Method and system for judging priority of tunnel vehicle parking point of one-way lane

Abstract

The invention discloses a method and system for judging the priority of a tunnel vehicle parking point of a one-way lane, and relates to the technical field of intelligent traffic. In the priority ranking stage, the state of the parking point and the influence of subsequent vehicles are comprehensively considered, so that a scientific and reasonable parking priority sequence is obtained; the method is beneficial for the vehicle to select the stop points according to the optimized sequence, reduces the time consumption for the vehicle to find a proper stop point, improves the overall smoothness of tunnel traffic, balances the use frequency of each stop point, avoids the situation that some stop points are excessively used and other stop points are idle, and improves the visual risk assessment efficiency in the stop point visual risk assessment process. By calculating the visual risk assessment coefficient, the parking point with the high visual risk can be recognized in advance, the visual safety of a driver during parking operation is guaranteed, parking points which do not meet the visual risk requirement are reasonably avoided, and traffic accidents caused by visual disturbance are effectively reduced.

Description

Technical Field

[0001] The present invention relates to the field of intelligent transportation technology, and in particular to a method and system for determining priority of a vehicle stop point in a tunnel of a single lane. Background Art

[0002] As traffic volume increases, the contradiction between vehicle stopping demand and safety management in single-lane tunnels becomes more prominent. Traditional management methods make it difficult to efficiently allocate stopping resources and ensure safety. It is necessary to comprehensively evaluate multiple factors such as vehicle stopping demand, stopping point status, subsequent vehicle risks, and visual risks to scientifically sort the stopping priorities, in order to improve the efficiency and safety of tunnel traffic operations.

[0003] At present, the priority judgment method and system of vehicle stopping points in single-lane tunnels have the following technical problems: 1. In terms of judging the stopping demand, if we only rely on manual observation or single sensor data, there is a lack of multi-mode comprehensive information collection and intelligent judgment, which is not conducive to accurately identifying the vehicle's true stopping intention, and will cause the vehicle to wait or stop illegally, seriously affecting the smoothness of tunnel traffic and even causing traffic accidents.

[0004] 2. In the process of evaluating the status of vehicle stops, the traditional method of determining the priority of tunnel vehicle stops lacks comprehensive consideration and only focuses on individual factors. For example, it only looks at the remaining parking spaces and ignores the comprehensive analysis of the estimated departure time of parked vehicles and the traffic congestion index. This is not conducive to grasping the overall status of the stops and will cause vehicles to gather in areas that seem to have vacancies but are difficult to evacuate subsequently, causing local congestion to worsen. In the event of an emergency, it will be difficult for rescue vehicles to arrive quickly.

[0005] 3. The traditional method of determining the priority of vehicle stops in tunnels lacks the impact assessment on subsequent vehicles, the vehicle behavior parameters and reasonable calculation of risk factors, and the quantitative analysis of the complex dynamic relationship between multiple vehicles. This is not conducive to accurately estimating the degree of interference of subsequent vehicles on the docking operation, and will cause the vehicle to be frequently threatened by the rear vehicles during the docking process, increasing the risk of scratches and collisions, and disrupting the driving order in the tunnel.

[0006] 4. The traditional method of determining the priority of vehicle stops in tunnels lacks the visual risk assessment of each vehicle stop, and lacks the assessment of the light change gradient, high-risk period factors and vehicle visual compensation coefficient. This is not conducive to ensuring the visual safety of drivers when stopping. It will make it difficult for drivers to accurately operate vehicles at stops with poor visual conditions, and it is easy to make parking errors. Visual impairments will cause collisions with surrounding facilities or other vehicles, endangering the lives of people and vehicle safety, and will also reduce the safety and reliability of the overall operation of the tunnel. Summary of the invention

[0007] The purpose of the present invention is to provide a method and system for determining the priority of a vehicle stop point in a single-lane tunnel, which solves the problems existing in the background technology.

[0008] To solve the above technical problems, the present invention adopts the following technical solutions: The present invention provides a method for determining the priority of vehicle stopping points in a single-lane tunnel, comprising: Step 1, obtaining the stopping demand of a moving vehicle: evaluating whether a designated moving vehicle entering a designated tunnel has a stopping demand.

[0009] Step 2: Vehicle stop prediction and evaluation: When a designated vehicle entering a designated tunnel has a stop demand, the real-time status evaluation index of each vehicle stop point in the designated tunnel is calculated.

[0010] Step 3: Risk assessment of subsequent vehicle impact: Collect vehicle behavior parameters corresponding to each vehicle stop point that has entered the designated tunnel, and then calculate the risk impact factor corresponding to each vehicle stop point in the designated tunnel.

[0011] Step 4: Priority sorting: Based on the real-time status evaluation index corresponding to each vehicle stop and the risk impact factor of the corresponding subsequent vehicles in the designated tunnel, the stop priority of each vehicle stop in the designated tunnel is evaluated.

[0012] Step 5: Visual risk assessment of stop points: Based on the stop priority of each vehicle stop point, analyze whether the visual risk of each vehicle stop point in the designated tunnel meets the requirements, so as to complete the arrangement of vehicle stop points for designated vehicles.

[0013] In a second aspect, the present invention provides a single-lane tunnel vehicle stop point priority determination system, comprising: a vehicle stop demand acquisition module for evaluating whether a designated vehicle entering a designated tunnel has a stop demand.

[0014] The vehicle stop prediction and evaluation module is used to calculate the real-time status evaluation index of each vehicle stop point in the designated tunnel when a designated vehicle entering the designated tunnel has a stop demand.

[0015] The subsequent vehicle impact risk assessment module is used to collect vehicle behavior parameters corresponding to each vehicle stop point that has entered the designated tunnel, and then calculate the risk impact factor corresponding to each vehicle stop point in the designated tunnel.

[0016] The priority sorting module is used to evaluate the parking priority of each vehicle stop in the designated tunnel according to the real-time status evaluation index corresponding to each vehicle stop and the risk impact factor of the subsequent vehicles in the designated tunnel.

[0017] The stop point visual risk assessment module is used to analyze whether the stop visual risks corresponding to each vehicle stop point in the designated tunnel meet the requirements according to the stop priority corresponding to each vehicle stop point, so as to complete the vehicle stop point arrangement for the designated moving vehicles.

[0018] The beneficial effects of the present invention are as follows: 1. A method and system for determining priority of vehicle stopping points in a single-lane tunnel provided by the present invention, in the process of determining vehicle stopping demand, combines a variety of methods to assess whether a designated vehicle entering a designated tunnel has a stopping demand. The multi-channel assessment method is conducive to comprehensively and accurately determining whether the vehicle has a stopping demand, avoiding misjudgment due to the limitations of a single judgment method, thereby effectively improving the accuracy and reliability of the entire system's judgment on vehicle stopping demand, ensuring that subsequent processes can be carried out based on correct demand information, and reducing traffic congestion or waste of resources caused by incorrect judgments.

[0019] 2. In the vehicle stop prediction and evaluation stage, the embodiment of the present invention obtains real-time status information such as the number of remaining parking spaces for each vehicle stop in the designated tunnel, the estimated shortest departure time of parked vehicles, and the traffic congestion index, and uses a special calculation formula to calculate the real-time status evaluation index, which is conducive to comprehensively considering various aspects of the stop, so that the evaluation result can more truly reflect the actual carrying capacity and operation status of each stop.

[0020] 3. In the process of collecting vehicle behavior parameters, the embodiment of the present invention uses high-definition cameras in the designated tunnel to obtain information such as the speed, number and distance of vehicles that have entered the set range of each vehicle stop. Through detailed and accurate data support, it is helpful to scientifically quantify the risk level brought by subsequent vehicles, so that the traffic management system can formulate targeted strategies to reduce the probability of accidents such as collisions and interferences during the parking process, thereby ensuring the safety of vehicle driving and parking in the tunnel.

[0021] 4. In the priority sorting stage, the embodiment of the present invention calculates the stop priority coefficient according to the real-time status evaluation index and risk impact factor of each vehicle stop point, and sorts the stops accordingly. By comprehensively considering the stop point's own status and the impact of subsequent vehicles, it is helpful to obtain a scientific and reasonable stop priority sequence, which helps vehicles select stops in an optimized order, reduces the time consumed by vehicles in searching for suitable stops, improves the overall smoothness of tunnel traffic, and balances the usage frequency of each stop point at the same time, avoiding the situation where some stops are overused while other stops are idle.

[0022] 5. In the process of visual risk assessment at a stop, the embodiment of the present invention collects visual risk parameters such as light change gradient, high-risk period factor, and vehicle visual compensation coefficient, and calculates a visual risk assessment coefficient, which is conducive to identifying stops with higher visual risks in advance, ensuring the visual safety of drivers during docking operations, and reasonably avoiding stops that do not meet visual risk requirements, effectively reducing traffic accidents caused by visual impairment. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0024] Figure 1 It is a schematic flow chart of the implementation steps of the present invention.

[0025] Figure 2 It is a schematic diagram of the system structure connection of the present invention. DETAILED DESCRIPTION

[0026] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0027] See also Figure 1 As shown, the present invention provides a method for determining priority of vehicle stopping points in a single-lane tunnel, the method comprising: step one, obtaining stopping demand of a moving vehicle: evaluating whether a designated moving vehicle entering a designated tunnel has a stopping demand.

[0028] In a specific embodiment, the evaluation of whether a designated vehicle entering a designated tunnel has a need to stop is performed as follows: when the designated vehicle has a tunnel driving application installed in the vehicle system and the vehicle information of the designated vehicle is entered in the tunnel driving application, when the designated vehicle enters the designated tunnel, the vehicle information of the designated vehicle is identified by a high-definition camera to determine whether the designated vehicle has a need to stop. If the designated vehicle sends a specific identification signal to the traffic management platform in the designated tunnel, it indicates that the designated vehicle has a need to stop; otherwise, it indicates that the designated vehicle does not have a need to stop.

[0029] If the designated vehicle does not have a tunnel driving application installed in the vehicle system, when the designated vehicle enters the designated tunnel, the vehicle driving status is monitored by a high-definition camera and a speed sensor at each set monitoring time point. The vehicle driving status includes the vehicle speed and the lateral distance from the tunnel wall on the same side of the stop point. The speed and position of the designated vehicle in the single lane corresponding to each detection time point are recorded as and , is the number of each monitoring time point, , is the total number corresponding to the monitoring time point, is a positive integer, and the standard vehicle driving state corresponding to the vehicle stop in the specified tunnel is obtained from the database. The standard vehicle driving state includes the standard vehicle speed and the lateral distance of the tunnel wall on the same side of the standard distance stop point, which are recorded as and , the parking demand corresponding to the specified vehicle is recorded as ,when for When , it indicates that the designated vehicle has no need to stop. for When , it indicates that the specified vehicle has a need to stop, and the vehicle stop status is determined by the expression: , get the parking demand corresponding to the specified vehicle ,in Represents logic and relationship, Indicates logic or relationship, Indicates logical NOT.

[0030] It should be noted that when the designated vehicle has a tunnel driving application installed in the vehicle system and the vehicle information of the designated vehicle is entered in the installed tunnel driving application, it means, for example, that the driver clicks the "I need to stop" option on the vehicle screen, or informs the tunnel vehicle stop point priority judgment system through voice commands that he has a stop demand. If the driver does not click the "I need to stop" option, the tunnel vehicle stop point priority judgment system will not judge the vehicle stop demand of the vehicle driven by the driver.

[0031] Step 2: Vehicle stop prediction and evaluation: When a designated vehicle entering a designated tunnel has a stop demand, the real-time status evaluation index of each vehicle stop point in the designated tunnel is calculated.

[0032] In a specific embodiment, the real-time status evaluation index corresponding to each vehicle stop point in the designated tunnel is calculated, and the specific process is as follows: when a designated vehicle entering the designated tunnel has a stop demand, the real-time status information corresponding to each vehicle stop point in the designated tunnel is obtained, and the real-time status information includes the number of remaining parking spaces, the expected shortest departure time of the parked vehicles, and the traffic congestion index, which are respectively recorded as , and , get the maximum number of vehicles that can be parked at each vehicle stop from the database .

[0033] By calculation formula: , get the real-time status evaluation index of each vehicle stop in the specified tunnel , is the number of each vehicle stop. , is the total number of vehicle stops. is a positive integer, where is a natural number, and They are respectively expressed as the adjustment coefficient corresponding to the expected shortest departure time of parked vehicles and the adjustment coefficient corresponding to the traffic congestion index.

[0034] It should be noted that the number of remaining parking spaces corresponding to each vehicle stop is obtained through the camera at each vehicle stop, and the stop type of the vehicle corresponding to each vehicle stop is obtained through telephone communication. The historical stop time corresponding to each parked vehicle of the same stop type is obtained from the database, and the historical stop time corresponding to each parked vehicle is averaged. The result is the estimated shortest departure time of the parked vehicles corresponding to each vehicle stop, which is calculated by the calculation formula: , is the reference speed corresponding to the specified tunnel obtained from the database, The reference vehicle density corresponding to each vehicle stop in the specified tunnel within the set range obtained from the database, , Respectively expressed as The average vehicle speed and vehicle density corresponding to the set range of each vehicle stop point.

[0035] In the vehicle stop prediction and evaluation stage, the embodiment of the present invention obtains real-time status information such as the number of remaining parking spaces at each vehicle stop in a designated tunnel, the estimated shortest departure time of parked vehicles, and the traffic congestion index, and uses a special calculation formula to calculate the real-time status evaluation index, which is conducive to comprehensively considering various aspects of the stop point, so that the evaluation result can more truly reflect the actual carrying capacity and operating status of each stop point.

[0036] Step 3: Risk assessment of subsequent vehicle impact: Collect vehicle behavior parameters corresponding to each vehicle stop point that has entered the designated tunnel, and then calculate the risk impact factor corresponding to each vehicle stop point in the designated tunnel.

[0037] In a specific embodiment, the vehicle behavior parameters corresponding to each vehicle stop point that has entered the designated tunnel are collected, and the specific process is as follows: the vehicle behavior parameters include the speed and number of each vehicle corresponding to the set range of each vehicle stop point that has entered the designated tunnel, and the distance between each vehicle stop point and each vehicle corresponding to the set range. The vehicle behavior parameters corresponding to each vehicle stop point that has entered the designated tunnel are obtained by a high-definition camera in the designated tunnel. The speed of each vehicle corresponding to the set range of each vehicle stop point that has entered the designated tunnel and the distance between each vehicle stop point and each vehicle corresponding to the set range are respectively calculated by the mean, and the results obtained are the average speed of the corresponding vehicles within the set range of each vehicle stop point that has entered the designated tunnel and the average distance between each vehicle stop point and the corresponding vehicles within the set range, and are recorded as and , the number of vehicles that have entered the designated tunnel within the set range of each vehicle stop is recorded as , the maximum speed of each vehicle within the set range of each vehicle stop point that has entered the designated tunnel and the maximum distance between each vehicle stop point and each vehicle within the set range are recorded as and , obtain the maximum number of vehicles allowed to travel within the set range of each vehicle stop in the specified tunnel from the database, recorded as .

[0038] In a specific embodiment, the risk impact factor corresponding to each vehicle stop point in the specified tunnel is calculated, and the specific process is as follows: by calculating the formula: , and obtain the risk impact factor of each vehicle stop in the specified tunnel ,in , , They are respectively expressed as the weight factor corresponding to the average vehicle speed, the weight factor corresponding to the average distance, and the weight factor corresponding to the number of vehicles.

[0039] It should be noted that , , The values ​​of are all greater than and less than , the process of setting the weight factor is as follows: for example, in a city tunnel, first collect a large number of driving data of vehicles near each stop, including the average speed, average distance and number of vehicles, and record the corresponding traffic conditions, such as whether there has been a scratch and the degree of congestion. If it is found that when the average speed is high, the probability of an accident near the stop increases significantly, indicating that the average speed has a greater impact on the risk, then the weight factor corresponding to the average speed is set to 0.5. When the average distance is within a certain set range, such as too close, although there is an impact, it is relatively small, and the weight factor corresponding to the average distance is set to 0.3. If the increase in the number of vehicles only slightly increases the traffic jam duration, but does not significantly increase the risk of accidents, then the weight factor corresponding to the number of vehicles is set to 0.2.

[0040] In the process of collecting vehicle behavior parameters, the embodiment of the present invention uses high-definition cameras in designated tunnels to obtain information such as the speed, number, and distance from the vehicles that have entered the set range of each vehicle stop. Through detailed and accurate data support, it helps to scientifically quantify the risk level brought by subsequent vehicles, so that the traffic management system can formulate targeted strategies to reduce the probability of accidents such as collisions and interferences during the parking process, thereby ensuring the safety of vehicle driving and parking in tunnels.

[0041] Step 4: Priority sorting: Based on the real-time status evaluation index corresponding to each vehicle stop and the risk impact factor of the corresponding subsequent vehicles in the designated tunnel, the stop priority of each vehicle stop in the designated tunnel is evaluated.

[0042] In a specific embodiment, the stopping priority of each vehicle stop point in the designated tunnel is specifically evaluated as follows: based on the real-time status evaluation index and risk impact factor corresponding to each vehicle stop point in the designated tunnel, the stopping priority coefficient corresponding to each vehicle stop point in the designated tunnel is calculated, and the stopping priority coefficients of each vehicle stop point are sorted in descending order, and the vehicle stop point corresponding to the first-ranked stopping priority coefficient is recorded as the first vehicle stop point, and the vehicle stop point corresponding to the second-ranked stopping priority coefficient is recorded as the second vehicle stop point, so as to obtain the stopping priority of each vehicle stop point in the designated tunnel.

[0043] In a specific embodiment, the calculation obtains the stop priority coefficient corresponding to each vehicle stop point in the specified tunnel, and the specific calculation process is as follows: the maximum real-time state evaluation index, the minimum real-time state evaluation index, the maximum risk impact factor and the minimum risk impact factor are respectively selected from the real-time state evaluation index and the risk impact factor corresponding to each vehicle stop point in the specified tunnel, and are respectively recorded as , , and .

[0044] By calculation formula: , specify the stop priority coefficient for each vehicle stop in the tunnel ,in , They are respectively expressed as the weight factor corresponding to the real-time status assessment index and the weight factor corresponding to the risk impact factor.

[0045] It should be noted that , The values ​​of are all greater than and less than , , The setting process and , , The setting process is the same as , so I will not go into details here.

[0046] In the priority sorting stage, the embodiment of the present invention calculates the stop priority coefficient according to the real-time status evaluation index and risk impact factor of each vehicle stop point, and sorts the stop points accordingly. By comprehensively considering the stop point's own status and the impact of subsequent vehicles, it is helpful to obtain a scientific and reasonable stop priority sequence, which helps vehicles select stops in an optimized order, reduces the time consumed by vehicles in searching for suitable stops, improves the overall smoothness of tunnel traffic, and balances the usage frequency of each stop point at the same time, avoiding the situation where some stops are overused while other stops are idle.

[0047] Step 5: Visual risk assessment of stop points: Based on the stop priority corresponding to each vehicle stop point, analyze whether the visual risk corresponding to each vehicle stop point in the designated tunnel meets the requirements, so as to complete the arrangement of vehicle stop points for designated vehicles.

[0048] In a specific embodiment, the analysis specifies whether the visual risk of parking corresponding to each vehicle stop point in the tunnel meets the requirements. The specific analysis process is as follows: collect visual risk parameters corresponding to each vehicle stop point, the visual risk parameters include light change gradient, high risk period factor and vehicle vision compensation coefficient, and then calculate the visual risk assessment coefficient corresponding to each vehicle stop point in the specified tunnel, obtain the standard visual risk assessment coefficient threshold of the corresponding vehicle stop point in the specified tunnel from the database, and compare the visual risk assessment coefficient corresponding to each vehicle stop point in the specified tunnel with the standard visual risk assessment coefficient threshold. If the visual risk assessment coefficient corresponding to each vehicle stop point in the specified tunnel is greater than or equal to the standard visual risk assessment coefficient threshold, it indicates that the parking visual risk corresponding to the vehicle stop point does not meet the requirements. Otherwise, it indicates that the parking visual risk corresponding to the vehicle stop point meets the requirements.

[0049] If the parking visual risk corresponding to the first vehicle stop point does not meet the requirements, it means that the first vehicle stop point does not meet the parking requirements of the designated moving vehicle, and the designated moving vehicle will be arranged to stop at the second vehicle stop point, so as to obtain a vehicle stop point that meets the parking requirements of the designated moving vehicle.

[0050] It should be noted that the collection process of visual risk parameters corresponding to each vehicle stop is as follows: For example, the light change gradient is determined by setting light intensity sensors at different positions in the tunnel, with a light intensity sensor installed every 50 meters. The light intensity sensor monitors and transmits light data to the tunnel vehicle stop priority judgment system in real time, and calculates the light intensity change within a unit distance by comparing the data of adjacent light intensity sensors. At the entrance of a certain tunnel, the light intensity of the first light intensity sensor is 500 lux, and the light intensity of the sensor at 50 meters is 300 lux, then the light change gradient The degree is (500-300) ÷ 50 = 4 lux / meter; the high-risk period factor is pre-set based on the sunrise and sunset time of the tunnel area, the historical accident-prone period and other information. The high-risk period factor within 1 hour before and after sunset in the area where a tunnel is located is set to 1, and the other periods are set to 0. The vehicle vision compensation coefficient is detected by vehicle detection equipment to detect vehicle headlight brightness, window transmittance and other information. If the headlight brightness of a vehicle meets the standard and the window transmittance is good, the comprehensive assessment of its vehicle vision compensation coefficient is 0.8. If the headlights are dim and the window film is too deep, affecting the line of sight, the coefficient is as low as 0.3.

[0051] In a specific embodiment, the visual risk assessment coefficient corresponding to each vehicle stop point in the specified tunnel is calculated as follows: by the calculation formula: , and obtain the visual risk assessment coefficient corresponding to each vehicle stop in the specified tunnel ,in , , Respectively expressed as The light change gradient, high-risk period factor, and vehicle vision compensation coefficient corresponding to each vehicle stop point are Expressed as The average change in light intensity during the high-risk period corresponding to each vehicle stop is , , They are respectively expressed as the adjustment coefficient corresponding to the light change gradient, the adjustment coefficient corresponding to the high-risk period factor, and the adjustment coefficient corresponding to the vehicle vision compensation coefficient. , , They are respectively the weight factor corresponding to the set light change gradient, the weight factor corresponding to the high-risk time period factor, and the weight factor corresponding to the vehicle vision compensation coefficient.

[0052] It should be noted that , , The values ​​of are all greater than and less than , , , The setting process and , , The setting process is the same as , so I will not go into details here.

[0053] It should also be noted that The value of or For example, set the 30 minutes before and after sunrise and sunset as the high-risk period. If the current time is within this range, then , otherwise , set each collection time point during the high-risk period, and obtain the light intensity of each vehicle stop corresponding to each collection time point through sensor collection, select the maximum light intensity and minimum light intensity of each vehicle stop corresponding to each collection time point, and calculate the difference to obtain the average change of light intensity of each vehicle stop during the high-risk period.

[0054] It should also be noted that the process of obtaining the adjustment coefficient corresponding to the light change gradient, the adjustment coefficient corresponding to the high-risk time period factor, and the adjustment coefficient corresponding to the vehicle visual compensation coefficient is as follows: for example, the accident frequency under different light change gradients is collected. When it is found that the light change gradient is above 5 lux / m, the accident rate increases significantly. By fitting the curve, the adjustment coefficient in the gradient range above 5 lux / m is set to 0.6, and the adjustment coefficient below 5 lux / m is set to 0.3. The adjustment coefficient corresponding to the high-risk time period factor is determined according to the proportion of accidents in different time periods. For example, it is found that accidents occurring in high-risk time periods account for 60% of all accidents throughout the day. The adjustment coefficient corresponding to the high-risk time period factor is set to 0.6, and the adjustment coefficient corresponding to the non-high-risk time period is set to 0.4. The adjustment coefficient corresponding to the vehicle visual compensation coefficient is obtained through vehicle equipment detection and accident correlation analysis. For example, accident tracking is performed on vehicles with high vehicle visual compensation coefficients. Vehicles with high vehicle visual compensation coefficients refer to vehicles with good vehicle lighting and vision. If it is found that vehicles with high vehicle visual compensation coefficients account for a low proportion of accidents, their adjustment coefficients are increased accordingly, such as 0.7. The adjustment coefficient corresponding to vehicles with low vehicle visual compensation coefficients is set to 0.3.

[0055] It should also be noted that It is used to adjust the parameters of the light gradient function shape. By changing its own value, it affects the function curve trend of the light gradient contribution to the overall visual risk level, avoiding unreasonable overestimation or underestimation of the impact of this item on the visual risk level due to excessive or small light gradient. Represents the range of light intensity fluctuations during high-risk periods, and is used to measure the instability of the light environment during high-risk periods. The value directly reflects the magnitude of changes in lighting conditions during high-risk periods. The regulation effect is nonlinear, for example, when When smaller, The proportion in the denominator is relatively large. caused by small changes in The change is gentle, such as: , When ,like ,but , doubled, but The growth rate is relatively small.

[0056] During the visual risk assessment process of a stop point, the embodiment of the present invention collects visual risk parameters such as light change gradient, high-risk time period factor and vehicle vision compensation coefficient and calculates the visual risk assessment coefficient, which is conducive to identifying stops with higher visual risks in advance, ensuring the visual safety of the driver during docking operations, and reasonably avoiding stops that do not meet the visual risk requirements, effectively reducing traffic accidents caused by visual impairment.

[0057] See also Figure 2 As shown, a single-lane tunnel vehicle stop point priority judgment system includes the following modules: a moving vehicle stop demand acquisition module, a vehicle stop prediction and evaluation module, a subsequent vehicle impact risk assessment module, a priority sorting module, a stop point visual risk assessment module and a database.

[0058] The moving vehicle stop demand acquisition module is connected to the vehicle stop prediction and evaluation module and the database respectively, the vehicle stop prediction and evaluation module is connected to the subsequent vehicle impact risk assessment module and the database respectively, the subsequent vehicle impact risk assessment module is connected to the priority sorting module and the database respectively, the priority sorting module is connected to the stop point visual risk assessment module, and the stop point visual risk assessment module is connected to the database.

[0059] The vehicle stopping demand acquisition module is used to evaluate whether a designated vehicle entering a designated tunnel has a stopping demand.

[0060] The vehicle stop prediction and evaluation module is used to calculate the real-time status evaluation index of each vehicle stop point in the designated tunnel when a designated vehicle entering the designated tunnel has a stop demand.

[0061] The subsequent vehicle impact risk assessment module is used to collect vehicle behavior parameters corresponding to each vehicle stop point that has entered the designated tunnel, and then calculate the risk impact factor corresponding to each vehicle stop point in the designated tunnel.

[0062] The priority sorting module is used to evaluate the parking priority of each vehicle stop in the designated tunnel according to the real-time status evaluation index corresponding to each vehicle stop and the risk impact factor of the subsequent vehicles in the designated tunnel.

[0063] The stop point visual risk assessment module is used to analyze whether the stop visual risks corresponding to each vehicle stop point in the designated tunnel meet the requirements according to the stop priority corresponding to each vehicle stop point, so as to complete the vehicle stop point arrangement for the designated moving vehicles.

[0064] The database is used to store the standard vehicle driving status corresponding to the vehicle stop in the designated tunnel, the standard vehicle driving status includes the standard vehicle speed and the lateral spacing of the tunnel wall on the same side of the standard distance stop point, and also stores the maximum number of vehicles that can be parked corresponding to each vehicle stop point, and also stores the maximum number of vehicles allowed to travel within the set range corresponding to each vehicle stop point in the designated tunnel, and also stores the standard visual risk assessment coefficient threshold value of the vehicle stop point in the designated tunnel, and also stores the reference speed corresponding to the designated tunnel and the reference vehicle density corresponding to each vehicle stop point in the designated tunnel within the set range.

[0065] The present invention provides a method and system for determining priority of vehicle stopping points in a single-lane tunnel. In the process of determining vehicle stopping demand, a plurality of methods are combined to evaluate whether a designated vehicle entering a designated tunnel has a stopping demand. The multi-channel evaluation method is conducive to comprehensively and accurately determining whether the vehicle has a stopping demand, avoiding misjudgment due to the limitations of a single judgment method, thereby effectively improving the accuracy and reliability of the entire system's judgment on vehicle stopping demand, ensuring that subsequent processes can be carried out based on correct demand information, and reducing traffic congestion or resource waste caused by incorrect judgments.

[0066] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined in this specification, they shall all fall within the protection scope of the present invention.

Claims

1. A method for determining the priority of a vehicle stop point in a single-lane tunnel, characterized in that: include: Assess whether a designated vehicle entering a designated tunnel needs to stop; When a designated vehicle entering a designated tunnel has a need to stop, the real-time status evaluation index of each vehicle stop point in the designated tunnel is calculated; Collect vehicle behavior parameters corresponding to each vehicle stop point that has entered the designated tunnel, and then calculate the risk impact factor corresponding to each vehicle stop point in the designated tunnel; According to the real-time status evaluation index corresponding to each vehicle stop point and the risk impact factor of the corresponding subsequent vehicles in the designated tunnel, the stop priority of each vehicle stop point in the designated tunnel is evaluated; According to the stop priority corresponding to each vehicle stop point, the visual risk corresponding to each vehicle stop point in the designated tunnel is analyzed to see whether it meets the requirements, so as to complete the arrangement of vehicle stop points for designated vehicles.

2. The method for determining the priority of a vehicle stop point in a single lane tunnel according to claim 1, characterized in that: The specific evaluation process of evaluating whether a designated vehicle entering a designated tunnel has a need to stop is as follows: When the designated vehicle has installed a tunnel driving application in the vehicle system and has entered the vehicle information of the designated vehicle in the tunnel driving application, when the designated vehicle enters the designated tunnel, the vehicle information of the designated vehicle is identified by a high-definition camera to determine whether the designated vehicle has a need to stop. If the designated vehicle sends a specific identification signal to the traffic management platform in the designated tunnel, it indicates that the designated vehicle has a need to stop; otherwise, it indicates that the designated vehicle does not have a need to stop. If the designated vehicle does not have a tunnel driving application installed in the vehicle system, when the designated vehicle enters the designated tunnel, the vehicle driving status is monitored by a high-definition camera and a speed sensor at each set monitoring time point. The vehicle driving status includes the vehicle speed and the lateral distance from the tunnel wall on the same side of the stop point. The speed and position of the designated vehicle in the single lane corresponding to each detection time point are recorded as and , is the number of each monitoring time point, , is the total number corresponding to the monitoring time point, is a positive integer, and the standard vehicle driving state corresponding to the vehicle stop in the specified tunnel is obtained from the database. The standard vehicle driving state includes the standard vehicle speed and the lateral distance of the tunnel wall on the same side of the standard distance stop point, which are recorded as and , the parking demand corresponding to the specified vehicle is recorded as ,when for When , it indicates that the designated vehicle has no need to stop. for When , it indicates that the specified vehicle has a need to stop, and the vehicle stop status is determined by the expression: , get the parking demand corresponding to the specified vehicle ,in Represents logic and relationship, Indicates logic or relationship, Indicates logical NOT.

3. The method for determining the priority of a vehicle stop point in a single lane tunnel according to claim 2, characterized in that: The specific process of calculating the real-time status evaluation index corresponding to each vehicle stop point in the specified tunnel is as follows: When a designated vehicle entering a designated tunnel has a parking demand, the real-time status information corresponding to each vehicle parking point in the designated tunnel is obtained. The real-time status information includes the number of remaining parking spaces, the expected shortest departure time of parked vehicles, and the traffic congestion index, which are recorded as , and , get the maximum number of vehicles that can be parked at each vehicle stop from the database ; By calculation formula: , get the real-time status evaluation index of each vehicle stop in the specified tunnel , is the number of each vehicle stop. , is the total number of vehicle stops. is a positive integer, where is a natural number, and They are respectively expressed as the adjustment coefficient corresponding to the expected shortest departure time of parked vehicles and the adjustment coefficient corresponding to the traffic congestion index.

4. The method for determining the priority of a vehicle stop point in a single lane tunnel according to claim 3, characterized in that: The specific process of collecting the vehicle behavior parameters corresponding to each vehicle stop point that has entered the designated tunnel is as follows: The vehicle behavior parameters include the speed and number of each vehicle within the set range of each vehicle stop point that has entered the designated tunnel, as well as the distance between each vehicle stop point and each vehicle within the set range. The vehicle behavior parameters corresponding to each vehicle stop point that has entered the designated tunnel are obtained through a high-definition camera in the designated tunnel. The speed of each vehicle within the set range of each vehicle stop point that has entered the designated tunnel and the distance between each vehicle stop point and each vehicle within the set range are calculated by the average respectively. The result obtained is the average speed of the vehicles within the set range of each vehicle stop point that has entered the designated tunnel and the average distance between each vehicle stop point and the vehicles within the set range, which are recorded as and , the number of vehicles that have entered the designated tunnel within the set range of each vehicle stop is recorded as , the maximum speed of each vehicle within the set range of each vehicle stop point that has entered the designated tunnel and the maximum distance between each vehicle stop point and each vehicle within the set range are recorded as and , obtain the maximum number of vehicles allowed to travel within the set range of each vehicle stop in the specified tunnel from the database, recorded as .

5. The method for determining the priority of a vehicle stop point in a single lane tunnel according to claim 4, characterized in that: The specific process of calculating the risk impact factor corresponding to each vehicle stop in the specified tunnel is as follows: By calculation formula: , and obtain the risk impact factor of each vehicle stop in the specified tunnel ,in , , They are respectively expressed as the weight factor corresponding to the average vehicle speed, the weight factor corresponding to the average distance, and the weight factor corresponding to the number of vehicles.

6. The method for determining the priority of a vehicle stop point in a single lane tunnel according to claim 5, characterized in that: The stop priority of each vehicle stop point in the designated tunnel is evaluated as follows: According to the real-time status assessment index and risk impact factor corresponding to each vehicle stop point in the designated tunnel, the stop priority coefficient corresponding to each vehicle stop point in the designated tunnel is calculated, and the stop priority coefficient of each vehicle stop point is sorted in order from large to small. The vehicle stop point corresponding to the first stop priority coefficient is recorded as the first vehicle stop point, and the vehicle stop point corresponding to the second stop priority coefficient is recorded as the second vehicle stop point, so as to obtain the stop priority of each vehicle stop point in the designated tunnel.

7. The method for determining the priority of a vehicle stop point in a single lane tunnel according to claim 6, characterized in that: The calculation obtains the stop priority coefficient corresponding to each vehicle stop point in the specified tunnel, and the specific calculation process is as follows: The maximum real-time status assessment index, the minimum real-time status assessment index, the maximum risk impact factor and the minimum risk impact factor are selected from the real-time status assessment indexes and risk impact factors corresponding to each vehicle stop point in the designated tunnel, and are recorded as , , and ; By calculation formula: , specify the stop priority coefficient for each vehicle stop in the tunnel ,in , They are respectively expressed as the weight factor corresponding to the real-time status assessment index and the weight factor corresponding to the risk impact factor.

8. The method for determining the priority of a vehicle stop point in a single lane tunnel according to claim 7, characterized in that: The analysis specifies whether the visual risk of each vehicle stop point in the tunnel meets the requirements. The specific analysis process is as follows: The visual risk parameters corresponding to each vehicle stop are collected, and the visual risk parameters include the light change gradient, the high-risk period factor and the vehicle vision compensation coefficient, and then the visual risk assessment coefficient corresponding to each vehicle stop in the specified tunnel is calculated, and the standard visual risk assessment coefficient threshold corresponding to the vehicle stop in the specified tunnel is obtained from the database, and the visual risk assessment coefficient corresponding to each vehicle stop in the specified tunnel is compared with the standard visual risk assessment coefficient threshold. If the visual risk assessment coefficient corresponding to each vehicle stop in the specified tunnel is greater than or equal to the standard visual risk assessment coefficient threshold, it indicates that the parking visual risk corresponding to the vehicle stop does not meet the requirements, otherwise, it indicates that the parking visual risk corresponding to the vehicle stop meets the requirements; If the parking visual risk corresponding to the first vehicle stop point does not meet the requirements, it means that the first vehicle stop point does not meet the parking requirements of the designated moving vehicle, and the designated moving vehicle will be arranged to stop at the second vehicle stop point, so as to obtain a vehicle stop point that meets the parking requirements of the designated moving vehicle.

9. A method for determining priority of a vehicle stop point in a single lane tunnel according to claim 8, characterized in that: The calculation obtains the visual risk assessment coefficient corresponding to each vehicle stop point in the specified tunnel, and the specific process is as follows: By calculation formula: , and obtain the visual risk assessment coefficient corresponding to each vehicle stop in the specified tunnel ,in , , Respectively expressed as The light change gradient, high-risk period factor, and vehicle vision compensation coefficient corresponding to each vehicle stop point are Expressed as The average change in light intensity during the high-risk period corresponding to each vehicle stop is , , They are respectively expressed as the adjustment coefficient corresponding to the light change gradient, the adjustment coefficient corresponding to the high-risk period factor, and the adjustment coefficient corresponding to the vehicle vision compensation coefficient. , , They are respectively the weight factor corresponding to the set light change gradient, the weight factor corresponding to the high-risk time period factor, and the weight factor corresponding to the vehicle vision compensation coefficient.

10. A tunnel vehicle stop point priority determination system for executing the method for determining the priority of a single lane tunnel vehicle stop point according to any one of claims 1 to 9, characterized in that: Includes the following modules: A vehicle stopping demand acquisition module is used to evaluate whether a designated vehicle entering a designated tunnel has a stopping demand; The vehicle stop prediction and evaluation module is used to calculate the real-time status evaluation index of each vehicle stop point in the designated tunnel when a designated vehicle entering the designated tunnel has a stop demand; The subsequent vehicle impact risk assessment module is used to collect vehicle behavior parameters corresponding to each vehicle stop point that has entered the designated tunnel, and then calculate the risk impact factor corresponding to each vehicle stop point in the designated tunnel; A priority sorting module is used to evaluate the parking priority of each vehicle stop in the designated tunnel according to the real-time status evaluation index of each vehicle stop and the risk impact factor of the subsequent vehicle in the designated tunnel; The stop point visual risk assessment module is used to analyze whether the stop visual risks corresponding to each vehicle stop point in the designated tunnel meet the requirements according to the stop priority corresponding to each vehicle stop point, so as to complete the vehicle stop point arrangement for the designated moving vehicles.

Images