A traffic data analysis system based on fusion perception

Abstract

The application relates to the technical field of data analysis, and particularly discloses a traffic data analysis system based on fusion perception, which comprises a data processing module, which analyzes relevant data, predicts the traffic efficiency coefficient interval of a main road and the traffic efficiency coefficient interval of an auxiliary road when a user arrives at a long-congestion road section; and a data analysis module, which analyzes the traffic efficiency coefficient of the main road and the traffic efficiency coefficient of the auxiliary road, and generates a recommended scheme. When a long-congestion road section is congested, the application quantifies the traffic data generated by the main road and the traffic data generated by the auxiliary road in terms of traffic efficiency, carries out fusion analysis, provides a recommended scheme with the shortest predicted traffic time to the user according to the fusion analysis result, and thus saves the driving time of the user for the long-congestion road section.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data analysis, in particular, to a traffic data analysis system based on fusion perception. BACKGROUND

[0002] The expressway is one of the important components of urban traffic, however, due to lane changing, merging or traffic accidents, etc., some sections of the expressway are congested during the morning and evening peak hours, and the congestion caused by the merging of the auxiliary road into the main road will exist in the fixed section during the morning and evening peak hours, especially when the section has multiple auxiliary road merging entrances, which is more likely to cause congestion.

[0003] In addition, one of the characteristics of the expressway is that there is an auxiliary road parallel to it for vehicle traffic, that is, vehicles moving in the direction of the congested section can selectively avoid the congested section from the auxiliary road before entering the congested section, the problem is:

[0004] 1. The expressway generally has three to four lanes in one direction, and during the morning and evening peak hours with high traffic volume, if the lane cannot be changed in advance, the vehicle will be unable to enter the auxiliary road due to the early morning and evening peak traffic flow if it cannot change lanes in time when it sees the auxiliary road exit;

[0005] 2. As the distance of the main road congestion increases, more and more vehicles will choose to pass through the auxiliary road, and the auxiliary road will be limited by traffic lights, and the vehicle traffic efficiency is limited. Obviously, walking on the auxiliary road does not save time in the case of too many auxiliary road vehicles, and the existing navigation only provides congestion information, and it is impossible to accurately determine the route that is relatively more time-saving for the main road and the auxiliary road by relying on the naked eye to observe the navigation or road information.

[0006] In order to give users reasonable suggestions, reduce the time spent by users in long-term congestion sections, and reasonably allocate traffic flow, and reduce the congestion time of long-term congestion sections as a whole, the present application provides a traffic data analysis system based on fusion perception. SUMMARY

[0007] The purpose of the present application is to provide a traffic data analysis system based on fusion perception, which solves the following technical problems:

[0008] How to give users reasonable suggestions, reduce the time spent by users in long-term congestion sections, and reasonably allocate traffic flow, and reduce the congestion time of long-term congestion sections as a whole.

[0009] The purpose of the present application can be achieved by the following technical solutions:

[0010] A traffic data analysis system based on fusion perception, comprising:

[0011] A data collection module acquires relevant data, including a vehicle statistics unit for collecting data of passing vehicles, a communication unit for acquiring auxiliary road traffic light information data, and a vehicle terminal unit;

[0012] A data processing module analyzes the relevant data to predict the traffic efficiency coefficient interval of the main road and the traffic efficiency coefficient interval of the auxiliary road when a user reaches the long-term congestion road section;

[0013] A data analysis module analyzes the traffic efficiency coefficient of the main road and the traffic efficiency coefficient of the auxiliary road to generate a recommended solution.

[0014] Through the above technical solution: when congestion occurs in the long-term congestion road section, the traffic data generated by the main road and the traffic data generated by the auxiliary road are quantified in terms of traffic efficiency, and fusion analysis is performed, and a recommended solution with the shortest predicted travel time is provided to the user according to the fusion analysis result, thereby saving the user's travel time for the long-term congestion road section.

[0015] As a further technical solution of the present application: the vehicle statistics unit is provided with a plurality of vehicle statistics units, and records the number of vehicles passing through each lane of the route, and is arranged on the main road and the auxiliary road side of the long-term congestion road section of the expressway, and at least one is arranged at each traffic flow merging point and traffic flow splitting point.

[0016] As a further technical solution of the present application: the process of analyzing the relevant data includes:

[0017] The process of predicting the traffic efficiency coefficient interval of the main road and the traffic efficiency coefficient interval of the auxiliary road when a user reaches the long-term congestion road section includes:

[0018] The time interval of the main road congestion is divided into: decline period, stable period and growth period, and the division basis is the average speed;

[0019] The vehicle terminal unit is also used to acquire the departure location and departure time of the user, and according to the departure location and departure time and the historical driving data of the user, the arrival time interval of the user to the congestion location and the relationship between the time interval and the congestion time interval are acquired;

[0020] When the arrival time interval intersects with the stable period, the traffic efficiency coefficient interval of the main road and the traffic efficiency coefficient interval of the auxiliary road when a user reaches the long-term congestion road section are predicted;

[0021] When the arrival interval is not located in the stable period, the recommended solution of the vehicle terminal unit is to travel from the main road.

[0022] As a further technical solution of the present application: the process of predicting the traffic efficiency coefficient interval of the main road and the traffic efficiency coefficient interval of the auxiliary road when a user reaches the long-term congestion road section includes:

[0023] By formula one Obtain the traffic efficiency of the main road at the expected arrival time point, and according to Obtain the main road traffic efficiency coefficient interval;

[0024] Under the condition of auxiliary road congestion, by formula two Obtain the regular traffic efficiency, and according to Obtain the auxiliary road traffic efficiency coefficient interval;

[0025] Wherein is the passing efficiency of the jth lane of the main road, n is the number of lanes of the main road, is the interval span coefficient of the main road, is the traffic time of the kth traffic light of the auxiliary road, is the waiting time of the kth traffic light, is the traffic time of the kth traffic light about the conversion function of the traffic volume, is the interval span coefficient of the auxiliary road.

[0026] As a further technical solution of the present application: the process of analyzing the traffic efficiency coefficient of the main road and the traffic efficiency coefficient of the auxiliary road to generate a recommended scheme includes:

[0027] When the data analysis module obtains the time point of the expected arrival of the long-term congestion road section, the number of vehicles to be passed on the main road And the number of vehicles to be passed on the auxiliary road ;

[0028] From the number of vehicles to be passed on the main road And the number of vehicles to be passed on the auxiliary road , and the main road traffic efficiency coefficient interval and the auxiliary road traffic efficiency coefficient interval, obtain the main road predicted traffic time interval and the auxiliary road predicted traffic time interval, and compare the two;

[0029] If the minimum value of the main road predicted traffic time interval is greater than the maximum value of the auxiliary road predicted traffic time interval, the car terminal unit recommends the scheme to pass from the auxiliary road;

[0030] If the maximum value of the main road predicted traffic time interval is less than the minimum value of the auxiliary road predicted traffic time interval, the car terminal unit recommends the scheme to pass from the main road;

[0031] If the main road predicted traffic time interval and the auxiliary road predicted traffic time interval have intersection, analyze each lane of the main road and the auxiliary road, and the car terminal unit recommends the scheme to pass one or several lanes in all lanes of the main road or the auxiliary road.

[0032] The above technical solution analyzes the traffic efficiency coefficients of the main road and the auxiliary road to more accurately perceive the traffic status of the main road and the auxiliary road when the user is driving near a traffic jam. Based on the real-time data of the day, suggestions are made to help the user make quick decisions and provide sufficient response time for lane changing in the case of heavy traffic.

[0033] As a further technical solution of the present invention: the process of analyzing each lane of the main road and the auxiliary road includes:

[0034] The trafficability of each lane is analyzed to obtain the traffic evaluation coefficient for each lane;

[0035] Each lane is ranked according to its traffic evaluation coefficient, and the vehicle terminal unit recommends the lane with the highest traffic evaluation coefficient.

[0036] As a further technical solution of the present invention: the trafficability of each lane is analyzed to obtain the traffic evaluation coefficient for each lane.

[0037] The trafficability of each lane is analyzed to obtain the traffic evaluation coefficient for each lane:

[0038] Through Formula 3 Obtain the traffic evaluation coefficient of the j-th lane of the main road. ;

[0039] in, , and These are weighting coefficients. It is the number of effective detection points. It is the average throughput of the lane obtained from the i-th valid detection point in the j-th lane. There are m. The average value, Under the condition of no traffic accident The standard deviation of the average traffic efficiency of each effective detection point Let f be the percentage of trucks in the j-th lane, and let f be the truck percentage conversion function. This is the standard speed for traffic during periods of congestion on road sections without truck lanes.

[0040] The above technical solution involves analyzing the traffic efficiency coefficient of each lane on the main road separately when the traffic efficiency coefficients of the main road and the auxiliary road are similar. The traffic evaluation coefficient is used to evaluate the traffic status of the lanes. The traffic status reflects the current traffic status of the lanes today. When a traffic accident or other problem occurs in a lane, the traffic evaluation coefficient will drop sharply, thus helping users to avoid the most difficult lanes to pass in advance.

[0041] As a further technical scheme of the present application: when the terminal unit recommendation scheme is multiple lanes with the highest traffic evaluation coefficient, the multiple lanes are in an adjacent state.

[0042] As a further technical scheme of the present application: the auxiliary road congestion condition is that the number of waiting vehicles on the auxiliary road is greater than the number of vehicles released by a round of traffic light.

[0043] The beneficial effects of the present application are:

[0044] (1) When congestion occurs on a long-term congestion section, the present application quantifies the traffic data generated by the main road and the traffic data generated by the auxiliary road in terms of traffic efficiency, and performs fusion analysis, and provides a recommendation scheme with the shortest predicted traffic time to the user according to the fusion analysis result, thereby saving the user's driving time on the long-term congestion section.

[0045] (2) The present application analyzes the traffic efficiency coefficient of the main road and the traffic efficiency coefficient of the auxiliary road, more accurately perceives the traffic state of the main road and the auxiliary road when the user drives to the vicinity of the congestion point, and provides suggestions based on real-time data on the day to assist the user to quickly choose and provide sufficient response time for lane changing in the case of heavy traffic.

[0046] (3) In the case where the traffic efficiency coefficient of the main road and the traffic efficiency coefficient of the auxiliary road are similar, the present application separately analyzes the traffic evaluation coefficient of each lane of the main road, and evaluates the traffic state of the lane by the traffic evaluation coefficient. The traffic state can reflect the traffic state of the current lane on the day, and the traffic evaluation coefficient will sharply decrease when a certain lane has a traffic accident or other problems, thereby helping the user to avoid the lane with the most difficult traffic in advance. BRIEF DESCRIPTION OF DRAWINGS

[0047] The present application will be further described below in conjunction with the accompanying drawings.

[0048] Figure 1 The present application is a module relationship diagram. DETAILED DESCRIPTION

[0049] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of the present application.

[0050] Please refer to Figure 1 shown, in one embodiment, a traffic data analysis system based on fusion perception is provided, comprising:

[0051] The data collection module acquires relevant data, including a vehicle statistics unit for collecting data of passing vehicles, preferably using a camera device and acquiring data of passing vehicles from images through software, a communication unit for acquiring auxiliary road red and green light information data from public information provided by the traffic department, and a vehicle terminal unit;

[0052] The data processing module analyzes the relevant data to predict the traffic efficiency coefficient interval of the main road and the traffic efficiency coefficient interval of the auxiliary road when the user reaches the long-term congestion road section.

[0053] The data analysis module analyzes the traffic efficiency coefficient of the main road and the traffic efficiency coefficient of the auxiliary road to generate a recommended solution.

[0054] Through the above technical solution: when congestion occurs in a long-term congestion road section, the traffic data generated by the main road and the traffic data generated by the auxiliary road are quantified in terms of traffic efficiency, and fusion analysis is performed, and a recommended solution with the shortest predicted travel time is provided to the user according to the results of the fusion analysis, thereby saving the user's travel time for the long-term congestion road section.

[0055] The vehicle statistics unit is provided with multiple units and records the number of vehicles passing through each lane on the route. It is arranged on the main road and the auxiliary road side of the long-term congestion road section of the expressway, and at least one is arranged at each traffic merging point and traffic splitting point.

[0056] The process of analyzing the relevant data includes:

[0057] The process of predicting the traffic efficiency coefficient interval of the main road and the traffic efficiency coefficient interval of the auxiliary road when the user reaches the long-term congestion road section includes:

[0058] The time interval of the main road congestion is divided into: decline period, stable period and growth period, and the division is based on the average speed;

[0059] The vehicle terminal unit is also used to acquire the departure location and departure time of the user, and to acquire the arrival time interval of the user reaching the congestion location and the relationship between the time interval and the congestion time interval according to the departure location and departure time and the historical driving data of the user;

[0060] When the arrival time interval intersects with the stable period, the traffic efficiency coefficient interval of the main road and the traffic efficiency coefficient interval of the auxiliary road when the user reaches the long-term congestion road section are predicted.

[0061] When the arrival interval is not located within the stable period, the vehicle terminal unit recommends a solution of driving from the main road.

[0062] The process of predicting the traffic efficiency coefficient interval of the main road and the traffic efficiency coefficient interval of the auxiliary road when the user reaches the long-term congestion road section includes:

[0063] By formula one Obtain the main road traffic efficiency at the expected arrival time point, and according to Obtain the main road traffic efficiency coefficient interval;

[0064] Under the condition of auxiliary road congestion, by formula two

[0065] Obtain the regular traffic efficiency, and according to Obtain the auxiliary road traffic efficiency coefficient interval;

[0066] Wherein is the passing efficiency of the jth lane of the main road, which is obtained by dividing the number of passing vehicles by the passing time, n is the number of lanes of the main road, is the interval span coefficient of the main road, which is used to expand the traffic efficiency at the main road stable period to obtain the main road traffic efficiency coefficient interval, and the main road traffic efficiency coefficient interval contains the main road traffic efficiency under all conditions, is the passing time of the kth traffic light of the auxiliary road, is the waiting time of the kth traffic light, is the conversion function of the passing time of the kth traffic light with respect to the number of passing vehicles, which is preferably obtained by setting a fixed passing time and then statistically analyzing the data, is the interval span coefficient of the auxiliary road, which is used to expand the regular traffic efficiency under the auxiliary road congestion state to obtain the auxiliary road traffic efficiency coefficient interval, and the auxiliary road traffic efficiency coefficient interval contains the auxiliary road traffic efficiency under all conditions.

[0067] The process of analyzing the traffic efficiency coefficient of the main road and the traffic efficiency coefficient of the auxiliary road to generate a recommended scheme includes:

[0068] When the data analysis module obtains the number of vehicles to be passed on the main road at the time point of the expected arrival at the long-term congestion road section And the number of vehicles to be passed on the auxiliary road The number of vehicles is preferably obtained by the vehicle statistical unit;

[0069] From the number of vehicles to be passed on the main road And the number of vehicles to be passed on the auxiliary road , and the main road traffic efficiency coefficient interval and the auxiliary road traffic efficiency coefficient interval, the main road predicted passing time interval and the auxiliary road predicted passing time interval are obtained, and the two are compared;

[0070] If the minimum value of the main road predicted passing time interval is greater than the maximum value of the auxiliary road predicted passing time interval, the vehicle terminal unit recommends the scheme of passing from the auxiliary road;

[0071] If the highest value of the estimated travel time interval for the main road is less than the lowest value of the estimated travel time interval for the auxiliary road, the recommended solution for the vehicle terminal unit is to travel on the main road.

[0072] If the estimated travel time intervals of the main road and the auxiliary road overlap, each lane of the main road and the auxiliary road is analyzed, and the recommended solution of the vehicle terminal unit is one or more lanes of all lanes of the main road or the auxiliary road.

[0073] The above technical solution analyzes the traffic efficiency coefficients of the main road and the auxiliary road to more accurately perceive the traffic status of the main road and the auxiliary road when the user is driving near a traffic jam. Based on the real-time data of the day, suggestions are made to help the user make quick decisions and provide sufficient response time for lane changing in the case of heavy traffic.

[0074] The process of analyzing each lane of the main road and auxiliary roads includes:

[0075] The trafficability of each lane is analyzed to obtain the traffic evaluation coefficient for each lane;

[0076] Each lane is ranked according to its traffic evaluation coefficient, and the vehicle terminal unit recommends the lane with the highest traffic evaluation coefficient.

[0077] The trafficability of each lane is analyzed to obtain the traffic evaluation coefficient for each lane:

[0078] Through Formula 3 Obtain the traffic evaluation coefficient of the j-th lane of the main road. ;

[0079] in, , and These are weighting coefficients. It is the number of effective detection points. It is the average throughput of the lane obtained from the i-th valid detection point in the j-th lane. There are m. The average value, Under the condition of no traffic accident The standard deviation of the average traffic efficiency of each effective detection point Let f be the percentage of trucks in the j-th lane, and let f be the truck percentage conversion function. This is the standard speed for traffic during periods of congestion on road sections without truck lanes.

[0080] By the technical scheme, in the case that the traffic efficiency coefficient of the main road and the traffic efficiency coefficient of the auxiliary road are similar, the traffic evaluation coefficient of each lane of the main road is analyzed separately, the traffic state of the lane is evaluated by the traffic evaluation coefficient, the traffic state can reflect the current traffic state of the lane, and when a lane has a traffic accident or other problems, the traffic evaluation coefficient will sharply decrease, thereby helping the user to avoid the lane with the most difficult traffic in advance.

[0081] When the vehicle terminal unit recommendation scheme is the multiple lanes with the highest traffic evaluation coefficient, the multiple lanes are in an adjacent state.

[0082] The auxiliary road congestion condition is that the number of waiting vehicles on the auxiliary road is greater than the number of vehicles released by a round of traffic light.

[0083] The above describes one embodiment of the present application in detail, but the content is only the preferred embodiment of the present application, and cannot be considered as limiting the implementation range of the present application. Any equivalent changes and improvements made according to the application scope of the present application should still belong to the patent coverage range of the present application.​

Claims

1. A fusion perception based traffic data analysis system, characterized in that, The application relates to a traffic jam prediction system and method. The system comprises a data collection module, a vehicle statistics unit for collecting data of passing vehicles, a communication unit for collecting auxiliary road traffic light information, and a vehicle terminal unit. The vehicle statistics unit is provided with a plurality of units, and records the number of vehicles passing through each lane on the route, is arranged on the main road and the auxiliary road of a long-term congestion section of an expressway, and at least one is arranged at each vehicle flow merging port and vehicle flow separating port. A data processing module analyzes the relevant data and predicts the traffic efficiency coefficient interval of the main road and the traffic efficiency coefficient interval of the auxiliary road when a user reaches the long-term congestion section. The process of analyzing the relevant data comprises: The process of predicting the traffic efficiency coefficient interval of the main road and the traffic efficiency coefficient interval of the auxiliary road when a user reaches the long-term congestion section comprises: The time interval of the main road traffic jam is divided into a falling period, a stable period and a growth period, and the division is based on the average vehicle speed. The vehicle terminal unit is also used to collect the departure position and departure time of the user, and to collect the arrival time interval of the user reaching the traffic jam position and the relationship between the time interval and the traffic jam time interval according to the departure position and departure time and the historical driving data of the user. When the arrival time interval intersects with the stable period, the traffic efficiency coefficient interval of the main road and the traffic efficiency coefficient interval of the auxiliary road when the user reaches the long-term congestion section are predicted. When the arrival interval is not located in the stable period, the vehicle terminal unit recommends a scheme of driving from the main road. The process of predicting the traffic efficiency coefficient interval of the main road and the traffic efficiency coefficient interval of the auxiliary road when a user reaches the long-term congestion section comprises: By formula one Obtain the traffic efficiency of the main road at the expected arrival time point of the stable period, and according to Obtain the main road traffic efficiency coefficient interval; Under the condition of auxiliary road congestion, the formula two obtain the regular traffic efficiency, and according to obtain the auxiliary road traffic efficiency coefficient interval; wherein is the passing efficiency of the jth lane of the main road, n is the number of lanes of the main road, is the span coefficient of the main road, is the passing time of the kth traffic light of the auxiliary road, is the waiting time of the kth traffic light, is the conversion function of the passing time of the kth traffic light with respect to the number of passages, is the span coefficient of the auxiliary road; A data analysis module analyzes the traffic efficiency coefficient of the main road and the traffic efficiency coefficient of the auxiliary road, and generates a recommended scheme. The process of analyzing the traffic efficiency coefficient of the main road and the traffic efficiency coefficient of the auxiliary road, and generating a recommended scheme comprises: The data analysis module obtains the number of vehicles to be passed on the main road and the number of vehicles to be passed on the auxiliary road at the time point when the vehicle is expected to arrive at the long-term congestion road section and the auxiliary road ; the number of vehicles to be passed by the main road and the number of vehicles to be passed by the auxiliary road , and the main road traffic efficiency coefficient interval and the auxiliary road traffic efficiency coefficient interval, obtain the main road predicted traffic time interval and the auxiliary road predicted traffic time interval, and compare the two If the minimum value of the main road predicted traffic time interval is greater than the maximum value of the auxiliary road predicted traffic time interval, the vehicle terminal unit recommends a scheme of driving from the auxiliary road; If the maximum value of the main road predicted traffic time interval is less than the minimum value of the auxiliary road predicted traffic time interval, the vehicle terminal unit recommends a scheme of driving from the main road; If the main road predicted traffic time interval and the auxiliary road predicted traffic time interval have an intersection, the vehicle terminal unit recommends a scheme of driving from one or several lanes of the main road or the auxiliary road.

2. The traffic data analysis system based on fusion perception according to claim 1, wherein, The process of analyzing each lane of the main road and the auxiliary road comprises: Analyzing the traffic of each lane to obtain a traffic evaluation coefficient of each lane; According to the traffic evaluation coefficient, each lane is sorted, and the vehicle terminal unit recommends a scheme of driving from one or several lanes with the highest traffic evaluation coefficient. 3.The traffic data analysis system based on fusion perception according to claim 2, wherein, The process of analyzing the traffic of each lane to obtain a traffic evaluation coefficient of each lane comprises: By equation three Obtain the traffic evaluation coefficient of the jth lane of the main road ; in, , and These are weighting coefficients. It is the number of effective detection points. It is the average throughput of the lane obtained from the i-th valid detection point in the j-th lane. There are m. The average value, Under the condition of no traffic accident The standard deviation of the average traffic efficiency of each effective detection point Let f be the percentage of trucks in the j-th lane, and let f be the truck percentage conversion function. This is the standard speed for traffic during periods of congestion on road sections without truck lanes.

4. The traffic data analysis system based on fusion perception according to claim 3, wherein, When the vehicle terminal unit recommends a scheme of driving from several lanes with the highest traffic evaluation coefficient, the several lanes are in an adjacent state.

5. The traffic data analysis system based on fusion perception according to claim 4, wherein, The auxiliary road congestion condition is that the number of waiting vehicles on the auxiliary road is greater than the number of vehicles released by one round of traffic light.

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