A method and system for generating road diversion suggestions based on road network safety assessment

Abstract

This invention belongs to the field of traffic control and relates to a method and system for generating road diversion suggestions based on road network safety assessment. The method includes: collecting traffic data through various types of sensors and processing the traffic data to obtain scenario-based traffic data; the scenario-based traffic data includes diversion zone data and merging zone data; performing road network safety assessment on the scenario-based traffic data to obtain road network safety assessment results; the road network safety assessment results include diversion zone assessment results and merging zone assessment results; performing scenario-based diversion processing based on the road network safety assessment results to obtain diversion guidance strategies; the diversion guidance strategies include diversion zone guidance strategies and merging zone guidance strategies; executing the diversion guidance strategies through diversion equipment and continuously optimizing the road network safety assessment results based on the diversion effect; thereby improving scenario adaptability and enhancing the correlation between diversion suggestions and actual safety requirements.

Description

Technical Field

[0001] This invention relates to the field of traffic control, and specifically discloses a method and system for generating road diversion suggestions based on road network safety assessment. Background Technology

[0002] Current road network diversion technologies suffer from three major scenario-based pain points: First, there is a lack of guidance in low-visibility areas during diversion zones. In scenarios such as heavy fog, rain, snow, and nighttime, lane lines and outlines are blurred. Traditional diversion relies solely on manual instructions and lacks dedicated intelligent guidance equipment to enhance lane outlines, leading to untimely lane change preparations and a high risk of vehicles veering off the road. Second, there is a lack of prediction for merging accidents in merging zones. Differences in vehicle speed / volume between the main line and ramps in merging zones can easily cause traffic flow disturbances. The possibility of merging accidents cannot be accurately predicted, relying solely on post-event handling and failing to control vehicle speed and merging time in advance. Finally, there is insufficient guidance coordination. The guidance mode is not linked to real-time / expected traffic flow, resulting in a disconnect between diversion suggestions and actual safety requirements.

[0003] In view of this, the present invention provides a method and system for generating road diversion suggestions based on road network safety assessment, which improves scenario adaptability and enhances the correlation between diversion suggestions and actual safety requirements. Summary of the Invention

[0004] The purpose of this invention is to provide a method for generating road diversion suggestions based on road network safety assessment, addressing the problem of how to optimize guidance strategies in low-visibility scenarios within diversion zones, combining real-time traffic flow data to guide vehicles and prevent accidents. The specific solution is as follows:

[0005] A method for generating road diversion suggestions based on road network safety assessment includes: collecting traffic data through various types of sensors and processing the traffic data to obtain scenario-based traffic data; the scenario-based traffic data includes diversion zone data and merging zone data; performing road network safety assessment on the scenario-based traffic data to obtain road network safety assessment results; the road network safety assessment results include diversion zone assessment results and merging zone assessment results; performing scenario-based diversion processing based on the road network safety assessment results to obtain diversion guidance strategies; the diversion guidance strategies include diversion zone guidance strategies and merging zone guidance strategies; executing the diversion guidance strategies through diversion devices, and continuously optimizing the road network safety assessment results based on the diversion effect.

[0006] Furthermore, the diversion zone data includes basic traffic data, environmental data, and equipment status data: basic traffic data includes traffic flow, vehicle speed, and vehicle type distribution; environmental data includes visibility and weather type; equipment status data includes the operational status of guide lights, variable message signs, and broadcasts; merging data includes road condition data and time data: road condition data includes merging lane flow, ramp flow, mainline speed, ramp speed, and lane occupancy rate; event data includes the frequency and duration of merging conflict events.

[0007] Furthermore, the process of processing traffic data to obtain scenario-based traffic data includes: cleaning the traffic data to remove abnormal data and obtaining preprocessed traffic data; adding scenario tags to the preprocessed traffic data to obtain scenario-based traffic data; the scenario tags include merging and diverging tags and weather tags; the merging and diverging tags are related to the diversion and merging functions of roads; the weather tags are related to visibility.

[0008] Furthermore, the diversion zone assessment results are obtained, including: performing multi-dimensional statistical analysis on early warning events in the diversion zone data to obtain a heatmap of event frequency; the early warning events are related to visibility and traffic flow; matching the current visibility and current traffic flow to multiple diversion safety levels to obtain the current diversion safety level; constructing the diversion zone assessment results based on the current diversion safety level; and obtaining the merging zone assessment results, including: processing the merging zone data using a random forest model to obtain the predicted probability of lane merging accidents; matching the predicted probability of current lane merging accidents and the current lane occupancy rate to multiple merging safety levels to obtain the current merging safety level; and constructing the merging zone assessment results based on the current merging safety level.

[0009] Furthermore, diversion guidance strategies are implemented through diversion equipment, and the road network safety assessment results are continuously optimized based on the diversion effect. This includes: obtaining the execution results of diversion suggestions; the execution results of diversion suggestions include the operating status of diversion equipment, the actual number of diverted vehicles, and the driver feedback rate; calculating safety and efficiency indicators based on the execution results of diversion suggestions; optimizing multiple diversion safety level intervals and / or multiple merging safety level intervals based on the safety and efficiency indicators; and conducting road network safety assessment based on the new multiple diversion safety levels and / or new multiple merging safety levels.

[0010] This invention also provides a road diversion suggestion generation system based on road network safety assessment, including a scenario-based module, an assessment module, a measurement generation module, and an optimization module. The scenario-based module collects traffic data using various types of sensors and processes the traffic data to obtain scenario-based traffic data. The scenario-based traffic data includes diversion zone data and merging zone data. The assessment module performs road network safety assessment on the scenario-based traffic data to obtain road network safety assessment results. The road network safety assessment results include diversion zone assessment results and merging zone assessment results. The measurement generation module performs scenario-based diversion processing based on the road network safety assessment results to obtain diversion guidance strategies. The diversion guidance strategies include diversion zone guidance strategies and merging zone guidance strategies. The optimization module executes the diversion guidance strategies through diversion devices and continuously optimizes the road network safety assessment results based on the diversion effect.

[0011] Furthermore, the diversion zone data includes basic traffic data, environmental data, and equipment status data: basic traffic data includes traffic flow, vehicle speed, and vehicle type distribution; environmental data includes visibility and weather type; equipment status data includes the operational status of guide lights, variable message signs, and broadcasts; merging data includes road condition data and time data: road condition data includes merging lane flow, ramp flow, mainline speed, ramp speed, and lane occupancy rate; event data includes the frequency and duration of merging conflict events.

[0012] Furthermore, the scenario-based module includes a data processing unit and a tag adding unit; the data processing unit is used to clean the traffic data, remove abnormal data, and obtain preprocessed traffic data; the tag adding unit is used to add scenario tags to the preprocessed traffic data to obtain scenario-based traffic data; the scenario tags include merging and diverging tags and weather tags; the merging and diverging tags are related to the diversion and merging functions of the road; the weather tags are related to visibility.

[0013] Furthermore, the judgment module includes a diversion area judgment unit and a merging area judgment unit. The diversion area judgment unit is used to obtain diversion area judgment results, including: performing multi-dimensional statistical analysis based on early warning events in the diversion area data to obtain an event frequency heatmap; the early warning events are related to visibility and traffic flow; matching the current visibility and current traffic flow to multiple diversion safety levels to obtain the current diversion safety level; and constructing diversion area judgment results based on the current diversion safety level. The merging area judgment unit is used to obtain merging area judgment results, including: processing the merging area data using a random forest model to obtain the predicted probability of lane merging accidents; matching the current predicted probability of lane merging accidents and the current lane occupancy rate to multiple merging safety levels to obtain the current merging safety level; and constructing merging area judgment results based on the current merging safety level.

[0014] Furthermore, the optimization module includes an execution result acquisition unit, an indicator calculation unit, an optimization unit, and a loop unit; the execution result acquisition unit is used to acquire the diversion suggestion execution result; the diversion suggestion execution result includes the diversion equipment operating status, the actual number of diverted vehicles, and the driver feedback rate; the indicator calculation unit is used to calculate safety indicators and efficiency indicators based on the diversion suggestion execution result; the optimization unit is used to optimize multiple diversion safety level intervals and / or multiple merging safety level intervals based on the safety indicators and efficiency indicators; the loop unit is used to perform road network safety assessment based on the new multiple diversion safety levels and / or new multiple merging safety levels.

[0015] The present invention has the following advantages and beneficial effects:

[0016] This invention shortens the vehicle's lane-changing preparation time and reduces the probability of driving out of the road boundary in low-visibility scenarios by controlling intelligent diversion equipment.

[0017] This invention can improve the accuracy of predicting merging accidents, shorten the accident response time, and improve the traffic efficiency of merging areas. Attached Figure Description

[0018] Figure 1 This is an exemplary flowchart of a road diversion suggestion generation method based on road network safety assessment according to the present invention;

[0019] Figure 2 This is a diagram showing the interface of the GIS map in this invention;

[0020] Figure 3 This is a custom schematic diagram of the early warning logic in the diversion zone guidance strategy of the present invention;

[0021] Figure 4 This is a custom schematic diagram of the early warning logic in the merging zone guidance strategy of the present invention. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0023] Figure 1 This is an exemplary flowchart of a road diversion suggestion generation method based on road network safety assessment according to the present invention. Figure 1 As shown, the road diversion suggestion generation method based on road network safety assessment provided by the present invention includes:

[0024] Traffic data is collected through various types of sensors and processed to obtain contextualized traffic data. Contextualized traffic data includes divergence zone data and merging zone data. These sensors include video monitoring equipment, radar monitoring equipment, and meteorological monitoring equipment. Traffic data includes traffic flow data, event data, and weather data. Contextualized traffic data refers to traffic data after divergence and merging annotations. Divergence zone data refers to traffic-related data when roads diverge. Merging data refers to traffic-related data when roads merge. Divergence zone data includes basic traffic data, environmental data, and equipment status data.

[0025] Basic traffic data includes traffic flow, vehicle speed, and vehicle type distribution (including large, medium, and small vehicles). Environmental data includes visibility and weather type; weather type includes fog, rain, snow, and / or nighttime. Equipment status data includes the operational status of guidance lights, variable message signs, and broadcasts. Guidance lights are used to indicate lane contours. Broadcast operational status indicates whether there is a malfunction or not, with 1 indicating normal and 0 indicating a malfunction; broadcasts are used to guide vehicles via voice prompts. Variable message signs are used to display text prompts. Merging data includes road condition data and time data: real-time traffic flow data of the right lane of the main road is collected through roadside sensors and / or cameras, including merging lane flow, ramp flow, main road speed, ramp speed, and lane occupancy. Event data of lane merging conflict events (e.g., vehicles driving side-by-side at close range) is collected through video and / or radar monitoring, including the frequency and duration of lane merging conflict events.

[0026] In some embodiments, processing traffic data to obtain scenario-based traffic data includes: cleaning the traffic data to remove abnormal data, resulting in preprocessed traffic data. Data cleaning includes removing traffic flow data exceeding the maximum traffic flow threshold and abnormally congested speed data below the minimum speed. Preprocessed traffic data refers to data after removing abnormal data. Scenario labels are added to the preprocessed traffic data to obtain scenario-based traffic data; scenario labels include merging and diverging labels (diverging areas are assigned 1, merging areas are assigned 2) and weather labels (low visibility is assigned 1, normal visibility is assigned 0); merging and diverging labels are related to the diversion and merging functions of roads; weather labels are related to visibility. Scenario-based traffic data refers to traffic data after labeling merging and diverging scenarios and weather. For example, scenario-based traffic data can be... ,in, Represents contextualized traffic data. This represents traffic data for the diversion zone; , Indicates traffic flow. Indicates vehicle speed. Indicates vehicle model distribution. Indicates visibility. Indicates the weather type. Indicates the broadcast's operational status; Traffic data representing the merging zone ; This indicates the traffic flow in the right lane of the main road. Indicates the ramp flow rate. Indicates the speed of the main line. Indicates the speed of vehicles on the ramp. Indicates lane occupancy rate. Indicates the frequency of lane merging conflict incidents. Indicates the duration of the lane merging conflict. This indicates the operational status of the broadcast.

[0027] Road network safety assessment is performed on the scenario-based traffic data to obtain road network safety assessment results. These results include divergence zone assessment results and merging zone assessment results. The road network safety assessment results refer to the results obtained after judging road network safety. Road network safety can be divided into multiple levels, and the assessment result indicates the range of road network safety levels to which the current road network safety status falls. Divergence zone assessment results refer to the road network safety level to which the safety status of the road network in the divergence zone falls. Merging zone assessment results refer to the road network safety level to which the safety status of the road network in the merging zone falls.

[0028] In some embodiments, obtaining the diversion zone assessment results includes: performing multi-dimensional statistical analysis based on the warning events in the diversion zone data to obtain a heatmap of event frequency. The warning events are related to visibility and traffic flow; for example, events with visibility below a visibility threshold and traffic flow above a traffic flow threshold can be used as warning events. Statistical analysis can be performed from three dimensions: time (morning peak or holidays), region, and event type (low visibility or congestion) to output a heatmap of event frequency. For example, the heatmap value for low visibility events in the diversion zone during the morning peak hours of 7-9 am. The current visibility and current traffic flow are matched to multiple diversion safety levels to obtain the current diversion safety level. Current visibility refers to the visibility at the current time. Current traffic flow refers to the traffic flow at the current time. Multiple diversion safety levels can include multiple safety levels. For example, the initial multiple diversion safety levels can include high-risk diversion, medium-risk diversion, and low-risk diversion; low-risk diversion... This can refer to visibility greater than or equal to 500m and traffic flow less than or equal to 1200 standard vehicle equivalents per hour: Risk during traffic diversion. This refers to visibility greater than or equal to 200 meters and less than or equal to 500 meters, with traffic flow greater than 1200 standard vehicle equivalents per hour and less than or equal to 1800 standard vehicle equivalents per hour; high-risk diversion. This refers to visibility less than 200m and traffic flow greater than 1800 standard vehicle equivalents per hour. Based on the current diversion safety level, a diversion zone assessment result is constructed. The diversion zone assessment result includes the diversion safety level, heat map, and expected traffic flow for the next hour.

[0029] The merging zone assessment results include: processing the merging zone data using a random forest model to obtain the predicted probability of lane merging accidents. This predicted probability is used to quantify the likelihood of an accident occurring during a lane merging maneuver. The traffic flow in the right lane of the mainline can be used to... Ramp flow Mainline speed Ramp speed Frequency of lane merging and collision incidents Input a trained random forest model, and the model outputs the predicted probability of lane merging accidents.

[0030] ;

[0031] in, represents the predicted probability of a lane merging accident; i represents the decision tree variable; n represents the total number of decision trees; Let be the weight of the decision tree for the i-th lesson; represents the output of the i-th decision tree; X is the input feature vector. The current lane merging accident prediction probability and the current lane occupancy rate are matched to multiple merging safety levels to obtain the current merging safety level. The current lane merging accident prediction probability represents the probability that a lane merging accident may occur. The current lane occupancy rate represents the percentage of lanes occupied at the current time. Multiple merging safety levels can include multiple traffic safety-related levels at merging times, including high-risk, medium-risk, and low-risk merging. High-risk merging refers to a lane merging accident prediction probability greater than or equal to 30% or a lane occupancy rate greater than or equal to 80%; medium-risk merging refers to a lane merging accident prediction probability greater than or equal to 15% and less than 30% or a lane occupancy rate greater than or equal to 60% and less than 80%; low-risk merging refers to a lane merging accident prediction probability less than 15% and a lane occupancy rate less than 60%. The current merging safety level refers to the merging safety level at the current time. In some embodiments, the system also includes visualizing the road network status, presenting the merging and diverging zone safety levels on a GIS map, and outputting traffic condition indicators, such as... Figure 2 As shown, the icon highlighted in white is a safety warning for merging and diverging areas. The appearance of this icon on a road segment indicates a safety hazard at the merging or diverging area. The average traffic speed in the merging area is:

[0032] ;

[0033] in, This indicates the average speed of traffic in the merging zone; Indicates the speed of the main line; This indicates the predicted probability of a merging accident. Based on the current merging safety level, a merging area assessment result is constructed. The merging area assessment result includes the predicted probability of a merging accident, the merging safety level, and the average traffic speed in the merging area.

[0034] Based on the road network safety assessment results, traffic is diverted according to different scenarios to obtain diversion guidance strategies. These strategies include diversion zone guidance strategies and merging zone guidance strategies. Diversion guidance strategies refer to the strategies for diverting vehicles within the road network. Diversion zone guidance strategies refer to the strategies for guiding vehicles to divert from diverting sections, and may include guidance light parameters, variable message sign content, and warning logic. Merging zone guidance strategies refer to the strategies for guiding vehicles to divert from merging sections, and may include warning light frequency, speed limit instructions, and merging prompts.

[0035] Diversion zone guidance strategies can include intelligent guidance light configuration, guidance mode configuration, and customized warning logic. Intelligent guidance light configuration includes: when visibility is below 500m, lane-level road contour enhancement is activated, guidance lights illuminate at 2m intervals, and the light colors are white (contour indication) and yellow (lane change warning); when the merging safety level is high-risk for diversion, the guidance light flashing frequency is increased to 2Hz, illuminating 1km in advance to guide vehicles into the diversion lane. Guidance mode configuration includes: during holidays / inclement weather, a text prompt "High-risk diversion zone ahead, change lanes 2km in advance" is added via variable message signs, and a voice prompt is broadcast every 30 seconds; during off-peak hours, this is simplified to "Caution, maintain safe distance" and is broadcast repeatedly. Figure 3 As shown, the customizable warning logic includes displaying the green text "Caution, Keep Distance" with a synchronized voice prompt when driving normally; displaying the red text "No Stopping, Leave as Soon as Possible" with a high-frequency voice prompt when a vehicle enters the anchorage zone; displaying the red text "Attention, Following Vehicles, Leave as Soon as Possible" with a high-frequency voice prompt when a vehicle is reversing in the anchorage zone; and displaying the yellow text "Congestion Ahead, Slow Down" with a mid-frequency voice prompt when there is traffic congestion on the ramp.

[0036] Merging zone guidance strategies can include intelligent warning light control, speed and merging time control, and customizable warning logic. Intelligent warning light control includes: when merging is at high risk, a 3Hz flashing frequency (red) indicates that vehicles on the mainline should slow down and vehicles on the ramp should delay merging; when merging is at medium risk, a 2Hz flashing frequency (yellow) indicates that a safe following distance should be maintained. Speed ​​and merging time control includes: for vehicles on the mainline, speed limit instructions are issued via variable message signs. , This indicates a speed limit; for vehicles using ramps, a roadside broadcast will announce, "The current merging risk is high; it is recommended to merge after 10 seconds." Figure 4As shown, the customizable warning logic includes: When a vehicle approaches from the main road and there are no vehicles on the ramp, the main road device issues a green text warning "Caution, keep your distance," while the ramp device issues a yellow text warning "Vehicle approaching from the main road." When a vehicle approaches from the ramp and there are no vehicles on the main road, the main road device issues a yellow text warning "Vehicle approaching from the ramp," while the ramp device issues a green text warning "Caution, keep your distance." In the event of an accident on the main road / ramp, the main road device issues a red text warning "Accident ahead / Ramp accident," and the ramp device issues a red text warning "Accident ahead / Accident on the main road." In case of abnormal driving, the main road device issues a red text warning "Attention following vehicles, drive away as soon as possible," and the ramp device issues a red text warning "Attention following vehicles, drive away as soon as possible." In case of congestion and slow traffic, the main road device issues a yellow text warning "Congestion ahead, slow down," and the ramp device issues a yellow text warning "Congestion ahead, slow down."

[0037] Traffic diversion strategies are implemented using diversion devices, and the road network safety assessment results are continuously optimized based on the diversion effects. Diversion devices refer to various traffic equipment used for traffic diversion. For example, diversion devices may include intelligent guidance lights, intelligent warning lights, variable message signs, and roadside broadcasts. Diversion effects refer to the changes in traffic before and after the implementation of diversion strategies.

[0038] In some embodiments, a diversion guidance strategy is executed through diversion equipment, and the road network safety assessment results are continuously optimized based on the diversion effect. This includes: obtaining the execution results of the diversion suggestion; the execution results of the diversion suggestion include equipment operating status, actual number of diverted vehicles, and driver feedback rate. Equipment operating status refers to the real-time working status of the equipment related to road diversion during the execution of the diversion suggestion, which may include information such as whether the equipment is operating normally, fault type, and location. The actual number of diverted vehicles refers to the total number of vehicles that actually traveled according to the diversion suggestion's detour route, which can be obtained by statistical analysis using road monitoring equipment during the execution of the diversion suggestion. The driver feedback rate refers to the proportion of drivers who provided effective feedback on the diversion plan to the total number of drivers passing through the diversion section during that period, which can be collected after the diversion suggestion is executed through channels such as questionnaires, in-vehicle terminal feedback, or hotline calls.

[0039] Based on the results of the traffic splitting recommendations, safety and efficiency metrics are calculated. The safety metrics are:

[0040] ;

[0041] The efficiency indicators are:

[0042] ;

[0043] in, Indicates safety indicators; This represents the accident rate before optimization. This represents the optimized accident rate; Indicates efficiency metrics; This indicates the lane change preparation time before optimization; This indicates the optimized lane change preparation time.

[0044] Based on safety and efficiency indicators, optimize multiple diversion safety level intervals and / or multiple merging safety level intervals. For example, adjust the weights of the difference between mainline speed and ramp speed in the random forest model based on the actual number of diverting vehicles and safety indicators. Another example is increasing the threshold for determining diversion safety level intervals. Conduct road network safety assessments based on the new multiple diversion safety levels and / or new multiple merging safety levels.

[0045] This invention also provides a road diversion suggestion generation system based on road network safety assessment, including a scenario-based module, an assessment module, a measurement generation module, and an optimization module. The scenario-based module collects traffic data using various types of sensors and processes the traffic data to obtain scenario-based traffic data; the scenario-based traffic data includes diversion zone data and merging zone data. The assessment module performs road network safety assessment on the scenario-based traffic data to obtain road network safety assessment results; the road network safety assessment results include diversion zone assessment results and merging zone assessment results. The measurement generation module performs scenario-based diversion processing based on the road network safety assessment results to obtain diversion guidance strategies; the diversion guidance strategies include diversion zone guidance strategies and merging zone guidance strategies. The optimization module executes the diversion guidance strategies through diversion equipment and continuously optimizes the road network safety assessment results based on the diversion effect.

[0046] In some embodiments, the diversion zone data includes basic traffic data, environmental data, and equipment status data: basic traffic data includes traffic flow, vehicle speed, and vehicle type distribution; environmental data includes visibility and weather type; equipment status data includes the operating status of guide lights, variable message signs, and broadcasts; merging data includes road condition data and time data: road condition data includes merging lane flow, ramp flow, mainline speed, ramp speed, and lane occupancy rate; event data includes the frequency and duration of merging conflict events.

[0047] In some embodiments, the scenario-based module includes a data processing unit and a tag adding unit; the data processing unit is used to clean the traffic data, remove abnormal data, and obtain preprocessed traffic data; the tag adding unit is used to add scenario tags to the preprocessed traffic data to obtain scenario-based traffic data; the scenario tags include merging and diverging tags and weather tags; the merging and diverging tags are related to the diversion and merging functions of the road; the weather tags are related to visibility.

[0048] In some embodiments, the judgment module includes a diversion zone judgment unit and a merging zone judgment unit. The diversion zone judgment unit is used to obtain diversion zone judgment results, including: performing multi-dimensional statistical analysis based on warning events in the diversion zone data to obtain a heatmap of event frequency; the warning events are related to visibility and traffic flow; matching the current visibility and current traffic flow to multiple diversion safety levels to obtain the current diversion safety level; and constructing diversion zone judgment results based on the current diversion safety level. The merging zone judgment unit is used to obtain merging zone judgment results, including: processing the merging zone data using a random forest model to obtain the predicted probability of lane merging accidents; matching the predicted probability of current lane merging accidents and the current lane occupancy rate to multiple merging safety levels to obtain the current merging safety level; and constructing merging zone judgment results based on the current merging safety level.

[0049] In some embodiments, the optimization module includes an execution result acquisition unit, an indicator calculation unit, an optimization unit, and a loop unit; the execution result acquisition unit acquires the diversion suggestion execution result; the diversion suggestion execution result includes the diversion equipment operating status, the actual number of diverted vehicles, and the driver feedback rate; the indicator calculation unit calculates safety indicators and efficiency indicators based on the diversion suggestion execution result; the optimization unit optimizes multiple diversion safety level intervals and / or multiple merging safety level intervals based on the safety indicators and efficiency indicators; the loop unit performs road network safety assessment based on the new multiple diversion safety levels and / or new multiple merging safety levels.

[0050] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for generating road diversion suggestions based on road network safety assessment, characterized in that, include: Traffic data is collected by various types of sensors and processed to obtain contextualized traffic data. Contextualized traffic data includes divergence zone data and merging zone data; The scenario-based traffic data is used to perform road network safety assessment, and the road network safety assessment results are obtained. The road network safety assessment results include the assessment results of divergence areas and merging areas; The results of the diversion zone assessment include: Based on the early warning events in the diversion zone data, multi-dimensional statistical analysis is performed to obtain a heatmap of event frequency; the early warning events are related to visibility and traffic flow. The current visibility and current traffic flow are matched to multiple diversion safety levels to obtain the current diversion safety level; Based on the current diversion safety level, construct the diversion area assessment results; The results of the analysis of the merging zone include: A random forest model was used to process the merging zone data to obtain the predicted probability of merging accidents. The current lane merging accident prediction probability and the current lane occupancy rate are matched to multiple merging safety levels to obtain the current merging safety level; Based on the current merging safety level, a merging zone assessment result is constructed; the merging zone assessment result includes the predicted probability of merging accidents, the merging safety level, and the average traffic speed in the merging zone: ； in, This represents the predicted probability of a lane merging accident; i represents the decision tree variable; n represents the total number of decision trees; Let be the weight of the decision tree for the i-th lesson; X represents the output of the i-th decision tree; X is the input feature vector. The average speed in the merging zone is: ； in, This indicates the average speed of traffic in the merging zone; Indicates the speed of the main line; Indicates the predicted probability of a lane merging accident; Based on the road network safety assessment results, traffic diversion is performed in different scenarios to obtain diversion guidance strategies. The diversion guidance strategies include diversion area guidance strategies and merging area guidance strategies. The diversion area guidance strategy includes intelligent guidance light configuration, guidance mode configuration, and customized warning logic. The merging area guidance strategy includes intelligent warning light control, vehicle speed and merging time control, and customized warning logic. The diversion equipment executes diversion guidance strategies, and the road network safety assessment results are continuously optimized based on the diversion effect.

2. The method for generating road diversion suggestions based on road network safety assessment according to claim 1, characterized in that, The diversion zone data includes basic traffic data, environmental data, and equipment status data: Basic traffic data includes traffic flow, vehicle speed, and vehicle type distribution; Environmental data includes visibility and weather type; Equipment status data includes the operating status of guide lights, variable message signs, and broadcasts; Merging data includes traffic data and time data: Traffic data includes merging lane flow, ramp flow, mainline speed, ramp speed, and lane occupancy rate; The event data includes the frequency and duration of lane merging conflict events.

3. The method for generating road diversion suggestions based on road network safety assessment according to claim 1, characterized in that, The process of processing traffic data to obtain contextualized traffic data includes: Traffic data is cleaned to remove outliers, resulting in preprocessed traffic data. Scene labels are added to preprocessed traffic data to obtain scene-based traffic data; scene labels include merging and diverging labels and weather labels; merging and diverging labels are related to the diversion and merging effects of roads; weather labels are related to visibility.

4. The method for generating road diversion suggestions based on road network safety assessment according to claim 1, characterized in that, Traffic diversion and guidance strategies are implemented through diversion devices, and the road network safety assessment results are continuously optimized based on the diversion effects, including: Obtain the results of the diversion suggestion execution; the results include the operating status of the diversion equipment, the actual number of vehicles diverted, and the driver feedback rate. Based on the execution results of the traffic splitting suggestions, safety and efficiency metrics are calculated; the safety metrics are: ； The efficiency index is: ； in, Indicates safety indicators; This represents the accident rate before optimization; This represents the optimized accident rate; Indicates efficiency metrics; This indicates the lane change preparation time before optimization; This indicates the optimized lane change preparation time; Based on safety and efficiency indicators, optimize multiple diversion safety level intervals and / or multiple merging safety level intervals; Road network safety assessment is conducted based on multiple new diversion safety levels and / or multiple new merging safety levels.

5. A road diversion suggestion generation system based on road network safety assessment, characterized in that, It includes a scenario-based module, an analysis module, a measurement generation module, and an optimization module; The scenario-based module is used to collect traffic data through various types of sensors and process the traffic data to obtain scenario-based traffic data; the scenario-based traffic data includes divergence zone data and merging zone data; The analysis module is used to perform road network safety analysis on the scenario-based traffic data and obtain the road network safety analysis result. The road network safety assessment results include the assessment results of divergence areas and merging areas; The results of the diversion zone assessment include: Based on the early warning events in the diversion zone data, multi-dimensional statistical analysis is performed to obtain a heatmap of event frequency; the early warning events are related to visibility and traffic flow. The current visibility and current traffic flow are matched to multiple diversion safety levels to obtain the current diversion safety level; Based on the current diversion safety level, construct the diversion area assessment results; The results of the analysis of the merging zone include: A random forest model was used to process the merging zone data to obtain the predicted probability of merging accidents. The current lane merging accident prediction probability and the current lane occupancy rate are matched to multiple merging safety levels to obtain the current merging safety level; Based on the current merging safety level, a merging zone assessment result is constructed; the merging zone assessment result includes the predicted probability of merging accidents, the merging safety level, and the average traffic speed in the merging zone: ； in, This represents the predicted probability of a lane merging accident; i represents the decision tree variable; n represents the total number of decision trees; Let be the weight of the decision tree for the i-th lesson; X represents the output of the i-th decision tree; X is the input feature vector. The average speed in the merging zone is: ； in, This indicates the average speed of traffic in the merging zone; Indicates the speed of the main line; Indicates the predicted probability of a lane merging accident; The measurement generation module is used to perform scenario-based traffic diversion processing based on road network safety assessment results to obtain diversion guidance strategies. The diversion guidance strategies include diversion zone guidance strategies and merging zone guidance strategies. The diversion zone guidance strategy includes intelligent guidance light configuration, guidance mode configuration, and customized warning logic. The merging zone guidance strategy includes intelligent warning light control, vehicle speed and merging time control, and customized warning logic. The optimization module is used to execute diversion guidance strategies through diversion devices and continuously optimize the road network safety assessment results based on the diversion effect.

6. The road diversion suggestion generation system based on road network safety assessment according to claim 5, characterized in that, The diversion zone data includes basic traffic data, environmental data, and equipment status data: Basic traffic data includes traffic flow, vehicle speed, and vehicle type distribution; Environmental data includes visibility and weather type; Equipment status data includes the operating status of guide lights, variable message signs, and broadcasts; Merging data includes traffic data and time data: Traffic data includes merging lane flow, ramp flow, mainline speed, ramp speed, and lane occupancy rate; The event data includes the frequency and duration of lane merging conflict events.

7. The road diversion suggestion generation system based on road network safety assessment according to claim 5, characterized in that, The scenario-based module includes a data processing unit and a tag adding unit; The data processing unit is used to clean the traffic data, remove abnormal data, and obtain preprocessed traffic data. The tag adding unit is used to add scene tags to the preprocessed traffic data to obtain scene-based traffic data; the scene tags include merging and diverging tags and weather tags; the merging and diverging tags are related to the diversion and merging effects of roads; the weather tags are related to visibility.

8. The road diversion suggestion generation system based on road network safety assessment according to claim 5, characterized in that, The optimization module includes an execution result acquisition unit, an indicator calculation unit, an optimization unit, and a loop unit; The execution result is used to obtain the diversion suggestion execution result from the unit; the diversion suggestion execution result includes the diversion equipment operating status, the actual number of diverted vehicles, and the driver feedback rate; The indicator calculation unit is used to calculate safety indicators and efficiency indicators based on the execution results of the traffic splitting suggestions; the safety indicators are: ； The efficiency index is: ； in, Indicates safety indicators; This represents the accident rate before optimization; This represents the optimized accident rate; Indicates efficiency metrics; This indicates the lane change preparation time before optimization; This indicates the optimized lane change preparation time; The optimization unit is used to optimize multiple diversion safety level intervals and / or multiple merging safety level intervals based on safety indicators and efficiency indicators. The cyclic unit is used to assess road network safety based on multiple new diversion safety levels and / or multiple new merging safety levels.

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