=0-O k Calculating the final coordination phase difference of other intersections;
s1011 the final coordinated phase difference of all intersections is [0+ΔO, (O) 2 +ΔO)modC 2 、(O 3 +ΔO)modC 3 、...、(O n +ΔO)modC n ]；
When the bidirectional green wave coordination does not exist or the condition is met, calculating the coordination phase between the two intersections by using a forward coordination algorithm when the unidirectional coordination bandwidth is lower than a threshold value;
s1012. calculating the forward coordination phase of intersection i and intersection i+1, and entering s1012-s1015 when the type is forward coordination:
C. when the coordination is forward, the coordination phase difference between the intersection i and the intersection i+1 is calculated as [0 ], ]；
D. The steps are repeated to calculate the coordinated phase difference between the intersection i+1 and the intersection i+2 until the last intersection is calculated,
generating a final result list [0 ],...、/>]；
S1013 calculating phase difference of the intersection corrected relative to the first intersection as [0, O ] 2 、O 3 、...、O n ]，
s1014. acquiring whether there is a key intersection, if there is no key intersection, the final coordination phase difference of all intersections is s1013, if there is a key intersection to modify the final coordination phase difference, the final coordination phase difference of the key intersection is Off k =0, the critical intersection phase difference correction amount is Δo=0-O k Calculating the final coordination phase difference of other intersections;
s1015. final coordinated phase difference of all intersections is [0+Δ O, O ] 2 +ΔO、O 3 +ΔO、...、O n +ΔO]；
When the two-way green wave coordination does not exist or the condition is met, calculating the coordination phase between the two intersections by using a forward coordination algorithm when the one-way coordination bandwidth is lower than a threshold value;
s1016. calculating the reverse coordination phase of the intersection i and the intersection i+1, and entering s1016-s1020 when the type is reverse coordination, wherein the intersection sequence is calculated after reordering according to the reverse order:
s1017. calculate the reverse coordination phase of intersection i and intersection i-1, where i=n, n-1,..1;
C. when the coordination is reverse coordination, the coordination phase difference between the intersection i and the intersection i-1 is [0 ], ]；
D. Repeating the steps to calculate the coordinated phase difference between the intersection i-1 and the intersection i-2 until the last intersection is completed
Calculating, generating an initial reverse phase difference list of each intersection after the first circulation as [ O ] 1|r 、O 2|r 、...、O n|r ]；
s1018 calculating the corrected forward phase difference list of the intersection relative to the first intersection as [ O ] 1 、O 2 、O 3 、...、O n ]，
O 1 ＝0，
O 2 ＝(O 2|r -O 1|r -Δt 2|fr )modC 2 .......O n ＝[O n|r -(O n-1|r +...+O 3|r +O 2|r )-Δt n|fr ]modC n ；
s1019. acquiring whether there is a critical intersection, if there is no critical intersection, the final coordination phase difference of all intersections is s1017, if there is a critical intersection to modify the final coordination phase difference, the final coordination phase difference of the critical intersection is O k =0, the critical intersection phase difference correction amount is Δo=0-O k ；
s1020. calculating the final coordination phase difference of other intersections, wherein the final coordination phase difference of all intersections is [ 0+Delta O, O ] 2 +ΔO、O 3 +ΔO、...、O n +ΔO]In this case, the coordination phase is reversedA potential difference;
s1021. traffic signal phase difference of intersection n= (coordinated phase difference-length of coordinated phase from first phase start time) mod c n 。
According to some embodiments of the present application, the data information of the associated vehicle in the green wave scheme may be displayed in a User Interface (UI) of the user terminal 130, and the display scene of the data information may include, but is not limited to, any form or combination of forms of scene display through VR, AR, MR, XR. The data information may include, but is not limited to, one or a combination of several of speed information, lane information, etc.
It should be noted that the description of the process 200 above is for convenience of description only, and is not intended to limit the application to the scope of the illustrated embodiments. It will be understood by those skilled in the art that various modifications and changes in form and detail of the functions implementing the above-described processes and operations may be made based on the principles of the present system by any combination of the individual operations or by constituting sub-processes in combination with other operations without departing from such principles. For example, the process 200 may further include operations to calculate green wave road phase differences, and the like. Such variations are within the scope of the present application.
In summary, according to the road green wave optimization method and system of the embodiment of the application, the phase difference of a plurality of road sections in the intersection phase timing and the area is calculated according to the intersection traffic flow and the road section vehicle speed, so that the vehicle traffic capacity is improved, and the area traffic pressure is relieved.
It should be noted that the above-described embodiments are merely examples, and the present application is not limited to such examples, but various changes may be made.
It should be noted that in this specification the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
Finally, it is also to be noted that the above-described series of processes includes not only processes performed in time series in the order described herein, but also processes performed in parallel or separately, not in time series.
Those skilled in the art will appreciate that all or part of the processes in the methods of the embodiments described above may be implemented by hardware associated with computer program instructions, where the program may be stored on a computer readable storage medium, where the program, when executed, may include processes in embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), or the like.
The foregoing disclosure is only illustrative of some of the preferred embodiments of the present application and is not intended to limit the scope of the claims hereof, as persons of ordinary skill in the art will understand that all or part of the processes for accomplishing the foregoing embodiments may be practiced with equivalent changes which may be made by the claims herein and which fall within the scope of the invention.
Claims (2)
1. A method of road green wave optimization, the method comprising:
determining a green wave scene and acquiring a green wave road optimization control strategy table;
Dividing green wave time periods, including obtaining date types of calculation dates;
acquiring an operation scheme, and determining a scheme corresponding to the minimum saturation as a coordination period scheme;
generating a coordination phase, including obtaining phase parameters of the coordination period scheme;
calculating intersection timing, and acquiring a configured scheduling plan and a time period;
determining a green wave period, and determining an optimization period with the smallest deviation from the common period as a green wave coordination period;
determining the green wave band speed, and calculating the tertile of each road section data as a coordination band speed value;
generating a green wave scheme, and adjusting the phase difference according to the original phase difference of the green wave road;
the method for determining the green wave scene and obtaining the green wave road optimization control strategy table specifically comprises the following steps: acquiring a green wave road list to be optimized, wherein the green wave road list comprises green wave road optimization priorities and green wave road key intersections; acquiring green wave road parameter data to be optimized, wherein the parameter data comprises associated intersections, intersection sequences, intersection intervals and intersections; acquiring at least two green wave road groups, wherein each green wave road group comprises green wave roads with the same intersection, and optimizing the green wave roads of each green wave road group respectively;
Wherein, the dividing green wave period specifically includes:
s301 obtaining a date type of a calculated date, wherein the date type is the previous day when calculating the previous day;
s302, acquiring all key intersections in each green wave road group;
s303. obtaining the lane reference flow of each lane of all the key intersections of the date type in s302 every 5 minutes, and calculating the sum of the reference flows of each lane of the date type in 24 hours as follows:
s304. decimate data F i＝1....288 Generating an initial remainder set as
s305. find maximum data F i And its sequence number i;
s306. set the data comparison threshold αF of the present group i Generating a first set of dataCorresponding toThe remainder set is
s307. F i The data is compared from the beginning to the two sides, namely the data F is in the sequence number i bit i Respectively with forward sequence number i-1 data F i-1 And backward sequence number i+1 bit data F i+1 Comparing to determine deviation beta;
s308. determining beta and threshold value alpha F i A relationship;
s309. if β is less than or equal to αF i Sequence number i-1 bit data F i-1 And sequence number i+1 bit data F i+1 And sequence number i bit data F i Belongs to a group, updates the data set of the group intoThe corresponding remainder set is +.>
s310. continue to compare bit data F of sequence number i-2 i-2 And sequence number i+2 bit data F i+2 And sequence number i bit data F i The deviation beta of (2);
s311. If beta is not more than alpha F i Updating the set of data sets toThe corresponding remainder set is
s312. continue to compare the sequence number i-m bit data F i-m And sequence number i+u bit data F i+u And sequence number i bit data F i The deviation beta of (2);
s313. if beta is not more than alpha F i Updating the set of data sets toThe corresponding remainder set isWherein, i-m and i+u in the remainder set represent the data set to be put into after being sequentially and circularly compared;
s314. if beta>αF i Sequence number i-m bit data F i-m And sequence number i+u bit data F i+u And sequence number i bit data F i Not belonging to one group, i.e. the first set of data sets has the result shown in s311, the first set of data sets has a maximum value of F i ；
s315. in remainder setContinuing to select the maximum value, i.e. serial number z-bit data F z Generate a second set of data->The corresponding remainder set is +.>Wherein z is used to represent the data location of the maximum in the dataset;
s316. data F in serial number z z For starting point to compare data to two sides, i.e. with serial number z bit data F z Respectively with the forward sequence number z-1 bit data F z-1 And backward sequence number z+1 bit data F z+1 Comparing to determine deviation beta;
s317. judge the comparison sequence number z-1 bit data F before and after the sequence number z z-1 And sequence number z+1 bit data F z+1 Whether or not in remainder set D R In the remainder set D R In the corresponding direction search is continued, if not in the remainder set D R The corresponding direction search is ended;
s318. repeating s309-s317, determining the second set of data sets asThe maximum value of the second group of data sets is F z The corresponding remainder set is +.>The i-m and i+u in the remainder set are used for indicating whether the data set is needed to be put into after the sequential cyclic comparison;
s319. repeating s309-s318 until remainder set D R No residual data in the data D, x groups of data D are generated according to the original data sequence number 1 ，D 2 ..D x Reordering, namely:
comparing the data number of each group of data sets, when a certain group of data sets D x When the number of data in the data set D is less than gamma x Merging into D x At D 1、2...x A previous or subsequent set of data sets in the data set ordering;
s320. and->Representing the data sets of the previous group and the next group, respectively, judging +.> Is of a size of (2); when->Will D x Data sets are combined to->A data set; when (when)Will D x Data sets are combined to->A data set; when->Comparison and judgment->And D x Sum of absolute difference values of all data of data set and MAXD x And->The sum of absolute difference values of all data of the data set is D x Merging into a dataset with a smaller sum of absolute differences;
s321. from the repartitioned dataset:
performing data set analysis;
s322. outputting a 24-hour period division result in the date type:
(0、g*15/60)、(g*15/60、d*15/60)、(d*15/60、z*15/60、)......((j+1)*15/60、24:00)；
The method for obtaining the operation scheme includes the steps that a scheme corresponding to the minimum saturation is determined to be a coordination period scheme, and specifically includes:
s401, acquiring a configuration scheme of a green wave road in a present period, and performing period scheme matching on the green wave road divided by an update period;
s402. according to the time interval dividing result, respectively obtaining at least two schemes of each intersection in the time interval under the date type;
s403. obtaining 5 minutes reference flow and Σf of each lane of each intersection b-5 ；
s404. calculate the hourly traffic capacity C of each scenario obtained in s402 h ；
s405. calculate each scheme saturation Σf b-5 /C h ；
s406. determining at least two saturation Σf b-5 /C h The scheme corresponding to the minimum value in the system is an intersection coordination period scheme;
wherein, the generating a coordination phase specifically includes:
s501. acquiring the coordination phase of the green wave road in the existing period, and performing coordination phase matching on the green wave road divided by the updated period based on the coordination period scheme;
s502, acquiring the internal steering relation of all intersections of the green wave road, if the acquisition is successful, exiting the current green wave road optimization if the acquisition is unsuccessful;
s503, acquiring association relations between the upstream road section, the downstream road section and the intersection of the green wave road, if the acquisition succeeds, exiting the current green wave road optimization if the acquisition fails;
S504, respectively obtaining forward and reverse coordinated flow directions of each intersection of the green wave road according to the association relation between the upstream intersection and the downstream intersection of the green wave road;
s505. judging the direction of the road passing through the upstream road section, the connection road junction and the downstream road section to obtain the association relation between the two road sections and the connection road junction, judging the direction of the connection road junction of the starting road section and the ending road section, and judging the steering lane of the road junction from the steering starting direction of the road junction to the steering ending direction of the road junction;
s506, acquiring phase parameters according to the forward and reverse steering lanes of s505, and acquiring the phase of the current steering lane of the current coordination period scheme at the intersection, and if at least two phases exist, arranging the at least two phases according to the phase sequence to serve as coordination phases;
the method for calculating intersection timing comprises the steps of:
s601. acquiring a scheduling plan and a time period of a green wave road in a present time period, and acquiring initial timing parameters of each intersection;
s602, according to the dispatching plan and the time period, obtaining the sum Sigma f of the reference flow of each lane every 5 minutes in the time period of each intersection b-5 Performing timing optimization on the successfully acquired intersections, and configuring initial timing parameters for the unobtainable intersections;
s603. will Σf b-5 Converting the small flow rate to the intersectionT i The length of the hour period after the period division is the same;
s604. obtaining the traffic lane channelized information, the phase sequence of the coordination period scheme, the traffic capacity of the traffic lane and the period time T 0 ；
s605. calculating the flow ratio of each lane in the periodWherein f h C is the traffic lane hour flow x A configuration value for a lane hour saturation flow rate;
s606. determining the maximum flow ratio y of each phase of the current coordination period scheme i ＝max[y x ]Wherein i represents a phase number, and if the same lane exists in a plurality of phases, the same lane in different phases is assigned the same value;
s607. calculating the sum of the maximum flow ratios of each phase of the intersection y=Σy i ；
s608. calculate the green light loss time l=Σ (L) of the coordination period scheme i +I i -A i ) Wherein the signal loss time of phase i is L i Green light interval time I i Yellow light time A i ；
S609, judging Y value interval, if Y is less than 0.7, the period durationIf Y is more than or equal to 0.7 and less than 1, the period duration C 0 ＝1.23Le (2.46-0.02L)*Y The method comprises the steps of carrying out a first treatment on the surface of the If 1 is less than or equal to Y, exiting;
s610. judging the period duration;
s611. if C 0 ≤T 0 +30&C 0 < = 180, then C 0 ＝C 0 ；
s612. if C 0 ≤T 0 +30&C 0 > 180, then C 0 ＝180；
s613 if C 0 ＞T 0 +30&C 0 < = 180, then C 0 ＝T 0 +30；
s614 if C 0 ＞T 0 +30&C 0 > 180, then C 0 ＝180；
s615. calculating effective green light time length G of period e ＝C 0 -L；
s616. calculating the ratio of the sum of the flow ratios of the phase flow ratios
s617 calculating the effective green light time of each phase
s618. calculate green time Gl of each phase display i ＝Max(g ei 、g min )+L i -A i Wherein g min The minimum green light duration of all phases associated with the current period, max is the maximum value;
s619 calculating the optimization period C 0 ＝Σ(GL i +I i )；
The determining the green wave period, determining the optimization period with the smallest deviation from the common period as the green wave coordination period, specifically includes:
s701. obtain all key crossing optimization period C of green wave road group i ；
s702. determining the common period as MaxC i ；
s703. judging the optimization period of each intersectionMaxC i Difference of (2) to determine->MaxC i The green wave coordination period C of the crossing corresponding to the minimum difference value of the optimization period of the crossing co ；
s704. calculating green light time length of each phase of each crossing matching green wave coordination period
The method for determining the green wave band speed comprises the steps of calculating the tertile of each road section data as a coordination band speed value, and specifically comprises the following steps:
s801. obtaining the velocity v of forward and reverse coordinated flow direction in N continuous same date type current calculation periods at each road opening along the green wave road i ；
s802. calculating the tertile of each road opening speed value;
s803. determining that each third quartile is a coordinated belt speed value of the forward and reverse directions of the intersection;
the green wave generation scheme adjusts the phase difference according to the original phase difference of the green wave road, and specifically comprises the following steps:
s901. according to each green wave road group, calculating the original phase difference of each green wave road of each group;
s902. according to the optimized priority order of green wave road groups, adjusting the phase difference of the crossing;
s903 generating two arrays including a first array (1) of unadjusted phase difference green wave road arrays and a second array (2) of adjusted phase difference green wave road arrays;
A. acquiring a green wave road with the minimum optimization priority order from a first array (1), finishing adjustment if no data exists, and continuing to circularly adjust if the data exists;
B. acquiring a green wave road with the highest optimization priority order in a second array (2), if no data exists, putting the green wave road acquired by the A into the second array (2), and deleting the green wave road in the first array (1), wherein the phase difference of each intersection of the green wave road is unchanged; if the data exists, judging whether the green wave road obtained in the step (2) and the green wave road obtained in the step (1) have associated intersections, if at least two intersections with higher road grades exist, determining the intersections with higher road grades as reference intersections, adjusting the phase differences of all intersections of the green wave road obtained in the step (1), and transferring the adjusted green wave road from the first array (1) to the second array (2); the adjusting the phase difference includes:
the phase difference of the intersection in the green wave road of the second array (2) is t 0 The phase difference in the green wave road acquired in the first array (1) is t 1 The phase difference deviation is t 0 -t 1 The phase difference after the adjustment of other intersections of the green wave road obtained in the first array (1) is [ t ] i -(t 1 -t 0 )]mod C i ；
s904 repeating the above s903 until there is no green wave road data in the first array (1);
the green wave road phase difference calculation method specifically comprises the following steps:
s1001. obtaining green wave road parameters including green wave road numbers, intersection numbers and key intersections, wherein each green wave road is provided with at most one key intersection; width w of crossing i Forward distance l of crossing i→i+1 Reverse distance l of crossing i→i-1 Wherein i=1..n, n is the number of intersections;
s1002. obtain timing parameters of intersection i, and forward coordinate phase green light time t i|f Reverse coordination phase green light duration t i|r And forward and reverse coordination phase green light on time difference delta t i|fr ；
s1003. obtain the forward direction coordination belt speed V of intersection i i→i+1 And reverse coordination of belt speed V i→i-1 ；
s1004. obtain the forward coordinated phase difference O of intersection i i|f And a reversed coordinated phase difference O i|r ＝O i|f +Δt i|fr ；
s1005. obtain period C of intersection i i ；
S1006, acquiring current coordination types, including bidirectional coordination, forward coordination and reverse coordination;
s1007. calculating the bidirectional coordination phase of intersection i and intersection i+1, and when the type is bidirectional coordination, entering s1007-s1011:
A. Forward coordinated phase difference O of initial fixed intersection i i|f =0, reverse phase difference O i|r ＝Δt i|fr ；
B. Calculating the forward coordinated phase difference of intersection i+1Reverse coordinated phase difference O i+1|r ＝O i+1|f +Δt i+1|fr The method comprises the steps of carrying out a first treatment on the surface of the Wherein the phase difference of the intersection i+1 is respectively from 0 to C i+1 Performing cycle traversal;
C. judging whether the intersection i and the intersection i+1 form bidirectional green waves at the moment, if so, recording forward bandwidth q i→i+1|f ，
Reverse bandwidth q i+1→i|r The method comprises the steps of carrying out a first treatment on the surface of the Comprises the steps of D-G:
D. judging whether the forward direction forms a coordination phase at the moment:
[MC i+1 +O i+1|f 、MC i+1 +O i+1|f +t i+1|f ]wherein M is an integer greater than or equal to 0; the presence of M causes[MC i+1 +O i+1|f 、MC i+1 +O i+1|f +t i+1|f ]The overlapping part exists, namely the forward coordinated phase difference of the intersection i+1 is O i+1|f ，/>
E. Judging whether the reverse direction forms a coordination phase at the moment[NC i +O i|r 、NC i +O i|r +t i|r ]Wherein N is an integer greater than or equal to 0; the presence of N causes[NC i +O i|r 、NC i +O i|r +t i|r ]The coordinated phase difference of the reverse direction of the overlapped part, namely the intersection i+1 is O i+1|f ，/>Forward bandwidth at this time:
wherein,
is a point that is in the overlap interval;
F. reverse bandwidth:
wherein,
is a point that is in the overlap interval;
G. when the intersection i and the intersection i+1 form a bidirectional green wave, namely D, E steps are satisfied simultaneously, calculating B=q i→i+1|r +q i+1→i|r Acquiring max B corresponding toThe forward coordinated phase difference of the intersection i+1 is O i+1|f The phase difference is two-way coordination between the intersection i and the intersection i+1; if there are at least two values of maxB, obtaining smaller values of forward and reverse bandwidth deviations, and if there are multiple values at this time, determining that the forward coordinated phase difference of intersection i+1 is O i+1|f Is a smaller value of (2);
H. when the intersection i and the intersection i+1 cannot form a bidirectional green wave, namely the bidirectional coordination condition is not satisfied, determining forward coordination, and calculating the coordination phase difference of the intersection i and the intersection i+1 as
I. Recording whether intersection i and intersection i+1 form bidirectional coordination or not, if not, recording 0, if so, recording 1, and the phase difference of intersection i+1 relative to intersection i is O i+1|f ；
s1008. calculating the coordinated phase difference between intersection i+1 and intersection i+2 until the last intersection completes calculation, and generating final result list [0, O 2 f 、O 3 f 、...、O n f ]；
s1009 calculating the phase difference of the intersection corrected relative to the first intersection as [0, O ] 2 、O 3 、...、O n ]，O 2 ＝O 2 f ，O 3 ＝(O 3|f +O 2|f )mod C 3 ，O 4 ＝(O 4|f +O 3|f +O 2|f )mod C 4 ，O n ＝(O n-1|f +...+O 3|f +O 2|f )mod C n ；
S1010, obtaining whether key intersections exist, if not, the final coordination phase difference of all the intersections is s1008, and if so, modifying the final coordination phase difference, and if so, the final coordination phase difference Off of the key intersections k =0, the critical intersection phase difference correction amount is Δo=0-O k Calculating the final coordination phase difference of other intersections;
s1011 the final coordinated phase difference of all intersections is [0+ΔO, (O) 2 +ΔO)mod C 2 、(O 3 +ΔO)mod C 3 、...、(O n +ΔO)mod C n ]；
When the bidirectional green wave coordination does not exist or the condition is met, calculating a coordination phase between two intersections by using a forward coordination algorithm when the unidirectional coordination bandwidth is lower than a threshold value;
s1012. calculating the forward coordination phase of intersection i and intersection i+1, and entering s1012-s1015 when the type is forward coordination:
A. when the coordination is forward, calculating the coordination phase difference between the intersection i and the intersection i+1 as follows
B. Calculating the coordinated phase difference between the intersection i+1 and the intersection i+2 until the last intersection completes calculation, and generating a final result list
S1013 calculating phase difference of the intersection corrected relative to the first intersection as [0, O ] 2 、O 3 、...、O n ]，
s1014. acquiring whether there is a key intersection, if there is no key intersection, the final coordination phase difference of all intersections is s1013, if there is a key intersection to modify the final coordination phase difference, the final coordination phase difference of the key intersection is Off k =0, the critical intersection phase difference correction amount is Δo=0-O k Calculating the final coordination phase difference of other intersections;
s1015. final coordinated phase difference of all intersections is [0+Δ O, O ] 2 +ΔO、O 3 +ΔO、...、O n +ΔO]；
When the two-way green wave coordination does not exist or the condition is met, calculating the coordination phase between the two intersections by using a forward coordination algorithm when the one-way coordination bandwidth is lower than a threshold value;
s1016. calculating the reverse coordination phase of the intersection i and the intersection i+1, and entering s1016-s1020 when the type is reverse coordination, wherein the intersection sequence is calculated after reordering according to the reverse order:
s1017. calculate the reverse coordination phase of intersection i and intersection i-1, where i=n, n-1,..1;
A. when the coordination is reverse coordination, the coordination phase difference between the intersection i and the intersection i-1 is that
B. Calculating the coordinated phase difference between the intersection i-1 and the intersection i-2 until the last intersection completes calculation, and generating an initial reverse phase difference list of each intersection after the first circulation as [ O ] 1|r 、O 2|r 、...、O n|r ]；
s1018 calculating the corrected forward phase difference list of the intersection relative to the first intersection as [ O ] 1 、O 2 、O 3 、...、O n ]，
O 1 ＝0；
O 2 ＝(O 2|r -O 1|r -Δt 2|fr )modC 2 .......O n ＝[O n|r -(O n-1|r +...+O 3|r +O 2|r )-Δt n|fr ]mod C n ；
s1019. acquiring whether there is a critical intersection, if there is no critical intersection, the final coordination phase difference of all intersections is s1017, if there is a critical intersection to modify the final coordination phase difference, the final coordination phase difference of the critical intersection is O k =0, the critical intersection phase difference correction amount is Δo=0-O k ；
s1020. calculating the final coordination phase difference of other intersections, wherein the final coordination phase difference of all intersections is [ 0+Delta O, O ] 2 +ΔO、O 3 +ΔO、...、O n +ΔO]At this time, the phase difference is reversely coordinated;
s1021. traffic signal phase difference of intersection n= (coordinated phase difference-length of coordinated phase from first phase start time) mod c n 。
2. A road green wave optimization system, comprising:
a memory configured to store data and instructions;
a processor in communication with the memory, wherein the processor, when executing instructions in the memory, is configured to perform the road green wave optimization method of claim 1.
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Citations (26)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101206801A (en) * | 2007-12-17 | 2008-06-25 | 青岛海信网络科技股份有限公司 | Self-adaption traffic control method |
| CN104183145A (en) * | 2014-09-10 | 2014-12-03 | 河南理工大学 | Method for two-way green wave coordination control over artery traffic three-intersection control sub-areas |
| CN104978863A (en) * | 2015-06-29 | 2015-10-14 | 宁波工程学院象山研究院 | Multidimensional synchronous optimized bidirectional green wave control method |
| CN105139668A (en) * | 2015-07-27 | 2015-12-09 | 东南大学 | Urban trunk road two-way green wave control optimization method based on road section speed interval |
| CN105185130A (en) * | 2015-09-30 | 2015-12-23 | 公安部交通管理科学研究所 | Varying-period signal coordinating and controlling method of road intersections |
| CN105788298A (en) * | 2014-12-26 | 2016-07-20 | 浙江大华技术股份有限公司 | Bidirectional green wave control method and bidirectional green wave control device |
| WO2017166474A1 (en) * | 2016-03-29 | 2017-10-05 | 中国科学院深圳先进技术研究院 | Method and system for intersection group-based traffic control |
| CN107591009A (en) * | 2017-09-20 | 2018-01-16 | 广东振业优控科技股份有限公司 | Based on the two-way green wave coordination control method for improving red light queue clearance constraints in MAXBAND models |
| CN107730922A (en) * | 2017-09-11 | 2018-02-23 | 北方工业大学 | Unidirectional trunk line green wave coordination control self-adaptive adjustment method |
| CN108346302A (en) * | 2018-03-20 | 2018-07-31 | 青岛海信网络科技股份有限公司 | A kind of two-way green wave coordination control method and device |
| WO2018149308A1 (en) * | 2017-02-15 | 2018-08-23 | 阿里巴巴集团控股有限公司 | Road traffic optimization method and device and electronic apparatus |
| CN108877246A (en) * | 2018-07-25 | 2018-11-23 | 公安部交通管理科学研究所 | A kind of Automatic computing system and its calculation method of main line two-way green wave coordination parameter |
| CN109410610A (en) * | 2018-10-10 | 2019-03-01 | 扬州市鑫通智能信息技术有限公司 | A kind of simple and practical two-way green wave timing algorithm |
| CN109903569A (en) * | 2017-12-11 | 2019-06-18 | 上海宝康电子控制工程有限公司 | The two-way green wave control method of general more bandwidth |
| CN111210621A (en) * | 2019-12-27 | 2020-05-29 | 银江股份有限公司 | Signal green wave coordination route optimization control method and system based on real-time road condition |
| CN111383470A (en) * | 2018-12-28 | 2020-07-07 | 上海宝康电子控制工程有限公司 | System and method for realizing intelligent dynamic green wave control based on traffic big data |
| CN111915885A (en) * | 2020-06-24 | 2020-11-10 | 广州运星科技有限公司 | Urban road traffic simulation experiment method and system |
| WO2020224444A1 (en) * | 2019-05-06 | 2020-11-12 | 阿里巴巴集团控股有限公司 | Data processing method and apparatus, device, and computer-readable storage medium |
| CN112598900A (en) * | 2020-12-07 | 2021-04-02 | 上海宝康电子控制工程有限公司 | Evaluation processing system, method, device, processor and storage medium for realizing urban trunk road traffic coordination optimization control |
| CN113034937A (en) * | 2021-03-02 | 2021-06-25 | 武汉理工大学 | Urban arterial road segmented green wave coordination control method, device and system |
| CN113345255A (en) * | 2021-08-04 | 2021-09-03 | 华砺智行(武汉)科技有限公司 | Main line green wave coordination signal control method and device, electronic equipment and storage medium |
| WO2021174374A1 (en) * | 2020-03-02 | 2021-09-10 | 孟卫平 | Traffic signal polarization green wave control method |
| CN113593258A (en) * | 2021-07-23 | 2021-11-02 | 广州市交通规划研究院 | Signal timing and vehicle speed dynamic coordination control optimization method based on vehicle-road cooperation |
| CN113643554A (en) * | 2021-08-17 | 2021-11-12 | 阿波罗智联(北京)科技有限公司 | Green wave coordination control method and device, electronic equipment and storage medium |
| WO2022077131A1 (en) * | 2020-10-12 | 2022-04-21 | 孟卫平 | Traffic signal stable guide control method |
| CN114863687A (en) * | 2022-07-06 | 2022-08-05 | 华录易云科技有限公司 | Road traffic intelligent optimization method based on main line green wave |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9076332B2 (en) * | 2006-10-19 | 2015-07-07 | Makor Issues And Rights Ltd. | Multi-objective optimization for real time traffic light control and navigation systems for urban saturated networks |
-
2022
- 2022-08-10 CN CN202210956019.8A patent/CN115424460B/en active Active
Patent Citations (26)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101206801A (en) * | 2007-12-17 | 2008-06-25 | 青岛海信网络科技股份有限公司 | Self-adaption traffic control method |
| CN104183145A (en) * | 2014-09-10 | 2014-12-03 | 河南理工大学 | Method for two-way green wave coordination control over artery traffic three-intersection control sub-areas |
| CN105788298A (en) * | 2014-12-26 | 2016-07-20 | 浙江大华技术股份有限公司 | Bidirectional green wave control method and bidirectional green wave control device |
| CN104978863A (en) * | 2015-06-29 | 2015-10-14 | 宁波工程学院象山研究院 | Multidimensional synchronous optimized bidirectional green wave control method |
| CN105139668A (en) * | 2015-07-27 | 2015-12-09 | 东南大学 | Urban trunk road two-way green wave control optimization method based on road section speed interval |
| CN105185130A (en) * | 2015-09-30 | 2015-12-23 | 公安部交通管理科学研究所 | Varying-period signal coordinating and controlling method of road intersections |
| WO2017166474A1 (en) * | 2016-03-29 | 2017-10-05 | 中国科学院深圳先进技术研究院 | Method and system for intersection group-based traffic control |
| WO2018149308A1 (en) * | 2017-02-15 | 2018-08-23 | 阿里巴巴集团控股有限公司 | Road traffic optimization method and device and electronic apparatus |
| CN107730922A (en) * | 2017-09-11 | 2018-02-23 | 北方工业大学 | Unidirectional trunk line green wave coordination control self-adaptive adjustment method |
| CN107591009A (en) * | 2017-09-20 | 2018-01-16 | 广东振业优控科技股份有限公司 | Based on the two-way green wave coordination control method for improving red light queue clearance constraints in MAXBAND models |
| CN109903569A (en) * | 2017-12-11 | 2019-06-18 | 上海宝康电子控制工程有限公司 | The two-way green wave control method of general more bandwidth |
| CN108346302A (en) * | 2018-03-20 | 2018-07-31 | 青岛海信网络科技股份有限公司 | A kind of two-way green wave coordination control method and device |
| CN108877246A (en) * | 2018-07-25 | 2018-11-23 | 公安部交通管理科学研究所 | A kind of Automatic computing system and its calculation method of main line two-way green wave coordination parameter |
| CN109410610A (en) * | 2018-10-10 | 2019-03-01 | 扬州市鑫通智能信息技术有限公司 | A kind of simple and practical two-way green wave timing algorithm |
| CN111383470A (en) * | 2018-12-28 | 2020-07-07 | 上海宝康电子控制工程有限公司 | System and method for realizing intelligent dynamic green wave control based on traffic big data |
| WO2020224444A1 (en) * | 2019-05-06 | 2020-11-12 | 阿里巴巴集团控股有限公司 | Data processing method and apparatus, device, and computer-readable storage medium |
| CN111210621A (en) * | 2019-12-27 | 2020-05-29 | 银江股份有限公司 | Signal green wave coordination route optimization control method and system based on real-time road condition |
| WO2021174374A1 (en) * | 2020-03-02 | 2021-09-10 | 孟卫平 | Traffic signal polarization green wave control method |
| CN111915885A (en) * | 2020-06-24 | 2020-11-10 | 广州运星科技有限公司 | Urban road traffic simulation experiment method and system |
| WO2022077131A1 (en) * | 2020-10-12 | 2022-04-21 | 孟卫平 | Traffic signal stable guide control method |
| CN112598900A (en) * | 2020-12-07 | 2021-04-02 | 上海宝康电子控制工程有限公司 | Evaluation processing system, method, device, processor and storage medium for realizing urban trunk road traffic coordination optimization control |
| CN113034937A (en) * | 2021-03-02 | 2021-06-25 | 武汉理工大学 | Urban arterial road segmented green wave coordination control method, device and system |
| CN113593258A (en) * | 2021-07-23 | 2021-11-02 | 广州市交通规划研究院 | Signal timing and vehicle speed dynamic coordination control optimization method based on vehicle-road cooperation |
| CN113345255A (en) * | 2021-08-04 | 2021-09-03 | 华砺智行(武汉)科技有限公司 | Main line green wave coordination signal control method and device, electronic equipment and storage medium |
| CN113643554A (en) * | 2021-08-17 | 2021-11-12 | 阿波罗智联(北京)科技有限公司 | Green wave coordination control method and device, electronic equipment and storage medium |
| CN114863687A (en) * | 2022-07-06 | 2022-08-05 | 华录易云科技有限公司 | Road traffic intelligent optimization method based on main line green wave |
Non-Patent Citations (6)
| Title |
|---|
| Optimization model for regional green wave coordinated control based on ring-and-barrier structure;Kai Lu , Xin Tian, Shuyan Jiang , Jianmin Xu, Yinhai Wang;Journal of Intelligent Transportation Systems;第26卷(第1期);全文 * |
| 乐山市绿心路信号线控方案优化设计;徐桃让,赵斌,蒋阳升;交通运输工程与信息学报;第18卷(第01期);全文 * |
| 交通信号协调控制基础理论与关键技术研究;卢凯;中国博士学位论文全文数据库 (工程科技Ⅱ辑);全文 * |
| 交通流诱导与控制协同的双目标优化模型及准最优求解算法;保丽霞,杨兆升,胡健萌;吉林大学学报（工学版）;第37卷(第2期);全文 * |
| 城市交通控制信号配时参数优化方法研究;栗红强;中国优秀博硕士学位论文全文数据库（博士）工程科技Ⅱ辑(第4期);全文 * |
| 有轨电车信号优先控制策略——以松江为例;张其强，钱晓予，孙蕾，周园园;交通与港航;第4卷(第01期);全文 * |
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