A safety evaluation method and system for the traffic operation environment of highway tunnels

Abstract

The present invention relates to the technical field of traffic operation environment evaluation, and more particularly to a method and system for evaluating the safety of a highway tunnel's traffic operation environment. The method comprises the following steps: obtaining basic data, vehicle position, vehicle speed, physical load, vehicle type, and vehicle density of a target single-lane highway tunnel; obtaining the vehicle's global optimal following position and global optimal following speed based on the traffic operation data, and then calculating single-vehicle risk and global traffic risk; and constructing a dynamic digital twin model of the target single-lane highway tunnel, and then visually displaying the risk assessment results. The present invention can effectively evaluate the safety of a single-lane highway tunnel's traffic environment without constructing an evaluation index system, thereby improving the refinement and intelligence of highway tunnel safety management and ensuring the safe and efficient operation of tunnel traffic.

Description

Technical Field

[0001] The present invention relates to the technical field of traffic operation environment evaluation, and in particular to a method and system for evaluating the safety of traffic operation environment in a highway tunnel. Background Art

[0002] Single-lane highway tunnels present unique traffic environments. Vehicle failures or driver errors within the tunnel can easily trigger chain reactions such as rear-end collisions and collisions, resulting in serious traffic accidents. Therefore, accurately evaluating the safety of the traffic environment within highway tunnels is crucial for ensuring safe, smooth, and efficient tunnel traffic.

[0003] Currently, there are some relatively mature evaluation methods in the field of highway traffic safety assessment, but some problems still exist. For one thing, existing evaluation methods are primarily designed for open highway sections. There are relatively few methods specifically designed for highway tunnels, especially for specific types of highway tunnels. Furthermore, existing traffic environment safety assessments are mostly based on evaluation index systems and index weights for highway traffic safety ratings. This requires significant human, material, and time investment to construct the evaluation index system. The determination of index weights often relies on expert experience and subjective judgment. Furthermore, once established, the evaluation index system and index weights often remain unchanged for a certain period of time, making them difficult to adapt to dynamic changes in the traffic environment.

[0004] Therefore, it is necessary to explore a new evaluation method for highway tunnel traffic environment safety to provide more options and references for highway tunnel traffic environment safety evaluation. Summary of the Invention

[0005] In view of the defects in the prior art, the present invention provides a method and system for evaluating the safety of the traffic operation environment in a highway tunnel.

[0006] To achieve the above objectives, in a first aspect, the present invention provides a method for evaluating the traffic operation environment safety of a highway tunnel, the method comprising the following steps: obtaining basic data and traffic operation data of a target single-lane highway tunnel, the traffic operation data including vehicle position, vehicle speed, physical load, vehicle type, and vehicle density; obtaining the global optimal following position and global optimal following speed of each vehicle in the target single-lane highway tunnel based on the traffic operation data; calculating single-vehicle risk and global traffic risk based on the traffic operation data, the global optimal following position, and the global optimal following speed; and constructing a dynamic digital twin model of the target single-lane highway tunnel using the basic data and the traffic operation data, thereby visually displaying the risk assessment results. The present invention can better evaluate the safety of the traffic environment of a single-lane highway tunnel without constructing an evaluation index system, which is conducive to improving the refinement and intelligence level of highway tunnel safety management and ensuring the safe and efficient operation of tunnel traffic.

[0007] Optionally, obtaining the global optimal following position and the global optimal following speed of each vehicle in the target single-lane highway tunnel according to the traffic operation data comprises the following steps:

[0008] Get the following distance reference value;

[0009] After obtaining the following distance reference value, the global optimal following distance and the global optimal following speed of the vehicle are obtained under the constraints with the goal of balancing traffic safety and traffic efficiency;

[0010] The vehicle position of the rear vehicle between two adjacent vehicles is adjusted according to the global optimal following distance to obtain the global optimal following position of the rear vehicle between the two adjacent vehicles.

[0011] Based on obtaining the reference value of the following distance, this method aims to balance traffic safety and traffic efficiency, and obtains the global optimal following position and speed under constraints, which is conducive to improving the accuracy of traffic environment safety evaluation in single-lane highway tunnels.

[0012] Optionally, obtaining a following distance reference value includes the following steps:

[0013] Determine the lighting conditions at the vehicle's location;

[0014] The safety distance formula in the intelligent driving model is improved according to the light conditions, and then the following distance reference value is calculated.

[0015] The following distance reference value of this method not only takes into account vehicle speed, driver reaction time, acceleration and deceleration, but also further considers vehicle type and light factors in the tunnel, thereby improving the accuracy and reliability of the following distance reference value. It provides a data basis for accurately evaluating the global optimal following position and global optimal following speed of vehicles in single-lane highway tunnels.

[0016] Optionally, the constraints include lane speed limit and braking distance constraint.

[0017] Optionally, after obtaining the following distance reference value, obtaining a global optimal following distance and a global optimal following speed of the vehicle under constraints with the goal of balancing traffic safety and traffic efficiency includes the following steps:

[0018] After obtaining the following distance reference value, a state balance equation is set with the goal of balancing traffic safety and traffic efficiency to calculate a global risk state score;

[0019] The partial derivatives of the global risk state score with respect to the following distance and the vehicle speed are calculated respectively, and then the following distance and the vehicle speed are updated according to the gradient descent method under the constraints:

[0020] The updated following distance and vehicle speed are brought into the state balance equation to calculate the global risk state score, and the global optimal following distance and the global optimal following speed are output when a maximum number of iterations is reached or a convergence condition is met.

[0021] This method aims to balance traffic safety and efficiency by obtaining the global optimal following distance and speed within the constraints of lane speed limits and braking distances. This approach considers both tunnel driving safety and traffic efficiency, making the evaluation results more practical and instructive. Furthermore, by setting a state equilibrium equation and using gradient descent to update the following distance and vehicle speed, the method outputs the global optimal following distance and speed when the maximum number of iterations is reached or convergence conditions are met. This improves the accuracy and reliability of the global optimal following distance and speed calculations, contributing to the intelligent evaluation of traffic environment safety in single-lane highway tunnels.

[0022] Optionally, after obtaining the following distance reference value, setting a state balance equation with the goal of balancing traffic safety and traffic efficiency to calculate the global risk state score includes the following steps:

[0023] Setting a traffic safety item based on the following distance of the vehicle and the following distance reference value, and setting a traffic efficiency item based on the vehicle speed and the expected speed;

[0024] The weights of the traffic safety item and the traffic efficiency item are set according to the vehicle density and the critical vehicle density, and the weighted sum of the traffic safety item and the traffic efficiency item is used as a state balance equation to calculate the global risk state score.

[0025] The state balance equation of this method includes a traffic safety term set according to the vehicle-to-vehicle distance and a traffic efficiency term set according to the vehicle speed. This can ensure that the vehicle spacing always meets the braking distance constraint and avoid the reduction of tunnel traffic efficiency caused by excessive vehicle conservatism.

[0026] Optionally, the calculating of the single vehicle risk and the global traffic risk based on the traffic operation data, the global optimal following vehicle position, and the global optimal following vehicle speed comprises the following steps:

[0027] A distance deviation term is set according to the actual following distance of the vehicle and the global optimal following distance, and a speed deviation term is set according to the actual vehicle speed of the vehicle and the global optimal following speed, and a weighted sum of the distance deviation term and the speed deviation term is used as the single vehicle risk;

[0028] The average bicycle risk is calculated as a bicycle risk item, the vehicle density and the critical vehicle density are used to set a density risk item, and a weighted sum of the bicycle risk item and the density risk item is used as the global traffic risk.

[0029] This method calculates single-vehicle risk and global traffic risk based on traffic operation data, the global optimal following position, and the global optimal following speed. It not only provides an important decision-making basis for tunnel traffic safety management, but also avoids the construction of a complex evaluation index system, making highway tunnel traffic safety evaluation more convenient.

[0030] Optionally, the constructing a dynamic digital twin model of the target single-lane highway tunnel using the basic data and the traffic operation data, and then visually displaying the risk assessment results, comprises the following steps:

[0031] Constructing a dynamic digital twin model of the target single-lane highway tunnel using the basic data and the traffic operation data;

[0032] The single-vehicle risk and the global traffic risk are marked on the dynamic digital twin model of the target highway tunnel, and the risk assessment results are visualized.

[0033] This method constructs a dynamic digital twin model of the target single-lane highway tunnel and marks the single-vehicle risk and global traffic risk on the model, achieving a visual display of the risk assessment results, allowing managers to understand the traffic safety status in the tunnel in real time and intuitively.

[0034] Optionally, the constructing of a dynamic digital twin model of the target single-lane highway tunnel using the basic data and the traffic operation data, and then visually displaying the risk assessment results, further comprises the following steps:

[0035] Set a single-vehicle risk threshold and a global traffic risk threshold;

[0036] When the global traffic risk exceeds the global traffic risk threshold, a global warning is triggered;

[0037] When the bicycle risk exceeds the bicycle risk safety threshold, a bicycle warning is triggered.

[0038] This method forms a multi-level early warning mechanism by setting a single-vehicle risk threshold, a global traffic risk threshold, and a single-vehicle risk safety threshold, which can promptly remind managers to pay attention to the traffic safety conditions in the tunnel and quickly locate problem vehicles.

[0039] In a second aspect, the present invention provides a system for evaluating the safety of the traffic operating environment in a highway tunnel. The system comprises a data acquisition device, a data output device, a processor, and storage. The storage comprises a computer-readable storage medium storing a computer program comprising program instructions that, when executed by the processor, cause the processor to implement a method for evaluating the safety of the traffic operating environment in a highway tunnel provided by the present invention. This system can improve the efficiency of highway tunnel traffic operating environment safety assessments and enhance the practicality of the method, facilitating its widespread dissemination. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without creative work.

[0041] Figure 1 A schematic flow chart of a method for evaluating the safety of a highway tunnel traffic operation environment according to an embodiment of the present invention;

[0042] Figure 2 This is a schematic diagram of the framework of a highway tunnel traffic operation environment safety assessment system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0043] Specific embodiments of the present invention will be described in detail below. It should be noted that the embodiments described herein are for illustrative purposes only and are not intended to limit the present invention. In the following description, numerous specific details are set forth to provide a thorough understanding of the present invention. However, it will be apparent to one of ordinary skill in the art that these specific details are not necessarily required to practice the present invention. In other instances, well-known circuits, software, or methods are not specifically described to avoid obscuring the present invention.

[0044] Throughout this specification, references to "one embodiment," "an embodiment," "an example," or "an example" mean that a particular feature, structure, or characteristic described in connection with the embodiment or example is included in at least one embodiment of the present invention. Therefore, appearances of the phrases "in one embodiment," "in an embodiment," "an example," or "an example" in various places throughout this specification are not necessarily all referring to the same embodiment or example. Furthermore, the particular features, structures, or characteristics may be combined in any suitable combinations and / or subcombinations in one or more embodiments or examples. Furthermore, those of ordinary skill in the art will appreciate that the figures provided herein are for illustrative purposes only and are not necessarily drawn to scale.

[0045] It should be noted in advance that, in an optional embodiment, except for independent explanations, the same symbols or letters appearing in all formulas have the same meanings and values.

[0046] In an alternative embodiment, see Figure 1 The present invention provides a method for evaluating the safety of traffic operation environment in a highway tunnel, the method comprising the following steps:

[0047] S1. Obtain basic data and traffic operation data of a target single-lane highway tunnel, wherein the traffic operation data includes vehicle position, vehicle speed, physical load, vehicle type, and vehicle density.

[0048] Specifically, in this embodiment, the target single-lane highway tunnel will be referred to as the tunnel below, and its basic data includes geometric structure data, geological condition data, structural health data, and tunnel environmental data. Geometric structure data includes, but is not limited to, design parameters such as tunnel cross-sectional dimensions, slope, and curvature, as well as lining type, thickness, and support structure layout; geological condition data includes, but is not limited to, rock and soil type, surrounding rock grade, and groundwater distribution; structural health data includes, but is not limited to, data such as lining cracks, water seepage, and support structure stress; tunnel environmental data mainly refers to light condition data at different monitoring points in the tunnel, and is reflected by visibility collected by tunnel visibility detection sensors. The means of obtaining basic data for highway tunnels are all existing technical means.

[0049] Furthermore, in this embodiment, the physical load of the vehicle includes the real-time physical load and empty vehicle mass. Traffic operation data is acquired through curved plate sensors installed on the road surface at the tunnel entrance and high-definition cameras installed in the tunnel. The general process is as follows:

[0050] The real-time physical load of the vehicle is measured by bending plate sensors placed on the road surface at the tunnel entrance;

[0051] We collected images of different types of vehicles and annotated them, including the brand and model. We then used these annotated images to construct a dataset for training and validating the YOLOv8 algorithm. We then used the YOLOv8 algorithm to detect and identify vehicles in images captured by high-definition cameras. After identifying the vehicles, we calculated the number of vehicles per kilometer in the tunnel to determine vehicle density.

[0052] By collecting and integrating information from sources such as announcement data, actual measurement data, industry white papers, manufacturer databases, and third-party APIs for different types of vehicles through the Internet, a database is established that contains parameters such as weight, maximum acceleration, and comfortable deceleration of different types of vehicles when unloaded. Then, once the vehicle type is identified, its unloaded mass, maximum acceleration, and comfortable deceleration when unloaded can be obtained.

[0053] After the vehicle is detected, the homography matrix is obtained through camera calibration, and the pixel coordinates of the vehicle detection frame are mapped to the world coordinate system to obtain the vehicle position, including the front and rear positions;

[0054] Using target tracking algorithms such as SORT (Simple Online and Realtime Tracking) or DeepSORT, detected vehicles are tracked across frames to obtain each vehicle's unique ID and motion trajectory. The vehicle's actual speed, i.e., vehicle velocity, is estimated by calculating the vehicle's trajectory length between two adjacent frames and combining it with the inter-frame time interval.

[0055] The methods for acquiring traffic operation data are all existing technical means, so they will not be described in detail here.

[0056] S2. Obtaining a global optimal following position and a global optimal following speed of each vehicle in the target single-lane highway tunnel according to the traffic operation data.

[0057] Wherein, step S2 specifically includes the following steps:

[0058] S21. Obtain a following distance reference value.

[0059] Step S21 specifically includes the following steps:

[0060] S211. Determine the light conditions at the location of the vehicle.

[0061] S212: Improve the safety distance formula in the intelligent driving model according to the light conditions, and then calculate a following distance reference value.

[0062] Specifically, in this embodiment, the interaction between adjacent lanes does not need to be considered in a single-lane highway tunnel. Therefore, this embodiment improves the safety distance formula in the intelligent driving model based on the lighting conditions and vehicle types in the tunnel to calculate the following distance reference value for each vehicle. The following distance reference value satisfies the following relationship:

[0063]

[0064] in, is the reference value of the vehicle’s following distance, For standard visibility, is the measured visibility at the vehicle’s location, For the static safety distance, is the vehicle speed, is the driver's reaction time, is the speed difference between the vehicle and the previous vehicle in the same lane, is the maximum acceleration of the vehicle, For the comfortable deceleration of the vehicle, and Both are related to physical load.

[0065] More specifically, the static safety distance is 2m. The standard visibility in non-rainy days is 150m, and in rainy days it is 100m. The standard visibility needs to be automatically switched according to the environmental conditions monitored by the environmental sensors outside the tunnel. The driver's reaction time is 1.5s. If the vehicle is the lead vehicle, then 、 and All are set to 0.

[0066] This embodiment calculates the following distance reference value based on the intelligent driving model and the lighting conditions at the vehicle's location. It takes into account the impact of the complex and changeable lighting environment in the tunnel on the following distance, making the calculated following distance reference value more consistent with the actual situation, helping to improve the accuracy of the subsequent global optimal following position and speed, and thus helping to improve the accuracy of the traffic environment safety assessment in single-lane highway tunnels.

[0067] Furthermore, when calculating the reference value of the following distance, the empirical coefficient method is used to quickly determine the final values of the maximum acceleration and the comfortable deceleration, namely:

[0068]

[0069]

[0070] in, is the maximum acceleration of the vehicle under no-load conditions, is the comfortable deceleration when the vehicle is unloaded. is the empty vehicle mass, Add real-time physical weight to vehicles.

[0071] S22. After obtaining the following distance reference value, with the goal of balancing traffic safety and traffic efficiency, obtain the global optimal following distance and the global optimal following speed of the vehicle under constraints.

[0072] The following distance reference value represents an ideal following state for the vehicle ahead. However, simply following this distance ignores the overall vehicle distribution and traffic flow within the tunnel. This can lead to traffic congestion or localized traffic flow problems in some cases, potentially creating safety hazards and impacting overall tunnel efficiency. Therefore, after obtaining the following distance reference value for each vehicle, the goal is to balance traffic safety and efficiency, and determine the global optimal following distance and speed for each vehicle within the tunnel, subject to constraints and consistent with the vehicle distribution and traffic flow within the tunnel.

[0073] Step S22 specifically includes the following steps:

[0074] S221. After obtaining the following distance reference value, a state balance equation is set with the goal of balancing traffic safety and traffic efficiency to calculate a global risk state score.

[0075] Step S221 specifically includes the following steps:

[0076] S2211. Set a traffic safety item according to the following distance of the vehicle and the following distance reference value, and set a traffic efficiency item according to the vehicle speed and the expected speed.

[0077] Specifically, in this embodiment, the traffic safety item can be expressed as , the traffic efficiency term can be expressed as . N is the total number of vehicles, is the following distance of the i-th vehicle, is the reference value of the following distance of the i-th vehicle, is the vehicle speed of the i-th vehicle, is the expected vehicle speed.

[0078] S2212. Set the weights of the traffic safety item and the traffic efficiency item according to the vehicle density and the critical vehicle density, and then use the weighted sum of the traffic safety item and the traffic efficiency item as a state balance equation to calculate the global risk state score.

[0079] Specifically, in this embodiment, the weights of the traffic safety item and the traffic efficiency item are used in sequence and Indicates that the weight of the traffic safety item and the state balance equation satisfy the following relationships:

[0080]

[0081]

[0082] Among them, Q is the global risk status score, is the vehicle density, is the critical vehicle density. , The maximum speed limit for the lane, The minimum speed limit for the lane. It needs to be set by comprehensively considering the length of the tunnel, the designed traffic capacity, the traffic flow and the common types of vehicles passing through, etc. There is no fixed value. It should be noted that when i=1, .

[0083] More specifically, in the state equilibrium equation, the following distance is the length of the road centerline between two adjacent vehicles. Specifically, for a given pair of adjacent vehicles, the following distance of the trailing vehicle is the actual length of the road centerline between the rear end of the leading vehicle and the front end of the trailing vehicle, obtained through numerical integration. For specific tunnel scenarios, the road centerline can be obtained by manually marking key points of the road centerline, such as line segment endpoints and curve control points, by professionals. Once the key points are located in the real-world coordinate system, a spline curve or polynomial fitting method is used to generate a smooth centerline.

[0084] The state balance equation of this embodiment includes a traffic safety term based on vehicle-to-vehicle distance and a traffic efficiency term based on vehicle speed. This ensures that vehicle spacing consistently meets braking distance constraints while also preventing vehicles from being overly conservative and causing a decrease in tunnel traffic efficiency, making the evaluation results more practical and instructive. Furthermore, the state balance equation of this embodiment adaptively adjusts weights based on vehicle density, allowing the state balance equation to prioritize different terms in different situations, ensuring both traffic safety and traffic efficiency in the tunnel.

[0085] S222. Calculate the partial derivatives of the global risk state score with respect to the real-time following distance and vehicle speed according to the state balance equation, and then update the following distance and vehicle speed according to the gradient descent method under the constraints.

[0086] Specifically, in this embodiment, the constraints include lane speed limit and braking distance constraint. The braking distance constraint satisfies , is the road friction coefficient, is the acceleration due to gravity.

[0087] Furthermore, the following distance and vehicle speed are updated according to the following formula:

[0088]

[0089]

[0090] in, is the learning rate, which is set to 0.05 to ensure smooth updates.

[0091] S223: Substitute the updated following distance and vehicle speed into the state balance equation to calculate the global risk state score, and output the global optimal following distance and the global optimal following speed when the maximum number of iterations is reached or the convergence condition is met.

[0092] Specifically, in this embodiment, the updated following distance and vehicle speed are entered into the state balance equation to recalculate the global risk state score. A determination is then made as to whether the maximum number of iterations has been reached or the convergence condition has been satisfied. If not, the process returns to step S222. Steps S222 through S223 are repeated until the maximum number of iterations has been reached or the convergence condition has been satisfied, ultimately outputting the global optimal following distance and global optimal following speed for each vehicle.

[0093] More specifically, the maximum number of iterations is 50, and the convergence condition is , is the global risk status score obtained at the j-th iteration, is the global risk status score obtained at the j-1th iteration.

[0094] This embodiment sets a state balance equation, uses the gradient descent method to update the following distance and vehicle speed, and outputs the global optimal following distance and speed when the maximum number of iterations is reached or the convergence condition is met. This improves the accuracy and reliability of the global optimal following distance and speed calculation, and is conducive to improving the intelligent level of traffic environment safety evaluation in single-lane highway tunnels.

[0095] It should be noted that, since this embodiment only uses an algorithm to obtain the global optimal following distance and global optimal following speed of each vehicle as a reference for judging the traffic environment in the tunnel, there is no need to consider whether a collision will occur if each vehicle adjusts to the corresponding global optimal following distance and global optimal following speed.

[0096] S23. Adjust the vehicle position of the rear vehicle between two adjacent vehicles according to the global optimal following distance to obtain the global optimal following position of the rear vehicle between the two adjacent vehicles.

[0097] Specifically, in this embodiment, vehicle positions are adjusted based on the global optimal following distance so that the following distance of the rear vehicle of two adjacent vehicles is the corresponding global optimal following distance. For each of the two adjacent vehicles, the position of the leading vehicle's rear end is first projected onto the road centerline. A point on the road centerline behind the leading vehicle that is at the global optimal following distance from this projected point is then determined as the target following point. This target following point is then the global optimal following position of the rear vehicle.

[0098] Furthermore, this embodiment believes that when all vehicles travel at their globally optimal following positions and speeds, the tunnel's traffic environment is both safe and efficient. Therefore, subsequent safety assessments of the tunnel's traffic environment will be conducted based on the globally optimal following positions and speeds.

[0099] S3. Calculate the single vehicle risk and the global traffic risk based on the traffic operation data, the global optimal following vehicle position, and the global optimal following vehicle speed.

[0100] This embodiment calculates single-vehicle risk and global traffic risk based on traffic operation data, the global optimal following position, and the global optimal following speed. This not only provides an important decision-making basis for tunnel traffic safety management, but also avoids the need to construct a complex evaluation index system, making highway tunnel traffic safety assessment more convenient. Step S3 specifically includes the following steps:

[0101] S31. Set a distance deviation item according to the actual following distance of the vehicle and the global optimal following distance, and set a speed deviation item according to the actual vehicle speed of the vehicle and the global optimal following speed, and use the weighted sum of the distance deviation item and the speed deviation item as the single vehicle risk.

[0102] Specifically, in this embodiment, the bicycle risk satisfies the following relationship:

[0103]

[0104] in, is the distance deviation term, is the speed deviation term, is the bicycle risk of the i-th vehicle, is the distance risk item weight, is the actual following distance of the i-th vehicle, is the global optimal following distance of the i-th vehicle, is the speed risk item weight, is the actual vehicle speed of the i-th vehicle, is the global optimal following speed of the i-th vehicle. and Take 0.6 and 0.4 respectively.

[0105] S32. Calculate the average single-vehicle risk as a single-vehicle risk item, use the vehicle density and the critical vehicle density to set a density risk item, and use the weighted sum of the single-vehicle risk item and the density risk item as the global traffic risk.

[0106] Specifically, in this embodiment, the global traffic risk satisfies the following relationship:

[0107]

[0108] in, is the global traffic risk, N is the total number of vehicles, is the vehicle density in the tunnel, is the critical vehicle density. and Both are taken as 0.5.

[0109] S4. Use the basic data and the traffic operation data to build a dynamic digital twin model of the target single-lane highway tunnel, and then visualize the risk assessment results.

[0110] Step S4 specifically includes the following steps:

[0111] S41. Use the basic data and the traffic operation data to construct a dynamic digital twin model of the target single-lane highway tunnel.

[0112] S42. Mark the single-vehicle risk and the global traffic risk on the dynamic digital twin model of the target highway tunnel, and then visualize the risk assessment results.

[0113] This embodiment constructs a dynamic digital twin model of the target single-lane highway tunnel and marks the single-vehicle risk and global traffic risk on the model, thereby realizing a visual display of the risk assessment results, enabling managers to understand the traffic safety status in the tunnel in real time and intuitively.

[0114] S43. Set a bicycle risk threshold and a global traffic risk threshold.

[0115] Specifically, in this embodiment, the setting of the single-vehicle risk threshold needs to consider factors including but not limited to the tunnel's geological conditions, traffic flow, and accident frequency, and needs to be regularly adjusted based on the frequency and severity of accidents in the tunnel. The following example illustrates this.

[0116] Tunnels with complex geological conditions, fault fracture zones, karst development, and other adverse geological conditions have relatively low risk tolerance and should be set at a lower per-vehicle risk threshold. Tunnels with favorable geological conditions and higher surrounding rock grades may have a higher per-vehicle risk threshold. For example, if a tunnel passes through a karst area with abundant groundwater and a high risk of water and mud inrush, the per-vehicle risk threshold could be set at 0.6.

[0117] In tunnels with heavy traffic, the interaction between vehicles is more significant, and the risk of accidents increases accordingly. For example, in tunnels with an average daily traffic volume exceeding 50,000 vehicles, the per-vehicle risk threshold could be set at 0.65. In tunnels with lower daily traffic volumes, the per-vehicle risk threshold could be appropriately relaxed.

[0118] The accident frequency of a tunnel over the past five years is calculated. Frequent accidents indicate a low risk tolerance for the tunnel, and a lower per-vehicle risk threshold should be set. Otherwise, the per-vehicle risk threshold can be appropriately relaxed. For example, if a tunnel experiences more than five accidents annually, the per-vehicle risk threshold can be set at 0.6. Otherwise, the per-vehicle risk threshold can be appropriately relaxed.

[0119] Furthermore, the global traffic risk threshold needs to be set based on factors including, but not limited to, the tunnel's geological conditions, traffic volume, and accident frequency. It also needs to be regularly adjusted based on the frequency and severity of accidents within the tunnel. The following example illustrates this.

[0120] Tunnels with complex geological conditions, fault fracture zones, karst development, and other adverse geological conditions have relatively low risk tolerance and should be set at a lower global traffic risk threshold. Tunnels with favorable geological conditions and higher surrounding rock grades may have their global traffic risk threshold appropriately increased. For example, if a tunnel passes through a karst area with abundant groundwater and a high risk of water and mud inrush, the global traffic risk threshold should be set at 0.7.

[0121] In extra-long tunnels or tunnels with steep longitudinal slopes, the probability and impact of accidents during vehicle operation may be greater, and the risk tolerance may be relatively weaker. For example, for extra-long tunnels over 3,000 meters in length, the global traffic risk threshold can be set at 0.75, while for tunnels of average length, the global traffic risk threshold can be set at 0.8.

[0122] The accident frequency of a tunnel over the past five years is calculated. Frequent accidents indicate a low risk tolerance for the tunnel, and a lower global traffic risk threshold should be set. Otherwise, the threshold can be appropriately relaxed. For example, if a tunnel experiences more than five accidents annually, the global traffic risk threshold can be set at 0.75. Otherwise, the threshold can be appropriately relaxed.

[0123] S44. Trigger a global warning when the global traffic risk exceeds the global traffic risk threshold.

[0124] Specifically, in this embodiment, when the global traffic risk exceeds the global traffic risk threshold, a global warning sound is triggered to implement a global risk warning.

[0125] S45. Trigger a bicycle warning when the bicycle risk exceeds the bicycle risk safety threshold.

[0126] Specifically, in this embodiment, when the bicycle risk exceeds the bicycle risk safety threshold, the corresponding vehicle will be marked red and a bicycle warning sound will be triggered to implement a bicycle risk warning.

[0127] This embodiment also forms a multi-level early warning mechanism by setting a single-vehicle risk threshold and a global traffic risk threshold, which can promptly remind management personnel to pay attention to the traffic safety conditions in the tunnel and quickly locate problem vehicles.

[0128] It should be noted that, in some cases, the actions described in the specification can be performed in a different order and still achieve the desired results. In this embodiment, the order of steps given is only to make the embodiment appear clearer and easier to explain, rather than to limit it.

[0129] In an alternative embodiment, see Figure 2 In order to improve the efficiency of the highway tunnel traffic operation environment safety evaluation and the practicality of the present method, the present invention also provides a highway tunnel traffic operation environment safety evaluation system, which includes: a data acquisition device 1, a data output device 2, a processor 3 and a storage 4, the storage 4 includes a computer-readable storage medium, the computer-readable storage medium stores a computer program, the computer program includes program instructions, and when the program instructions are executed by the processor 3, the processor 3 implements the highway tunnel traffic operation environment safety evaluation method provided by the present invention.

[0130] In summary, this embodiment provides an optional new method for evaluating the safety of the traffic operation environment in a single-lane highway tunnel.

[0131] First, based on the intelligent driving model, this method further considers factors such as vehicle type and lighting conditions at the vehicle's location to calculate the following distance reference value, making the calculated following distance reference value more consistent with the actual situation and helping to improve the accuracy of the subsequent global optimal following position and speed.

[0132] Then, this method sets the state equilibrium equation with the goal of balancing traffic safety and traffic efficiency, and uses the gradient descent method to obtain the global optimal following distance and speed under the constraints of lane speed limit and braking distance. It takes into account both the safety of driving in the tunnel and the traffic efficiency, which is conducive to improving the accuracy of traffic environment safety evaluation in single-lane highway tunnels.

[0133] Next, this method uses the global optimal following distance and speed of each vehicle as a reference and compares it with the real-time traffic operation data in the tunnel. The safety of the tunnel traffic operation environment is evaluated by calculating the risk of each vehicle and the global traffic risk.

[0134] Finally, this method sets corresponding risk thresholds and constructs a dynamic digital twin model of a single-lane highway tunnel, realizing the visualization of risk assessment results and real-time early warning, enabling managers to understand the traffic safety status in the tunnel in real time and intuitively.

[0135] In addition, this embodiment also provides a system compatible with the method, which improves the efficiency of the safety evaluation of the highway tunnel traffic operation environment and the practicality of the method.

[0136] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or make equivalent replacements for some or all of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the claims and description of the present invention.

Claims

1. A method for evaluating the safety of traffic operation environment in a highway tunnel, characterized in that: The steps include: Acquiring basic data and traffic operation data of a target single-lane highway tunnel, wherein the traffic operation data includes vehicle position, vehicle speed, physical load, vehicle type, and vehicle density; Get the following distance reference value; Setting a traffic safety item based on the following distance of the vehicle and the following distance reference value, and setting a traffic efficiency item based on the vehicle speed and the expected speed; The traffic safety term can be expressed as , the traffic efficiency term can be expressed as , N is the total number of vehicles, is the following distance of the i-th vehicle, is the reference value of the following distance of the i-th vehicle, is the vehicle speed of the i-th vehicle, is the expected vehicle speed; Setting weights for the traffic safety item and the traffic efficiency item based on the vehicle density and the critical vehicle density, and then using the weighted sum of the traffic safety item and the traffic efficiency item as a state balance equation for calculating a global risk state score; The weights of the traffic safety item and the traffic efficiency item are used in turn and Indicates that the weight of the traffic safety item and the state balance equation satisfy the following relationships: Among them, Q is the global risk status score, is the vehicle density, is the critical vehicle density, , The maximum speed limit for the lane, is the minimum speed limit of the lane, when i=1, ; Calculating the partial derivatives of the global risk state score with respect to the following distance and the vehicle speed, respectively, and then updating the following distance and the vehicle speed according to the gradient descent method under the constraints; Substituting the updated following distance and vehicle speed into the state balance equation to calculate the global risk state score, and outputting the global optimal following distance and global optimal following speed when the maximum number of iterations is reached or the convergence condition is met; adjusting the vehicle position of the rear vehicle between two adjacent vehicles according to the global optimal following distance to obtain the global optimal following position of the rear vehicle between the two adjacent vehicles; Calculating a single vehicle risk and a global traffic risk based on the traffic operation data, the global optimal following vehicle position, and the global optimal following vehicle speed; A dynamic digital twin model of the target single-lane highway tunnel is constructed using the basic data and the traffic operation data, and the risk assessment results are then visualized.

2. A highway tunnel traffic operation environment safety evaluation method according to claim 1, characterized in that: The method of obtaining the following vehicle distance reference value comprises the following steps: Determine the lighting conditions at the vehicle's location; The safety distance formula in the intelligent driving model is improved according to the light conditions, and then the following distance reference value is calculated.

3. A highway tunnel traffic operation environment safety assessment method according to claim 1, characterized in that: The constraints include lane speed limit and braking distance constraint.

4. A highway tunnel traffic operation environment safety assessment method according to claim 1, characterized in that: Calculating the single vehicle risk and the global traffic risk based on the traffic operation data, the global optimal following vehicle position, and the global optimal following vehicle speed comprises the following steps: A distance deviation term is set according to the actual following distance of the vehicle and the global optimal following distance, and a speed deviation term is set according to the actual vehicle speed of the vehicle and the global optimal following speed, and a weighted sum of the distance deviation term and the speed deviation term is used as the single vehicle risk; The average bicycle risk is calculated as a bicycle risk item, the vehicle density and the critical vehicle density are used to set a density risk item, and a weighted sum of the bicycle risk item and the density risk item is used as the global traffic risk.

5. A highway tunnel traffic operation environment safety assessment method according to claim 1, characterized in that: The step of constructing a dynamic digital twin model of the target single-lane highway tunnel using the basic data and the traffic operation data, and then visually displaying the risk assessment results, comprises the following steps: Constructing a dynamic digital twin model of the target single-lane highway tunnel using the basic data and the traffic operation data; The single-vehicle risk and the global traffic risk are marked on the dynamic digital twin model of the target single-lane highway tunnel, and the risk assessment results are visualized.

6. A highway tunnel traffic operation environment safety assessment method according to claim 5, characterized in that: The step of constructing a dynamic digital twin model of the target single-lane highway tunnel using the basic data and the traffic operation data, and then visually displaying the risk assessment results, further includes the following steps: Set a single-vehicle risk threshold and a global traffic risk threshold; When the global traffic risk exceeds the global traffic risk threshold, a global warning is triggered; When the bicycle risk exceeds the bicycle risk safety threshold, a bicycle warning is triggered.

7. A highway tunnel traffic operation environment safety evaluation system, characterized by: The highway tunnel traffic operation environment safety assessment system includes: a data acquisition device, a data output device, a processor and a storage device, the storage device includes a computer-readable storage medium, the computer-readable storage medium stores a computer program, the computer program includes program instructions, and when the program instructions are executed by the processor, the processor implements the highway tunnel traffic operation environment safety assessment method according to any one of claims 1 to 6.

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