CN109559506B - Method for predicting delay time of intermittent traffic flow of urban road in rainfall weather - Google Patents
Method for predicting delay time of intermittent traffic flow of urban road in rainfall weather Download PDFInfo
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
- G08G1/0133—Traffic data processing for classifying traffic situation
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
- G08G1/0129—Traffic data processing for creating historical data or processing based on historical data
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/065—Traffic control systems for road vehicles by counting the vehicles in a section of the road or in a parking area, i.e. comparing incoming count with outgoing count
Abstract
The invention provides a method for predicting delay time of intermittent traffic flow of an urban road in rainfall weather, which aims at the problem that the delay time of the traffic flow of the urban road in the rainfall weather is difficult to accurately and effectively predict, builds an intermittent traffic flow relation model of the urban road in different rainfall intensity levels by mining and analyzing the relation between meteorological data and traffic flow data and analyzing the running characteristics and rules of the traffic flow of the urban road in the rainfall weather, analyzes the delay time of the intermittent traffic flow of the urban road by adopting an evanescent wave theory in combination with signal control parameters of road intersections, gives a corresponding delay time calculation method by considering different traffic running states such as undersaturation and saturation and the like, and finally realizes the prediction of the delay time of the intermittent traffic flow of the urban road in the rainfall weather.
Description
Technical Field
The invention discloses a method for predicting delay time of intermittent traffic flow of an urban road in rainfall weather, and belongs to the technical field of urban traffic intermittent flow prediction in severe weather.
Background
Because the urban road traffic flow has the characteristics of uncertainty, randomness, nonlinearity and the like, the urban traffic system is a variable complex system, and the characteristics also increase the difficulty of urban traffic management and cause a series of problems of traffic jam, safety accidents and the like. In order to improve the effectiveness and safety of urban traffic management and improve the accurate perception and prediction capability of road traffic, enhancing the prediction and forecast of urban road traffic flow has become a necessary means for solving the effective monitoring and management of the current complex traffic system. Due to the characteristics of real-time fluctuation of urban traffic flow and the like, the technical difficulty of road traffic flow prediction is mainly to predict short-time traffic flow, various prediction models are generally established in the conventional method, such as a multiple regression model, a time sequence model, a historical trend model, a neural network model, a Kalman filtering model and the like, short-time prediction is carried out, corresponding fluctuation of traffic flow can occur under the influence of external interference factors, such as urban rainfall weather influences the normal operation of road traffic, the urban road traffic flow prediction under the rainfall condition is rarely considered in the conventional method, and targeted traffic management and control cannot be carried out due to the fact that the traffic flow operation characteristics cannot be effectively estimated and predicted, and under the background condition, the urban road traffic operation efficiency becomes extremely low, and the situations of traffic jam, delay and the like become more serious.
Aiming at the defects of the existing urban road traffic flow prediction technology, the method establishes the urban road traffic flow prediction method technology in the rainfall weather, and due to the fact that the urban road traffic is influenced by intersection signal control, the delay time of the intermittent traffic flow of the urban road under the weather background is predicted by combining control signals of intersections and considering the road traffic flow operation characteristics and rules under different rainfall intensity levels, and the effective estimation and accurate prediction capabilities of the urban road traffic flow in the rainfall weather are improved.
Compared with the prior art, the invention has the following advantages:
1) the method integrates rainfall meteorological data and road traffic flow detection data, fully considers the influence of rainfall weather on urban traffic flow, respectively establishes corresponding urban road traffic flow relation models aiming at different rainfall intensity levels, and can apply traffic flow relation equations corresponding to the models according to different rainfall intensity level situations, thereby improving the accuracy and effectiveness of urban road discontinuous flow prediction.
2) The method comprehensively considers the characteristics of the urban intermittent traffic flow, analyzes and judges the traffic flow running state of the road intersection, and adopts the distributed wave theory to construct an urban road intermittent traffic flow running mechanism model, so that the model is more in line with the running characteristics and rules of the actual urban road traffic flow, and the prediction result of the urban road intermittent traffic flow delay time is more intuitively and obviously obtained.
Disclosure of Invention
The invention discloses a method for predicting delay time of intermittent traffic flow of urban road under rainfall condition, which integrates meteorological data such as rainfall and road traffic detection data such as traffic flow, analyzes corresponding relation between rainfall and traffic data at different rainfall intensity levels to construct a road section traffic flow parameter relation model under rainfall condition, further analyzes aggregate wave and dispersion wave operation rules of signal control intersection traffic flow at different rainfall intensity levels to construct a signal control intersection traffic flow aggregate dispersion wave base model, provides a delay time calculation method under corresponding traffic state at different rainfall intensity levels on the basis of aggregate dispersion wave speed calculation, traffic state judgment and delay time analysis, combines intersection traffic signal control parameters, an actual road traffic discontinuous flow collecting and distributing wave model can be constructed, and finally, a prediction result of the delay time of the urban road discontinuous traffic flow in the rainfall weather can be obtained, so that the aim of estimating and predicting the delay time of the urban traffic flow in the rainfall weather is finally achieved. The basic method flow of the invention is shown in figure 1, and the following scheme is specifically adopted:
step 1: screening and preprocessing meteorological data and traffic flow data, analyzing precipitation intensity levels based on the meteorological data, detecting by a vehicle detector to obtain traffic flow data, and sorting the acquired basic road traffic operation data such as traffic flow, speed, occupancy and the like;
step 2: according to the precipitation intensity grade division standard, the corresponding relation between meteorological data and traffic data under different grades is established, a road traffic flow data mapping environment under the rainfall scene is established, and the basic data relation is expressed as follows.
In the formula (I), the compound is shown in the specification,
and
weather data and traffic data, r, respectively, at a rainfall intensity level llower,rupperThe upper limit and the lower limit of the precipitation are respectively, and the q and the u are respectively the traffic flow and the traffic speed;
and step 3: aiming at different precipitation intensity levels, relevant meteorological data and traffic data are fused, corresponding traffic flow relation equations are respectively established, and a road section traffic flow parameter relation model under precipitation conditions is established
Fi＝fi(l,q,u)
Where l represents the precipitation intensity level, q represents the traffic flow at that time, and u represents the link average traffic flow velocity.
And 4, step 4: constructing a basic model of traffic flow collecting and dispersing waves of the signal control intersection, analyzing the operation rules of the collecting waves and the dispersing waves of the traffic flow of the signal control intersection under different rainfall intensity levels, respectively obtaining corresponding wave speed parameters of the collecting and dispersing waves and the like, and forming the basic model of the traffic flow collecting and dispersing waves of the intersection under the rainfall condition based on the collecting and dispersing wave theory into
Wherein w is the wave velocity of the scattered wave of the traffic flow and q1And q is2Representing upstream and downstream traffic flow, respectively, k1And k2Representing upstream and downstream traffic flow density, u, respectively2And u1Representing the average speeds of the upstream and downstream traffic flows respectively;
and 5: calculating the wave velocity w of the traffic flow set
Calculating the wave velocity of the aggregate wave
w1＝q1u1/(q1-u1klm)，
Calculating the wave velocity of an evanescent wave
w2＝klmulm/klm-klj，
In the formula, w1Wave velocity, w, of traffic flow queuing at the entrance at red light of intersection2Wave velocity, k, for successive departure from an intersection of traffic flows queued behind green lights at the intersectionlmIs the saturated traffic density u under the precipitation intensity level llmSaturated traffic flow velocity, k, at precipitation intensity level lljFor blockage at precipitation intensity level lTraffic density;
step 6: the method comprises the steps of traffic state judgment, analyzing and judging traffic flow running states of road intersections, preliminarily judging that the traffic is in an undersaturation state at the moment when the vehicles do not stop or can pass the intersections only by one-time stop and queuing based on a distributed wave model, preliminarily judging that the traffic is in an oversaturation state at the moment when the vehicles stop more than one time in a queuing mode at the intersections, and judging that the traffic is in a critical saturation state when the vehicles can pass the intersections only by one-time queuing and stopping waiting or approaching the stopping state;
and 7: and (4) analyzing the delay time of the road traffic discontinuous flow, wherein t 'is the time when the motor vehicle i passes through the upstream intersection and the downstream intersection between two adjacent intersections'i,tiAfter passing through the upstream intersection, the vehicle i is at speed uiDriving to the tail of the queue of the vehicles, stopping for waiting, and after the green light of the downstream intersection is released, the motor vehicle i at the saturated traffic speed umPassing through the intersection, and controlling the theoretical time t under the condition of the intersection according to the passing no signal of the motor vehiclenAnd the actual time t for the actual vehicle to pass through the downstream intersectioniCalculating the delay time Tdelay。
In the formula, tiIs the actual time, t, of the motor vehicle passing the downstream intersectionnThe method comprises the following steps that (1) theoretical time when a motor vehicle passes through an intersection without signal control is adopted, wherein l is the length of a road section, and d is the width of the intersection in the same direction;
and 8: and constructing an actual road traffic discontinuous flow collecting and dispersing wave model based on the road traffic discontinuous flow delay prediction result of the actual collecting and dispersing wave and by combining intersection traffic signal control parameters, and obtaining corresponding delay time prediction results under different precipitation intensity levels.
The invention has the following beneficial technical effects:
1) according to the method, the urban road traffic flow operation rule and mechanism in rainfall weather are discovered by analyzing the urban road traffic operation data in rainfall weather, excavating weather and traffic corresponding relations in different rainfall intensity levels and constructing a road section traffic flow parameter relation model in rainfall weather.
2) The method integrates the theoretical characteristics of distributed waves, considers the queuing and dissipation conditions of the urban road traffic discontinuous flow at the signal control intersection, combines a signal control scheme, analyzes the delay time composition of the urban road traffic flow, establishes a delay time calculation method and realizes the prediction of the delay time of the urban road traffic discontinuous flow.
3) According to the method and the system, urban traffic planning route delay time prediction, traffic jam time analysis, traffic trip route selection based on delay time prediction and the like in rainfall can be carried out, on one hand, the accuracy and the effectiveness of urban traffic flow delay time prediction in a rainfall scene can be improved, and on the other hand, the urban traffic trip efficiency and the road resource utilization rate can be improved.
Drawings
The invention is further illustrated by the following figures and examples:
FIG. 1 is a flow chart of a rainfall weather urban road intermittent traffic flow delay time prediction.
FIG. 2 is a schematic view of a road vehicle detector arrangement.
FIG. 3 is a traffic flow collecting and distributing wave model of a signal control intersection.
Fig. 4 is a schematic view of undersaturated traffic conditions.
Fig. 5 is an illustration of an over-saturated traffic condition.
Detailed Description
The following detailed description is made on the technical scheme adopted by the invention content part with reference to the accompanying drawings, and the main steps are as follows:
step 1: and (4) screening and preprocessing meteorological data and traffic flow data. And analyzing the level of rainfall intensity based on meteorological data, detecting to obtain traffic flow data based on a vehicle detector, and sorting to obtain basic road traffic operation data such as traffic flow, speed, occupancy and the like. The rainfall level was performed according to the relevant standards of the national weather service, as shown in table 1, and the road vehicle detector settings are shown in fig. 2.
TABLE 1 precipitation Strength Scale division Standard
Step 2: according to the precipitation intensity grade division standard, the corresponding relation between meteorological data and traffic data under different grades is established, a road traffic flow data mapping environment under the rainfall scene is established, and the basic data relation is expressed as follows.
In the formula (I), the compound is shown in the specification,
and
weather data and traffic data, r, respectively, at a rainfall intensity level llower,rupperThe upper limit and the lower limit of the precipitation are respectively, and the q and the u are respectively the traffic flow and the traffic speed.
And step 3: and aiming at different precipitation intensity levels, relevant meteorological data and traffic data are fused, corresponding traffic flow relation equations are respectively established, a road section traffic flow parameter relation model under precipitation conditions is established, and a basic mathematical expression is shown as the following formula.
Fi＝fi(l,q,u)
Where l represents the precipitation intensity level, q represents the traffic flow at that time, and u represents the link average traffic flow velocity.
And 4, step 4: constructing a basic model of traffic flow collecting and dispersing waves of the signal control intersection, analyzing the operation rules of the collecting waves and the dispersing waves of the traffic flow of the signal control intersection under different rainfall intensity levels, respectively obtaining corresponding wave speed parameters of the collecting and dispersing waves and the like, and forming the basic model of the traffic flow collecting and dispersing waves of the intersection under the rainfall condition based on a collecting and dispersing wave theory, wherein the basic model is shown in figure 3.
In the figure, w1The wave velocity of the traffic flow queuing at the inlet when the intersection is red is shown, namely the aggregation wave velocity; w is a2And the wave speed of the traffic flow queued after the green light of the intersection, namely the dissipation wave speed, is shown. The mathematical expression is as follows.
In the formula, q1And q is2Representing upstream and downstream traffic flow, respectively, k1And k2Representing upstream and downstream traffic flow density, u, respectively2And u1Representing the average speed of the upstream and downstream traffic flow, respectively.
And 5: and calculating the wave speed w of the traffic flow collective dispersed wave. Wherein the wave velocity w of the aggregate wave1＝q1u1/(q1-u1klm) Wave velocity w of the evanescent wave2＝klmulm/klm-klj. In the two formulae, q1、u1Respectively the detected road section traffic flow and the road section vehicle average speed, klmIs the saturated traffic density u under the precipitation intensity level llmSaturated traffic flow velocity, k, at precipitation intensity level lljThe traffic density is the traffic density of the blockage under the precipitation intensity level l.
Step 6: and (5) judging the traffic state. Analyzing and judging the traffic flow running state of the road intersection, based on the distributed wave model, taking the number of times of the vehicles passing through the intersection as a reference, and preliminarily judging that the traffic is in an undersaturation state at the moment when the vehicles do not stop or can pass through the intersection only by one-time stopping and queuing, as shown in figure 4; when the number of times of waiting in line at the intersection exceeds one, it is preliminarily determined that the traffic is in a state of being saturated at that time, as shown in fig. 5. Particularly, when vehicles need to wait in line or approach to a parking state to pass through the intersection, the traffic is in a critical saturation state.
And 7: and analyzing delay time of road traffic discontinuous flow. Taking two adjacent intersections as an example, the time when the motor vehicle i passes through the upstream intersection and the downstream intersection is t'i,tiBy passingVehicle i following the upstream intersection at speed uiDriving to the tail D point of the queue of the vehicles in line, stopping for waiting, after the green light of the downstream intersection is released, the evanescent wave is propagated to the point C, and then the motor vehicle i is at the saturated traffic speed umAnd (4) passing through the intersection. From both figures, it can be derived that if there is no control signal at the downstream junction, the theoretical time for the vehicle i to pass the downstream junction should be tnAnd the actual transit time is tiSo that a delay time T can be obtaineddelay. And calculating the delay time of the road traffic discontinuous flow. Under undersaturation conditions, the delay time for theoretically stopping and waiting of the motor vehicle generally does not exceed the red light time of the downstream intersection, as shown by T in FIG. 4delay<tred(ii) a Similarly, in the over-saturation state, the delay time of the vehicle stopping waiting exceeds the red light time of the downstream intersection, as shown by T in FIG. 5delay＞tred。
Wherein the time T is delayeddelay：
In the formula, tiIs the actual time, t, of the motor vehicle passing the downstream intersectionnThe method is characterized in that the theoretical time when a motor vehicle passes through the intersection without signal control is represented by l, the length of a road section and d, the width of the intersection in the same direction is represented by d.
And 8: and constructing an actual road traffic discontinuous flow collecting and dispersing wave model based on the road traffic discontinuous flow delay prediction result of the actual collecting and dispersing wave and by combining intersection traffic signal control parameters, and obtaining corresponding delay time prediction results under different precipitation intensity levels.
Claims (1)
1. A method for predicting the delay time of intermittent traffic flow of urban roads in rainfall weather is characterized by comprising the following steps:
step 1: screening and preprocessing meteorological data and traffic flow data, analyzing precipitation intensity levels based on the meteorological data, detecting by a vehicle detector to obtain traffic flow data, and sorting the acquired basic road traffic operation data such as traffic flow, speed, occupancy and the like;
step 2: according to the precipitation intensity grade division standard, establishing corresponding relations between meteorological data and traffic data under different grades, and establishing a road traffic flow data mapping environment under the rainfall scene, wherein the basic data relation is expressed as follows:
in the formula (I), the compound is shown in the specification,
and
weather data and traffic data, r, respectively, at a rainfall intensity level llower,rupperThe upper limit and the lower limit of the precipitation are respectively, and the q and the u are respectively the traffic flow and the traffic speed;
and step 3: aiming at different precipitation intensity levels, relevant meteorological data and traffic data are fused, corresponding traffic flow relation equations are respectively established, and a road section traffic flow parameter relation model under precipitation conditions is established
Fi＝fi(l,q,u)
Wherein l represents the precipitation intensity level, q represents the traffic flow at the moment, and u represents the average traffic flow speed of the road section;
and 4, step 4: constructing a basic model of traffic flow collecting and dispersing waves of the signal control intersection, analyzing the operation rules of the collecting waves and the dispersing waves of the traffic flow of the signal control intersection under different rainfall intensity levels, respectively obtaining corresponding wave speed parameters of the collecting and dispersing waves and the like, and forming the basic model of the traffic flow collecting and dispersing waves of the intersection under the rainfall condition based on the collecting and dispersing wave theory into
Wherein w is the wave velocity of the scattered wave of the traffic flow and q1And q is2Representing upstream and downstream traffic flow, respectively, k1And k2Representing upstream and downstream traffic flow density, u, respectively2And u1Representing the average speeds of the upstream and downstream traffic flows respectively;
and 5: calculating the wave velocity w of the traffic flow set
Calculating the wave velocity of the aggregate wave
w1＝q1u1/(q1-u1klm)，
Calculating the wave velocity of an evanescent wave
w2＝klmulm/klm-klj，
In the formula, w1Wave velocity, w, of traffic flow queuing at the entrance at red light of intersection2Wave velocity, k, for successive departure from an intersection of traffic flows queued behind green lights at the intersectionlmIs the saturated traffic density u under the precipitation intensity level llmSaturated traffic flow velocity, k, at precipitation intensity level lljThe traffic density is the traffic jam density under the precipitation intensity level l;
step 6: the method comprises the steps of traffic state judgment, analyzing and judging traffic flow running states of road intersections, preliminarily judging that the traffic is in an undersaturation state at the moment when the vehicles do not stop or can pass the intersections only by one-time stop and queuing based on a distributed wave model, preliminarily judging that the traffic is in an oversaturation state at the moment when the vehicles stop more than one time in a queuing mode at the intersections, and judging that the traffic is in a critical saturation state when the vehicles can pass the intersections only by one-time queuing and stopping waiting or approaching the stopping state;
and 7: and (4) analyzing the delay time of the road traffic discontinuous flow, wherein t 'is the time when the motor vehicle i passes through the upstream intersection and the downstream intersection between two adjacent intersections'i,tiAfter passing through the upstream intersection, the vehicle i is at speed uiDriving to the tail of the queue of the vehicles, stopping for waiting, and after the green light of the downstream intersection is released, the motor vehicle i at the saturated traffic speed umPassing through the intersection, and controlling the theoretical time t under the condition of the intersection according to the passing no signal of the motor vehiclenAnd the actual time t for the actual vehicle to pass through the downstream intersectioniCalculating the delayTime of error Tdelay；
In the formula, tiIs the actual time, t, of the motor vehicle passing the downstream intersectionnThe method comprises the following steps that (1) theoretical time when a motor vehicle passes through an intersection without signal control is adopted, wherein l is the length of a road section, and d is the width of the intersection in the same direction;
and 8: and constructing an actual road traffic discontinuous flow collecting and dispersing wave model based on the road traffic discontinuous flow delay prediction result of the actual collecting and dispersing wave and by combining intersection traffic signal control parameters, and obtaining corresponding delay time prediction results under different precipitation intensity levels.
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| CN111681429B (en) * | 2020-06-08 | 2021-05-18 | 浙江警察学院 | Method and system for identifying fragile road section in severe weather based on GPS data |
| CN112258856B (en) * | 2020-08-10 | 2022-01-18 | 北方工业大学 | Method for establishing regional traffic signal data drive control model |
| CN112164239B (en) * | 2020-10-27 | 2024-02-13 | 重庆市市政设计研究院有限公司 | RFID-based traffic signal lamp abnormal state identification and early warning system |
| CN114241751B (en) * | 2021-11-30 | 2022-12-27 | 东南大学 | Multi-entrance dynamic and static traffic coordination optimization method for large parking lot |
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| CN103093611A (en) * | 2011-10-27 | 2013-05-08 | 株式会社电装 | Congestion prediction unit and congestion prediction system |
| CN106448171A (en) * | 2016-11-25 | 2017-02-22 | 北京掌行通信息技术有限公司 | Ponding road prediction method and device |
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| CN103680150B (en) * | 2013-12-02 | 2015-10-28 | 同济大学 | Based on traffic events coverage and the duration defining method of Coil Detector |
| CN103680157B (en) * | 2014-01-06 | 2015-09-16 | 东南大学 | A kind of vehicle queue's overflow pre-judging method towards city bottleneck road |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN106448171A (en) * | 2016-11-25 | 2017-02-22 | 北京掌行通信息技术有限公司 | Ponding road prediction method and device |
Non-Patent Citations (1)
| Title |
|---|
| A time-series analysis of motorway collisions in England considering;Paraskevi Michalaki；Mohammed Quddus;《Journal of Transport & Health》;20160211;全文 * |
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