Data screening system for intelligent traffic big data

Abstract

The invention discloses a data screening system for smart traffic big data, and relates to the technical field of big data. The historical driving data screening module is used for obtaining the historical driving data storage database through the satellite navigation system, and then the historical driving data of the vehicle is screened according to the historical driving data storage database; a road data screening module is used for screening historical road data according to the vehicle historical running data, and then data association is carried out on the vehicle historical running data and the historical road data through an association data processing module to establish a road running model; obtaining a to-be-selected driving route according to a demand data screening module; and finally, acquiring a traffic jam index and a safety index according to the road driving model by utilizing an optimal driving route screening module, and screening an optimal vehicle driving route. And the accuracy of screening the driving route is effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of big data, and specifically to a data screening system for big data of intelligent transportation. Background Art

[0002] With the acceleration of the urbanization process and the diversification of transportation means, the volume of traffic data has shown an explosive growth. This data comes from various traffic monitoring devices, vehicle sensors, public transportation systems, mobile phone location information, etc., covering multiple dimensions such as traffic flow, vehicle speed, congestion status, traffic accidents, weather conditions, and public transportation usage. Effectively utilizing this big data is of great significance for improving traffic management efficiency, optimizing traffic network design, reducing traffic congestion, and enhancing travel safety; In the prior art, a satellite navigation system is usually used to screen corresponding driving routes. The satellite navigation system usually obtains the optimal vehicle driving route by screening the driving route only according to the total road mileage and road traffic light data based on the input starting point and ending point. However, this method does not consider vehicle driving data and road data. Therefore, the selected optimal vehicle driving route is not accurate enough. Therefore, in order to solve the above technical problems, the present invention provides a data screening system for big data of intelligent transportation. Summary of the Invention

[0003] In order to solve the above technical problems, the present invention provides a data screening system for big data of intelligent transportation; The object of the present invention can be achieved by the following technical solutions: A data screening system for big data of intelligent transportation, the system includes a historical driving data screening module, a road data screening module, an associated data processing module, a demand data screening module, and an optimal driving route screening module; The historical driving data screening module is used to obtain a historical driving data storage database through a satellite navigation system, and then screen vehicle historical driving data according to the historical driving data storage database; The road data screening module is used to screen historical road data according to vehicle historical driving data; The associated data processing module is used to establish a road driving model by associating vehicle historical operation data with historical road data; The demand data screening module obtains the to-be-selected driving route; The optimal driving route screening module is used to obtain the traffic congestion index and safety index corresponding to the to-be-selected driving route according to the road driving model, and screen the optimal vehicle driving route.

[0004] Further, the process by which the historical driving data screening module obtains the historical driving data storage database through the satellite navigation system includes: A corresponding historical driving data storage database is set up in the satellite navigation system for storing vehicle historical driving data; When the vehicle is navigating through the satellite navigation system, the license plate number is collected for navigation, and the corresponding vehicle speed is collected in real time. After the navigation ends, the historical driving route and the driving time period corresponding to the historical driving route are obtained; and the vehicle speed is mapped on the historical driving route for display to generate vehicle historical driving data, which is stored in the historical driving data storage database.

[0005] Further, the process of screening vehicle historical driving data according to the historical driving data storage database includes: Collect the license plate number corresponding to the vehicle, dispatch the vehicle historical driving data corresponding to the license plate number through the historical driving data storage database, intercept the vehicle historical driving data corresponding to the license plate number in the past year, and obtain the average value of the historical driving speeds corresponding to all vehicle historical driving data as the historical average driving speed; obtain the historical driving acceleration corresponding to each historical driving route according to the historical driving route and the historical driving speed; and further obtain the average value of the corresponding historical driving accelerations as the historical average driving acceleration; Dispatch the traffic violation records according to the license plate number to obtain vehicle violation behavior information, where the vehicle violation behavior information includes the violation time and the violation type; screen the number corresponding to the red light running violation type in the past year according to the violation time, and mark it as the historical red light running number; Integrate the historical average driving speed, the historical average driving acceleration, and the historical red light running number to obtain the vehicle historical driving data.

[0006] Further, the process of the road data screening module screening historical road data according to vehicle historical driving data includes: Obtain the historical total mileage and the historical number of traffic lights corresponding to each historical driving route through the satellite navigation system; Obtain the road monitoring nodes generated by displaying the positions of the road monitoring devices deployed on each driving route in the satellite navigation system through GIS for collecting the traffic flow corresponding to each driving route; Set a unit prediction section, divide the driving route into several unit prediction sections according to the unit prediction section; obtain the sum of the traffic flows of the road monitoring nodes corresponding to the unit prediction section, and mark it as the unit traffic flow corresponding to each unit prediction section, and further obtain the sum of each unit traffic flow, and mark it as the historical traffic flow corresponding to the historical driving route; Obtain the historical total mileage, the historical number of traffic lights, and the historical traffic flow corresponding to all historical driving routes, and respectively obtain the corresponding average values as the historical road total mileage, the historical road traffic light data, and the historical road traffic flow; Integrate the total historical road mileage, the number of traffic lights on the historical road, and the historical road traffic flow to obtain the historical road data corresponding to the historical driving route.

[0007] Further, the process of the associated data processing module constructing a road driving model by associating vehicle historical operation data with historical road data includes: Taking nearly one year as the collection period, collecting n vehicle historical driving data and historical road data corresponding to the recent n years, and integrating them to generate a historical data set, marked as (x1n, x2n, x3n, x4n, x5n, x6n), where n = 1, 2, 3,..., i, and i is a positive integer; x1, x2, x3, x4, x5, and x6 respectively represent the historical average driving speed, historical average driving acceleration, historical number of red-light violations, total historical road mileage, number of traffic lights on the historical road, and historical road traffic flow. Construct a traffic flow prediction model and a safety index model based on the historical data set.

[0008] Further, the construction process of the traffic flow prediction model and the safety index model includes: ; Among them, Y represents the traffic flow; a represents a constant; b represents a deviation value; w 1 , w 2 , w 3 , w 4 , and w 5 Corresponding weights respectively; Among them, w 1 , w 2 , w 3 , w 4 , and w 5 The acquisition process of includes: ; Among them, R min Represents the minimum value; w 1 , w 2 , w 3 , w 4 , and w 5 The values of are the values when R min Takes the minimum value; ; Among them, Q represents the safety index; k represents a constant; p represents a deviation value; d 1 , d 2 , d 3 , d 4 , and d 5 Corresponding weights respectively; Among them, d1 , d 2 , d 3 , d 4 and d 5 The obtaining process of includes: ; wherein, F min represents the minimum value; d 1 , d 2 , d 3 , d 4 and d 5 have the values when F min takes the minimum value.

[0009] Furthermore, the process by which the demand data screening module obtains the to-be-selected driving routes includes: Input the starting point and the ending point through the satellite navigation system to screen the vehicle driving routes to obtain the to-be-selected driving routes, and obtain the total road mileage and road traffic light data corresponding to each to-be-selected driving route through the satellite navigation system, and obtain the average waiting driving speed, average waiting driving acceleration, and road traffic flow corresponding to each to-be-selected driving route.

[0010] Furthermore, the process by which the optimal driving route screening module obtains the traffic congestion index and safety index corresponding to the to-be-selected driving routes according to the road driving model and screens the optimal vehicle driving routes includes: Send the total road mileage, road traffic light data, average waiting driving speed, average waiting driving acceleration, and road traffic flow to the road driving model to obtain the traffic flow and safety index corresponding to each to-be-selected driving route; Set the congestion levels and the corresponding traffic flow congestion level threshold ranges, and the congestion levels include first-level congestion, second-level congestion, and third-level congestion respectively; Compare the traffic flow with the traffic flow congestion level threshold ranges to obtain the corresponding congestion level, and then display the traffic flow, congestion level, and safety index on the corresponding to-be-selected driving routes; The vehicle owner selects the to-be-selected driving routes according to the total road mileage, road traffic light data, traffic flow, congestion level, and safety index to obtain the optimal vehicle driving route.

[0011] Compared with the prior art, the beneficial effects of the present invention are as follows: The present invention uses the historical driving data screening module to obtain the historical driving data storage database through the satellite navigation system, and then screens the vehicle historical driving data according to the historical driving data storage database; and uses the road data screening module to screen the historical road data according to the vehicle historical driving data, and then through the associated data processing module, associates the vehicle historical operation data with the historical road data to establish a road driving model; then obtains the to-be-selected driving route according to the demand data screening module; finally, uses the optimal driving route screening module to obtain the traffic congestion index and safety index according to the road driving model, and screens the optimal vehicle driving route; effectively improving the accuracy of driving route screening. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required in the embodiments. Obviously, the drawings described below are only some embodiments recorded in the present invention, and those of ordinary skill in the art can also obtain other drawings based on these drawings.

[0013] Figure 1 It is the schematic diagram of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0014] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0015] As Figure 1 shown, a data screening system for intelligent transportation big data, the system includes a historical driving data screening module, a road data screening module, an associated data processing module, a demand data screening module, and an optimal driving route screening module; The historical driving data screening module is used to screen the vehicle historical driving data through the satellite navigation system; The road data screening module is used to screen the historical road data according to the vehicle historical driving data; The associated data processing module is used to associate the vehicle historical operation data with the historical road data to establish a road driving model; The demand data screening module obtains the to-be-selected driving route; The optimal driving route screening module is used to obtain the traffic congestion index and safety index corresponding to the to-be-selected driving route according to the road driving model, and screen the optimal vehicle driving route.

[0016] It should be further explained that the historical driving data screening module screens the historical driving data of the vehicle through the satellite navigation system; including: A corresponding historical driving data storage database is provided in the satellite navigation system for storing historical driving data of the vehicle; When the vehicle is navigating through the satellite navigation system, the license plate number is collected for navigation, and the corresponding vehicle speed is collected in real time. After the navigation is completed, the historical driving route and the driving time period corresponding to the historical driving route are obtained; the vehicle speed is mapped on the historical driving route for display, and the vehicle historical driving data is generated and stored in the historical driving data storage database; Collect vehicle information data corresponding to the vehicle, the vehicle information data including the license plate number, the owner's name, ID number and contact information; dispatch the vehicle historical driving data corresponding to the license plate number through the historical driving data storage database, intercept the vehicle historical driving data corresponding to the license plate number in the past year, and obtain the average value of the historical driving speeds corresponding to all the vehicle historical driving data as the historical average driving speed; obtain the historical driving acceleration corresponding to each historical driving route according to the historical driving route and the historical driving speed; and then obtain the average value corresponding to each historical driving acceleration as the historical average driving speed; Dispatching traffic violation records according to the license plate number to obtain vehicle violation information, including violation time and violation type; screening violation types in the past year according to violation time to select the number corresponding to red light running, and marking it as the number of historical red light running; In the above embodiment, it is necessary to further explain that the vehicle's historical driving data is better stored by inputting the license plate number corresponding to the vehicle when starting navigation. The existing satellite navigation system does not store the vehicle's historical driving data when navigating directly, and the vehicle's historical driving data cannot be used as a screening condition for the best driving route. The screening process does not consider the vehicle's historical driving data, and the selected driving route cannot be used as the best driving route. The historical average driving speed, historical average driving acceleration and historical number of red light violations are integrated to obtain the vehicle's historical driving data.

[0017] It should be further explained that the road data screening module is used to screen historical road data according to historical vehicle driving data; it includes: Obtain the total historical travel distance and the number of historical traffic lights corresponding to each historical driving route through the satellite navigation system; Obtain the road monitoring equipment deployed on each driving route through GIS and display the generated road monitoring nodes at the corresponding positions of the satellite navigation system to collect the traffic flow corresponding to each driving route; Set a unit prediction section, and divide the driving route into several unit prediction sections according to the unit prediction sections; obtain the sum of the traffic flows of the road monitoring nodes corresponding to the unit prediction sections, and mark them as the unit traffic flows corresponding to each unit prediction section, and then obtain the sum of each unit traffic flow, and mark it as the historical traffic flow corresponding to the historical driving route; Obtain the historical total mileage, historical number of traffic lights and historical traffic flow corresponding to all historical driving routes, and obtain the corresponding average values ​​as the historical road total mileage, historical road traffic light data and historical road traffic flow; The total distance traveled on historical roads, the number of traffic lights on historical roads, and the traffic flow on historical roads are integrated to obtain the historical road data corresponding to the historical driving routes.

[0018] In the above specific implementation process, it needs to be further explained that the satellite navigation system includes but is not limited to Baidu Navigation, Amap, etc.; the road monitoring equipment adopts geomagnetic induction, microwave radar, video image recognition and other technologies, and can monitor traffic flow in real time.

[0019] It should be further explained that the associated data processing module associates the historical vehicle operation data with the historical road data to construct a road travel model; including: Taking the past year as the collection cycle, collect n vehicle historical driving data and historical road data corresponding to the past n years, and integrate them to generate a historical data set, marked as (x1n, x2n, x3n, x4n, x5n, x6n), where n=1, 2, 3, ..., i, and i is a positive integer; x1, x2, x3, x4, x5 and x6 represent the historical average driving speed, the historical average driving acceleration, the historical number of red light violations, the historical total road mileage, the historical number of red lights and the historical road traffic flow respectively; Build traffic flow prediction models and safety index models based on historical data sets; The construction process of the traffic flow prediction model includes: ; Among them, Y represents the traffic flow; a represents a constant; b represents the deviation value; w1, w2, w3, w4 and w5 correspond to weights respectively; The acquisition process of w1, w2, w3, w4 and w5 includes: ; Among them, Rmin represents the minimum value; the values ​​of w1, w2, w3, w4 and w5 are the values ​​when Rmin is the minimum value.

[0020] The construction process of the safety index model includes: ; Among them, Q represents the safety index; k represents a constant; p represents the deviation value; d1, d2, d3, d4 and d5 respectively correspond to the weights; The acquisition process of d1, d2, d3, d4 and d5 includes: ; Among them, Fmin represents the minimum value; the values ​​of d1, d2, d3, d4 and d5 are the values ​​when Fmin is the minimum value.

[0021] In the above embodiment, it needs to be further explained that a road driving model is established through a historical data set, and the driving route is screened based on the vehicle driving data and the road data, thereby improving the accuracy of route screening.

[0022] It should be further explained that the demand data screening module obtains the driving route to be selected; including: Obtain traffic congestion index and safety index based on road driving model, and select the optimal vehicle driving route; The starting point and the end point are input through the satellite navigation system to filter the vehicle driving route to obtain the driving route to be selected, and the total road travel and road traffic light data corresponding to each driving route to be selected are obtained through the satellite navigation system, and the average driving speed, average driving acceleration and road traffic flow corresponding to each driving route to be selected are obtained.

[0023] It should be further explained that the optimal driving route screening module obtains the traffic congestion index and safety index corresponding to the driving route to be selected according to the road driving model, and screens the optimal vehicle driving route; including: The total road travel, road traffic light data, average speed to be driven, average acceleration to be driven and road traffic flow are sent to the road driving model to obtain the traffic flow and safety index corresponding to each driving route to be selected; Setting a congestion level and setting a traffic flow congestion level threshold range corresponding to the congestion level, wherein the congestion levels include level one congestion, level two congestion and level three congestion, and the corresponding traffic flow congestion level threshold ranges are (0, 1Y], (1Y, 2Y] and (2Y, +∞); Compare the traffic flow with the traffic flow congestion level threshold range to obtain the corresponding congestion level, and then display the traffic flow, congestion level and safety index on the corresponding driving route to be selected; The car owner selects the optimal vehicle driving route based on the total road mileage, road traffic light data, traffic flow, congestion level and safety index.

[0024] In the above embodiment, it needs to be further explained that, therefore, the satellite navigation system selects the driving route to be selected according to the input starting point and end point only according to the total road travel and road traffic light data to obtain the optimal vehicle driving route.

[0025] Working principle: The present invention utilizes a historical driving data screening module to obtain a historical driving data storage database through a satellite navigation system, and then screens the vehicle's historical driving data according to the historical driving data storage database; and utilizes a road data screening module to screen historical road data according to the vehicle's historical driving data, and then uses an associated data processing module to perform data association between the vehicle's historical operating data and historical road data to establish a road driving model; and then obtains a driving route to be selected according to a demand data screening module; and finally utilizes an optimal driving route screening module to obtain a traffic congestion index and a safety index according to the road driving model, and screens the optimal vehicle driving route; and effectively improves the accuracy of driving route screening.

[0026] The features and exemplary embodiments of various aspects of the present application are described in detail above. In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is further described in detail in combination with the drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application rather than to limit the present application. For those skilled in the art, the present application can be implemented without some of these specific details. The above description of the embodiments is merely to provide a better understanding of the present application by showing examples of the present application.

[0027] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A data screening system for smart traffic big data, characterized in that: The system includes a historical driving data screening module, a road data screening module, a related data processing module, a demand data screening module and an optimal driving route screening module; The historical driving data screening module is used to obtain the historical driving data storage database through the satellite navigation system, and then screen the vehicle historical driving data according to the historical driving data storage database; The road data screening module is used to screen historical road data according to historical vehicle travel data; The associated data processing module is used to associate the historical vehicle operation data with the historical road data to establish a road travel model; The demand data screening module obtains a driving route to be selected; The optimal driving route screening module is used to obtain the traffic congestion index and safety index corresponding to the driving route to be selected according to the road driving model, and screen the optimal vehicle driving route.

2. According to claim 1, a data screening system for intelligent traffic big data is characterized in that: The process of the historical driving data screening module acquiring the historical driving data storage database through the satellite navigation system includes: A corresponding historical driving data storage database is provided in the satellite navigation system for storing historical driving data of the vehicle; When the vehicle is navigating through the satellite navigation system, the license plate number is collected for navigation, and the corresponding vehicle speed is collected in real time. After the navigation is completed, the historical driving route and the driving time period corresponding to the historical driving route are obtained; the vehicle speed is mapped on the historical driving route for display to generate the vehicle's historical driving data and store it in the historical driving data storage database.

3. According to claim 2, a data screening system for intelligent traffic big data is characterized in that: The process of filtering the historical driving data of a vehicle according to the historical driving data storage database includes: Collect the license plate number corresponding to the vehicle, dispatch the historical driving data of the vehicle corresponding to the license plate number through the historical driving data storage database, intercept the historical driving data of the vehicle corresponding to the license plate number in the past year, and obtain the average value of the historical driving speeds corresponding to all the historical driving data of the vehicle as the historical average driving speed; obtain the historical driving acceleration corresponding to each historical driving route according to the historical driving route and the historical driving speed; and then obtain the average value corresponding to each historical driving acceleration as the historical average driving acceleration; Dispatching traffic violation records according to the license plate number to obtain vehicle violation information, including the violation time and violation type; screening the number of violations corresponding to red light running in the past year according to the violation time, and marking it as the number of historical red light running; The historical average driving speed, historical average driving acceleration and historical number of red light violations are integrated to obtain the vehicle's historical driving data.

4. According to claim 3, a data screening system for intelligent traffic big data is characterized in that: The process of the road data screening module screening historical road data according to the historical vehicle driving data includes: Obtain the total historical travel distance and the number of historical traffic lights corresponding to each historical driving route through the satellite navigation system; Obtain the road monitoring equipment deployed on each driving route through GIS and display the generated road monitoring nodes at the corresponding positions of the satellite navigation system to collect the traffic flow corresponding to each driving route; Set a unit prediction section, and divide the driving route into several unit prediction sections according to the unit prediction sections; obtain the sum of the traffic flows of the road monitoring nodes corresponding to the unit prediction sections, and mark them as the unit traffic flows corresponding to each unit prediction section, and then obtain the sum of each unit traffic flow, and mark it as the historical traffic flow corresponding to the historical driving route; Obtain the historical total mileage, historical number of traffic lights and historical traffic flow corresponding to all historical driving routes, and obtain the corresponding average values ​​as the historical road total mileage, historical road traffic light data and historical road traffic flow; The total distance traveled on historical roads, the number of traffic lights on historical roads, and the traffic flow on historical roads are integrated to obtain the historical road data corresponding to the historical driving routes.

5. The data screening system for intelligent traffic big data according to claim 4 is characterized in that: The process of the associated data processing module associating the historical vehicle operation data with the historical road data to construct a road travel model includes: Taking the past year as the collection cycle, collect n vehicle historical driving data and historical road data corresponding to the past n years, and integrate them to generate a historical data set, marked as (x1n, x2n, x3n, x4n, x5n, x6n), where n=1, 2, 3, ..., i, and i is a positive integer; x1, x2, x3, x4, x5 and x6 represent the historical average driving speed, the historical average driving acceleration, the historical number of red light violations, the historical total road mileage, the historical number of red lights and the historical road traffic flow respectively; Build traffic flow prediction models and safety index models based on historical data sets.

6. The data screening system for intelligent traffic big data according to claim 5 is characterized in that: The construction process of the traffic flow prediction model and the safety index model includes: ； Among them, Y represents the traffic flow; a represents a constant; b represents the deviation value; w1, w2, w3, w4 and w5 correspond to weights respectively; ； Among them, Q represents the safety index; k represents a constant; p represents the deviation value; d1, d2, d3, d4 and d5 represent the corresponding weights respectively.

7. The data screening system for intelligent traffic big data according to claim 1 is characterized in that: The process of the demand data screening module acquiring the driving route to be selected includes: The starting point and the end point are input through the satellite navigation system to filter the vehicle driving route to obtain the driving route to be selected, and the total road travel and road traffic light data corresponding to each driving route to be selected are obtained through the satellite navigation system, and the average driving speed, average driving acceleration and road traffic flow corresponding to each driving route to be selected are obtained.

8. The data screening system for intelligent traffic big data according to claim 7 is characterized in that: The optimal driving route screening module obtains the traffic congestion index and safety index corresponding to the driving route to be selected according to the road driving model, and screens the optimal vehicle driving route, including: The total road travel, road traffic light data, average speed to be driven, average acceleration to be driven and road traffic flow are sent to the road driving model to obtain the traffic flow and safety index corresponding to each driving route to be selected; Setting a congestion level and setting a traffic flow congestion level threshold range corresponding to the congestion level, wherein the congestion levels include level one congestion, level two congestion and level three congestion; Compare the traffic flow with the traffic flow congestion level threshold range to obtain the corresponding congestion level, and then display the traffic flow, congestion level and safety index on the corresponding driving route to be selected; The car owner selects the optimal vehicle driving route based on the total road mileage, road traffic light data, traffic flow, congestion level and safety index.

Images