CN107705591A - A kind of tramcar and the cooperative control method of social wagon flow - Google Patents
A kind of tramcar and the cooperative control method of social wagon flow Download PDFInfo
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Abstract
The invention discloses a kind of tramcar and the cooperative control method of social wagon flow, comprise the following steps：(1) determination of road traffic basic data acquisition and signal common period, (2) setting and activation of detector, (3) after arrival detector detects tramcar, signal controlling machine generates tramcar priority pass application, signal time distributing conception adjustment is carried out according to tramcar and the cooperative control method of social wagon flow, (4) tramcar reaches the closing and unlatching of detector.The technical scheme integrates the technology of prediction, signal priority, coordination control, to ensure tramcar continuous priority pass between intersection, while make it that delay of the public vehicles in intersection is as small as possible.
Description
Technical Field
The invention belongs to the technical field of bus signal control, is used for a tramcar system, and relates to a cooperative control method of a tramcar and social traffic flow considering the stop time of a modern tramcar.
Background
Modern trams are increasingly popular as an efficient and clean way of public transportation since france in the 90 s of the last century, but they require sufficient space-time rights to ensure their efficiency and service level. In recent years, no matter in the research field or the patent application field, there are few methods related to tramcar signal priority, and few of the related method strategies mainly belong to active signal priority, the priority range given to tramcars is limited, and the phenomenon of negative influence on the passage of social vehicles due to lack of coordination with other traffic modes is more obvious when the saturation is higher. The present invention has been made in such a context.
Disclosure of Invention
The invention provides a tramcar and social traffic flow cooperative control method based on an electromagnetic wave superposition principle, aiming at solving the defect of large error in thickness measurement of an earth coupling antenna, and the scheme provides an important basis for highway nondestructive testing.
In order to achieve the purpose, the invention adopts the following technical scheme: a coordinated control method for a tramcar and social traffic flow is characterized by comprising the following steps:
(1) the acquisition of road traffic basic data and the determination of signal public period,
(2) the setting and activation of the detector(s) is,
(3) after the arrival detector detects the tramcar, the signal controller generates a tramcar priority passing application, adjusts a signal timing scheme according to a cooperative control method of the tramcar and the social traffic flow,
(4) closing and opening the tramcar arrival detector; and (3) closing the tramcar arrival detector temporarily after the optimized signal control scheme is implemented on the coordinated section, ending the signal priority cooperative control flow of the tramcar when the detector detects that the tramcar leaves the coordinated section, and recovering to the original control scheme, wherein the tramcar arrival detector is restarted to wait for the signal priority cooperative control of the next tramcar, and the step (3) is re-entered if the arrival of the tramcar is detected again.
As an improvement of the invention, the step (1) is specifically as follows, the signal period is calculated by adopting a Webster formula, and the maximum period in each intersection is taken as a common period for coordination control;
L＝∑I(l+I-A)；
the period duration(s) calculated by the C-Webster formula;
l-cycle loss time(s);
y-total flow ratio at the intersection;
a-yellow lamp time(s);
i-green interval time(s);
l-start loss time(s), and looking up a table;
yi＝maxj(qij/Sij) Flow ratio of the i-th phase;
qij-hour flow for ith phase jth lane;
Sij-the traffic capacity of the ith phase jth lane, derived from the basic traffic capacity;
through correlation analysis, the basic road traffic data required by the scheme comprises the following data: number of lanes N at each intersectionijAnd the specified lane direction includes straight running, left turning, right turning, straight left turning, straight right turning, left straight right turning and the distance l between adjacent intersectionsijEqual static data, flow direction data of intersection (saturation y of each inlet lane)i) Dynamic data such as the current situation of signal timing (yellow light time A, phase number I in one period, green light interval time I) and the like, a vehicle parking time sequence y, the actual arrival time x1 of the tramcar, the number x2 of the passengers getting on the tramcar, the number x3 of the passengers getting off the tramcar, the time interval x4 between the passengers and the previous passenger of the tramcar, and the length L of the tramcartrClear distance L at intersectiondAnd a tramcar speed Vtr.
As an improvement of the present invention, the setting and activation of the detector in the step (2) are specifically such that a tram arrival detector is arranged at an upstream entrance of the cooperative control section, a tram departure detector is arranged at a downstream exit of the cooperative control section, and when the first tram passes the departure detector, the tram arrival detector is activated, and is in a state capable of receiving a subsequent tram priority application.
As an improvement of the present invention, in the step (3), after the arrival detector detects the tramcar, the signal controller generates a tramcar priority passage application, performs signal timing scheme adjustment according to a coordinated control method of the tramcar and social traffic, and when the detector detects the tramcar, the signal controller generates a tramcar priority passage application, which is specifically as follows;
31) forecasting the stop time of the tramcar station: the 'station stop time of the tramcar in the invention' is predicted based on an SVM (support vector machine), and can be operated by software such as C + + and the like;
32) and (3) a signal coordination optimization scheme: through the prediction of the stop time of the tramcar station of 31), the time when the tramcar reaches the stop line of the intersection can be obtained on the basis, then the parameters of the intersection such as the green time, the phase difference and the like are obtained on the basis of a nesting algorithm by combining the arrival rate of the social vehicles, and a signal coordination optimization scheme is determined according to the index of the green time and the phase difference.
As an improvement of the invention, the prediction of the stop time of the tramcar station in the step (31) is specifically as follows, the prediction process of the time of the tramcar reaching the stop line is simplified, the stop time of the tramcar at the station is mainly predicted, namely the abnormal running duration time caused by the stop is mainly predicted, the stop time of the tramcar and the characteristics of a tramcar system and the interaction between the tramcar and passengers are considered to present a nonlinear relation, the nonlinear regression is carried out based on an SVM model design algorithm, the scheme adopts a polynomial kernel function algorithm, and the prediction of the stop time is realized based on the algorithm; and predicting the time of the tramcar reaching the intersection based on the time;
the algorithm is as follows:
wherein f (x) is a nonlinear regression function,andfor the Lagrangian undetermined coefficient, it can be found from equation (3), SVsRepresenting a set of support vector machines, and epsilon is an insensitive coefficient;
wherein y is a sample sequence, which is an original sequence of the collected vehicle parking time, l is the number of support vectors, and x is (x)1，x2，x3，x4) The attribute variables are closely related to the stop time of the tramcar, and are respectively the actual arrival time of the tramcar, the number of people getting on the tramcar, the number of people getting off the tramcar and the head time span of the previous tramcar entering the tramcar, and the actual arrival time, the number of people getting on the tramcar, the head time span and the head time span of the tramcar entering the tramcar can be obtained through the.
As an improvement of the invention, in the step (32), a nesting algorithm is adopted to determine the green light time length and the phase difference, the first module takes the minimum stopping of the tramcar in the coordination section as a target, and takes the target as a new constraint to be brought into the second module, namely, the minimum total delay of the control section is taken as an optimization target, so that the delay of the social vehicles at the intersection is minimized while the tramcar is ensured to continuously and preferentially pass between the intersections;
a first module: green wave passing of the tramcar;
the optimal state for realizing the coordinated control of the tramcar is that the tramcar can pass through the target section without stopping, so the first module applies for the accumulated stopping times S of the tramcar in the target section with priorityallThe minimum is an objective function, and the corresponding algorithm is as follows:
wherein,for the on-time of the tramcar passing phase green light at the jth intersection ojThe absolute phase difference of the jth intersection is shown, a is a positive integer, and C is the public cycle duration of the coordinated control;
the time when the tramcar reaches the jth intersection is taken as the time;
temp＝(Ltr+Ld)/vtrthe method comprises the following steps of (1) obtaining the emptying time of the tramcar crossing an intersection;for the green time of the ith phase at the jth intersection,the shortest green time, q, of the ith phase of the jth intersectionijFor the ith phase of the jth intersection, the flow of the single-cycle vehicle, SijA lane saturation flow rate for phase i at the jth intersection;
solving the formula (5) and the formula (6) through an integer space particle swarm algorithm, and taking the solved result as a new constraint condition to be brought into a module II;
and a second module: timing optimization based on expected delays;
the signal of the tramcar gives priority to the passing time of the vehicles occupying other phases of society, and in order to reduce the passing delay of the vehicles occupying other phases of society as much as possible during signal timing on the premise of ensuring the passing right of the tramcar, the algorithm is as follows:
wherein,the time when the vehicle at the jth phase of the ith intersection reaches the stop line is taken as the time; u. ofijConsidering the arrival rate of the j phase at the ith intersection after the influence of the upstream intersection is considered;
the signal phase timing and phase difference of each intersection meeting the objective function can be obtained by utilizing the particle swarm algorithm of the integer space.
Compared with the prior art, the invention has the beneficial effects that (1) the invention is a new attempt in the field of tramcar signal control, combines the technologies of prediction, signal priority and coordination control into a whole, ensures that the tramcar continuously and preferentially passes between crossings, simultaneously ensures that the delay of social vehicles at the crossings is as small as possible, gives consideration to benefits in various aspects and intends to ensure that the system obtains the optimal implementation effect; (2) the method of the invention does not need additional road modification and infrastructure investment, so the method has the advantages of low capital investment, low requirement on urban finance and very strong operability.
Drawings
FIG. 1 is a flow chart of the method of the present invention;
FIG. 2 is a graph of road information and dynamic data;
FIG. 3 is a schematic diagram of solving an objective.
Detailed Description
For the purposes of promoting an understanding and understanding of the invention, reference will now be made to the following descriptions taken in conjunction with the accompanying drawings and specific examples.
Referring to fig. 1 to fig. 3, fig. 1 is a flow chart of a method for cooperatively controlling a tramcar and a social traffic flow, which is further described with reference to an example.
(1) Acquiring basic data of road traffic and determining a signal common period;
the invention firstly adopts a Webster formula to calculate the signal period, and takes the maximum period in each intersection as the common period for coordination control.
Cycle duration(s) calculated by C-Webster equation
L-period loss time(s)
Total flow ratio at Y-intersection
A-yellow time(s)
I-Green light interval time(s)
l-Start loss time(s), from table lookup
yi＝maxj(qij/Sij) Flow ratio of i-th phase
qij-hourly flow rate of ith phase jth lane
Sij-the throughput of the ith phase jth lane is derived from the basic throughput.
Through correlation analysis, the basic road traffic data required by the method comprises the following steps: number of lanes N at each intersectionijAnd the specified lane direction (straight, left turn, right turn, straight left, straight right, straight left, right turn), and the distance l between adjacent intersectionsijEqual static data, flow direction data of intersection (saturation y of each inlet lane)i) Dynamic data such as the current situation of signal timing (yellow light time A, phase number I in one period, green light interval time I) and the like, a vehicle parking time sequence y, the actual arrival time x1 of the tramcar, the number x2 of the passengers getting on the tramcar, the number x3 of the passengers getting off the tramcar, the time interval x4 between the passengers and the previous passenger of the tramcar, and the length L of the tramcartrClear distance L at intersectiondAnd a tramcar speed Vtr.
In this example, the number of lanes N at each intersectionijAnd the specified lane direction (straight, left turn, right turn, straight left, straight right, straight left, right turn), and the distance l between adjacent intersectionsijFlow direction data of intersection (saturation y of each inlet lane)i) Current situation of signal timing (yellow light time A, phase number I in one period, green light interval time I), length L of tramcartrCan be obtained by field investigation; time of vehicle stopThe sequence y, the actual arrival time x1 of the tramcar, the number x2 of the passengers getting on the tramcar, the number x3 of the passengers getting off the tramcar, the time span x4 between the passengers and the previous arrival tramcar, the speed Vtr of the tramcar and the like can be collected by adopting a camera method, namely, relevant videos are collected by a camera, and the video information is processed by special video processing software (for example, PremierePro 2.0 of Adobe company) to obtain required data.
(2) Setting and activation of the detector:
the tramcar arrival detector is arranged at the upstream entrance of the coordinated control section, the tramcar departure detector is arranged at the downstream exit of the coordinated control section, when the first tramcar passes through the departure detector, the tramcar arrival detector is activated, and the tramcar arrival detector is in a state capable of receiving the priority application of the subsequent tramcar, and the position of the detector is shown in figure 2.
The arrangement of the tramcar arrival detector is kept at a certain distance from the stop station and the intersection, so that the influence of queue overflow of the tramcars is avoided.
(3) After the arrival detector detects the tramcar, the signal controller generates a tramcar priority passing application, adjusts a signal timing scheme according to a cooperative control method of the tramcar and the social traffic flow,
when the detector detects the tramcar, the signal controller generates a tramcar priority application, specifically as follows,
31) forecasting the stop time of the tramcar station: the 'station stop time of the tramcar in the invention' is predicted based on an SVM (support vector machine), and can be operated by software such as C + + and the like;
32) and (3) a signal coordination optimization scheme: by predicting the stop time of the tramcar station in the step 1), the time when the tramcar reaches the stop line of the intersection can be obtained on the basis, then parameters such as green time, phase difference and the like of the intersection are obtained on the basis of a nesting algorithm by combining the arrival rate of social vehicles, and a signal coordination optimization scheme is determined according to the index of the green time and the phase difference.
(4) Closing and opening the tramcar arrival detector;
and (3) executing the optimized signal control scheme on the coordinated section, temporarily closing the arrival detector of the tramcar, ending the signal priority cooperative control flow of the tramcar when the detector detects that the tramcar leaves the coordinated section, restarting the arrival detector of the tramcar, waiting for the signal priority cooperative control of the next tramcar, and re-entering the step (3) if the arrival of the tramcar is detected again.
By adjusting the signal timing of the intersection according to the method, a coordinated control method of the tramcar and the social traffic flow can be obtained, so that the tramcar can pass preferentially, and the delay of the social vehicle at the intersection is as small as possible.
Application example: in order to verify the effectiveness of the present invention, the present invention will be further described below with reference to actual survey data of a tram in a certain market and VISSIM.
And a certain trunk road is provided with 5 intersections which are numbered as 1, 2, 3, 4 and 5 in sequence. This area contains the signal priority coordination control intersection: the intersection (2) of the Tongjiang-Taihu lake road, the intersection (3) of the Tongjiang-Longjinlu road and the intersection (4) of the Tongjiang-Longcheng road, and the intersections (1) and (5) are used as transition intersections for coordinated control, and all indexes are not counted to offset the influence of an upstream intersection on the control effect. As shown in fig. 2:
(1) through the acquisition of basic data, the obtained results are as follows:
information such as signal periods, phase schemes, intersection canalization, intersection intervals, specific positions of bus stations, flow directions of all intersections and the like of main intersections in the cooperative priority control area are shown in the attached figure 2;
(2) analyzing the effect;
in order to verify the effect of the invention, a coordination control method under the prior condition of the tramcar is compared with an original signal timing control method and a static two-way green wave control method only considering social vehicles, namely, each signal timing method corresponds to a signal timing strategy in effect analysis, the actual signal timing control is respectively carried out, timing data is shown in an attached figure 2, the traditional static two-way green wave is that a public signal period is determined through a Webster formula, then green light time is distributed according to each phase flow ratio, and finally, a phase difference between intersections meeting the maximum green wave bandwidth of the social vehicles is solved by a numerical solution.
In actual engineering, traffic demand fluctuation is often encountered, so the method is not limited to optimizing traffic efficiency under the current traffic, and in order to further test the stability of the signal control effect of the method under different traffic volumes, 5 traffic levels are set under the three signal timing strategies, wherein the traffic levels are respectively 80%, 90%, 100%, 110% and 120% of the original traffic. That is, 3 signal control strategies are constructed in the effect analysis, each strategy tests 5 flow conditions, and the specific setting of the effect analysis is shown in table 1.
TABLE 1 Signal timing strategy design
The driving speed of the vehicle is an important parameter for predicting the time of the vehicle reaching a stop line so as to realize signal control through a nested algorithm, and the input of the vehicle speed in the VISSIM is defined in a form. In urban roads, due to the influence of signal control, the arrival rate of traffic flowing to downstream intersections is not uniform, so that transitional signal lamps are arranged at the upstream of a signal coordination section in effect analysis to ensure the occurrence of a fleet, so that the actual situation of traffic operation is more approached, and the intersections are not listed in final index statistics, such as intersections 1 and 5 in the attached figure 2.
The stop time of the tramcar at the platform has an important influence on the effect of signal priority. The effect analysis is to set different passenger arrival rates in different time intervals to ensure that the number of passengers carried by the tramcar is consistent with the observation data in the table 1, so that the stopping process of the tramcar at the platform is presumed. Another important factor that affects tram stopping time and arrival time at an intersection is the time at which the vehicle enters the signal coordination zone. The investigation is carried out by acquiring the time of the tramcar entering signal coordination section through video, and the time is recorded into an effect analysis system in a timetable mode, namely, each tramcar corresponds to one time of entering the effect analysis system.
The whole effect analysis time length is 3600s, and the corresponding actual time period is the late peak 17: 15-18: 15 of the research area. Each flow condition for each scenario in table 1 was subjected to 10 effect analyses, each effect analysis taking a different random seed.
(3) Effect analysis results;
(31) analyzing the prediction result of the station parking time of the tramcar;
the number of stations affecting the prediction of the arrival time of the tram at the stop line in the coordinated control section is 4, which is already indicated in fig. 2. Because the prediction of the stop time of the tramcar is related to the self characteristics, the invention utilizes the related data of the tramcar meta-communication station in the Hexi region of Nanjing to calibrate the penalty factor E, the insensitive coefficient epsilon and the kernel function parameter gamma based on the SVM model algorithm, and then brings the attribute vectors of 4 stations of the research section into the regression function, thereby predicting the stop time of the tramcar. The stopping time y and the related attribute vector x of the tramcar at the Yuantong station are (x)1,x2,x3,x4) The sample size was 115. Wherein x is1～x4Is an attribute variable closely related to the stop time of the tramcar, wherein the attribute variable is the actual arrival time of the tramcar, the number of passengers getting on the tramcar and the number of passengers getting off the tramcarCounting the time interval between the current time and the current time of the previous incoming electric car. The parameter calibration result is as follows: e-24.619, E-0.4972, and γ -0.9997. The two indexes of the average relative percentage error (MAPE) and the Mean Square Error (MSE) of the algorithm are respectively 8.12 percent and 37.58s2And the prediction effect based on the SVM model algorithm is more reliable, and a sufficient basis is provided for predicting the arrival time of the tramcar at the intersection and setting a signal priority coordination control scheme.
(32) The impact on trams;
reducing the unnecessary stay time and the parking times of the tramcar on the road section as much as possible is a main target for improving the running benefit of the tramcar, so that the delay and the parking rate are main evaluation indexes for the tramcar to coordinate the priority control of the signal, and are one of the most powerful and effective arguments of the tramcar signal priority control strategy. The flow sensitivity results of the three control strategies according to the evaluation index output by the VISSIM are shown in table 2.
In general, under the current flow condition, the static bidirectional green wave control does not take into account the difference of the running characteristics of the tramcar and the social vehicle, and causes larger travel delay of the tramcar in a research section, and the parking rate of the tramcar is slightly improved compared with the original condition. After the cooperative control method of the tramcar and the social traffic flow is implemented, the travel delay and the parking rate of the tramcar are greatly reduced by 76.46% and 95.05%.
More notably, it is easy to find through the flow sensitivity that, because the actual signal timing control and the traditional static bidirectional green wave belong to the static timing method, the running index of the tramcar is not changed due to the change of the road flow and is always at a lower level. The signal control strategy of the invention can obviously reduce the travel delay of the tramcar to more than 77% no matter under any saturation degree, and correspondingly, the parking rate is reduced by more than 90% compared with the current signal control scheme. The strict target of the module I is fully proved, namely the tramcar which is applied for priority passes through the target section as few as possible in a parking mode, the important significance of the method for improving the tramcar passing benefit is achieved, and the accuracy of the tramcar parking time prediction and the outstanding contribution to the control algorithm are indirectly verified.
TABLE 2 tramcar indexes under different signal control strategies
(33) Influence on social traffic
The original intention of giving priority to tram signals is not to sacrifice the right of way for social vehicles, so it is necessary to make statistics on the running indexes of social vehicles to evaluate the influence of the signal priority algorithm on social vehicles. The method is used for analyzing the average queuing length of each node while counting the delay of social vehicles and each node and considering the constraint of the geometric condition of the road at the intersection. The results are shown in Table 3.
TABLE 3 various indexes of social vehicles under different signal control strategies
Note: 1 represents the mean delay value generated when the vehicle travels from the intersection 2 to the intersection 4 in fig. 2, which is the target section of the cooperative control.
The index is reduced by more than 50% relative to the current situation, and the control method can remarkably improve the driving benefit of the vehicle.
The drop amplitude of the index relative to the current situation is 20% -50%, and the control method has a certain effect on improving the vehicle passing benefit.
From the indexes of delay and parking rate, under the current flow condition, the traditional static bidirectional green wave only reduces the vehicle delay and parking rate by about 20 percent, and the coordinated control method of the tramcar and the social traffic flow not only greatly reduces the delay of the tramcar in the north-south direction, but also greatly improves the running benefit of the social vehicle in the direction, and the delay and parking rate are further reduced by 74.49 percent and 73.06 percent compared with the static bidirectional green wave.
Under the current situation of traffic, the static bidirectional green wave strategy cannot obviously improve the traffic benefit of social vehicles, but increases the delay and the parking rate of the social vehicles at partial intersections. In contrast, although the cooperative control method of the tram and the social traffic flow cannot ensure that vehicles in all phases can efficiently run like vehicles passing in a green wave period, the delay and the average value of the stopping rate at each intersection can still be obviously reduced relative to the current situation.
The high-efficiency control of the traffic flow under different saturation degrees is the embodiment of the superiority and the robustness of a signal control algorithm. Compared with vehicle running indexes under different flow ratios, the method has the advantages that with the increase of the flow, delay reduction values obtained by vehicles passing in the north-south direction due to static bidirectional green waves show a gradually-descending trend, and delay and queue length of each intersection in a section are also influenced in a negative way. Although the rise of the flow rate also affects the delay reduction of vehicles in the north and south directions under the control of the cooperative control method of the tramcar and the social traffic flow, the cooperative control method of the tramcar and the social traffic flow can still provide much higher traffic efficiency than static bidirectional green waves under various saturation degrees.
The great advantages of the tramcar and social traffic flow cooperative control method in giving preference to the stretchy signal and reducing interference to other social vehicles are well proved by the large number of evaluation indexes, and the stability and the robustness of the method for different traffic flow saturations are also shown by a multi-flux sensitivity test.
The above description is only of the preferred embodiments of the present invention, and it should be noted that: it will be apparent to those skilled in the art that several contemplated modifications and adaptations can be made without departing from the principles of the invention and these are intended to be included within the scope of the invention.
Claims (6)
1. A coordinated control method for a tramcar and social traffic flow is characterized by comprising the following steps:
(1) the acquisition of road traffic basic data and the determination of signal public period,
(2) the setting and activation of the detector(s) is,
(3) after the arrival detector detects the tramcar, the signal controller generates a tramcar priority passing application, adjusts a signal timing scheme according to a cooperative control method of the tramcar and the social traffic flow,
(4) closing and opening the tramcar arrival detector; and (3) closing the tramcar arrival detector temporarily after the optimized signal control scheme is implemented on the coordinated section, ending the signal priority cooperative control flow of the tramcar when the detector detects that the tramcar leaves the coordinated section, and recovering to the original control scheme, wherein the tramcar arrival detector is restarted to wait for the signal priority cooperative control of the next tramcar, and the step (3) is re-entered if the arrival of the tramcar is detected again.
2. The cooperative control method of the tramcar and the social traffic flow as claimed in claim 1, wherein the step (1) is specifically that a Webster formula is adopted to calculate a signal period, and a maximum period in each intersection is taken as a common period for cooperative control;
<mrow> <mi>C</mi> <mo>=</mo> <mfrac> <mrow> <mn>1.5</mn> <mi>L</mi> <mo>+</mo> <mn>5</mn> </mrow> <mrow> <mn>1</mn> <mo>-</mo> <mi>Y</mi> </mrow> </mfrac> <mo>;</mo> </mrow>
L＝∑I(l+I-A)；
<mrow> <mi>Y</mi> <mo>=</mo> <msubsup> <mo>&Sigma;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </msubsup> <msub> <mi>y</mi> <mi>i</mi> </msub> <mo>;</mo> </mrow>
the period duration(s) calculated by the C-Webster formula;
l-cycle loss time(s);
y-total flow ratio at the intersection;
a-yellow lamp time(s);
i-green interval time(s);
l-start loss time(s), and looking up a table;
yi＝maxj(qij/Sij) Flow ratio of the i-th phase;
qij-hour flow for ith phase jth lane;
Sij-the traffic capacity of the ith phase jth lane, derived from the basic traffic capacity;
through correlation analysis, the basic road traffic data required by the scheme comprises the following data: number of lanes N at each intersectionijAnd the specified lane direction includes straight running, left turning, right turning, straight left turning, straight right turning, left straight right turning and the distance l between adjacent intersectionsijEqual static data, flow direction data of intersection (saturation y of each inlet lane)i) Dynamic data such as the current situation of signal timing (yellow light time A, phase number I in one period, green light interval time I) and the like, a vehicle parking time sequence y, the actual arrival time x1 of the tramcar, the number x2 of the passengers getting on the tramcar, the number x3 of the passengers getting off the tramcar, the time interval x4 between the passengers and the previous passenger of the tramcar, and the length L of the tramcartrClear distance L at intersectiondAnd a tramcar speed Vtr.
3. The method for cooperative control of trams and social traffic flow according to claim 2, wherein the setting and activation of the detector in step (2) are specifically such that a tram arrival detector is disposed at an upstream entrance of the cooperative control section, a tram departure detector is disposed at a downstream exit of the cooperative control section, and when the first tram passes the departure detector, the tram arrival detector is activated and is in a state capable of receiving a priority application of a subsequent tram.
4. The cooperative control method for a streetcar and a social traffic flow according to claim 2 or 3, wherein in the step (3), after the arrival detector detects the streetcar, the signal controller generates a streetcar priority passage application, adjusts the signal timing scheme according to the cooperative control method for the streetcar and the social traffic flow,
when the detector detects the tramcar, the signal controller generates a tramcar priority application, specifically as follows,
31) forecasting the stop time of the tramcar station:
32) and (3) a signal coordination optimization scheme: through the prediction of the stop time of the tramcar station of 31), the time when the tramcar reaches the stop line of the intersection can be obtained on the basis, then the parameters of the intersection such as the green time, the phase difference and the like are obtained on the basis of a nesting algorithm by combining the arrival rate of the social vehicles, and a signal coordination optimization scheme is determined according to the index of the green time and the phase difference.
5. The method for cooperatively controlling the tramcar and the social traffic flow according to claim 4, wherein the forecasting of the stop time of the tramcar in the step (31) is specifically as follows, the forecasting process of the time of the tramcar reaching the stop line is simplified, the stopping time of the tramcar at the station platform is mainly forecasted, namely the abnormal running duration time caused by stopping, a polynomial kernel function algorithm is adopted in the scheme, and the forecasting of the stop time is realized based on the algorithm; and predicting the time of the tramcar reaching the intersection based on the time;
the algorithm is as follows:
<mrow> <mi>f</mi> <mrow> <mo>(</mo> <mi>x</mi> <mo>)</mo> </mrow> <mo>=</mo> <munder> <mo>&Sigma;</mo> <mrow> <mi>S</mi> <mi>V</mi> <mi>s</mi> </mrow> </munder> <mrow> <mo>(</mo> <mover> <msub> <mi>&alpha;</mi> <mi>i</mi> </msub> <mo>-</mo> </mover> <mo>-</mo> <mover> <msubsup> <mi>&alpha;</mi> <mi>i</mi> <mo>*</mo> </msubsup> <mo>-</mo> </mover> <mo>)</mo> </mrow> <mi>K</mi> <mrow> <mo>(</mo> <msub> <mi>x</mi> <mi>i</mi> </msub> <mo>,</mo> <mi>x</mi> <mo>)</mo> </mrow> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>;</mo> </mrow>
<mrow> <msub> <mi>L</mi> <mi>&epsiv;</mi> </msub> <mrow> <mo>(</mo> <mi>N</mi> <mo>)</mo> </mrow> <mo>=</mo> <mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <mn>0</mn> </mtd> <mtd> <mrow> <mo>|</mo> <mi>f</mi> <mrow> <mo>(</mo> <msub> <mi>x</mi> <mi>i</mi> </msub> <mo>)</mo> </mrow> <mo>-</mo> <msub> <mi>N</mi> <mi>i</mi> </msub> <mo>|</mo> <mo>-</mo> <mi>&epsiv;</mi> <mo><</mo> <mn>0</mn> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <mo>|</mo> <mi>f</mi> <mrow> <mo>(</mo> <msub> <mi>x</mi> <mi>i</mi> </msub> <mo>)</mo> </mrow> <mo>-</mo> <msub> <mi>N</mi> <mi>i</mi> </msub> <mo>|</mo> <mo>-</mo> <mi>&epsiv;</mi> </mrow> </mtd> <mtd> <mrow> <mo>|</mo> <mi>f</mi> <mrow> <mo>(</mo> <msub> <mi>x</mi> <mi>i</mi> </msub> <mo>)</mo> </mrow> <mo>-</mo> <msub> <mi>N</mi> <mi>i</mi> </msub> <mo>|</mo> <mo>-</mo> <mi>&epsiv;</mi> <mo>></mo> <mo>=</mo> <mn>0</mn> </mrow> </mtd> </mtr> </mtable> </mfenced> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>2</mn> <mo>)</mo> </mrow> <mo>;</mo> </mrow>
wherein f (x) is a nonlinear regression function,andfor the Lagrangian undetermined coefficient, it can be found from equation (3), SVsRepresenting a set of support vector machines, and epsilon is an insensitive coefficient;
<mrow> <munder> <mi>max</mi> <mrow> <mi>&alpha;</mi> <mo>,</mo> <msup> <mi>&alpha;</mi> <mo>*</mo> </msup> </mrow> </munder> <mi>W</mi> <mrow> <mo>(</mo> <mi>&alpha;</mi> <mo>,</mo> <msup> <mi>&alpha;</mi> <mo>*</mo> </msup> <mo>)</mo> </mrow> <mo>=</mo> <munder> <mi>max</mi> <mrow> <mi>&alpha;</mi> <mo>,</mo> <msup> <mi>&alpha;</mi> <mo>*</mo> </msup> </mrow> </munder> <mo>{</mo> <mo>-</mo> <mfrac> <mn>1</mn> <mn>2</mn> </mfrac> <munderover> <mo>&Sigma;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>l</mi> </munderover> <munderover> <mo>&Sigma;</mo> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>l</mi> </munderover> <mrow> <mo>(</mo> <msubsup> <mi>&alpha;</mi> <mi>i</mi> <mo>*</mo> </msubsup> <mo>-</mo> <msub> <mi>&alpha;</mi> <mi>i</mi> </msub> <mo>)</mo> </mrow> <mrow> <mo>(</mo> <msubsup> <mi>&alpha;</mi> <mi>j</mi> <mo>*</mo> </msubsup> <mo>-</mo> <msub> <mi>&alpha;</mi> <mi>j</mi> </msub> <mo>)</mo> </mrow> <mi>K</mi> <mrow> <mo>(</mo> <msub> <mi>x</mi> <mi>i</mi> </msub> <mo>,</mo> <msub> <mi>x</mi> <mi>j</mi> </msub> <mo>)</mo> </mrow> <mo>+</mo> <munderover> <mo>&Sigma;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>l</mi> </munderover> <msubsup> <mi>&alpha;</mi> <mi>i</mi> <mo>*</mo> </msubsup> <mrow> <mo>(</mo> <msub> <mi>y</mi> <mi>i</mi> </msub> <mo>-</mo> <mi>&epsiv;</mi> <mo>)</mo> </mrow> <mo>-</mo> <msub> <mi>&alpha;</mi> <mi>i</mi> </msub> <mrow> <mo>(</mo> <msub> <mi>y</mi> <mi>i</mi> </msub> <mo>+</mo> <mi>&epsiv;</mi> <mo>)</mo> </mrow> <mo>}</mo> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>3</mn> <mo>)</mo> </mrow> <mo>;</mo> </mrow>
<mrow> <mi>s</mi> <mo>.</mo> <mi>t</mi> <mo>.</mo> <mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <mrow> <mn>0</mn> <mo>&le;</mo> <msub> <mi>&alpha;</mi> <mi>i</mi> </msub> <mo>&le;</mo> <mi>E</mi> <mo>,</mo> <mi>i</mi> <mo>=</mo> <mn>1</mn> <mo>,</mo> <mn>...</mn> <mo>,</mo> <mi>l</mi> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <mn>0</mn> <mo>&le;</mo> <msubsup> <mi>&alpha;</mi> <mi>i</mi> <mo>*</mo> </msubsup> <mo>&le;</mo> <mi>E</mi> <mo>,</mo> <mi>i</mi> <mo>=</mo> <mn>1</mn> <mo>,</mo> <mn>...</mn> <mo>,</mo> <mi>l</mi> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <munderover> <mo>&Sigma;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>l</mi> </munderover> <mrow> <mo>(</mo> <msubsup> <mi>&alpha;</mi> <mi>i</mi> <mo>*</mo> </msubsup> <mo>-</mo> <msub> <mi>&alpha;</mi> <mi>i</mi> </msub> <mo>)</mo> </mrow> <mo>=</mo> <mn>0</mn> </mrow> </mtd> </mtr> </mtable> </mfenced> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>4</mn> <mo>)</mo> </mrow> <mo>;</mo> </mrow>
wherein y is a sample sequence, which is an original sequence of the collected vehicle parking time, l is the number of support vectors, and x is (x)1，x2，x3，x4) Is composed ofThe attribute variables are closely related to the stop time of the tramcar, and are respectively the actual arrival time of the tramcar, the number of people getting on the tramcar, the number of people getting off the tramcar and the head time span of the tramcar getting on the tramcar, and the attribute variables can be obtained through the following survey.
6. The coordinated control method of the tramcar and the social traffic flow as claimed in claim 5, wherein in the step (32), a nesting algorithm is adopted to determine the green light time length and the phase difference, the first module takes the minimum stopping of the tramcar in the coordination section as a target, and takes the target as a new constraint to be brought into the second module, namely, the minimum total delay of the control section is an optimization target, so that the delay of the social vehicle at the intersection is minimized while the continuous preferential passing of the tramcar between the intersections is ensured;
a first module: green wave passing of the tramcar;
the first module applies for the accumulated parking times S of the prior tramcar in the target sectionallThe minimum is an objective function, and the corresponding algorithm is as follows:
<mrow> <mi>min</mi> <mi> </mi> <msub> <mi>S</mi> <mrow> <mi>a</mi> <mi>l</mi> <mi>l</mi> </mrow> </msub> <mo>=</mo> <mi>min</mi> <munderover> <mo>&Sigma;</mo> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <mi>S</mi> <mi> </mi> <mi>S</mi> <mo>=</mo> <mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <mn>0</mn> </mtd> <mtd> <mtable> <mtr> <mtd> <mrow> <msubsup> <mi>t</mi> <mi>s</mi> <mi>j</mi> </msubsup> <mo>&le;</mo> <msubsup> <mi>t</mi> <mrow> <mi>a</mi> <mi>r</mi> <mi>r</mi> </mrow> <mi>j</mi> </msubsup> </mrow> </mtd> <mtd> <mrow> <mi>a</mi> <mi>n</mi> <mi>d</mi> </mrow> </mtd> <mtd> <mrow> <msubsup> <mi>t</mi> <mrow> <mi>a</mi> <mi>r</mi> <mi>r</mi> </mrow> <mi>j</mi> </msubsup> <mo>+</mo> <msub> <mi>t</mi> <mrow> <mi>e</mi> <mi>m</mi> <mi>p</mi> </mrow> </msub> <mo>&le;</mo> <msubsup> <mi>t</mi> <mi>s</mi> <mi>j</mi> </msubsup> <mo>+</mo> <msubsup> <mi>t</mi> <mi>g</mi> <mrow> <mn>1</mn> <mi>j</mi> </mrow> </msubsup> </mrow> </mtd> </mtr> </mtable> </mtd> </mtr> <mtr> <mtd> <mn>1</mn> </mtd> <mtd> <mrow> <mi>e</mi> <mi>l</mi> <mi>s</mi> <mi>e</mi> </mrow> </mtd> </mtr> </mtable> </mfenced> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>5</mn> <mo>)</mo> </mrow> <mo>;</mo> </mrow>
<mrow> <mi>s</mi> <mo>.</mo> <mi>t</mi> <mo>.</mo> <mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <mrow> <msubsup> <mi>t</mi> <mi>g</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msubsup> <mo>&GreaterEqual;</mo> <msubsup> <mi>t</mi> <mrow> <mi>g</mi> <mi>min</mi> </mrow> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msubsup> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <munderover> <mo>&Sigma;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>m</mi> </munderover> <msubsup> <mi>t</mi> <mi>g</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msubsup> <mo>=</mo> <mi>C</mi> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <mn>0</mn> <mo>&le;</mo> <msub> <mi>o</mi> <mi>j</mi> </msub> <mo>&le;</mo> <mi>C</mi> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <msubsup> <mi>t</mi> <mi>g</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msubsup> <mo>,</mo> <msubsup> <mi>t</mi> <mrow> <mi>g</mi> <mi>min</mi> </mrow> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msubsup> <mo>,</mo> <msub> <mi>o</mi> <mi>j</mi> </msub> <mo>&GreaterEqual;</mo> <mn>0</mn> <mo>&Element;</mo> <mi>int</mi> <mi>e</mi> <mi>g</mi> <mi>e</mi> <mi>r</mi> </mrow> </mtd> </mtr> </mtable> </mfenced> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>6</mn> <mo>)</mo> </mrow> <mo>;</mo> </mrow>
wherein,for the on-time of the tramcar passing phase green light at the jth intersection ojThe absolute phase difference of the jth intersection is shown, a is a positive integer, and C is the public cycle duration of the coordinated control;
the time when the tramcar reaches the jth intersection is taken as the time;
temp＝(Ltr+Ld)/vtrthe method comprises the following steps of (1) obtaining the emptying time of the tramcar crossing an intersection;for the green time of the ith phase at the jth intersection,the shortest green time, q, of the ith phase of the jth intersectionijFor the ith phase of the jth intersection, the flow of the single-cycle vehicle, SijIs the jth intersectionLane saturation flow rate for the ith phase of the fork;
solving the formula (5) and the formula (6) through an integer space particle swarm algorithm, and taking the solved result as a new constraint condition to be brought into a module II;
and a second module: timing optimization based on expected delays;
the signal of the tramcar gives priority to the passing time of the vehicles occupying other phases of society, and in order to reduce the passing delay of the vehicles occupying other phases of society as much as possible during signal timing on the premise of ensuring the passing right of the tramcar, the algorithm is as follows:
<mrow> <mi>min</mi> <mi> </mi> <msub> <mi>D</mi> <mrow> <mi>a</mi> <mi>l</mi> <mi>l</mi> </mrow> </msub> <mo>=</mo> <mi>m</mi> <mi>i</mi> <mi>n</mi> <munderover> <mo>&Sigma;</mo> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <munderover> <mo>&Sigma;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>2</mn> </mrow> <mi>m</mi> </munderover> <msub> <mi>D</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msub> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>7</mn> <mo>)</mo> </mrow> <mo>;</mo> </mrow>
<mrow> <msub> <mi>D</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msub> <mo>=</mo> <mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <mfrac> <mrow> <msup> <mrow> <mo>(</mo> <msubsup> <mi>t</mi> <mi>s</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msubsup> <mo>-</mo> <msubsup> <mi>t</mi> <mrow> <mi>a</mi> <mi>a</mi> </mrow> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msubsup> <mo>)</mo> </mrow> <mn>2</mn> </msup> <mo>&times;</mo> <msub> <mi>u</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msub> <mo>&times;</mo> <msub> <mi>S</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msub> </mrow> <mrow> <mn>2</mn> <mo>&times;</mo> <mrow> <mo>(</mo> <msub> <mi>S</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msub> <mo>-</mo> <msub> <mi>u</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msub> <mo>)</mo> </mrow> </mrow> </mfrac> </mtd> <mtd> <mrow> <msubsup> <mi>t</mi> <mi>s</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msubsup> <mo>&GreaterEqual;</mo> <msubsup> <mi>t</mi> <mrow> <mi>a</mi> <mi>a</mi> </mrow> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msubsup> </mrow> </mtd> </mtr> <mtr> <mtd> <mn>0</mn> </mtd> <mtd> <mtable> <mtr> <mtd> <mrow> <msubsup> <mi>t</mi> <mi>s</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msubsup> <mo>&le;</mo> <msubsup> <mi>t</mi> <mrow> <mi>a</mi> <mi>a</mi> </mrow> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msubsup> </mrow> </mtd> <mtd> <mrow> <mi>a</mi> <mi>n</mi> <mi>d</mi> </mrow> </mtd> <mtd> <mrow> <msub> <mi>q</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msub> <mo>-</mo> <msub> <mi>u</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msub> <mo>&times;</mo> <mrow> <mo>(</mo> <msubsup> <mi>t</mi> <mi>g</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msubsup> <mo>-</mo> <msubsup> <mi>t</mi> <mrow> <mi>a</mi> <mi>a</mi> </mrow> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msubsup> <mo>+</mo> <msubsup> <mi>t</mi> <mi>s</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msubsup> <mo>)</mo> </mrow> <mo>&GreaterEqual;</mo> <mn>0</mn> </mrow> </mtd> </mtr> </mtable> </mtd> </mtr> <mtr> <mtd> <mrow> <mfrac> <mn>1</mn> <mn>2</mn> </mfrac> <mrow> <mo>(</mo> <mn>2</mn> <mi>C</mi> <mo>-</mo> <mn>3</mn> <msubsup> <mi>t</mi> <mi>s</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msubsup> <mi>mod</mi> <mi> </mi> <mi>C</mi> <mo>-</mo> <msubsup> <mi>t</mi> <mi>g</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msubsup> <mo>+</mo> <msubsup> <mi>t</mi> <mrow> <mi>a</mi> <mi>a</mi> </mrow> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msubsup> <mi>mod</mi> <mi> </mi> <mi>C</mi> <mo>-</mo> <msub> <mi>q</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msub> <mo>/</mo> <msub> <mi>u</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msub> <mo>)</mo> </mrow> <mo>&times;</mo> <mrow> <mo>(</mo> <msub> <mi>q</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msub> <mo>-</mo> <msub> <mi>u</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msub> <mo>&times;</mo> <mo>(</mo> <mrow> <msubsup> <mi>t</mi> <mi>g</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msubsup> <mo>-</mo> <msubsup> <mi>t</mi> <mrow> <mi>a</mi> <mi>a</mi> </mrow> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msubsup> <mo>+</mo> <msubsup> <mi>t</mi> <mi>s</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msubsup> </mrow> <mo>)</mo> <mo>)</mo> </mrow> </mrow> </mtd> <mtd> <mrow> <mi>e</mi> <mi>l</mi> <mi>s</mi> <mi>e</mi> </mrow> </mtd> </mtr> </mtable> </mfenced> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>8</mn> <mo>)</mo> </mrow> <mo>;</mo> </mrow>
<mrow> <mi>s</mi> <mo>.</mo> <mi>t</mi> <mo>.</mo> <mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <mrow> <msubsup> <mi>t</mi> <mi>g</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msubsup> <mo>&GreaterEqual;</mo> <msubsup> <mi>t</mi> <mrow> <mi>g</mi> <mi>min</mi> </mrow> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msubsup> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <munderover> <mo>&Sigma;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>m</mi> </munderover> <msubsup> <mi>t</mi> <mi>g</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msubsup> <mo>=</mo> <mi>C</mi> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <mn>0</mn> <mo>&le;</mo> <msub> <mi>o</mi> <mi>j</mi> </msub> <mo>&le;</mo> <mi>C</mi> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <msubsup> <mi>t</mi> <mi>g</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msubsup> <mo>,</mo> <msubsup> <mi>t</mi> <mrow> <mi>g</mi> <mi>min</mi> </mrow> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msubsup> <mo>,</mo> <msub> <mi>o</mi> <mi>j</mi> </msub> <mo>&GreaterEqual;</mo> <mn>0</mn> <mo>&Element;</mo> <mi>int</mi> <mi>e</mi> <mi>g</mi> <mi>e</mi> <mi>r</mi> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <mi>min</mi> <mi> </mi> <msub> <mi>S</mi> <mrow> <mi>a</mi> <mi>l</mi> <mi>l</mi> </mrow> </msub> <mo>=</mo> <mi>min</mi> <munderover> <mo>&Sigma;</mo> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <mi>S</mi> </mrow> </mtd> </mtr> </mtable> </mfenced> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>9</mn> <mo>)</mo> </mrow> <mo>;</mo> </mrow>
wherein,the time when the vehicle at the jth phase of the ith intersection reaches the stop line is taken as the time; u. ofijConsidering the arrival rate of the j phase at the ith intersection after the influence of the upstream intersection is considered;
the signal phase timing and phase difference of each intersection meeting the objective function can be obtained by utilizing the particle swarm algorithm of the integer space.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710868230.3A CN107705591B (en) | 2017-09-22 | 2017-09-22 | Tramcar and social traffic flow cooperative control method |
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| CN109712414A (en) * | 2019-01-30 | 2019-05-03 | 同济大学 | A kind of optimization method of more bandwidth arterial highway public transport control programs |
| CN110364003A (en) * | 2019-07-18 | 2019-10-22 | 大连海事大学 | Intersection double-circuit tramcar signal priority control method based on car networking |
| CN111028508A (en) * | 2019-12-19 | 2020-04-17 | 东南大学 | Tramcar steering control method and device based on path control |
| CN111028521A (en) * | 2019-12-19 | 2020-04-17 | 东南大学 | Tramcar network green wave coordination control method and device |
| CN111311933A (en) * | 2020-02-19 | 2020-06-19 | 东南大学 | Green wave coordination control method and device for road-type left-turn line tramcar |
| CN111383466A (en) * | 2018-12-27 | 2020-07-07 | 上海宝康电子控制工程有限公司 | System and method for realizing tramcar intersection signal control function |
| CN111462477A (en) * | 2019-01-22 | 2020-07-28 | 上海宝康电子控制工程有限公司 | Method for realizing anti-congestion control of tramcar based on road traffic state |
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| CN113291357A (en) * | 2021-04-25 | 2021-08-24 | 东南大学 | Intersection signal priority control method based on tramcar departure interval |
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| CN109003445A (en) * | 2018-07-09 | 2018-12-14 | 北方工业大学 | Tramcar priority signal control method facing effective green wave |
| CN109191835A (en) * | 2018-09-03 | 2019-01-11 | 北京全路通信信号研究设计院集团有限公司 | Tramcar operation control method and system |
| CN109102705A (en) * | 2018-10-15 | 2018-12-28 | 上海市城市建设设计研究总院（集团）有限公司 | Tramcar control method conllinear with public transport |
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| CN111383466A (en) * | 2018-12-27 | 2020-07-07 | 上海宝康电子控制工程有限公司 | System and method for realizing tramcar intersection signal control function |
| CN111462477A (en) * | 2019-01-22 | 2020-07-28 | 上海宝康电子控制工程有限公司 | Method for realizing anti-congestion control of tramcar based on road traffic state |
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| CN109712414B (en) * | 2019-01-30 | 2021-09-03 | 同济大学 | Optimization method of multi-bandwidth trunk road bus control scheme |
| CN110364003A (en) * | 2019-07-18 | 2019-10-22 | 大连海事大学 | Intersection double-circuit tramcar signal priority control method based on car networking |
| CN110364003B (en) * | 2019-07-18 | 2021-05-14 | 大连海事大学 | Intersection double-line tramcar signal priority control method based on Internet of vehicles |
| CN111028521A (en) * | 2019-12-19 | 2020-04-17 | 东南大学 | Tramcar network green wave coordination control method and device |
| CN111028508A (en) * | 2019-12-19 | 2020-04-17 | 东南大学 | Tramcar steering control method and device based on path control |
| CN111311933A (en) * | 2020-02-19 | 2020-06-19 | 东南大学 | Green wave coordination control method and device for road-type left-turn line tramcar |
| CN111554107A (en) * | 2020-03-27 | 2020-08-18 | 北京星云互联科技有限公司 | Traffic control method, management platform, road side equipment and system |
| CN111554107B (en) * | 2020-03-27 | 2021-04-16 | 北京星云互联科技有限公司 | Traffic control method, management platform, road side equipment and system |
| CN112820126A (en) * | 2020-12-31 | 2021-05-18 | 北京交通大学 | Road right priority operation control and simulation method for non-invasive guided transport vehicle |
| CN112820126B (en) * | 2020-12-31 | 2021-08-24 | 北京交通大学 | Road right priority operation control and simulation method for non-invasive guided transport vehicle |
| CN113291357A (en) * | 2021-04-25 | 2021-08-24 | 东南大学 | Intersection signal priority control method based on tramcar departure interval |
| CN113291357B (en) * | 2021-04-25 | 2022-06-17 | 东南大学 | Intersection signal priority control method based on tramcar departure interval |
| CN113299081A (en) * | 2021-04-30 | 2021-08-24 | 东南大学 | Green wave cooperative control optimization method for social vehicles and tramcars |
| CN113299081B (en) * | 2021-04-30 | 2022-06-07 | 东南大学 | Green wave cooperative control optimization method for social vehicles and tramcars |
| CN115311868A (en) * | 2022-07-20 | 2022-11-08 | 武汉理工大学 | Bus priority-based trunk line coordination control method and device |
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