A method for identifying risk areas of highways based on static road risk field theory

Abstract

The present invention relates to a highway risk area identification method based on road static risk field theory, comprising the following steps: 1) determining the structure type, guardrail type and road section type of the highway risk area to be identified; 2) determining the structure field source risk quantity Q gzw , guardrail source risk quantity Q lc And the road section source risk quantity Q lx ; 3) Calculate the static risk field strength of the structure #imgabs0# roadside static risk field strength #imgabs1# and the linear static risk field strength E v '; 4) Based on the linear static risk field strength #imgabs2#, the structure static risk field strength #imgabs3# and the roadside static risk field strength #imgabs4#, the static risk field comprehensive field strength #imgabs5# is calculated. 5) Based on the static risk field comprehensive field strength E cp , get the average risk field strength #imgabs6# and based on the average risk field strength E avg , determine the evaluation level of the risk area of ​​the highway to be identified. This method has good applicability and effectiveness when applied to risk area identification.

Description

Technical Field

[0001] The present invention belongs to the technical field of road traffic safety, and relates to a method for distinguishing risk areas of expressways, and in particular to a method for distinguishing risk areas of expressways based on road static risk field theory. Background Art

[0002] The operation of road vehicles is composed of a series of movements of vehicles in the traffic flow on the road. This movement brings about the randomness of the traffic flow. This randomness is formed by the combined influence of people, vehicles, roads, and the environment. The poor state of any factor may lead to the loss of control of vehicle movement and thus create road driving risks, which further affects the safe operation of the entire road traffic system. The process of road risk generation is the effect of the road and environment on the driver and the vehicle, plus the combined effect of the randomness of the driver's subjective driving and the objectivity of the vehicle's own attributes, which makes vehicle driving produce unpredictable dangers.

[0003] Risk field is an extension of physical field theory. Its essence is to extend the properties of physical field to the field of risk research and measure the state of field by the fluctuation of risk quantity. Based on the basic idea of ​​potential field theory, various factors and research processes considered in the process of road risk research are introduced, and the research of potential field theory in road risk is gradually deepening.

[0004] Although there is a certain foundation for the research on potential field theory in the field of transportation, it is mostly applied to microscopic vehicle interaction scenarios in engineering practice, and the research on potential field theory involving road factors is not in-depth. How to construct a road risk field from the perspective of road intrinsic safety is the core issue that the current research needs to solve. Introducing potential field theory in road risk assessment can intuitively depict the essence of risk effects and reveal the mechanism of risk generation, which is of great significance to road safety research.

[0005] Based on the above-mentioned defects of the prior art, there is an urgent need to study a highway risk area identification method based on road static risk field theory. Summary of the invention

[0006] The purpose of the present invention is to quantify the road risk area in the highway design stage and to propose a method for distinguishing the risk area of ​​highways based on the static road risk field theory. The method combines the influence of three road elements, namely road structure, line shape and roadside facilities on driving safety, calibrates the risk amount based on statistical data such as accident rate and accident severity, and establishes a theoretical model of static comprehensive road risk field, thereby proposing a method for distinguishing risk areas and better evaluating the driving risk of roads.

[0007] In order to achieve the above object, the present invention provides the following technical solutions:

[0008] A method for identifying risk areas of expressways based on static road risk field theory, characterized in that it comprises the following steps:

[0009] 1) Determine the structure type, guardrail type and road section type of the risk area of ​​the highway to be identified;

[0010] 2) Determine the structure source risk Q based on the structure type gzw , determine the guardrail source risk quantity Q based on the guardrail type lc And determine the road section source risk quantity Q based on the road section type lx ;

[0011] 3) Based on the structure source risk Q gzw Calculate static risk field strength of structures Based on the guardrail source risk quantity Q lc Calculate the static risk field strength on the roadside Based on the road section field source risk quantity Q lx Calculate the linear static risk field strength E′ v ;

[0012] 4) Based on the linear static risk field strength Static risk field strength of structures and roadside static risk field strength Calculate the static risk field comprehensive field strength of the highway risk area to be identified

[0013] 5) Based on the comprehensive field strength E of the static risk field cp , and the average risk field strength is obtained Based on the average risk field strength E avg , determine the evaluation level of the risk area of ​​the highway to be identified.

[0014] Preferably, the structure types include general road sections, tunnels, interchanges and bridges; the guardrail types include flexible guardrails, semi-rigid guardrails and rigid guardrails; the road section types include straight line-small longitudinal slope section, straight line-large uphill section, straight line-large downhill section, small radius curve-small longitudinal slope section, small radius curve-large uphill section, small radius curve-large downhill section, large radius curve-small longitudinal slope section, large radius curve-large uphill section and large radius curve-large downhill section.

[0015] Preferably, before step 1), the method further includes: counting the length L of each structure, the annual traffic volume V, the annual number of traffic accidents N, the number of casualties λ in each guardrail, and predicting the running speed v of passenger cars.

[0016] Preferably, in step 2), the structure source risk quantity Q is determined based on the structure type. gzw Specifically:

[0017] (1) Based on the annual number of traffic accidents N, annual traffic volume V and the length of the structure L, use the formula Calculate the accident rate R per million vehicles per kilometer in one year c , the unit is times / (million vehicles·km);

[0018] (2) Based on the accident rate R per million vehicles per kilometer in one year c Calculate the risk of structural sources in is the accident rate per million vehicle kilometers on general roads in one year, R ci is the accident rate per million vehicle-kilometers in one year for the type of structure to which the risk area of ​​the highway to be identified belongs.

[0019] Preferably, in step 2), the guardrail source risk quantity Q is determined based on the guardrail type. lc Specifically:

[0020] (1) Calculate the severity of the accident based on the number of casualties λ in the guardrail and the number of traffic accidents N throughout the year.

[0021] (2) Based on the severity of the accident N lc Calculate the risk of guardrail source Where N lci is the accident severity of the guardrail type to which the risk area of ​​the highway to be identified belongs, is the accident severity of the flexible guardrail.

[0022] Preferably, in step 2), the road section source risk quantity Q is determined based on the road section type. lx Specifically:

[0023] (1) Based on the annual number of traffic accidents N, annual traffic volume V and the length of the structure L, use the formula Calculate the accident rate R' per 100 million vehicles per kilometer in one year c ;

[0024] (2) Based on the accident rate R′ per 100 million vehicles per kilometer in one year c , calculate the road section source risk quantity of the highway risk area to be identified in is the accident rate per 100 million vehicles per kilometer in a year on the straight-slight longitudinal slope section, R′ ci It is the accident rate per 100 million vehicles per kilometer in one year for the road section type to which the risk area of ​​the highway to be identified belongs.

[0025] Preferably, in step 3), the static risk field strength of the structure is calculated Specifically:

[0026] (1) Calculate the static risk field factor K of the structure based on the running speed v gzw =ΔV=V i -V j , where V i is the running speed of the section with pile number i, V j is the running speed of the section with pile number j;

[0027] (2) Based on the static risk field factor K of the structure gzw and the structural source risk Q gzw , calculate the static risk field strength of the structure Where R is the equivalent distance, that is, the comprehensive value of the distance from the location point in the field to the risk source and the target attraction constant. is a unit direction vector.

[0028] Preferably, in step 3), the roadside static risk field strength is calculated Specifically:

[0029] (1) Based on the guardrail source risk quantity Q lc , respectively calculate the static risk field intensity of the left road side and the static risk field intensity on the right side of the road

[0030]

[0031]

[0032] Among them, K lc is the roadside risk field gain coefficient, which is 1 for straight sections, 0.8 for guardrails located inside the curve, and 1.2 for guardrails located outside the curve; * is the minimum radius of the circular curve without superelevation, R is the radius of the circular curve of the road; d l is the distance between the position point on the road and the left guardrail, dr is the distance between the position point on the road and the right guardrail; l is the lateral width of the road;

[0033] (2) Based on the static risk field strength on the left side of the road and the static risk field intensity on the right side of the road Get the roadside static risk field strength

[0034] Preferably, in step 3), the linear static risk field strength is calculated Specifically:

[0035] (1) Based on the running speed v, the linear static risk field potential energy at each position is calculated by linear interpolation method. ΔV A =V BP -V EP ,in, represents the linear static risk field potential energy at lateral position j and pile number i, S is the distance between the passenger car and the starting point of the road section unit, L V is the length of the road section unit, V BP is the running speed at the starting point of the road section, v EP is the running speed at the end of the road section; when only the speed of the inner lane is known, based on the linear interpolation method, the formula is used Calculate the linear static risk field potential energy at each location, where β is the lateral distribution coefficient;

[0036] (2) Calculate the speed standard deviation based on the running speed v of the fixed section Among them, n is the number of small passenger cars passing through the section, v i is the running speed of the i-th passenger car when it passes through the section, and the speed variation coefficient in Velocity potential field strength coefficient

[0037] (3) In this road section, two points are selected with coordinates (i1, j1) and (i2, j2) respectively. Based on the road section field source risk quantity Q lx , Linear static risk field potential and velocity potential field strength coefficient K lx , calculate the lateral linear static risk field intensity and longitudinal linear static risk field intensity in, is the linear static risk field potential energy difference, and are the linear static risk field potential at coordinates (i1, j1) and (i2, j2), and are the lateral and longitudinal distance vectors, respectively;

[0038] (4) Calculate the linear static risk field intensity

[0039] Compared with the prior art, the highway risk area identification method based on the road static risk field theory of the present invention has one or more of the following beneficial technical effects:

[0040] 1. The present invention combines potential field theory with static road conditions, integrates the research ideas of qualitative analysis and quantitative analysis, establishes a static road risk field theory based on the characteristics of road risks, and proposes a risk area identification method based on the measured traffic data of highways. Finally, a new highway risk area identification method is established, so that the risk area can be quantified in the highway design stage.

[0041] 2. The discrimination method of the present invention can be used to predict and evaluate the risk levels of different road areas. Moreover, the accuracy of the risk level prediction results using the discrimination method of the present invention reaches 78.79%, and the accuracy within one level difference from the actual risk level results reaches 90.91%. Therefore, the discrimination method of the present invention has good applicability and effectiveness in risk area discrimination. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 It is a flow chart of the highway risk area identification method based on the road static risk field theory of the present invention.

[0043] Figure 2 It is a three-dimensional schematic diagram of the spatial distribution of static risk field strength on the roadside.

[0044] Figure 3 Schematic diagram of the distribution of linear static risk field potential energy in the road.

[0045] Figure 4 This is the running speed trend chart.

[0046] Figure 5 It is the comprehensive field strength distribution map of the road static risk field. DETAILED DESCRIPTION

[0047] The present invention is further described below in conjunction with the accompanying drawings and embodiments, and the contents of the embodiments are not intended to limit the protection scope of the present invention.

[0048] The present invention takes road factors as the research object, constructs a risk field model within the road domain based on potential field theory, and proposes a highway risk area identification method based on road static risk field theory.

[0049] Figure 1 FIG. 2 is a flow chart showing a method for identifying highway risk areas based on the static road risk field theory of the present invention. Figure 1 As shown, the highway risk area identification method based on the road static risk field theory of the present invention includes the following steps:

[0050] 1. Determine the structure type, guardrail type and road section type of the risk area of ​​the highway to be identified.

[0051] For expressways, the types of structures include general sections, tunnels, interchanges and bridges. The types of guardrails include flexible guardrails, semi-rigid guardrails and rigid guardrails.

[0052] At the same time, based on the design file data of the expressway section, for mountain expressways, the radius of 1000m is used as the standard for dividing flat curves, and the sections with a flat curve radius less than 1000m are small radius curve sections, and the sections with a flat curve radius greater than 1000m are large radius curve sections; the longitudinal slope of 3% is used as the standard for dividing longitudinal slope sections, and the sections with a longitudinal slope less than 3% are small longitudinal slope sections, and the sections with a longitudinal slope greater than 3% are large longitudinal slope sections. Therefore, the expressway can be divided into the following section types: straight line-small longitudinal slope section, straight line-large uphill section, straight line-large downhill section, small radius curve-small longitudinal slope section, small radius curve-large uphill section, small radius curve-large downhill section, large radius curve-small longitudinal slope section, large radius curve-large uphill section, large radius curve-large downhill section, and the above section types are numbered 1-9 respectively.

[0053] Therefore, based on the design data of the highway, the various sections of the highway can be determined, that is, whether the structure type of the risk area of ​​the highway to be identified is a general section, a tunnel, an interchange, or a bridge, whether the guardrail type is a flexible guardrail, a semi-rigid guardrail, or a rigid guardrail, and which of the section types is numbered 1-9.

[0054] 2. Determine the structural source risk Q based on the structural type gzw , determine the guardrail source risk quantity Q based on the guardrail type lc And determine the road section source risk quantity Q based on the road section type lx .

[0055] First, the design document data, statistical data, and test data of the highway section were extracted, and the running speed of passenger cars in each section was predicted by the design speed. The length L of different structure types, including general sections, tunnels, interchanges, and bridges, was counted, and the annual traffic volume V, the number of traffic accidents N, and the number of casualties in each guardrail were studied.

[0056] Among them, the prediction process of the running speed of passenger cars in each section is predicted by the design speed, and the running speed prediction method provided in Appendix (B) of the "Highway Project Safety Evaluation Specification" (JTG B05-2015) is used to predict the running speed of passenger cars.

[0057] In the present invention, the structure source risk quantity Q is determined based on the structure type. gzw Specifically:

[0058] 1. Based on the annual number of traffic accidents N, annual traffic volume V and length of the structure L, use the formula Calculate the accident rate R per million vehicles per kilometer in a year for the structure c , the unit is times / (million vehicles·km). Therefore, using the formula The accident rate per million vehicles per kilometer over a period of one year can be calculated for various structure types (including general road sections, tunnels, interchanges and bridges).

[0059] 2. Based on the accident rate R per million vehicles per kilometer in one year c Calculate the risk of structural sources in is the accident rate per million vehicle kilometers on general roads in one year, B ci is the accident rate per million vehicle-kilometers in one year for the type of structure to which the risk area of ​​the highway to be identified belongs.

[0060] It can be seen that in determining the structure source risk Q gzw When calculating the risk of structure source in general sections, the general sections are taken as the benchmark, that is, the structure source risk of general sections is 1, and the structure source risk of other types of structures is the ratio of the accident rate of the structure type per million vehicle-kilometers in one year to the accident rate of the general sections per million vehicle-kilometers in one year.

[0061] At the same time, in the present invention, the guardrail source risk quantity Q is determined based on the guardrail type. lc Specifically:

[0062] 1. Calculate the severity of the accident based on the number of casualties λ in the guardrail and the number of traffic accidents N throughout the year Therefore, using the formula Accident severity can be calculated for a variety of guardrail types, including flexible guardrails, semi-rigid guardrails, and rigid guardrails.

[0063] 2. Based on the severity of the accident N lc Calculate the risk of guardrail source Where N lci is the accident severity of the guardrail type to which the risk area of ​​the highway to be identified belongs, is the accident severity of the flexible guardrail.

[0064] It can be seen that in determining the guardrail source risk Q lc When the flexible guardrail is used as the benchmark, that is, the guardrail source risk of the flexible guardrail is 1, and the guardrail source risk of other guardrail types is the ratio of the accident severity of the guardrail type to the accident severity of the flexible guardrail.

[0065] Furthermore, in the present invention, the road section source risk quantity Q is determined based on the road section type.lx Specifically:

[0066] 1. Based on the annual number of traffic accidents N, annual traffic volume V and the length L of the structure on the road section, use the formula Calculate the accident rate R' per 100 million vehicles per kilometer in one year c Therefore, using the formula The accident rate per 100 million vehicles per kilometer in one year for each type of road section (straight line-small longitudinal slope section, straight line-large uphill section, straight line-large downhill section, small radius curve-small longitudinal slope section, small radius curve-large uphill section, small radius curve-large downhill section, large radius curve-small longitudinal slope section, large radius curve-large uphill section, large radius curve-large downhill section) can be calculated.

[0067] 2. Based on the accident rate R′ per 100 million vehicles per kilometer in one year c , calculate the road section source risk quantity of the highway risk area to be identified in is the accident rate per 100 million vehicles per kilometer in a year on the straight-slight longitudinal slope section, R′ ci It is the accident rate per 100 million vehicles per kilometer in one year for the road section type to which the risk area of ​​the highway to be identified belongs.

[0068] It can be seen that in determining the road section field source risk quantity Q lx When the straight line-small longitudinal slope section is taken as the benchmark, that is, the section source risk of the straight line-small longitudinal slope section is 1, and the section source risk of other section types is the ratio of the accident rate per 100 million vehicles per kilometer of the section type in one year to the accident rate per 100 million vehicles per kilometer of the straight line-small longitudinal slope section in one year.

[0069] 3. Based on the structure source risk quantity Q gzw Calculate static risk field strength of structures Based on the guardrail source risk quantity Q lc Calculate the static risk field strength on the roadside Based on the road section field source risk quantity Q lx Calculation of linear static risk field strength

[0070] In the present invention, based on the structure source risk quantity Q gzw Calculate static risk field strength of structures Specifically:

[0071] 1. Calculate the static risk field factor K of the structure based on the previously predicted running speed v of the small car gzw =ΔV=V i -V j Among them, V i is the running speed of the section with pile number i, Vj is the running speed of the section with pile number j.

[0072] 2. Based on the static risk field factor K of the structure gzw and the structural source risk Q gzw , calculate the static risk field strength of the structure Among them, R is the equivalent distance, that is, the comprehensive value of the distance from the location point in the field to the risk source and the target attraction constant. is a unit direction vector.

[0073] Therefore, in calculating the static risk field strength of the structure When the target attraction constant is introduced, the field potential energy at the field source point can be eliminated, which can represent the expected value that the driver needs to drive to the structure.

[0074] At the same time, in the present invention, based on the guardrail source risk quantity Q lc Calculate the static risk field strength on the roadside Specifically:

[0075] 1. Based on the guardrail source risk quantity Q lc , respectively calculate the static risk field intensity of the left road side and the static risk field intensity on the right side of the road The formula is as follows:

[0076]

[0077]

[0078] Among them, K lc is the roadside risk field gain coefficient, which is 1 for straight sections, 0.8 for guardrails located inside the curve, and 1.2 for guardrails located outside the curve; * is the minimum radius of the circular curve without superelevation, R is the radius of the circular curve of the road; d l is the distance between the position point on the road and the left guardrail, d r is the distance between the position point on the road and the right guardrail; l is the lateral width of the road.

[0079] 2. Based on the static risk field strength on the left side of the road and the static risk field intensity on the right side of the road Get the roadside static risk field strength That is, the magnitude of the roadside static risk field strength is the scalar sum of the risk field strengths generated by the guardrails on both sides. The three-dimensional schematic diagram of the spatial distribution of the roadside static risk field strength is shown in Figure 2 shown.

[0080] Furthermore, in the present invention, based on the road section field source risk quantity Qlx Calculation of linear static risk field strength Specifically:

[0081] 1. Based on the running speed v, the linear interpolation method is used to calculate the linear static risk field potential energy at each position ΔV A =V BP -V EP .in, represents the linear static risk field potential energy at lateral position j and pile number i, S is the distance between the passenger car and the starting point of the road section unit, L V is the length of the road section unit, V BP is the running speed at the starting point of the road section, v EP It is the running speed at the end point of the road section.

[0082] Among them, when only the speed of the inner lane is known, based on the linear interpolation method, the formula β is used to calculate the linear static risk field potential energy at each position, where β is the lateral distribution coefficient. β is the lateral distribution coefficient, and its specific value is shown in Table 1.

[0083] Table 1 Lateral distribution coefficient value table

[0084]

[0085] 2. Calculate the speed standard deviation based on the running speed v of the fixed section Among them, n is the number of small passenger cars passing through the section, v i is the running speed of the i-th passenger car when it passes through the section, and the speed variation coefficient in Velocity potential field strength coefficient The speed variation coefficient CV refers to the ratio of the speed standard deviation to the average speed. The larger the value, the greater the dispersion.

[0086] 3. In this road section, select two points with coordinates (i1, j1) and (i2, j2) respectively, based on the road section field source risk quantity Q lx , Linear static risk field potential and velocity potential field strength coefficient K lx , calculate the lateral linear static risk field intensity and longitudinal linear static risk field intensity in, is the linear static risk field potential energy difference, and are the linear static risk field potential at coordinates (i1, j1) and (i2, j2), and Refers to the lateral and longitudinal distance vectors respectively.

[0087] 4. Calculate the linear static risk field intensity The distribution of linear static risk field potential energy on the road is as follows: Figure 3 .

[0088] 4. Based on the linear static risk field strength E' v , Static risk field strength of structures and roadside static risk field strength Calculate the static risk field comprehensive field strength of the highway risk area to be identified

[0089] V. Based on the comprehensive field strength E of the static risk field cp , and the average risk field strength is obtained Based on the average risk field strength E avg , determine the evaluation level of the risk area of ​​the highway to be identified. Specifically, according to the risk area evaluation level table 2, the prediction and identification of the risk area of ​​the highway is achieved.

[0090] In the present invention, by introducing the average risk field strength index, the level of the risk area gradient can be accurately quantified.

[0091] Table 2 Risk area evaluation level table

[0092]

[0093] The following is an example of a characteristic section of a highway (YX highway) in a mountainous area in the west to illustrate the highway risk area identification method based on the static road risk field theory of the present invention. The specific process is as follows:

[0094] 1. Extract the design file data of the road section, count the lengths L of different structures, study the annual traffic volume V, the annual number of traffic accidents N, the number of casualties in each guardrail, and other data, and predict the running speed of passenger cars. The running speed prediction results are as follows: Figure 4 shown.

[0095] 2. Calculate the linear static risk field, the structural static risk field and the roadside static risk field respectively, and finally obtain the comprehensive field strength E of the road static risk field cp , and identify the risk area. In the vertical direction, the comprehensive field strength and field strength distribution diagram of each pile are finally obtained, as shown in Table 3 and Figure 5 shown.

[0096] Table 3 Road static risk field intensity

[0097]

[0098] 3. According to the risk area evaluation level table in Table 2, the risk level of different areas is predicted and judged. At the same time, the risk level of the CR value of the accident rate per million vehicle kilometers is selected to divide the risk level of the actual road section. The CR value division standard is that if CR≤0.3, it means that the vehicle basically has no accidents in this section, and the risk level is defined as extremely low; if 0.3<CR<0.6, it means that the vehicle has few accidents in this section, and the risk level is defined as low; if 0.6≤CR<0.975, it means that the number of accidents of the vehicle in this section is normal, and the risk level is defined as low; if 0.975≤CR<1.2, it means that the number of accidents of the vehicle in this section is slightly more than the normal value, and the risk level is defined as medium; if 1.25≤CR<1.5, it means that the number of accidents of the vehicle in this section is large, and the risk level is defined as high; if CR≥1.5, it is considered that the number of accidents of the vehicle in this section is large, and the risk level is defined as high. The specific results of the predicted risk level and actual risk level of each region are shown in Table 4.

[0099] Table 4 Prediction results of risk levels in each region

[0100]

[0101] After calculation and comparison, the prediction results of the discrimination method of the present invention are different from the actual risk level results in 7 places, with an accuracy rate of 78.79%. Analysis shows that the error mainly comes from the boundary of the risk area division, and the accuracy rate of the prediction results of the discrimination method of the present invention and the actual risk level results within one level is 90.91%. Especially in the identification of higher risk and high risk areas, when the error between the prediction results of the discrimination method of the present invention and the actual risk level results is set within one level, the prediction results are more accurate.

[0102] The highway risk area identification method based on the road static risk field theory of the present invention mainly combines the impact of three road elements, namely road structures, line shapes and roadside facilities, on driving safety, proposes a basic theory and model of road static risk field, and obtains a road static comprehensive risk field theoretical model by calibrating the risk quantities of conditions such as structure field sources, line field sources, and roadside field sources, ultimately achieving the prediction and identification of risk areas and levels.

[0103] The above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is impossible to list all the embodiments here. Any obvious changes or modifications derived from the technical solution of the present invention are still within the scope of protection of the present invention.

Claims

1. A highway risk area identification method based on road static risk field theory, characterized in that: The following steps are involved: 1) Determine the structure type, guardrail type and road section type of the risk area of ​​the highway to be identified; 2) Determine the structure source risk Q based on the structure type gzw , determine the guardrail source risk quantity Q based on the guardrail type lc And determine the road section source risk quantity Q based on the road section type lx ; 3) Based on the structure source risk Q gzw Calculate static risk field strength of structures Based on the guardrail source risk quantity Q lc Calculate the static risk field strength on the roadside Based on the road section field source risk quantity Q lx Calculation of linear static risk field strength 4) Based on the linear static risk field strength Static risk field strength of structures and roadside static risk field strength Calculate the static risk field comprehensive field strength of the highway risk area to be identified 5) Based on the comprehensive field strength E of the static risk field cp , and the average risk field strength is obtained Based on the average risk field strength E avg , determine the evaluation level of the risk area of ​​the highway to be identified; In step 2), the structure source risk Q is determined based on the structure type. gzw Specifically: (1) Based on the annual number of traffic accidents N, annual traffic volume V and the length of the structure L, use the formula Calculate the accident rate R per million vehicles per kilometer in one year c , the unit is times / (million vehicles·km); (2) Based on the accident rate R per million vehicles per kilometer in one year c Calculate the risk of structural sources in is the accident rate per million vehicle kilometers on general roads in one year, R ci is the accident rate per million vehicle kilometers in one year for the type of structure to which the risk area of ​​the highway to be identified belongs; In the step 2), the guardrail source risk quantity Q is determined based on the guardrail type. lc Specifically: (1) Calculate the severity of the accident based on the number of casualties λ in the guardrail and the number of traffic accidents N throughout the year. (2) Based on the severity of the accident N lc Calculate the risk of guardrail source Where N lci is the accident severity of the guardrail type to which the risk area of ​​the highway to be identified belongs, is the accident severity of the flexible guardrail; In the step 2), the road section source risk quantity Q is determined based on the road section type. lx Specifically: (1) Based on the annual number of traffic accidents N, annual traffic volume V and the length of the structure L, use the formula Calculate the accident rate R' per 100 million vehicles per kilometer in one year c ; (2) Based on the accident rate R′ per 100 million vehicles per kilometer in one year c , calculate the road section source risk quantity of the highway risk area to be identified in is the accident rate per 100 million vehicles per kilometer in a year on the straight-slight longitudinal slope section, R′ ci The accident rate per 100 million vehicles per kilometer in one year for the road section type to which the risk area of ​​the highway to be identified belongs; In step 3), the static risk field strength of the structure is calculated Specifically: (1) Calculate the static risk field factor K of the structure based on the running speed v gzw =ΔV=V i -V j , where V i is the running speed of the section with pile number i, V j is the running speed of the section with pile number j; (2) Based on the static risk field factor K of the structure gzw and the structural source risk Q gzw , calculate the static risk field strength of the structure Where R is the equivalent distance, that is, the comprehensive value of the distance from the location point in the field to the risk source and the target attraction constant. is the unit direction vector; In step 3), calculate the roadside static risk field strength Specifically: (1) Based on the guardrail source risk quantity Q lc , respectively calculate the static risk field intensity of the left road side and the static risk field intensity on the right side of the road Among them, K lc is the roadside risk field gain coefficient, which is 1 for straight sections, 0.8 for guardrails located inside the curve, and 1.2 for guardrails located outside the curve; * is the minimum radius of the circular curve without superelevation, R is the radius of the circular curve of the road; d l is the distance between the position point on the road and the left guardrail, d r is the distance between the position point on the road and the right guardrail; l is the lateral width of the road; (2) Based on the static risk field strength on the left side of the road and the static risk field intensity on the right side of the road Get the roadside static risk field strength In step 3), the linear static risk field strength is calculated Specifically: (1) Based on the running speed v, the linear static risk field potential energy at each position is calculated by linear interpolation method. ΔV A =V BP -V EP ,in, represents the linear static risk field potential energy at lateral position j and pile number i, S is the distance between the passenger car and the starting point of the road section unit, L V is the length of the road section unit, V BP is the running speed at the starting point of the road section, V EP is the running speed at the end of the road section; when only the speed of the inner lane is known, based on the linear interpolation method, the formula is used Calculate the linear static risk field potential energy at each location, where β is the lateral distribution coefficient; (2) Calculate the speed standard deviation based on the running speed v of the fixed section Among them, n is the number of small passenger cars passing through the section, v i is the running speed of the i-th passenger car when it passes through the section, and the speed variation coefficient in Velocity potential field strength coefficient (3) In this road section, two points are selected with coordinates (i1, j1) and (i2, j2) respectively. Based on the road section field source risk quantity Q lx , Linear static risk field potential and velocity potential field strength coefficient K lx , calculate the lateral linear static risk field intensity and longitudinal linear static risk field intensity in, is the linear static risk field potential energy difference, and are the linear static risk field potential at coordinates (i1, j1) and (i2, j2), and are the lateral and longitudinal distance vectors, respectively; (4) Calculate the linear static risk field intensity 2. The highway risk area identification method based on road static risk field theory according to claim 1 is characterized in that: The types of structures include general road sections, tunnels, interchanges and bridges; the types of guardrails include flexible guardrails, semi-rigid guardrails and rigid guardrails; the types of road sections include straight line-small longitudinal slope section, straight line-large uphill section, straight line-large downhill section, small radius curve-small longitudinal slope section, small radius curve-large uphill section, small radius curve-large downhill section, large radius curve-small longitudinal slope section, large radius curve-large uphill section and large radius curve-large downhill section.

3. The highway risk area identification method based on road static risk field theory according to claim 2 is characterized in that: Before step 1), the method also includes: counting the length L of each structure, the annual traffic volume V, the annual number of traffic accidents N, the number of casualties λ in each guardrail, and predicting the running speed v of the passenger car.

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