CN115063970A - Driving risk evaluation method for small-clear-distance road section with tunnel and intercommunicated entrance and exit - Google Patents
Driving risk evaluation method for small-clear-distance road section with tunnel and intercommunicated entrance and exit Download PDFInfo
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- CN115063970A CN115063970A CN202210460415.1A CN202210460415A CN115063970A CN 115063970 A CN115063970 A CN 115063970A CN 202210460415 A CN202210460415 A CN 202210460415A CN 115063970 A CN115063970 A CN 115063970A
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- G08—SIGNALLING
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- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
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- G—PHYSICS
- G08—SIGNALLING
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- G08G1/00—Traffic control systems for road vehicles
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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
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- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/052—Detecting movement of traffic to be counted or controlled with provision for determining speed or overspeed
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- G—PHYSICS
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- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
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Abstract
The invention discloses a method for evaluating the driving risk of a small-clear-distance road section of a tunnel and an intercommunicated entrance/exit, which comprises the steps of firstly obtaining the road parameters of the small-clear-distance road section to be evaluated; then, the road parameters are respectively input into a first evaluation model and a second evaluation model to obtain a corresponding first evaluation result and a corresponding second evaluation result, the first evaluation model is an evaluation model taking a traffic conflict rate as an index, and the second evaluation model is an evaluation model taking a heart rate increase rate as an index; and finally, determining the risk grade of the small-clear-distance road section to be evaluated in a risk grade table according to the first evaluation result and the second evaluation result, so that the driving risk of the tunnel and the small-clear-distance road section with the intercommunicated entrance and exit can be quickly and simply evaluated.
Description
Technical Field
The invention belongs to the technical field of driving risk evaluation, and particularly relates to a driving risk evaluation method for a small-clear-distance road section with a tunnel and an intercommunicated entrance and exit.
Background
With the improvement of highway network construction in China, large structures such as tunnels and intercommunicating roads in the highway become more and more dense, the intercommunicating points are particularly the junction points of the highway and other roads, and numerous engineering examples with too close distance between the tunnels and the intercommunicating overpass exit and entrance are presented, which causes the problems of high accident rate and increasingly serious highway operation safety.
When the distance between the tunnel and the intercommunicated gateway is larger, the driver has sufficient time to identify the highway information and make a decision; when the distance is small, the decision-making time of a driver is insufficient, the appropriate lane change time is easy to miss, and dangerous driving behaviors such as sudden lane change, reversing and the like occur, so that a malignant traffic accident is caused. The existing quantitative risk evaluation model has the defects of being too complex, difficult to solve, low in real operability and the like.
Therefore, how to quickly and simply evaluate the driving risk of the small-clear-distance road section of the tunnel and the intercommunicating entrance and exit is a technical problem to be solved by technical personnel in the field.
Disclosure of Invention
The invention aims to quickly and simply evaluate the traffic risk of a small-clear-distance road section of a tunnel and an intercommunicating entrance and exit, and provides a traffic risk evaluation method of the small-clear-distance road section of the tunnel and the intercommunicating entrance and exit.
The technical scheme of the invention is as follows: a driving risk evaluation method for a tunnel and a small-clear-distance road section with an intercommunicated entrance and exit comprises the following steps:
s1, acquiring road parameters of the small clear distance road section to be evaluated;
s2, inputting the road parameters into a first evaluation model and a second evaluation model respectively to obtain corresponding first evaluation results and second evaluation results, wherein the first evaluation model is an evaluation model taking a traffic conflict rate as an index, and the second evaluation model is an evaluation model taking a heart rate increase rate as an index;
and S3, determining the risk level of the small-clearance road section to be evaluated in a risk level table according to the first evaluation result and the second evaluation result.
Further, the first evaluation model is specifically as follows:
TC out ＝(0.0259Q+0.8225H+1.1971P+1208921×L -2.5537 -64.9029)10 -3 R 2 ＝0.9385
TC in ＝0.0010Q+0.0271H+0.0578P+13.4660×e -0.1069L -2.5650R 2 ＝0.7355
in the formula, TC out Traffic conflict rate prediction value, TC, for small clear distance road section between tunnel exit and intercommunication exit in Is a traffic conflict rate predicted value of a small clear distance road section of an intercommunication inlet and a tunnel inlet, Q is traffic volume, H is a large-scale vehicle proportion, P is a steering traffic flow proportion, L is clear distance length, e is a natural base number, R is a natural base number 2 Are fitting coefficients.
Further, the second evaluation model is specifically as follows:
HRI out ＝-0.0323lnR+0.0132i 2 -0.0453i+12.9075L -1.1383 +0.3689R 2 ＝0.8348
HRI in ＝34.7473r -0.9966 +0.0076i 2 -0.0168i-0.0299lnL+0.2610R 2 ＝0.8933
in the formula, HRI out Predicted value of the heart rate increase rate, HRI, of the driver for the small clear distance section between the tunnel exit and the intercommunication exit in The predicted value of the heart rate increase rate of the driver at the small clear distance road section of the intercommunication entrance and the tunnel entrance is R, the radius of a flat curve, ln is a logarithmic function, i is the gradient of a longitudinal slope, L is the length of the clear distance, R 2 Are fitting coefficients.
Further, the risk level table is specifically determined by the following steps:
a1, marking a first risk grade sequence for the small-distance road sections based on the traffic conflict rate;
a2, dividing a second risk grade sequence for the small-distance road section based on the heart rate increase rate;
a3, constructing the risk level table based on the first risk level sequence and the second risk level sequence.
Compared with the prior art, the invention has the following beneficial effects:
the method comprises the steps of firstly, acquiring road parameters of a small clear distance road section to be evaluated; then, the road parameters are respectively input into a first evaluation model and a second evaluation model to obtain corresponding first evaluation results and second evaluation results, the first evaluation model is an evaluation model taking a traffic conflict rate as an index, and the second evaluation model is an evaluation model taking a heart rate increase rate as an index; and finally, determining the risk grade of the small-clear-distance road section to be evaluated in a risk grade table according to the first evaluation result and the second evaluation result, so that the driving risk of the tunnel and the small-clear-distance road section with the intercommunicated entrance and exit can be quickly and simply evaluated.
Drawings
Fig. 1 is a schematic flow chart illustrating a driving risk evaluation method for a small-clear-distance road section of a tunnel and an intercommunicated entrance and exit provided in an embodiment of the present invention;
FIG. 2 is a schematic view of a small clear distance section of a tunnel exit in an embodiment of the present invention;
FIG. 3 is a schematic diagram illustrating a membership function of a traffic conflict rate of a small-distance road segment between a tunnel exit and an intercommunication exit according to an embodiment of the present invention;
FIG. 4 is a schematic diagram illustrating a membership function of a traffic conflict rate of a small-clear-distance road segment between a tunnel entrance and an intercommunication entrance in the embodiment of the present invention;
fig. 5 is a schematic diagram illustrating a heart rate increase rate membership function of a small clear distance section between a tunnel entrance and an intercommunicating entrance according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. It is to be understood that the embodiments described are only a few embodiments of the present application and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
Fig. 1 is a schematic flow chart of a method for evaluating driving risk of a small-clearance road section with a tunnel and an intercommunicated entrance and exit provided in an embodiment of the present application, where the method includes the following steps:
and step S1, acquiring road parameters of the small clear distance road section to be evaluated.
Specifically, the road parameters include traffic volume, a ratio of large vehicles, a ratio of turning traffic flow, a radius of a flat curve, and a gradient of a longitudinal slope.
And step S2, inputting the road parameters into a first evaluation model and a second evaluation model respectively to obtain corresponding first evaluation result and second evaluation result, wherein the first evaluation model is an evaluation model using a traffic conflict rate as an index, and the second evaluation model is an evaluation model using a heart rate increase rate as an index.
Specifically, the first evaluation model and the second evaluation model are determined by using simulation software. Firstly, a road simulation model is established through simulation software, the road simulation model comprises road section establishment, parameter setting, model calibration and simulation test, attributes such as road length, lane number and lane width are input to establish a tunnel and intercommunicate an entrance and exit road section model, and simulation test parameters are set: traffic volume, traffic composition, set driving paths and conflict areas; setting a speed limit value: the tunnel road section is set according to the speed limit of 80km/h, the variable speed lane road section of the intercommunicating outlet adopts the grading speed limit, and the ramp speed limit is 40 km/h.
In order to make the simulation model more accurately simulate the actual scene, the model needs to be calibrated by using the measured data. Collecting traffic flow video data of a tunnel at a high speed of 5 in Western Han province and a small clear distance road section of an intercommunicating entrance and exit, and detecting the speed of a target vehicle by applying a background difference method.
And carrying out parameter calibration on the expected speed distribution curves of the speed changing lane section and the small-clear-distance section by using a five-point calibration method (namely, the accumulated frequency is 0%, 15%, 50%, 85% and 100%) according to the measured data. The expected speed distribution curve calibration is realized by controlling the relative error of 6 data detection points distributed in the simulation to be within 5 percent, and the result is shown in the following table 1:
TABLE 1
The traffic conflict rate and the accident rate have positive correlation and can objectively and accurately reflect the risk degree of the tunnel and the intercommunicating entrance, so the traffic conflict rate (f) selected by the invention can be used as one of traffic safety risk evaluation indexes, and the traffic conflict rate is calculated according to the formula (1):
in the formula: f is the collision rate (sub/(Veh.km)); TC is the average number of collisions per hour (times/h); q is vehicle throughput (Veh/h); and L is the clear distance length (km) between the tunnel and the intercommunication outlet.
Taking four factors of clear distance length (L), traffic volume (Q), large-scale vehicle proportion (H) and turning traffic flow proportion (P) of a traffic flow angle as experimental design variables, and adopting L under the condition of not considering interaction of the factors 25 (5 6 ) Orthogonal tables were designed experimentally. And screening the simulation operation result to obtain the traffic conflict number of each group of experiments, and calculating the traffic conflict rate according to the formula (1).
In order to screen out the factors having strong correlation with the traffic collision rate, the test statistic F value of each factor is calculated by the equations (2) to (5), and the result is shown in table 2. The results of analyzing the dispersion and the variance show that the clear distance length (L), the traffic volume (Q), the large-scale vehicle proportion (H) and the turning traffic flow proportion (P) have obvious influence on the traffic conflict rate.
S c ＝∑S j (4)
In the formula, K jb The sum of the collision rates (sub-veh) corresponding to the factor level b in column j -1 ·km -1 ) Wherein j is a positive integer and j is less than or equal to 6; f. of jbi The conflict rate corresponding to the factor level b in the jth column; s j Is the column deviation sum of squares; n is the total times of tests under different lane numbers, and the number of the tests is 25; f. of i The conflict rate of the ith group of tests is shown, wherein i is a positive integer and is not more than n; s c For the sum of squares of error term deviations, the invention is equal to the sum of squares of empty column deviations; c is the number of occurrences of the jth factor level b, which is 5 in the present invention; f j Test statistics for the jth factor; n is j The degree of freedom of the factor of the jth column is equal to the horizontal number of the column minus 1, and the degree of freedom is 4; n is c The degree of freedom of the error term is that the error term of the invention is a null column with a value of 4.
TABLE 2
Because four factors of clear distance length (L), traffic volume (Q), large vehicle proportion (H) and turning traffic flow proportion (P) are strongly correlated with the traffic conflict rate, a regression model of the tunnel and the intercommunicated small clear distance road section with the traffic conflict rate as an index can be constructed according to the formula (6).
TC＝f(L,Q,H,P) (6)
In the formula, TC is the traffic conflict rate (sub/(veh & km)) of the small-clear-distance road section; l is the clear distance length (m) of the small clear distance road section; q is the traffic volume (veh/h); h is the proportion (%) of the large vehicle; p is a steering traffic volume ratio (%).
In order to determine an optimal regression model, firstly, a plurality of measurement equations are constructed according to a common multivariate nonlinear function form, iteration is carried out by adopting a Levenberg-Marquardt method and a general global optimization method in nonlinear analysis professional software 1stOpt, and a regression coefficient of each function is determined; the different types of regression functions above are then optimized using the akage information content criterion (AIC). And the AIC is used as a model evaluation comprehensive index, the regression function is evaluated by taking the sample size (3n), the coefficient number (K) in the fitting equation and the sum of squares of residuals (SSE) as analysis objects, and the minimum value of the AIC is taken as an optimal discrimination standard. The AIC value was calculated as equation (7):
for the small-clear-distance road section of the tunnel outlet and the intercommunication outlet, the form fitting degree of a linear function and a power function is better; for the small-clear-distance road section of the intercommunicating entrance and the tunnel entrance, the combination form fitting degree of the linear function and the exponential function is better, and the optimal regression model, namely the first evaluation model, is shown as the formula (8) and the formula (9).
TC out ＝(0.0259Q+0.8225H+1.1971P+1208921×L -2.5537 -64.9029)10 -3 R 2 ＝0.9385 (8)
TC in ＝0.0010Q+0.0271H+0.0578P+13.4660×e -0.1069L -2.5650R 2 ＝0.7355 (9)
In the formula, TC out Predicted value of traffic conflict rate (sub/(veh km)) for small-clear-distance road section of tunnel exit and intercommunication exit, TC in The predicted value of the traffic conflict rate (sub/(veh & km)) of a small-clear-distance road section of an intercommunication entrance and a tunnel entrance, Q is traffic volume, H is the proportion of large vehicles, P is the proportion of steering traffic flow, L is clear-distance length, e is natural base number, R is the traffic volume 2 Are fitting coefficients.
The safety level is divided into 5 grades according to the traffic conflict rate by clustering analysis of the traffic conflict rate under each simulation working condition: safety (level I), safer (level II), critical safety (level III), relative hazard (level IV), hazard (level V)
After the clustering center is determined, a function form of a reduced-half trapezoid is adopted to construct a fuzzy membership function of the traffic conflict rate of the tunnel and the road section with small clear distance at the entrance and the exit of the intercommunication, the expressions of the fuzzy membership function are shown as formulas (10) to (11), fig. 4 is a schematic diagram of the traffic conflict rate membership function of the road section with small clear distance at the entrance and the exit of the tunnel in the embodiment of the invention, and fig. 3 is a schematic diagram of the traffic conflict rate membership function of the road section with small clear distance at the exit and the exit of the tunnel in the embodiment of the invention.
The heart rate variability and heart rate increase rate of the driver are widely applied to physiological load research. Studies have shown that the use of heart rate increase rate (HRI) reflects more clearly the psychological load of the driver. In consideration of individual differences of drivers, the heart rate increase rate of the drivers is selected as a risk evaluation index, and the heart rate increase rate is calculated according to the formula (12).
In the formula: HRI is driver heart rate increase (%); HR (human HR) 1 The heart rate value (times/min) of a driver in a calm state; HR (human HR) 2 The driving state is the driving person heart rate value (times/min).
In order to enable the driving simulation model to simulate the actual driving environment more accurately, the model needs to be calibrated by acquiring the measured data. Heart rates of simulated driving and real vehicle experiment drivers are respectively monitored by utilizing the multi-lead physiological instrument, and simulation error analysis and parameter calibration are carried out on comparison data.
Selecting 3 drivers in the simulation driving experiment, and taking the average value of the non-collision test group in multiple experiments; the measured data comes from the tunnel and the real vehicle experiment of 7 point locations of the intercommunicating inlet (4) and outlet (3), and each measuring point is measured once. The results of the simulation driving and the actual vehicle test are shown in table 3.
TABLE 3
The difference value between the average heart rate increase rate of each driver in the simulation driving experiment and the heart rate increase rate in the real vehicle experiment is small and constant, and is about 4% -9%, so that the heart rate increase rate of the driver in the small-clear-distance road section can be measured through driving simulation.
The net distance length (L), the flat curve radius (r) and the longitudinal slope gradient (i) of the geometric linear angle of the road are used as experimental design variables, interaction of all factors is not considered, an orthogonal table L25(56) is selected for designing experiments, and the heart rate increase rate of each group of heart rate values measured in the driving simulation process is calculated according to the formula (12).
In order to screen out factors having strong correlation with the heart rate increase rate, the test statistic F value of each factor is calculated according to the formulas (2) to (5) by analogy with a calculation method of the statistical F value in the first evaluation model. The results of the analysis of the dispersion and the variance show that the clear distance length (L), the flat curve radius (r) and the longitudinal slope gradient (i) have obvious influence on the heart rate increase rate, and the correlation between the curve corner (theta) and the heart rate increase rate is not strong.
Because the clear distance length (L), the flat curve radius (r) and the longitudinal slope gradient (i) have obvious influence on the heart rate increase rate, and the curve corner (theta) has low correlation with the heart rate increase rate. Therefore, a regression model with the heart rate increase rate as an evaluation index can be constructed for the small-clear-distance road section of the tunnel and the intercommunicated entrance and exit according to the formula (13).
HRI＝f(r,i,L) (13)
Wherein, HRI is the average value (%) of the heart rate increase rate of the driver; l is the clear distance length (m) of the small clear distance road section; r is the radius (m) of the flat curve of the small clear distance road section; and i is the longitudinal slope gradient (%) of the small-clear-distance downhill section.
And (4) referring to a traffic flow simulation part, constructing various function measurement equations and selecting an optimal regression model. For the small-clear-distance road section of the tunnel outlet and the intercommunication outlet, the fitting degree of the combination form of the logarithmic function and the power function is better; for the small-clear-distance road section of the intercommunicating entrance and the tunnel entrance, the goodness of fit of the power function and the logarithm function is optimal, and the optimal regression models are respectively shown as a formula (14) and a formula (15).
HRI out ＝-0.0323lnR+0.0132i 2 -0.0453i+12.9075L -1.1383 +0.3689R 2 ＝0.8348 (14)
HRI in ＝34.7473r -0.9966 +0.0076i 2 -0.0168i-0.0299lnL+0.2610R 2 ＝0.8933 (15)
In the formula, HRI out For drivers at small clear distance sections of tunnel exit and intercommunicating exitPredicted value of heart rate increase rate, HRI in The predicted value of the heart rate increase rate of the driver at the small clear distance section of the intercommunicating entrance and the tunnel entrance is R, the radius of a flat curve, ln is a logarithmic function, i is the gradient of a longitudinal slope, L is the clear distance length, R 2 Are fitting coefficients.
As shown in fig. 5, it is a schematic diagram of a membership function of a heart rate increase rate of a small clear distance road section between a tunnel entrance and a tunnel exit, and the membership function expression is as shown in formula (16):
and step S3, determining the risk grade of the small-clear-distance road section to be evaluated in a risk grade table according to the first evaluation result and the second evaluation result.
In the embodiment of the present application, the risk level table is specifically determined by the following steps:
a1, dividing a first risk grade sequence for the small-distance road sections based on the traffic conflict rate;
a2, dividing a second risk grade sequence for the small-distance road section based on the heart rate increase rate;
a3, constructing the risk level table based on the first risk level sequence and the second risk level sequence.
Specifically, the risk rating table is shown in table 4 below:
TABLE 4
It should be noted that, in step S2, the traffic conflict rate and the heart rate increase rate are ranked according to the preset threshold, the first risk sequence is specifically the level I, the level II, the level III, the level IV and the level V of the traffic conflict rate, and the second risk sequence is specifically the level I, the level II, the level III, the level IV and the level V of the heart rate increase rate.
Specifically, when the heart rate increase rate is more than or equal to ten percent and less than fourteen percent, the corresponding second evaluation result is grade I; when the heart rate increase rate is more than or equal to fourteen percent and less than twenty percent, the corresponding second evaluation result is II grade; when the heart rate increase rate is more than or equal to twenty percent and less than thirty percent, the corresponding second evaluation result is grade III; when the heart rate increase rate is more than or equal to thirty percent and less than thirty-nine percent, the corresponding second evaluation result is grade IV; when the heart rate increase rate is not less than thirty-nine percent, the corresponding second evaluation result is a V grade.
The conflict rate is divided into the following according to the difference between the small clear distance as the outlet and the inlet:
if the small clear distance to be evaluated is a tunnel outlet or an intercommunication outlet, then: when the predicted value of the traffic conflict rate is greater than or equal to 0.0131 and less than 0.0316, the corresponding first evaluation result is level I; when the predicted value of the traffic conflict rate is greater than or equal to 0.0316 and less than 0.0526, the corresponding first evaluation result is level II; when the predicted value of the traffic conflict rate is greater than or equal to 0.0526 and less than 0.1095, the corresponding first evaluation result is grade III; when the predicted value of the traffic conflict rate is greater than or equal to 0.1095 and less than 0.1456, the corresponding first evaluation result is grade IV; and when the predicted value of the traffic conflict rate is greater than or equal to 0.1456, the corresponding first evaluation result is in a V level.
If the small clear distance to be evaluated is a tunnel entrance or an intercommunication entrance, then: when the predicted value of the traffic conflict rate is greater than or equal to 0.2644 and less than 0.8619, the corresponding first evaluation result is grade I; when the predicted value of the traffic conflict rate is greater than or equal to 0.8619 and less than 1.8683, the corresponding first evaluation result is II level; when the predicted value of the traffic conflict rate is greater than or equal to 1.8683 and less than 2.9571, the corresponding first evaluation result is grade III; when the predicted value of the traffic conflict rate is greater than or equal to 2.9571 and less than 4.8333, the corresponding first evaluation result is grade IV; and when the predicted value of the traffic conflict rate is greater than or equal to 4.8333, the corresponding first evaluation result is in a V level.
It will be appreciated by those of ordinary skill in the art that the embodiments described herein are intended to assist the reader in understanding the principles of the invention and are to be construed as being without limitation to such specifically recited embodiments and examples. Those skilled in the art, having the benefit of this disclosure, may effect numerous modifications thereto and changes may be made without departing from the scope of the invention in its aspects.
Claims (4)
1. A driving risk evaluation method for a small-clear-distance road section with a tunnel and an intercommunicated entrance and exit is characterized by comprising the following steps:
s1, acquiring road parameters of the small clear distance road section to be evaluated;
s2, inputting the road parameters into a first evaluation model and a second evaluation model respectively to obtain corresponding first evaluation results and second evaluation results, wherein the first evaluation model is an evaluation model taking a traffic conflict rate as an index, and the second evaluation model is an evaluation model taking a heart rate increase rate as an index;
and S3, determining the risk level of the small-clearance road section to be evaluated in a risk level table according to the first evaluation result and the second evaluation result.
2. The method for evaluating the driving risk of the small-clearance road section with the tunnel and the intercommunicated entrance and exit according to claim 1, wherein the first evaluation model is specifically as follows:
TC out ＝(0.0259Q+0.8225H+1.1971P+1208921×L -2.5537 -64.9029)10 -3 R 2 ＝0.9385
TC in ＝0.0010Q+0.0271H+0.0578P+13.4660×e -0.1069L -2.5650R 2 ＝0.7355
in the formula, TC out Traffic conflict rate prediction value, TC, for small clear distance road section between tunnel exit and intercommunication exit in Is a traffic conflict rate predicted value of a small clear distance road section of an intercommunication inlet and a tunnel inlet, Q is traffic volume, H is a large-scale vehicle proportion, P is a steering traffic flow proportion, L is clear distance length, e is a natural base number, R is a natural base number 2 Are fitting coefficients.
3. The method for evaluating the driving risk of the small-clearance road section with the tunnel and the intercommunicated entrance and exit according to claim 1, wherein the second evaluation model is specifically as follows:
HRI out ＝-0.0323lnR+0.0132i 2 -0.0453i+12.9075L -1.1383 +0.3689R 2 ＝0.8348
HRI in ＝34.7473r -0.9966 +0.0076i 2 -0.0168i-0.0299lnL+0.2610R 2 ＝0.8933
in the formula, HRI out Predicted value of the heart rate increase rate, HRI, of the driver for the small clear distance section between the tunnel exit and the intercommunication exit in The predicted value of the heart rate increase rate of the driver at the small clear distance road section of the intercommunication entrance and the tunnel entrance is R, the radius of a flat curve, ln is a logarithmic function, i is the gradient of a longitudinal slope, L is the length of the clear distance, R 2 Are fitting coefficients.
4. The method for evaluating the driving risk of the small-clearance road section with the tunnel and the intercommunicated entrance and exit according to claim 1, wherein the risk grade table is determined by the following steps:
a1, dividing a first risk grade sequence for the small-distance road sections based on the traffic conflict rate;
a2, dividing a second risk grade sequence for the small-distance road section based on the heart rate increase rate;
a3, constructing the risk level table based on the first risk level sequence and the second risk level sequence.
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