CN110889967B - Overflow risk balance signal control optimization method based on main road segmentation - Google Patents
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Abstract
The application discloses a method for controlling and optimizing overflow risk balance signals based on trunk road segmentation. The method comprises the following steps: identifying the overflow state of the intersection by using two indexes of the periodic queuing emptying area and the overflow risk area; dividing the arterial road into a set of overflow risk prevention and control subareas by an arterial road dividing method, wherein each subarea comprises three different types of intersections: input, output and connection intersections; and then, aiming at intersections of different types in the subareas, adopting an overflow risk balance signal control optimization strategy for the straight-going phase of the main road, and then, carrying out signal control optimization on the left-turning phase of the main road and the phase of the branch road according to the queuing length of each phase to determine the green light duration of each phase.
Description
Technical Field
The application relates to the field of traffic signal control, in particular to an overflow risk balance signal control optimization method based on trunk road segmentation.
Background
With the explosive growth of urban traffic demand, urban thoroughfares become increasingly congested, leading to frequent intersection queuing overflow. In the present time, the "internet+signal lamp" becomes a research hotspot. The Ali release "City brain 2.0" takes over timing optimization of 1300 signal lamps in Hangzhou city; the drip outlet utilizes crowd-sourced track data of taxis, special express buses and the like to construct a 'perception-evaluation-optimization-implementation' closed-loop traffic signal monitoring and optimizing system, and an optimizing scheme is adopted when the urban and regional land areas such as the Liuzhou, jinan and Beijing capital airports fall to 1500 sets of roads and openings, so that the traffic jam problem is relieved to a certain extent.
However, the above practice only enables "coarse-grained" traffic state assessment without lane splitting, without flow splitting, and "multi-period" periodic signal timing optimization for Time Of Day (TOD) partitioning. In addition, the optimal control is mostly passive in response to traffic demand changes, and deep analysis is lacking in the evolution process of queuing from a normal state to an overflow state and the control strategy. Considering that urban arterial road traffic demand continues to be large, intersections are often at high risk and frequency of queuing overflows.
The queuing length is an index for describing traffic running states intuitively in a space level, and the direct expression of queuing overflow is the generation of overlong queuing, so that how to evaluate traffic states based on the queuing length and the fine granularity of the queuing directions in different periods is an optimal theory and method system for timely and accurately predicting the queuing overflow risk and establishing the active prevention and the rapid elimination of the queuing overflow is a key theoretical problem to be solved in the field of traffic control.
Disclosure of Invention
1. Object of the application
Aiming at the problems that the existing signal control method cannot identify the queuing overflow risk timely and accurately and the signal control strategy is relatively lagged and responds to traffic demands, the application provides an overflow risk balance signal control optimization method based on main road segmentation, so that the main road overflow risk is eliminated.
2. The application adopts the technical proposal that
The overflow risk balance signal control optimization method based on the trunk road segmentation can be realized by the following steps:
(1) Calculating two indexes of a periodic emptying area and an overflow risk area of the intersection according to the straight-going phase queuing length of each intersection of the main road;
(2) Identifying overflow risk states of the intersections according to the periodic emptying areas and the overflow risk areas calculated in the step (1), and dividing the overflow risk states of the intersections into three types: low, medium and high overflow risk;
(3) According to the identification result in the step (2), adjacent intersections in a medium or high overflow risk state are brought into the same overflow subarea, so that the main road is divided into different overflow subareas, and each overflow subarea generally comprises three types of intersections: input, output and connection intersections;
(4) Aiming at intersections of different types in the overflow subarea, signal control optimization strategies such as current limiting, balancing, maximum flow and the like are adopted respectively, so that the risk balance of straight-going phase overflow of each intersection of the main road is realized.
The step (1) specifically comprises the following steps: because of the large number of vehicles accommodated at each intersection section of the main road, the poor control effect of one cycle signal is not enough to cause the occurrence of the queuing overflow phenomenon, which is usually the accumulated result of more than 2 cycles. Therefore, how to accurately identify the overflow risk of the intersection in the process of evolving from the saturation state to the overflow state is the key of the design of the control scheme for preventing overflow signals, and the periodic queuing empty area q is provided herein cr And overflow risk area s cr And identifying overflow risks of intersections in each period by the two indexes, and dividing the main road according to the overflow risks of the intersections.
The periodic queuing empty area is an index for evaluating whether an intersection is in a saturated state, and the length is firstly related to the traffic capacity in the period of the intersection. If the queuing length is greater than the period traffic capacity, the queuing vehicles in the period cannot be emptied, initial queuing can be generated when the next period starts, and the intersection is in a saturated state. The queuing flush capability may be calculated by the following formula:
q max ＝q s g k (1)
wherein q is s For the intersection saturation flow rate (vehicle/second), when the green light starts, queuing vehicles in the period pass through the intersection at the saturation flow rate g k Is the green light duration of the kth period of the intersection.
The length of the periodic queuing clear-up area is secondarily related to the coordination between the present intersection and the upstream intersection. The queuing vehicles at the upstream intersection enter the intersection in a vehicle queue mode after the green light of the upstream intersection starts, and if the queuing vehicles at the intersection are emptied, the upstream vehicle queue can directly pass through the intersection before the green light ends; if the queuing vehicles at the intersection are not completely dissipated when the upstream vehicle fleet arrives, the upstream vehicle fleet can join in the queuing, and the queuing length is rapidly increased due to the large traffic flow of the trunk, so that the risk of overflow is generated. The queuing length threshold under consideration of upstream intersection coordination may be calculated by the following formula:
wherein v is 2 For the velocity of the evanescent wave (m/s), v f Is the free flow velocity (meters per second), k j For congestion density (vehicles per meter),for the green light start time of the kth intersection, D is the distance from the stop line of the upstream intersection to the stop line of the intersection, T coor And q coor The generation time of the queuing length threshold and the queuing length threshold are respectively.
The periodic queuing and emptying area of the intersection can be determined by adopting the following formula by combining the queuing and emptying capacity of the intersection and the queuing length threshold value:
q cr ＝min(q max ,q coor ) (4)
the overflow risk area is located at the end of the road section and is an index for judging whether the intersection is in a high overflow risk state. The range of the overflow risk area is in a proportional relation with the length of the road section, the longer the length of the road section is, the larger the range of the overflow risk area is, and otherwise, the smaller the range of the overflow risk area is. The calculation formula of the overflow risk area can be obtained from the following formula:
s cr ＝β cr Lk j (5)
wherein beta is cr For overflow area coefficient, k j For the congestion density (vehicle/meter), L is the length (meter) of the road section.
The step (2) specifically comprises the following steps: the main road is segmented every cycle, and the overflow risk states of straight-going phases of all intersections on the main road in every cycle need to be identified first, and the overflow risk states of the intersections can be divided into three types based on the queuing emptying areas and the overflow risk areas described above: the principles of the division of low overflow risk, medium overflow risk and high overflow risk are as follows:
wherein q is total ＝k j L is the total number of vehicles that the road section can hold, and L is the length of this road section.
For the signal intersections with low overflow risks in the period, the signal control effect in the period is good, the traffic supply and demand are balanced, the signal control is not required to be optimized in the next period, and the traffic demands of the intersections adjacent to the intersections on the main road can be properly guided to the intersections with low overflow risks; for a signalized intersection at a medium overflow risk in a period, the signalized intersection is in a saturated state, the traffic demand is greater than the traffic supply, and the signalized intersection is required to be properly optimized to control and prevent the queuing vehicles from continuously accumulating to generate a queuing overflow phenomenon; for the signalized intersections with high overflow risks in the period, the requirement of the intersections is far greater than that of the supply of the intersections, the intersections are already or about to generate queuing overflow phenomena, signal control optimization needs to be performed in time, the supply and demand balance of the intersections is realized by limiting traffic inflow and increasing traffic supply, and the queuing overflow phenomena are prevented from being generated in the next period.
The step (3) specifically comprises the following steps: and (3) according to the overflow risk identification result in the step (2), adjacent intersections with medium and high overflow risks are incorporated into the same overflow subarea, so that the trunk is divided into a plurality of overflow subareas. Each overflow sub-zone contains three types of intersections: an input intersection, an output intersection, and a connection intersection. An upstream intersection of the uppermost stream overflow intersection in the overflow subarea is called an input intersection, and traffic flow of the upstream intersection of the overflow subarea flows into the overflow subarea through the input intersection; the output intersection is the intersection at the most downstream of the overflow subarea, and the traffic flow in the overflow subarea is output to the downstream road section of the overflow subarea through the output intersection; the junction intersections are all intersections between the input intersections and the output intersections, and traffic flow within the overflow sub-zone propagates downstream through the junction intersections.
The step (4) specifically comprises the following steps:
the straight-going phase in the urban main road is the main flow direction of the main road traffic flow, so that the key of the main road overflow prevention signal control is to prevent the main road straight-going phase from generating queuing overflow. And the signal control optimization of the straight line phase adopts different signal control optimization methods according to different intersection types in the overflow subarea.
The input intersection is the intersection located furthest upstream in the overflow subregion, and the traffic flow of outside flows into the overflow subregion through the input intersection. Because the straight-going phase of the input intersection is in an overflow-free state and the intersections inside the overflow subarea are all in a saturated state, the signal control of the input intersection aims to limit the traffic flow to flow into the overflow subarea by reducing the green light duration of the straight-going phase, and prevent the occurrence of queuing overflow caused by excessive vehicles flowing into the overflow subarea. The traffic supply is reduced due to the reduction of the green time of the straight-going phase of the input intersection, and the overflow risk is led to the upstream intersections from the inside of the overflow subarea, so that the overflow risk of each intersection of the main road is balanced.
The reduction of the green light duration of the input intersection is determined by the queuing length of the downstream straight line phase, and the green light duration calculation formula of the next period of the input intersection straight line phase is as follows:
wherein the method comprises the steps ofFor the green light duration of the kth cycle of the ith intersection, l +1 is the downstream intersection of the ith intersection,for the length of the queuing clearance area of the kth cycle of the ith intersection, the min (A, B) function returns the smaller value of A and B, +.>For the remaining vehicle capacity, K, in the straight-going phase section in the kth period of the ith intersection i1 And K i2 For entering the delta coefficients for the intersection.
The output intersection is the most downstream intersection in the overflow subarea, and the traffic flow in the overflow subarea flows out of the overflow subarea through the output intersection. The downstream intersection of the output intersection is in an overflow-free state, so that the signal control of the output intersection aims at maximizing the traffic supply of the output intersection by increasing the green light duration of the straight phase, so that the overflow risk is led to the downstream intersection, and the overflow risk of each intersection of the main road is balanced. The calculation formula of the increase of the green light time length of the output intersection is similar to the formula (7), the increase of the green light time length is determined by the excess of the queuing length exceeding the queuing emptying area and the change of the queuing length in the overflow risk area, and the formula is as follows:
wherein K is o1 And K o2 For the incremental coefficient controlled by the output intersection signal, the definition of the rest parameters is shown in formula (7).
The junction intersection is located between the input intersection and the output intersection of the overflow sub-zone, and traffic flow in the overflow sub-zone propagates downstream through the junction intersection. Because all the connection intersections are in the medium-high overflow risk state, the signal control of the connection intersections aims at balancing the overflow risk of each intersection in the overflow subarea by adjusting the green light duration of the straight phase of each connection intersection so that the overflow risk propagates to the intersection in the lower overflow risk state in the overflow subarea.
The change of the duration of the green light of the straight phase of the lower period of each connecting intersection is determined by overflow risks in the period of the intersection and the downstream intersection, and if the overflow risk degree of the intersection is higher than that of the downstream intersection, the duration of the green light of the straight phase of the intersection of the lower period is increased; if the overflow risk degree of the intersection is lower than that of the downstream intersection, the green light duration of the straight-going phase of the intersection of the lower period is reduced. The calculation formula of the green light duration of the period straight-going phase at the junction is as follows:
wherein K is c1 And K c2 For the incremental coefficient of the signal control of the junction, the definition of the rest parameters is shown in the formula (7).
After the green light duration of the straight phase of the trunk of the next period is determined, the green light duration of the left phase of the trunk of the next period needs to be determined. The algorithm firstly determines the left turn green light duration of the next period through the queuing length of the left turn phase in the period on the premise of ensuring the green light duration of the straight-going phase of the trunk, and the calculation formula is as follows:
where A and B are the relative traffic flow directions of the thoroughfares (east and west herein), T and L represent the straight-going phase and left-turning phase, respectively, and g and q represent the green light duration and queuing length. Thus (2)Left turn green light duration in the direction of the kth cycle A of the ith intersection, +.>The queuing length of the left turn phase in the kth period a direction of the ith intersection is shown. />For isolating the length at one side of the main road (namely the total green time of two-phase traffic of the same loop of the main road) in the double-loop structure, G max Maximum green light time length allowed by two-phase traffic of main road, q s For the saturation flow rate of the intersection(vehicle/second).
The signal control optimization method mainly aims at preventing the overflow phenomenon of the main road, and the traffic demand of the branch road is far lower than that of the main road, but the basic traffic capacity of the branch road is ensured, so that the overflow phenomenon of the branch road caused by insufficient traffic supply is avoided. Under the condition that the total green light duration of the main road is determined, the branch signal control method distributes the residual green light duration of the next period according to the queuing length ratio of the branch phase, and the calculation formula of the branch phase green light duration is as follows:
where C is a fixed period length. Since the signal bridging phenomenon is not assumed to exist in the branches, cs1 and cs2 represent different branch phases respectively.
In summary, the pseudo code of the overflow risk balance signal control optimization algorithm based on the trunk segmentation provided by the application is as follows:
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The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute a limitation on the application. In the drawings:
FIG. 1 is an actual dry road network satellite map according to an embodiment of the present disclosure;
FIG. 2 is a diagram of a VISSIM simulated road network and initial signal timing in accordance with embodiments of the present disclosure;
FIG. 3 is an exemplary diagram of a method for dividing a thoroughfare, according to an embodiment of the present disclosure;
FIG. 4 is a graph of a signal optimized forward trunk east-straight phase vehicle trajectory in accordance with embodiments of the present disclosure;
fig. 5 is a graph of a signal optimized trunk east-to-straight phase vehicle trajectory according to an embodiment of the present disclosure.
Fig. 6 is a main flow chart of a method according to an embodiment of the present disclosure.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. The following description of at least one exemplary embodiment is merely exemplary in nature and is in no way intended to limit the application, its application, or uses. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the present application. As used herein, the singular is also intended to include the plural unless the context clearly indicates otherwise, and furthermore, it is to be understood that the terms "comprises" and/or "comprising" when used in this specification are taken to specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof.
The relative arrangement of the components and steps, numerical expressions and numerical values set forth in these embodiments do not limit the scope of the present application unless it is specifically stated otherwise. Meanwhile, it should be understood that the sizes of the respective parts shown in the drawings are not drawn in actual scale for convenience of description. Techniques, methods, and apparatus known to one of ordinary skill in the relevant art may not be discussed in detail, but should be considered part of the authorization specification where appropriate. In all examples shown and discussed herein, any specific values should be construed as merely illustrative, and not a limitation. Thus, other examples of the exemplary embodiments may have different values. It should be noted that: like reference numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further discussion thereof is necessary in subsequent figures.
The overflow risk balance signal control optimization method based on the trunk road segmentation can be realized by the following steps:
(1) Calculating two indexes of a periodic emptying area and an overflow risk area of the intersection according to the straight-going phase queuing length of each intersection of the main road;
(2) Identifying overflow risk states of the intersections according to the periodic emptying areas and the overflow risk areas calculated in the step (1), and dividing the overflow risk states of the intersections into three types: low, medium and high overflow risk;
(3) And (3) according to the identification result of the step (2), adjacent intersections in the medium or high overflow risk state are brought into the same overflow subarea, so that the main road is divided into different overflow subareas. Meanwhile, three types of intersections are typically contained within each overflow sub-zone: input, output and connection intersections;
(4) Aiming at intersections of different types in the overflow subarea, signal control optimization strategies such as current limiting, balancing, maximum flow and the like are adopted respectively, so that the risk balance of straight-going phase overflow of each intersection of the main road is realized.
The specific method of each step is described in detail below.
Step (1): in order to simulate an actual dry road network, the embodiment adopts microscopic traffic software VISSIM to build a simulation road network model. As shown in FIG. 1, ten paths of continuous 6 signal intersections in Jinan city are selected as research objects, ten paths are important east-west traffic thoroughfares in Jinan city, traffic flow, especially traffic flow of peaks in the morning and evening, is large, the thoroughfares are in a saturated state for a long time, and queuing overflow phenomenon is easy to generate. The 6 intersections selected in the part are respectively a short-time ploughing road, a Qianfhan road, a mountain calendar road, a mountain craftsman road, a circular mountain road and an intersection of ten roads, the total length of each road section of the intersection is 2.8km, the road speed limit is 50km/h, the initial signal timing plan of each intersection is shown in fig. 2, and the period length is fixed to 210s.
The case assumes that the queuing length of each intersection of a main road can be accurately obtained as input, and firstly, two indexes of a periodic queuing emptying area of each intersection and an overflow risk area of a formula (5) are calculated by utilizing formulas (1) - (4), wherein the overflow risk area coefficient is set to be 0.2;
step (2): as shown in fig. 3, taking the case of ten consecutive 6 intersections in jinan city in the west-east direction as an example, how to implement the trunk road segmentation algorithm in one period is further described. In the period, identifying overflow risk states of all intersections of the arterial roads by using a formula (6), finding that the mountain-surrounding intersection is in a low overflow risk state, the mountain-surrounding intersection is in a medium overflow risk state, and the mountain-surrounding intersection, the mountain-surrounding intersection and the mountain-major intersection are in high overflow risk states;
step (3): according to the identification result of the step (2), after the adjacent intersections at medium and high overflow risks are incorporated into the same overflow subarea, the periodic trunk is divided into 2 overflow subareas, as shown in fig. 2. Wherein the overflow subarea 1 takes an upstream intersection of a first overflow intersection Qianfo mountain road as an input intersection, takes an eastern road of a downstream mountain as an output intersection, and takes two intersections (Qianfo mountain road and calendar mountain road) between the input intersection and the output intersection as connection intersections. The overflow subarea 2 takes a mountain loop road and a mountain loop road as an input intersection and an output intersection respectively, and as other intersections are not arranged between the input intersection and the output intersection, the overflow subarea 2 is not connected with the intersections;
step (4): aiming at different intersections in the overflow subarea, the straight-line phase signal control optimization is carried out by adopting formulas (7), (8) and (9), wherein the increment coefficient takes the value K respectively i1 ＝0.15，K i2 ＝0.8，K o1 ＝0.25，K o2 ＝0.8，K c1 ＝0.1，K c2 =0.5. After the green light duration of the straight-going phase of the trunk is determined, the green light duration of the left-turning phase of the trunk and the green light duration of the branch phase are determined by using formulas (10) and (11) respectively.
Fig. 3 shows a space-time trajectory diagram of all vehicles of one lane at each intersection straight-going phase of the east direction of the trunk road before and after signal optimization of 20 cycles. As can be seen from fig. 4, the main road is in a saturated state before signal optimization, and the overflow phenomenon of three intersections of the qianhu mountain road, the calendar mountain road and the eastern mountain road is serious due to unbalanced traffic supply and demand at the intersections, so that the queuing overflow phenomenon can be generated every cycle, and the operation efficiency of the intersections is seriously affected. As shown in fig. 5, after the signal control optimization algorithm proposed by the chapter is adopted, the queuing overflow phenomenon at the intersection is obviously reduced, and it can be seen that the overflow risk balance signal optimization algorithm based on the main road segmentation can effectively reduce the main road overflow risk.
In the embodiment, by using the overflow risk balance signal control optimization method based on the main road segmentation, simulation results show that after the main road in a saturated state is optimized by the signal control optimization algorithm provided by the chapter, the occurrence rate of the main road queuing overflow phenomenon is obviously reduced, and the main road passing efficiency is obviously improved.
Claims (2)
1. The method for optimally controlling the overflow risk balance signal based on the main road segmentation is characterized by comprising the following steps of:
identifying the overflow state of the intersection by using two indexes of the periodic queuing emptying area and the overflow risk area; dividing the main road into a set of overflow risk prevention and control subareas by using a main road dividing method based on overflow risk clustering, wherein the method utilizes a periodical emptying area and overflow risk area indexes to identify overflow risk states of intersections, wherein the overflow risk states comprise low, medium and high overflow risks, adjacent intersections in the medium or high overflow risk states are incorporated into the same overflow subarea, so that the main road is divided into different overflow subareas, and each subarea comprises three different types of intersections: the input intersection, the output intersection and the connection intersection are arranged, wherein an upstream intersection of the most upstream overflow intersection in the overflow subarea is called an input intersection, and traffic flow of the upstream intersection of the overflow subarea flows into the overflow subarea through the input intersection; the output intersection is the intersection at the most downstream of the overflow subarea, and the traffic flow in the overflow subarea is output to the downstream road section of the overflow subarea through the output intersection; the connection intersections are all intersections between the input intersections and the output intersections, and traffic flow in the overflow subarea propagates downstream through the connection intersections;
aiming at intersections of different types in the subareas, adopting an overflow risk balance signal control optimization strategy for the straight-going phase of the main road, specifically, reducing input intersection input, increasing output intersection output, adjusting the flow between all connected intersections, enabling overflow risks to spread to intersections in a lower overflow risk state in the overflow subareas, determining the left-turning green light duration of the next period through the queuing length of the left-turning phase in the period on the premise of guaranteeing the green light duration of the straight-going phase of the main road, and distributing the residual green light duration of the next period according to the queuing length ratio of the branch phases under the condition of determining the total green light duration of the main road.
2. The method of claim 1, wherein calculating two indicators of intersection periodic emptying area and overflow risk area based on the straight phase queuing length of each intersection of the thoroughfare comprises:
and calculating a periodic queuing emptying area according to the intersection queuing emptying capacity and considering a queuing length threshold under the coordination of an upstream intersection, and calculating an overflow risk area according to the road section length.
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Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2000259985A (en) * | 1999-03-11 | 2000-09-22 | Sumitomo Electric Ind Ltd | Traffic signal controller and its method |
| CN103544841A (en) * | 2013-10-22 | 2014-01-29 | 银江股份有限公司 | Method for dynamically dividing traffic control region |
| CN104157152A (en) * | 2014-08-13 | 2014-11-19 | 安徽科力信息产业有限责任公司 | Traffic signal optimization control method for vehicle queuing overflow state at road intersections |
| CN105225503A (en) * | 2015-11-09 | 2016-01-06 | 中山大学 | Traffic control subarea is optimized and self-adapting regulation method |
| CN105679032A (en) * | 2016-03-24 | 2016-06-15 | 浙江工业大学 | Traffic control subsegment division method in city traffic flow oversaturation state |
| CN105844927A (en) * | 2016-04-06 | 2016-08-10 | 深圳榕亨实业集团有限公司 | Novel control system and novel control method for sensing and controlling road intersection group signals |
| CN106023605A (en) * | 2016-07-15 | 2016-10-12 | 姹ゅ钩 | Traffic signal lamp control method based on deep convolution neural network |
| CN109215340A (en) * | 2018-08-31 | 2019-01-15 | 广州运星科技有限公司 | A kind of intersection flow dynamics control method, system, equipment and storage medium |
| CN109767625A (en) * | 2019-03-18 | 2019-05-17 | 苏州易通交通科技有限公司 | Recognition methods is overflowed in a kind of short lane queuing in intersection based on the alert data of electricity |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2004077377A1 (en) * | 2003-02-27 | 2004-09-10 | Shaopeng Yang | Road traffic control method and traffic facilities |
| JP2015212863A (en) * | 2014-05-01 | 2015-11-26 | 住友電気工業株式会社 | Traffic signal control device, traffic signal control method, and computer program |
-
2019
- 2019-11-28 CN CN201911195758.4A patent/CN110889967B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2000259985A (en) * | 1999-03-11 | 2000-09-22 | Sumitomo Electric Ind Ltd | Traffic signal controller and its method |
| CN103544841A (en) * | 2013-10-22 | 2014-01-29 | 银江股份有限公司 | Method for dynamically dividing traffic control region |
| CN104157152A (en) * | 2014-08-13 | 2014-11-19 | 安徽科力信息产业有限责任公司 | Traffic signal optimization control method for vehicle queuing overflow state at road intersections |
| CN105225503A (en) * | 2015-11-09 | 2016-01-06 | 中山大学 | Traffic control subarea is optimized and self-adapting regulation method |
| CN105679032A (en) * | 2016-03-24 | 2016-06-15 | 浙江工业大学 | Traffic control subsegment division method in city traffic flow oversaturation state |
| CN105844927A (en) * | 2016-04-06 | 2016-08-10 | 深圳榕亨实业集团有限公司 | Novel control system and novel control method for sensing and controlling road intersection group signals |
| CN106023605A (en) * | 2016-07-15 | 2016-10-12 | 姹ゅ钩 | Traffic signal lamp control method based on deep convolution neural network |
| CN109215340A (en) * | 2018-08-31 | 2019-01-15 | 广州运星科技有限公司 | A kind of intersection flow dynamics control method, system, equipment and storage medium |
| CN109767625A (en) * | 2019-03-18 | 2019-05-17 | 苏州易通交通科技有限公司 | Recognition methods is overflowed in a kind of short lane queuing in intersection based on the alert data of electricity |
Non-Patent Citations (3)
| Title |
|---|
| Quasi-optimal feedback control for an isolated intersection under oversaturation;Guizhen Yu 等;《Transportation Research Part C》;109-130 * |
| 交通流动态扰动下的区域交通信号协调控制;魏永涛;《自动化学报》;第45卷(第10期);1983-1994 * |
| 混合交通状态下区域信号协调控制;单敏;《中国优秀硕士学位论文全文数据库工程科技二辑》;C034-814 * |
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