CN111477002B - Highway confluence district traffic conflict early warning system based on danger degree is differentiateed - Google Patents
Highway confluence district traffic conflict early warning system based on danger degree is differentiateed Download PDFInfo
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Abstract
The invention relates to a highway confluence area traffic conflict early warning system based on danger degree judgment, which comprises an information acquisition module, an information processing module and an information publishing module, wherein the information acquisition module is used for acquiring and storing basic traffic parameter information of vehicles with traffic conflicts in a highway confluence area and sending the basic traffic parameter information to the information processing module, the information processing module is used for performing kinematic modeling processing and calculating and extracting traffic conflict characterization quantity based on the basic traffic parameter information of the vehicles in the highway confluence area and performing danger degree evaluation on the traffic conflicts, and the information publishing module is used for publishing different traffic early warning information according to danger degree evaluation results obtained by the information processing module. The invention not only can facilitate the vehicle owners passing through the confluence area to know the danger degree of the traffic conflict in the confluence area, but also can facilitate the traffic managers to collect and research the traffic conflict occurrence rule in the confluence area. The mathematical calculation related by the invention is more convenient, easy to operate, high in reliability and strong in pertinence.
Description
Technical Field
The invention belongs to the technical field of early warning of highway confluence areas, and particularly relates to a traffic conflict early warning system for a highway confluence area based on danger degree judgment.
Background
The main factors determining the severity of the traffic conflict include a conflict speed, a conflict angle, a conflict distance, and the like, and generally, the smaller the distance between two vehicles in which a traffic conflict exists, the greater the relative speed, the greater the conflict angle, and the more severe the conflict.
The existing traffic conflict judging methods include a distance judging method, a time judging method, an energy judging method and the like, but the methods have certain defects, for example, the distance judging method only takes the distance as a judging factor, and when the conflict distance between two parties is small but the relative speed is also small, the traffic conflict at the moment is not necessarily serious; the time discrimination method only takes time as a discrimination factor, although the time discrimination method is superior to the distance discrimination method, when short time and low speed exist at the same time, the traffic conflict at the time is not necessarily serious; the energy discrimination method has more obvious disadvantages in practical application, for example, the discrimination standard is difficult to unify, the energy is also related to specific vehicle types, vehicle weights, motor vehicles, non-motor vehicles, pedestrians and the like during calculation, and if the collision severity is to be accurately calculated based on the energy, great difficulty exists.
Disclosure of Invention
In order to overcome the defects, the invention aims to design a highway confluence area traffic conflict early warning system based on risk degree judgment so as to improve the accuracy and effectiveness of traffic conflict prediction of a highway confluence area.
In order to solve the above problem, the technical scheme provided by the patent comprises:
a highway confluence area traffic conflict early warning system based on danger degree discrimination is characterized by comprising:
the system comprises an information acquisition module, an information processing module and an information publishing module;
the information acquisition module is used for acquiring and storing the expresswayBasic traffic parameter information of vehicles with traffic conflicts in the road confluence area is sent to the information processing module, and the information acquisition module classifies the basic traffic parameter information of the vehicles with traffic conflicts in the highway confluence area when acquiring and storing the basic traffic parameter information; the classification comprises basic traffic parameter information of vehicles on the outermost lanes of a main road of the highway confluence area and basic traffic parameter information of vehicles on the ramps of the highway confluence area, and a pair of vehicles with traffic conflicts is marked as a conflict vehicle pair; each conflict vehicle pair comprises and only comprises one vehicle on the outermost lane of the main road of the highway confluence area and one vehicle on the ramp lane of the highway confluence area; the basic traffic parameter information of the vehicle pair with traffic conflict in the highway confluence area comprises that the distance from the head of the vehicle to the outermost lane of the main road of the highway confluence area to a conflict point is xiThe distance from the head of the vehicle to the bump point of the vehicle on the outermost lane of the main road of the highway confluence area is xiAt a velocity of viThe distance from the head of the vehicle to the bump point of the vehicle on the outermost lane of the main road of the highway confluence area is xiAt a velocity of ai(ii) a And the distance from the head of the vehicle to the conflict point of the ramp lane of the highway confluence zone is xjThe distance from the head of the vehicle to the conflict point of the ramp lane of the highway confluence zone is xjAt a velocity of vjThe distance from the head of the vehicle to the conflict point of the ramp lane of the highway confluence zone is xjAt a velocity of aj；i,j∈N+；
The information processing module firstly carries out kinematic modeling according to basic traffic parameter information of the vehicle pairs with traffic conflicts, which is acquired by the information acquisition module, then calculates and extracts traffic conflict characterization quantity normalization processing, then establishes a risk degree evaluation function model for risk degree evaluation, and finally sends a processed risk degree evaluation result to the information release module; when the information processing module carries out the kinematic modeling, the kinematic model adopted by the vehicle at the outermost lane of the main road of the highway merging area is a uniform deceleration motion model, and the ramp of the highway merging area is subjected to the kinematic modelingThe kinematic model adopted by the lane vehicle is a uniform acceleration motion model; the traffic conflict characteristic quantity comprises two components: conflict time and conflict angle; the conflict time is the time difference between two vehicles with traffic conflict and reaching the conflict point and is recorded as delta t; the collision angle is a speed included angle formed by two vehicles with traffic collision reaching a conflict point and is marked as alpha; the information processing module is used for carrying out normalization processing on the traffic conflict characterization quantity, namely, the factors with different dimensions are converted into dimensionless factors, and the values are all [0.1]]The indexes comprise a traffic conflict time normalization index and a traffic conflict angle normalization index, wherein the traffic conflict time normalization index is as follows:
said t is0The normal passing time of the vehicle in the confluence area is a constant, and the value range is set as follows: t is t0≥max(ti,tj) (ii) a The traffic conflict angle normalization index is as follows: y is 1-cos α,
the information processing module establishes the risk evaluation function model, which is a traffic conflict risk evaluation function established by taking the traffic conflict time normalization index and the traffic conflict angle normalization index as independent variables and taking the traffic conflict risk as a dependent variable, wherein the mathematical expression of the risk evaluation function model is G (X + m) Y, and the mathematical expression of the risk evaluation function model is as follows: giEvaluating a function value for the traffic conflict risk degree, wherein the value range is [0, 1%]M is a complex factor, X and Y are respectively a traffic conflict time normalization index and a traffic conflict angle normalization index; the information processing module carries out the risk degree grade division, namely carrying out [0,1] on the risk degree evaluation function value]Equally dividing the space into four equal parts, and then sequentially arranging the equal parts from small to large to carry out grade division; the information processing module sends the danger level classification result obtained by processing to the information publishing module;
the information issuing module performs different early warnings according to different danger grade division results received from the information processing module, and issues corresponding early warning information according to different grades.
Compared with the prior art, the invention has the beneficial effects that:
1. the invention firstly proposes that a normalization method is used for processing the traffic conflict characterization parameters, and a mathematical model is established through normalization indexes so as to facilitate subsequent data processing. The parameters with dimensions are converted into parameters without dimensions by a normalization method, and the variation trend of the normalized parameters is consistent with that of the original parameters which are not subjected to normalization processing, so that the processing converts the quantity which cannot be directly operated in two different units of conflict time and conflict angle into the quantity which can be directly operated in no unit, and a complex expression is introduced, and further comparative analysis is conveniently performed from the angle of complex representation (coordinate representation).
2. The invention firstly proposes to link the early warning grade of the traffic conflict with the danger degree of the traffic conflict point, and takes the danger degree of the traffic conflict point as the basis for dividing the early warning grade of the traffic, thereby improving the accuracy and the reliability of the classification of the traffic early warning, and the calculation process is simple and clear, is easy to operate and has excellent feasibility of implementation.
Drawings
FIG. 1 is a block diagram of the system of the present invention;
FIG. 2 is a diagram illustrating calculation of traffic collision risk model parameters according to the present invention.
Detailed description of the preferred embodiments
For the purpose of facilitating understanding, the following description is made in conjunction with the accompanying drawings:
the invention designs a highway confluence area traffic conflict early warning system based on danger degree discrimination, which is divided into three modules as shown in figure 1: the system comprises an information acquisition module, an information processing module and an information publishing module.
In specific implementation, the information acquisition module is used for acquiring and storing basic traffic parameter information of vehicles with traffic conflicts in the highway confluence area and sending the basic traffic parameter information to the information processing module, and the information acquisition module classifies the basic traffic parameter information of the vehicles with traffic conflicts in the highway confluence area when acquiring and storing the basic traffic parameter information;
the classification comprises basic traffic parameter information of vehicles on the outermost lanes of a main road of the highway confluence area and basic traffic parameter information of vehicles on the ramps of the highway confluence area, and a pair of vehicles with traffic conflicts is marked as a conflict vehicle pair;
each conflict vehicle pair comprises and only comprises one vehicle on the outermost lane of the main road of the highway confluence area and one vehicle on the ramp lane of the highway confluence area;
the basic traffic parameter information of the vehicle pairs with traffic conflicts in the highway confluence area comprises that the distance from the head of the vehicle to the outermost lane of the main road of the highway confluence area to the conflict point is xiThe distance from the head of the vehicle to the bump point of the vehicle on the outermost lane of the main road of the highway confluence area is xiAt a velocity of viThe distance from the head of the vehicle to the bump point of the vehicle on the outermost lane of the main road of the highway confluence area is xiAt a velocity of ai(ii) a And the distance from the head of the vehicle to the conflict point of the ramp lane of the highway confluence zone is xjThe distance from the head of the vehicle to the conflict point of the ramp lane of the highway confluence zone is xjAt a velocity of vjThe distance from the head of the vehicle to the conflict point of the ramp lane of the highway confluence zone is xjAt a velocity of aj；i,j∈N+。
The information processing module firstly carries out kinematic modeling according to basic traffic parameter information of a vehicle pair with traffic conflict, which is acquired by the information acquisition module, then calculates and extracts traffic conflict characterization quantity normalization processing, then establishes a risk degree evaluation function model for risk degree evaluation, and finally sends a risk degree evaluation result obtained by processing to the information publishing module;
when the information processing module carries out kinematic modeling, a kinematic model adopted by vehicles on an outermost lane of a main road of a highway confluence area is a uniform deceleration motion model, and a kinematic model adopted by vehicles on a ramp lane of the highway confluence area is a uniform acceleration motion model;
the traffic conflict feature quantity includes two: conflict time and conflict angle;
the collision time is the time difference between two vehicles with traffic collision and reaching the conflict point, and is recorded as delta t, the smaller the delta t is, the less the vehicle risk avoiding time is, the higher the risk degree of the collision is;
the collision angle is a speed included angle at which two vehicles with traffic collision reach a conflict point, and is recorded as alpha, the larger the alpha is, the larger the threat to the vehicles when the vehicle collision occurs is, and the higher the danger degree of the collision is;
the specific calculation method is as follows:
here, before calculating the collision time and the collision angle, the merging area is simplified and the related physical quantity is calibrated, and a simplified diagram of the merging area is shown in fig. 2.
First, two vehicles with traffic collision in the confluence area are respectively set as a vehicle a and a vehicle B. The method comprises the steps of setting a vehicle A to run on a main road, wherein the movement of the vehicle A from the position in the figure to the position of the conflict point is uniform deceleration movement, setting a vehicle B to run on a ramp, and setting the movement of the vehicle B from the position in the figure to the position of the conflict point to be uniform acceleration movement.
Recording: the distance between the head of the vehicle A and the conflict point is x1The distance between the head of the vehicle A and the conflict point is x1At a velocity of v1The distance between the head of the vehicle A and the conflict point is x1At an acceleration of a1. Recording: the distance between the head of the vehicle B and the conflict point is x2The distance between the head of the vehicle B and the conflict point is x2At a velocity of v2The distance between the head of the vehicle B and the conflict point is x2At an acceleration of a2. From the kinematic equation:
and (4) vehicle alignment A:
and (4) vehicle B:
solving t reversely by the above two equations1、t2It is possible to obtain:
therefore, the time difference between the arrival of the vehicles at the conflict point in the traffic conflict is:
Δt＝|t1-t2| (5)
the collision angle α is calculated as follows:
as shown in fig. 2, the collision angle is calculated by the speed angle between the colliding vehicles:
α＝|α1-α2| (6)
where α is the conflict angle;
α1-the speed angle of the front vehicle a at which there is a traffic conflict;
α2the speed angle of the front vehicle B at which there is a traffic conflict.
The information processing module carries out normalization processing on the traffic conflict representation quantity, which means that factors with different dimensions are converted into dimensionless indexes with values of [0.1],
the specific operation of normalizing the two conflict characterization factors of conflict time and conflict angle is as follows:
normalization processing of conflict time:
in terms of the collision time, the collision danger degree increases along with the reduction of the collision time, and the normal passing time of the vehicle in the confluence area is recorded as t0Is a constant, and the value range is set as:
t0≥max(t1,t2)， (7)
therefore, the normalization index X for determining the risk by the collision time is set as:
the smaller the above-mentioned index satisfies the collision time, the larger the index value is, and the higher the collision risk degree is.
The normalization process for the collision angle is as follows:
in the collision angle, since the collision risk increases as the collision angle α increases, the normalization index Y of the collision angle determination risk is set to:
Y＝1-cosα (9)
the above-mentioned indexes also satisfy that the larger the collision angle is, the larger the index value is, and the higher the collision risk degree is.
The risk degree evaluation in the information processing module is to calculate the risk degree of the traffic conflict by using a traffic conflict risk degree model, and can reflect the potential risk of the traffic conflict, wherein the potential risk refers to the possible damage caused when the traffic conflict develops into a traffic accident. The traffic conflict risk degree model is expressed through a risk degree evaluation function, and when the risk degree evaluation function is established, the traffic conflict risk degree model is established by taking a traffic conflict time normalization index and a traffic conflict angle normalization index as independent variables and taking the traffic conflict risk degree as a dependent variable. The mathematical expression of the risk assessment function is:
G＝X+m*Y (10)
wherein: giEvaluating a function for the traffic conflict risk;
m is a complex factor;
and X and Y are respectively a traffic conflict time normalization index and a traffic conflict angle normalization index.
The expressway confluence area traffic conflict grading early warning method based on traffic conflict point danger degree judgment is characterized in that the specific operation of grading and dividing the danger degree is as follows: before the conversion corresponding operation between the traffic conflict risk degree and the traffic conflict early warning level is carried out, the conversion corresponding operation of two normalization indexes and the risk degree is carried out, the specific operation is set to carry out the quartering on the values of two index functions with the range from 0 to 1, then the definition of the risk degree is carried out on each halved range, and the definition is explained in a table form. The details are shown in the following table.
The information processing module carries out risk degree grade division, namely carrying out equipartition between [0 and 1] on the risk degree evaluation function value, dividing the equipartition into four equal parts, then carrying out grade division from small to large in sequence, and dividing the risk degree evaluation function value into four grades of very dangerous, relatively dangerous, general dangerous and slight dangerous;
the information processing module sends the danger level division result obtained by processing to the information publishing module;
the information issuing module carries out different early warnings according to different danger grade division results received from the information processing module, and the method specifically comprises the following steps:
if the information processing module receives 'very dangerous' information sent by the information processing module, red characters are used for issuing early warning information, vehicles in the confluence area are reminded to increase the distance between vehicles and ask a vehicle owner to brake and decelerate, a manager is reminded to take corresponding vehicle control measures in the confluence area, and if necessary, the vehicles are divided into lanes to pass through the confluence area;
if the information processing module receives 'dangerous' information sent by the information processing module, orange words are used for early warning to remind a vehicle in the confluence area of pulling out the inter-vehicle distance and asking a vehicle owner to obviously slow down the vehicle speed, a manager is reminded of taking corresponding control measures of the vehicle in the confluence area, and the traffic flow passing in unit time is limited if necessary;
if the general danger information sent by the information processing module is received, early warning is carried out by using yellow characters, vehicles in the confluence area are reminded to keep the distance between vehicles and ask the vehicle owner to slow down, a manager is reminded to take corresponding vehicle control measures in the confluence area, and the vehicles pass through the confluence area in different time periods if necessary;
if the information processing module receives 'slight danger' information sent by the information processing module, the blue characters are used for early warning to remind the vehicles in the merging area to keep the distance between the vehicles and carefully and slowly move.
It should be noted that the above embodiments are only used for reference in specific implementation, and there are also places that can be extended, such as the method for calculating the conflict time and other methods, but it should be clear that the core content of the method described in this patent is still the protection object of this patent.
Claims (1)
1. A highway confluence area traffic conflict early warning system based on danger degree discrimination is characterized by comprising:
the system comprises an information acquisition module, an information processing module and an information publishing module;
the information acquisition module is used for acquiring and storing basic traffic parameter information of vehicles with traffic conflicts in the highway confluence area and sending the basic traffic parameter information to the information processing module, and the information acquisition module classifies the basic traffic parameter information of the vehicles with traffic conflicts in the highway confluence area when acquiring and storing the basic traffic parameter information; the classification comprises basic traffic parameter information of vehicles on the outermost lanes of a main road of the highway confluence area and basic traffic parameter information of vehicles on the ramps of the highway confluence area, and a pair of vehicles with traffic conflicts is marked as a conflict vehicle pair; each conflict vehicle pair comprises and only comprises one vehicle on the outermost lane of the main road of the highway confluence area and one vehicle on the ramp lane of the highway confluence area; the basic traffic parameter information of the vehicle pair with traffic conflict in the highway confluence area comprises that the distance from the head of the vehicle to the outermost lane of the main road of the highway confluence area to a conflict point is xiThe distance from the head of the vehicle to the bump point of the vehicle on the outermost lane of the main road of the highway confluence area is xiAt a velocity of viThe distance from the head of the vehicle to the bump point of the vehicle on the outermost lane of the main road of the highway confluence area is xiAt a velocity of ai(ii) a And the distance from the head of the vehicle to the conflict point of the ramp lane of the highway confluence zone is xjThe distance from the head of the vehicle to the conflict point of the ramp lane of the highway confluence zone is xjVelocity of (2)Size vjThe distance from the head of the vehicle to the conflict point of the ramp lane of the highway confluence zone is xjAt a velocity of aj；i,j∈N+；
The information processing module firstly carries out kinematic modeling according to basic traffic parameter information of the vehicle pairs with traffic conflicts, which is acquired by the information acquisition module, then calculates and extracts traffic conflict characteristic quantity normalization processing, then establishes a risk degree evaluation function model for risk degree evaluation, and finally sends a risk degree evaluation result obtained by processing to the information release module; when the information processing module carries out the kinematic modeling, a kinematic model adopted by vehicles on an outermost lane of a main road of a highway confluence area is a uniform deceleration motion model, and a kinematic model adopted by vehicles on a ramp lane of the highway confluence area is a uniform acceleration motion model; the traffic conflict characteristic quantity comprises two components: conflict time and conflict angle; the conflict time is the time difference between two vehicles with traffic conflict and reaching the conflict point and is recorded as delta t; the collision angle is a speed included angle formed by two vehicles with traffic collision reaching a conflict point and is marked as alpha; the information processing module is used for carrying out normalization processing on the traffic conflict characteristic quantity, namely, the factors with different dimensions are converted into dimensionless factors, and the values are all [0.1]]The indexes comprise a traffic conflict time normalization index and a traffic conflict angle normalization index, wherein the traffic conflict time normalization index is as follows:
said t is0The normal passing time of the vehicle in the confluence area is a constant, and the value range is set as follows: t is t0≥max(ti,tj) (ii) a The traffic conflict angle normalization index is as follows: y is 1-cos α,
the information processing module establishes the risk assessment function model by taking a traffic conflict time normalization index and a traffic conflict angle normalization index as independent variablesAnd a traffic conflict risk assessment function established by taking the traffic conflict risk as a dependent variable, wherein the mathematical expression of the risk assessment function model is G ═ X + m ×, Y, and the mathematical expression comprises: g is a traffic conflict risk assessment function value with a value range of [0, 1%]M is a complex factor, X and Y are respectively a traffic conflict time normalization index and a traffic conflict angle normalization index; the information processing module carries out the risk degree grade division, namely carrying out [0,1] on the risk degree evaluation function value]Equally dividing the space into four equal parts, and then sequentially arranging the equal parts from small to large to carry out grade division; the information processing module sends the danger level classification result obtained by processing to the information publishing module;
the information issuing module performs different early warnings according to different danger grade division results received from the information processing module, and issues corresponding early warning information according to different grades.
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| US20020154032A1 (en) * | 1996-12-03 | 2002-10-24 | Inductive Signature Technologies, Inc. | Automotive vehicle classification and identification by inductive signature |
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| CN109377785A (en) * | 2018-10-22 | 2019-02-22 | 北京航空航天大学 | A kind of highway merging area vehicle collision method for early warning based on deep learning |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| JPH07320188A (en) * | 1994-05-25 | 1995-12-08 | Mazda Motor Corp | Method and device for estimating yaw rate of vehicle |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| US20020154032A1 (en) * | 1996-12-03 | 2002-10-24 | Inductive Signature Technologies, Inc. | Automotive vehicle classification and identification by inductive signature |
| CN102314769A (en) * | 2010-07-07 | 2012-01-11 | 交通运输部公路科学研究所 | Intelligent safety early-warning control method for merging area of entrance ramp of expressway |
| CN104464317A (en) * | 2014-12-03 | 2015-03-25 | 武汉理工大学 | Expressway entrance ring road converging zone guiding control system and method |
| CN106530717A (en) * | 2016-12-26 | 2017-03-22 | 长安大学 | Construction road section risk evaluating method based on cloud model |
| CN108986492A (en) * | 2018-07-27 | 2018-12-11 | 东南大学 | A kind of fast road ramp wagon flow remittance bootstrap technique and system based on roadside device |
| CN109377785A (en) * | 2018-10-22 | 2019-02-22 | 北京航空航天大学 | A kind of highway merging area vehicle collision method for early warning based on deep learning |
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