TW201327458A - Transportation route network generation method using vehicle detection data - Google Patents

Abstract

The present invention relates to a transportation route network generation method using vehicle detection data, which uses vehicle detection data GPS and a wireless network signal as calculation analysis data, and integrates traditional electronic map route network data into transportation route network data suitable for traffic information applications. This invention, applying a geographic information system technology, a statistical analysis technology and a lot of collected vehicle detection data, analyzes vehicle traveling paths, establishes a road segment traffic mode, combines the road segments with endpoints adjacent to each other of high similarity and generates transportation route network basic data through; a traffic information collection technology, such as vehicle detectors, global positioning system floating vehicle detectors, and CFVDs, based on the transportation route network generation method, is used for reducing processed route network data, calculating road segment traffic information of various roads, increasing the system efficiency of the traffic information collection technology, and providing instant traffic information for satisfying the demands of people.

Description

Traffic road network generation method using vehicle detection data

The invention relates to a traffic network generation method for applying vehicle detection data, in particular to a road network data preparation method for introducing vehicle detection data; mainly using data exploration technology and geographic information system (GIS) technology to analyze a large number of Accumulated vehicle detection data to obtain the traffic patterns of each road segment, compare the traffic modes of each road segment, and merge the road segments with similar traffic patterns and geographical proximity, thereby reducing the number of data in the road network segment, making it more suitable for traffic field. Traffic information gathering technologies such as vehicle detectors, GPS Floating Vehicle Detector (GFVD), Cellular Floating Vehicle Detector (CFVD), etc., can calculate traffic information such as travel speed and traffic volume of each traffic road network segment based on the traffic road network of the present invention. Parameters to effectively post traffic information to mobile devices. The traffic information road network data generated by the present invention can be an important cornerstone for traffic information application services.

The Advanced Traveler Information System (ATIS) is one of the nine areas of the Intelligent Transportation System (ITS). Its main function is to provide real-time traffic information for passers-by, including road information and mass transit system information. The parking lot information and route guidance services allow passers-by to choose the most favorable roads based on traffic conditions and reduce travel time.

In order to provide ATIS-related services, government departments must build many hardware devices on the road side to collect road occupancy, traffic and speed. However, this method requires the construction of lines and detection equipment on each detection section, not only equipment. The cost is high, the range of the detection section is not easy to expand, and the subsequent maintenance cost is a huge burden. Therefore, in recent years, the use of detective vehicles to collect traffic information technology has become one of the hottest topics in domestic traffic information collection. Many telecom and value-added vendors have focused on exploring the advantages of small investment and rich content of vehicle traffic information collection system. The development of the vehicle traffic information collection field.

The exploration vehicle traffic information collection technology can be divided into two categories: GPS Floating Vehicle Detector (GFVD) technology and Cellular Floating Vehicle Detector (CFVD) technology. The main difference is that the analysis information is different, GFVD technology analyzes GPS data, and CFVD analyzes mobile network signaling data. At present, GFVD is the main technology in practice. The GFVD collects probes as traffic information by vehicles that are equipped with dedicated front-end equipment (with GPS positioning and wireless communication transmission modules). When the probe vehicle is walking on the road, the front-end equipment returns information such as the location of the vehicle, the direction and time of the vehicle, and the system collects the GPS data of the vehicle's return by analyzing and analyzing the vehicle. The cost of GFVD construction and maintenance is lower than that of roadside vehicle detectors, and the vehicle detector can only provide the driving speed of fixed locations and specific sections. If the number of detectors is sufficient and the range of detection vehicles is wide, GFVD can provide road network. Traffic information for all sections.

In the past, the detection of vehicle traffic information collection technology uses the traditional road network, which was originally applied to navigation and electronic maps and other information application services. The Detective Vehicle Traffic Information Collection Technology analyzes the GPS information or wireless network signaling reported by the Detective Vehicle and estimates the speed of the road segment. However, due to different application purposes, the traditional road network road segment segmentation principle is not based on road traffic conditions, resulting in too large road network data is difficult to analyze, so it is difficult to use as a road network for probe vehicle technology. Direct use of traditional network segment data may even cause misjudgment of the segment speed or affect the accuracy of the speed results. In the research of part of the exploration vehicle traffic information collection technology, the traditional road network is divided into multiple road sections to be tested through the GIS tool in a manual manner, and the road segmentation is carried out according to different traffic conditions. The advantage of adopting the manual method is that the segmentation is accurate, and the disadvantage is that it takes time and is difficult to process a wide range of road network data.

The main object of the present invention is to provide a method for generating a traffic road network using vehicle detection data, which is to analyze a large number of accumulated historical vehicle detection data, merge similar traffic patterns, reduce the number of road network data, and organize the traditional road network. It is a traffic network suitable for traffic information applications.

Another object of the present invention is to provide a traffic information collecting technology, such as a traffic detector network, a GPS Floating Vehicle Detector (GFVD), and a Cellular Floating Vehicle Detector (CFVD). The traffic information collecting technology can utilize the traffic road network generated by the present invention to perform functions such as collecting, calculating, and releasing traffic information. According to the historical traffic conditions combined with the traffic network segment, the traffic information collection technology can simplify the traffic change mode of each road segment, reduce the number of traffic road network data, speed up the real-time processing efficiency of GIS technology, and improve the performance of traffic information collection technology.

A traffic network generation method for applying vehicle detection data that can achieve the above object is to analyze a road network by using a large amount of historical vehicle detection data such as GPS data of a vehicle's timed back transmission which is extremely popular today, or mobile phone base station wireless network signaling. The traffic mode of the road section combines the similar traffic information mode with the adjacent road sections to generate a traffic road network. Traffic information gathering technologies such as vehicle detectors, GPS Floating Vehicle Detector (GFVD), Cellular Floating Vehicle Detector (CFVD), etc., can reduce the road network data required for processing based on the traffic road network of the present invention, and calculate traffic of each road section Information to enhance the effectiveness of the traffic information collection technology system to achieve the Intelligent Transportation System (ITS), the Advanced Traveler Information System (ATIS) provides instant traffic information reduction for passers-by Travel time needs.

A traffic road network generating method for applying vehicle detection data is based on a road network formed by a plurality of geometric polygonal line segments, analyzing a traffic mode of vehicle detection data, and combining overlapping road segments with similar traffic modes to generate a traffic road network. The method comprises the following steps: analyzing a vehicle trajectory, providing a driving trajectory analyzing unit, analyzing vehicle detection data of each vehicle to determine a road section through which the vehicle passes, and generating a road traffic mode, providing a traffic mode generating unit, The unit uses the road network traffic data from other sources, or calculates the traffic data of each road segment according to the road segment information and the results of the driving track analysis unit. After the traffic data of a certain period is accumulated in each road segment, the traffic mode generating unit is for each road segment. The traffic mode is established; the overlapping overlapping sections are provided, and the traffic mode comparison unit is provided, wherein the traffic mode of the overlapping overlapping sections is read, and the similarity of the traffic modes is calculated, and if the traffic patterns of the overlapping segments of the plurality of pens are similar, the traffic pattern is similar. Then merge the overlapping segments of the endpoint to remove the new segment. The merged road segment; if the traffic pattern similarity of the overlapping segments of the multiple endpoints is low, the merger is not combined, and the overlapping segments of the plurality of segments are set as reserved segments; if the endpoints of the single segment data do not overlap with the endpoints of other segments , the road section is set as a reserved road section; and the traffic network segment is stored, a road network storage unit is provided, and the new road section and the reserved road section are stored in the traffic network storage medium, wherein the vehicle detection data is global positioning system data, or Wireless communication network signaling, wherein the driving trajectory analysis unit reads the global positioning system data returned by the vehicle, and refers to the location information of the global positioning system data, and uses the spatial geometric algorithm to estimate the distance from the global positioning system. The network segment of the road refers to the time sequence of the global positioning system, and then obtains the road section through which the vehicle travels. The driving trajectory analysis unit analyzes the wireless communication network signaling by using the wireless communication network signaling returned by the mobile network base station. Base station ID field, by base station ID change using wireless communication network signaling And obtaining a road section through which the vehicle travels, wherein the road network traffic data of the other source that generates the road traffic mode is a road speed, a flow rate, or a occupancy rate, wherein the traffic mode generating unit system that generates the road traffic mode Using the traffic data of other sources, or based on the information of the road section and the results of the driving trajectory analysis unit, the traffic data of each road section is calculated. After the traffic data of a certain period is accumulated in each road section, the traffic mode generating unit establishes traffic data for each road section. The relationship with time changes to establish a traffic mode, wherein the traffic mode of the merged endpoint overlaps the traffic mode comparison unit to compare the traffic mode similarity of the overlapped road segment. The traffic mode comparison unit continuously compares the end point overlapping road section Zhizhi traffic mode until there is no overlapping road section with similar traffic mode in the road network, wherein the traffic network storage medium stored in the traffic network segment is data Library, or file system.

The present invention is accomplished by the following techniques:

1. After obtaining a large amount of accumulated historical vehicle detection data, the vehicle detection data is analyzed based on the basic attributes of the vehicle detection data and GIS technology. For example, GPS data has information such as time, latitude and longitude position and orientation. GIS technology can map the GPS to the network segment closest to the road, and then use the information such as time and orientation to know the route of the vehicle, and analyze the vehicle traffic. Track.

2. Using the vehicle's trajectory to calculate the traffic parameters such as speed, flow and occupancy, and using a large amount of accumulated vehicle detection data for a long time, establish a traffic mode model for each road segment.

3. Compare the traffic patterns of overlapping road sections. When there is a similar traffic mode, the road sections will be merged into new road sections. If the traffic modes of the road sections are not similar, the road sections will be retained. Finally, the new road section and the reserved road section will be recorded to generate a traffic road network.

The invention provides a method for generating a traffic road network using vehicle detection data, which can reduce the number of road network data and avoid the effect of segmenting too thin road network data on the traffic information application system. The generated traffic road network can be applied to traffic information gathering technologies such as GFVD. GFVD can use the traffic road network generated by the present invention as a traffic information road network to collect traffic information on the road. Due to the small number of data in the traffic network segment, GFVD can have better processing performance and improve the efficiency of traffic information calculation and release.

The method for generating a traffic road network using the vehicle detection data provided by the invention has the following advantages when compared with other conventional technologies:

1. The invention applies a large number of vehicle detection data, merges the adjacent road sections of the road network with similar traffic modes, and organizes the road network into a traffic road network, which can effectively reduce the number of road network data and improve the efficiency of the road network related applications.

2. The method for generating a traffic road network using vehicle detection data proposed by the present invention is particularly suitable for a GPS Floating Vehicle Detector (GFVD) system. Based on the traffic road network of the present invention, the GFVD system needs to process less road network data, which can improve the performance of the speed calculation process.

The invention is a traffic network generation method for applying vehicle detection data.

Please refer to FIG. 1 , which is a flowchart of an embodiment of a method for generating a traffic road network using vehicle detection data according to the present invention. The method for generating a traffic network can be divided into several steps:

1. Read vehicle detection data and road network data 105.

2. Analyze the vehicle travel trajectory 106.

3. Generate road segment traffic mode 107.

4. Detect whether there is a similar traffic mode 108 in the adjacent road segments. If yes, merge the adjacent road segments 109, if otherwise, retain the original road segment.

5. Store the traffic network 110.

The vehicle detection data 102 can be GPS data or mobile network wireless base station signaling, especially GPS data. The format field includes information such as time, latitude and longitude, direction and vehicle speed. The latitude and longitude and direction can be used to obtain GIS geometric operations. Out of the network segment data 101 closest to GPS. The road network segment data 101 is composed of a plurality of latitude and longitude points, which are geometric polygonal lines, and has two end points and intermediate points; the vehicle trajectory analysis 106 can obtain the road section of the vehicle, and can estimate the vehicle passing the road section according to the vehicle detection data 102. Traffic information such as speed, traffic and occupancy rate; after accumulating a large amount of traffic information on each section, traffic patterns 107 for each section can be established. If the middle point or the two end points of the two road sections overlap, indicating that the two road sections are adjacent, it can be judged whether the traffic modes are similar to 108. If the traffic modes are similar, the merged two road sections 109 are new road sections; if the traffic modes of the two road sections are not similar, then Keep two sections. Finally, the new road section 110 and the reserved road section are stored to the road network data storage medium 111 to complete the generation of the traffic road network.

Please refer to FIG. 2 , which is a system architecture diagram of an embodiment of a method for generating a traffic road network using vehicle detection data, and the composition thereof mainly includes the following parts:

1. Road network database 201: store general navigation road network, electronic map map and other information.

2. Vehicle Detection Database 202: Store vehicle detection data, such as GPS data that is periodically transmitted back by the vehicle.

3. Other sources traffic database 203: store the traffic database of other sources; the invention can use the vehicle detection data 102 to establish the vehicle trajectory, thereby establishing the road traffic mode 107, and directly using the traffic data 103 of other sources, such as the government. The traffic pattern generation unit 208 can establish a traffic mode according to other source traffic data 103 for the vehicle speed, traffic, and occupancy related parameters of the department or ETC (Electronic Toll Collection) system.

4. Road network formatting unit 204: The road network formatting unit 204 reads the road network data and converts it into a format that the system can process.

5. Vehicle detection data analysis module 205: The vehicle detection data analysis module 205 includes a driving trajectory analysis unit 107 and a traffic mode generation unit 208. The module reads the road network data 101, the vehicle detection data 102, and other sources. Traffic information 103, and the traffic patterns of the various sections are produced.

6. The travel trajectory analysis unit 207: The travel trajectory analysis unit 207 reads in the vehicle detection data 102 reported by each vehicle to analyze the road section through which the vehicle travels. For the GPS data, the driving trajectory analysis unit refers to the latitude and longitude information of the GPS data, and uses the spatial geometric algorithm to estimate the network segment closest to the GPS distance, and refers to the GPS time sequence, thereby obtaining the road section through which the vehicle travels. As tested in Annex 2, the dot indicates the vehicle trajectory data, the vehicle trajectory data is the data of the discrete time return, and the vehicle continuously moves on the road network. The vehicle trajectory analysis unit can be used to find the vehicle passing the Road-W. , Road-X, Road-Y and Road-Z sections. For the wireless communication network signaling returned by the mobile network base station, the travel trajectory analysis unit can analyze the base station ID field of the wireless communication network signaling, and can analyze the base station ID change situation of the wireless communication network signaling. The network segment through which the vehicle travels. As shown in Annex III, the vehicle is driven from the lower left to the upper right of the figure. The base station code of the collected wireless network signaling will be converted to A and B by D and E. The driving trajectory analysis unit can obtain this. The road section through which the vehicle passes is Road-X.

7. Traffic mode generating unit 208: According to the analysis result of the driving trajectory analyzing unit 207, the traffic mode generating unit 208 can know the road section through which the vehicle travels, so the traffic mode generating unit 208 can calculate the road segment information 101 and the vehicle detecting data 102. Traffic information such as road speed. After accumulating traffic information for a certain period of time, the traffic patterns can be established. As shown in Annex 1, the ordinate is the speed of time, the abscissa is the time point, and the traffic mode is the relationship between the speed of time and time. The traffic mode generating unit 208 stores the traffic mode data in the traffic mode database 209 for use by the traffic network generating module 206.

8. Traffic Mode Database 209: Stores the traffic patterns generated by the traffic pattern generation unit 208 for use by the traffic network generation module 206.

9. Traffic network generation module 206: The traffic network generation module 206 reads the traffic mode and the road network data in the traffic mode database 209, and after the road segment mode is compared and operated, the generated traffic road network is saved. Go to the traffic network database 212.

10. Traffic mode comparison unit 210: The traffic mode comparison unit 210 reads the traffic patterns of two adjacent road segments, and calculates the similarity between the two. If the similarity is high, the two adjacent road segments are merged into new road segments and the two road segments are removed. If the similarity is low, keep two segments. The traffic mode comparison unit 210 continuously performs the above process until there are no adjacent sections of the road network having similar traffic patterns. As shown in the attached section, the traffic mode of the road section is a vertical coordinate, the horizontal coordinate is the time point relationship table, and the Pattern-i and Pattern-j represent the traffic modes of the road sections i and j. Use the following formula to calculate the similarity between the two:

If the similarity between the road segment i and the road segment j is less than the threshold value, the two road segments are merged; otherwise, the road segment i and the road segment j are retained.

11. Road network storage unit 211: The road network storage unit 211 receives the traffic network data generated by the traffic mode comparison unit 210 and stores it in the traffic network database 212.

12. Traffic Network Database 212: The Traffic Network Database 212 stores traffic network data.

The detailed description of the present invention is intended to be illustrative of a preferred embodiment of the invention, and is not intended to limit the scope of the invention. The patent scope of this case.

To sum up, this case is not only innovative in terms of technical thinking, but also has many of the above-mentioned functions that are not in the traditional methods of the past. It has fully complied with the statutory invention patent requirements of novelty and progressiveness, and applied for it according to law. Approved this invention patent application, in order to invent invention, to the sense of virtue.

101. . . Road network information

102. . . Vehicle detection data

103. . . Road traffic information from other sources

104. . . Road network data formatting

105. . . Read vehicle detection data and road network data

106. . . Analyze vehicle trajectory

107. . . Generate road traffic patterns

108. . . Whether there are adjacent sections with similar traffic patterns

109. . . Merging adjacent sections

110. . . Storage traffic network

111. . . Traffic network storage medium

201. . . Road network database

202. . . Vehicle detection database

203. . . Road traffic information from other sources

204. . . Road network formatting unit

205. . . Vehicle detection data analysis module

206. . . Traffic network generation module

207. . . Trajectory analysis unit

208. . . Traffic mode generating unit

209. . . Traffic pattern database

210. . . Traffic mode comparison unit

211. . . Road network storage unit

212. . . Traffic network database

301. . . Traffic mode of section i

302. . . Traffic mode of road segment j

401. . . GPS vehicle detection data

501. . . Wireless communication signaling vehicle detection data

502. . . Wireless communication base station

Please refer to the detailed description of the present invention and the accompanying drawings, and the technical contents of the present invention and its effects can be further understood; the related drawings are:

The first figure is a flowchart of an embodiment of a method for generating a traffic road network using vehicle detection data according to the present invention;

The second figure is a system architecture diagram of an embodiment of a method for generating a traffic road network using vehicle detection data according to the present invention.

[A brief description of the attachment]

Annex 1 is a traffic pattern diagram of an embodiment of a method for generating a traffic road network using vehicle detection data according to the present invention;

Annex 2 is a trajectory diagram of a GPS vehicle probe data travel path according to an embodiment of the present invention;

Annex 3 is a trajectory diagram of the traveling path of the wireless communication signaling vehicle detecting data according to the embodiment of the present invention.

101. . . Road network information

102. . . Vehicle detection data

103. . . Road traffic information from other sources

104. . . Road network data formatting

105. . . Read vehicle detection data and road network data

106. . . Analyze vehicle trajectory

107. . . Generate road traffic patterns

108. . . Whether there are adjacent sections with similar traffic patterns

109. . . Merging adjacent sections

110. . . Storage traffic network

111. . . Traffic network storage medium

Claims (8)

A traffic road network generating method for applying vehicle detection data is based on a road network formed by a plurality of geometric polygonal line segments, analyzing a traffic mode of vehicle detection data, and combining overlapping road segments with similar traffic modes to generate a traffic road network. The method comprises the following steps: analyzing a vehicle trajectory, providing a driving trajectory analyzing unit, analyzing vehicle detection data of each vehicle to determine a road section through which the vehicle passes, and generating a road traffic mode, providing a traffic mode generating unit, The unit uses the road network traffic data from other sources, or calculates the traffic data of each road segment according to the road segment information and the results of the driving track analysis unit. After the traffic data of a certain period is accumulated in each road segment, the traffic mode generating unit is for each road segment. The traffic mode is established; the overlapping overlapping sections are provided, and the traffic mode comparison unit is provided, wherein the traffic mode of the overlapping overlapping sections is read, and the similarity of the traffic modes is calculated, and if the traffic patterns of the overlapping segments of the plurality of pens are similar, the traffic pattern is similar. Then merge the overlapping segments of the endpoint to remove the new segment. The merged road segment; if the traffic pattern similarity of the overlapping segments of the multiple endpoints is low, the merger is not combined, and the overlapping segments of the plurality of segments are set as reserved segments; if the endpoints of the single segment data do not overlap with the endpoints of other segments , the road section is set as a reserved road section; and the traffic network section is stored, a road network storage unit is provided, and the new road section and the reserved road section are stored to the traffic road network storage medium. A method for generating a traffic network using the vehicle detection data according to claim 1, wherein the vehicle detection data is global positioning system data or wireless communication network signaling. The method for generating a traffic road network using the vehicle detection data according to claim 1, wherein the travel trajectory analysis unit reads the global positioning system data returned by the vehicle, and refers to the location of the global positioning system data. Information, using the spatial geometric algorithm to calculate the nearest network segment from the global positioning system, refer to the global positioning system time sequence, and then obtain the road section of the vehicle. A method for generating a traffic road network using vehicle detection data according to claim 1, wherein the traffic trajectory analysis unit analyzes the wireless communication network signaling by using wireless communication network signaling returned by the mobile network base station. The base station ID field is obtained by using the base station ID change situation of the wireless communication network signaling to obtain the road section through which the vehicle travels. A method for generating a traffic road network using the vehicle detection data according to claim 1, wherein the road network traffic data of the other source that generates the road traffic mode is a link speed, a flow rate, or a occupancy rate. A method for generating a traffic road network using the vehicle detection data according to claim 1, wherein the traffic mode generating unit that generates the road traffic mode utilizes road network traffic data of other sources, or according to the road segment information The results of the driving trajectory analysis unit are used to calculate the traffic data of each road segment. After the traffic data of a certain period is accumulated in each road segment, the traffic mode generating unit establishes a relationship between the traffic data and the time for each road segment to establish a traffic mode. The traffic network generation method for applying vehicle detection data according to claim 1, wherein the traffic mode comparison unit of the merged end point overlaps the traffic pattern similarity of the overlapping road segments. The traffic mode comparison unit continuously compares the end point overlapping road section of the traffic mode until the end of the road network has no overlapping road sections with similar traffic modes. A method for generating a traffic network using the vehicle detection data according to claim 1, wherein the traffic network storage medium stored in the traffic network segment is a database or a file system.