WO2011082613A1

WO2011082613A1 - Processing method and processing system based on traffic information of floating car

Info

Publication number: WO2011082613A1
Application number: PCT/CN2010/079438
Authority: WO
Inventors: 殷庆丹; 胡健; 魏俊华; 李建军
Original assignee: 北京世纪高通科技有限公司
Priority date: 2010-01-08
Filing date: 2010-12-03
Publication date: 2011-07-14
Also published as: CN101807343A

Abstract

A processing method based on traffic information of a floating car comprises the following steps: acquiring raw GPS data of a floating car (11); collating the raw GPS data of the floating car, and converting the data into a standard data format (12); and preprocessing the collated raw GPS data of the floating car (13). A processing system based on traffic information of a floating car comprises a collecting device (31), a collation unit (32) and a preprocessing unit (33).

Description

The invention relates to a processing method and a processing system based on floating car traffic information, which is submitted on January 8, 2010, and whose application number is 201010033841.4. Priority of the Chinese application, the entire contents of which are incorporated herein by reference.

The invention relates to the field of Intelligent Transportation Systems (ITS), in particular to a processing method and a processing system based on floating car traffic information. Background technique

In the field of intelligent transportation, real-time and dynamic traffic information can provide effective traffic planning information for vehicle travel, thereby saving travel time, improving work efficiency, and reducing energy consumption. There are many techniques for collecting traffic data. Currently, the commonly used collection method is a buried coil detector (also known as a fixed detector), but the fixed detector has high installation and maintenance costs, small coverage, and can only be detected. Insufficient fixed-location data, etc., led to a large amount of information "vacuum" zones on urban road networks. Another automated detection method that can represent the trend of detectors is microwave radar, laser radar, ultrasonic, video detection technology and floating technology, but these methods adapt to different occasions due to different collection principles, and most of them are installed. The site and environment have special requirements.

The use of the Global Position System (GPS) and floating vehicles (also known as motion detectors) for wireless communication devices to collect traffic information is a new way of gathering information. According to the position information recorded by the floating car during the driving process (the floating car GPS data), the data of the relevant calculation model such as data collection, data filtering, map matching, path estimation and multi-vehicle fusion, so that the floating car GPS data and the city The road network is related in time and space, and finally obtains traffic congestion information such as the speed of the vehicle and the travel time of the road through which the floating vehicle passes. Summary of the invention

The invention provides a processing method and a processing system based on floating car traffic information.

In one aspect, the method for processing floating vehicle traffic information provided by the present invention includes the following steps: Obtain the original GPS data of the floating car;

The original GPS data of the floating car is sorted and converted into a standard data format;

Pre-process the original GPS data of the finished floating car.

Further, the step of acquiring the original GPS data of the floating car is specifically: receiving the original GPS data of the floating car from the monitoring center according to the network communication transmission protocol format.

Further, the step of sorting the original GPS data of the floating car into a standard data format comprises: extracting useful fields from the original GPS data of the floating car according to the floating car standard data format requirement, wherein the useful fields include Vehicle source ID, vehicle ID, sample time, latitude and longitude coordinates, speed, direction, state, etc.; convert the position coordinates derived from surveying into encrypted coordinates in accordance with national regulations; and save the sorted floating car GPS data to different Within the timestamp file.

Preferably, when the floating car GPS data is saved, the interval between the start time and the next time stamp is determined: if the interval time is less than twice the return period, the floating car GPS data is saved in the next time stamp file, Otherwise saved in the file with the current timestamp.

Further, the step of pre-processing the original GPS data of the finished floating car comprises: determining the validity of the floating car GPS data, filtering the invalid data; performing statistics on the filtered valid data records; and pre-processing the data result Make the output.

The determining the validity of the GPS data of the floating vehicle includes: determining whether the latitude and longitude coordinates of the GPS data are incorrect; determining whether the GPS data exceeds the sampling period; determining whether the latitude and longitude coordinates of the GPS data exceed the latitude and longitude range; determining the GPS data Whether it exceeds the grid range, where the grid range is the range in which the grid within the specified output grid extends to the outside world; and, whether the state of the floating vehicle GPS data is empty.

The statistics of the filtered valid data records include: Sorting the GPS data according to the vehicle ID, vehicle ID, and time sequence, and filtering the repeated GPS data records and the individual GPS data records under the vehicle ID.

The output of the preprocessed data results includes three cases: Case 1: The vehicle source ID and the vehicle ID are all consistent with the previous record, and the GPS data is stored in the current vehicle source ID and the data structure of the vehicle ID. Next, and the number of GPS data is increased by one; Case 2: The vehicle source ID is consistent with the previous record, the vehicle ID is inconsistent with the previous record, then the number of vehicle IDs is increased by one, and the vehicle ID is reset to the current new vehicle ID, new The number of GPS data of the vehicle ID is set to one, and the GPS data is stored under the data structure of the new vehicle ID; Case 3: The vehicle source ID is inconsistent with the previous record. Then, the number of the vehicle source ID is increased by one, the reset vehicle source ID is the current new vehicle source ID, the vehicle ID is the current new vehicle ID, the number of GPS data of the new vehicle ID is set to one, and the GPS data is stored in the new vehicle source ID. , under the data structure of the new vehicle ID.

On the other hand, corresponding to the processing method described above, the processing system based on the floating vehicle traffic information provided by the present invention includes:

a collecting device for acquiring original GPS data of the floating car;

a sorting unit, configured to sort the original GPS data of the floating car acquired by the collecting device, and convert the data into a standard data format;

And a pre-processing unit, configured to pre-process the original GPS data of the floating car after the finishing unit is finished.

Specifically, the collecting device may be configured to receive the original GPS data of the floating car from the monitoring center according to the network communication transmission protocol format; the sorting unit may be used to meet the standard data format requirement of the floating car, from the original GPS of the floating car Extracting useful fields from the data; converting the position coordinates derived from the survey to the encrypted coordinates conforming to the state; saving the sorted floating car GPS data to different time stamp files; the pre-processing unit can be used for floating The GPS data validity of the vehicle is determined, and the invalid data is filtered; the number of valid data records after filtering is counted; and the preprocessed data result is output.

According to the technical solution provided by the present invention, by using the floating car technology, the original data is first received from the monitoring center, and then the original data is sorted into a standard data format, and finally the processed data is preprocessed to filter the useless without any reference value or The erroneous data can greatly improve the point matching rate, reduce the abnormal situation processing, and improve the effectiveness and efficiency of the floating vehicle traffic information processing.

DRAWINGS

In order to more clearly illustrate the technical solution of the present invention, the following needs to be made in the description of the embodiments. The drawings are briefly introduced.

1 is a schematic flow chart of a method for processing traffic information based on floating vehicles according to the present invention; FIG. 2 is an illustration of a range of grids in the present invention;

FIG. 3 is a structural diagram of a processing system based on floating car traffic information provided by the present invention. detailed description

The technical solutions provided by the present invention are further described in detail below with reference to the accompanying drawings and embodiments.

Referring to Figure 1, the present invention provides a method for processing traffic information based on floating vehicles, including the following:

11 , Get the original GPS data of the floating car.

Specifically, the original GPS data of the floating car is received from the monitoring center according to the network communication transmission protocol format.

Floating car GPS data is generally transmitted to the floating car handling system by the taxi company/dispatch monitoring center (hereinafter referred to as the monitoring center) using network communication. Through the TCP/IP protocol, the monitoring center and the floating car processing system are connected, and the floating car GPS data is received from the monitoring center in real time and correctly.

Since the network transmission protocol between the monitoring center and the floating car processing system is different, in order to correctly receive and process the received floating car data from the monitoring center, it is necessary to write a raw data receiving program to facilitate the application and calculation of the subsequent processing program. . In order to improve scalability, the system can use the configuration table method to configure the network parameters of the receiving and sending targets. Configure the socket by reading the network parameters in the configuration table, then accept the raw floating car GPS data from the monitoring center.

Save the original floating car GPS data. Because in the subsequent processing of the floating car GPS data, once an abnormality is found, if the cause of the abnormality is to be found, it is often started from the analysis and inspection of the original data. In addition, in order to improve the processing efficiency, the processing is unified only when the received data reaches the specified number. At the same time, in the process of processing, if the format is wrong or the logic is not satisfied, the data needs to be stored in the error file for subsequent problem investigation. The processed data is stored in the corresponding timestamp file according to the received system time. 12. Organize the original GPS data of the floating car and convert it into a standard data format.

The data collected by the floating car generally includes time stamp, position coordinates, instantaneous speed, driving direction, operating status and other contents. Since the data recorded by taxis belonging to different cities and different monitoring centers will differ in parameter definition, type, format, etc., it is necessary to convert the received data into a standard format for subsequent processing. The specific steps to organize the data are as follows:

Step 1: According to the floating car standard data format requirements, extract useful fields from the original GPS data of the floating car.

From the raw data of the floating car, organize the valid information according to the floating car data format requirements. What must exist in the original data: vehicle ID, vehicle ID, sample time, latitude and longitude coordinates, speed and direction. If other field data does not exist, it is supplemented with the specified value, and the logic of the data is checked, such as the range of values such as repeatability, coordinates, speed, direction, etc., to filter the wrong floating car GPS data. In addition, some monitoring centers also provide some extension fields. If these extension fields match the subsequent maps, the path recommendation has no use and needs to be filtered.

The collated data structure only needs to include useful fields such as vehicle ID, vehicle ID, sampling time, longitude, latitude, speed, direction, status, etc., to delete those useless extension fields. In addition, in order to make the data collation as much as possible to adapt to the local data, the present invention can use the configuration table method to describe the data structure and the extracted data.

Step 2: Convert the position coordinates from the survey to the encrypted coordinates that meet the national regulations.

Step 3: Save the sorted floating car GPS data to a different time stamp file.

Evaluation criteria for floating-car GPS data systems typically include real-time, accuracy, and system coverage. In order to realize the real-time and feasibility of traffic information, it is necessary to save the sorted floating car GPS data to different time stamp files. The floating car handling system of the present invention stores floating car GPS data in five minutes as a time stamp.

When saving the GPS data of the floating car, it is necessary to judge the interval between the start of the receiving time and the next time stamp: If the interval time is less than twice the return period, the GPS data of the floating car is saved in the next time stamp file, otherwise it is saved. Within the file of the current timestamp. Because if it is less than back If the period is twice, then the vehicle ID has only one GPS data in the current time stamp, and the subsequent path estimation cannot be performed, but the floating vehicle GPS data is valid data, so the present invention starts when saving the floating vehicle GPS data. The time interval of the receiving time from the next time stamp is less than twice the return period, and the floating car GPS data is saved in the next time stamp file. This can effectively avoid the loss of valid data and improve the coverage of the floating car system.

For example: the start receiving time is 4'30", and the return period is 60 seconds. For the time of 4'30", the next timestamp is 5Ό0", then the next timestamp is 30 seconds, which is less than the two of the return period. Times, so the GPS data exists under 5时间戳0" under this timestamp file.

13 , Pre-processing the original GPS data of the finished floating car.

In general, the accuracy of GPS data is about 15m. Due to objective reasons such as GPS terminals being blocked by buildings, individual GPS data may cause drift errors. In order to facilitate the processing of the subsequent modules, the GPS data of the floating car needs to be sorted and sorted in order according to the vehicle source ID, the vehicle ID, and the chronological order. The specific steps of data preprocessing are as follows:

Step 1: Determine the validity of the GPS data of the floating car and filter the invalid data.

The quality of the GPS point location information sent by the floating car is uneven, there is useless data beyond the sampling period and coverage, and there may be useless or erroneous data that has no reference value for the road congestion state estimation, which needs to be valid for the GPS data itself. Judgment of state and state, filtering invalid data.

The effectiveness of the floating car GPS data itself is determined, including the following:

(1) determining whether the latitude and longitude coordinates of the GPS data are incorrect;

(2) determining whether the GPS data exceeds the sampling period;

(3) determining whether the latitude and longitude coordinates of the GPS data exceed the latitude and longitude range;

(4) determining whether the GPS data exceeds the grid range;

In order to prevent filtering of valid data, the grid range is a range of grids that are expanded to the outside world by a grid within the specified output grid. As shown in Figure 2, the blank grid is the specified output range grid, and the gray grid is the grid range added after expansion. The state of the GPS data of the floating car generally includes the states of no-load, full load, and the like. The taxis in the non-carrier state will be parked on the roadside or slowly travel along the road, so the data collected is It can't truly reflect the road conditions at that time, and when the instantaneous speed is very small, the GPS data tends to have a serious static drift phenomenon. Therefore, it is necessary to eliminate the data recorded as no-load in advance to truly reflect the current road condition.

Step 2: Perform statistics on the number of valid data records after filtering.

The data validity flag is set by sequentially determining the latitude and longitude of the data, the sampling period, the grid range, the event, state of the GPS data, and the like. After the validity of the data is set, the GPS data is sorted according to the vehicle source ID, the vehicle ID, and the time sequence, which facilitates the subsequent effective record count.

The number of valid data records is the number of valid vehicle IDs, the number of vehicle IDs, and the amount of valid GPS data for each vehicle ID. By counting the number of effective records, it is possible to allocate the number of vehicle sources, the number of vehicles, and the space of GPS point data at a time, which can improve the processing efficiency. The statistical method is specifically:

First, it is judged whether the record and the previous record are the same vehicle source ID, and then it is judged whether or not the previous record is the same vehicle ID, and finally it is judged whether the sample time is repeated, and the GPS data record of the repeated time is filtered. The number of valid records can be counted by the above three steps, and a single GPS data record under the vehicle ID can be filtered by counting the number of valid records.

That is, if the vehicle source ID is consistent with the previous record, but the vehicle ID is inconsistent with the previous record, if the number of GPS data records under the current vehicle ID is less than or equal to one, the record is a single point GPS data record under the vehicle ID. , is the need to filter. Or if the vehicle source ID is inconsistent with the current record, the vehicle ID under the current vehicle source ID is determined. If the number of GPS data records under the vehicle ID is less than or equal to one, the record is a single point GPS data record under the vehicle ID. It also needs to be filtered. This is because if a vehicle ID has only one GPS data, the GPS data cannot be used for subsequent path estimation, so the GPS data is invalid.

Step 3: Output the preprocessed data results.

For valid data, it should be judged whether the record and the previous record are the same vehicle source ID, and then judge whether the previous record is the same vehicle ID. There are three cases here: Case 1: When the vehicle source ID and the vehicle ID are both consistent with the previous record, the GPS data is stored under the current vehicle source ID and vehicle ID data structure, and the number of GPS data is increased by one.

Case 2: The vehicle source ID is consistent with the previous record. If the vehicle ID is inconsistent with the previous record, the vehicle ID is a new ID, so the number of vehicle IDs is increased by one, and the vehicle ID is reset to the current new vehicle ID. The number of GPS data of the vehicle ID is set to one, and the GPS data is stored under the data structure of the new vehicle ID.

Case 3: The source ID is inconsistent with the previous record. The source ID is a new vehicle ID, which is a new vehicle ID under the new vehicle ID. Therefore, the number of vehicle IDs is increased by one, the reset vehicle source ID is the current new vehicle source ID, the vehicle ID is the current new vehicle ID, the number of GPS data of the new vehicle ID is set to one, and the GPS data is stored in the new vehicle source ID. , under the new vehicle ID under the data structure.

Experience has shown that the original GPS data can significantly improve the point matching rate after data preprocessing. In addition, through data preprocessing, the map matching processing will be simpler and more convenient, and the abnormal situation processing can be reduced, which can improve the processing efficiency and speed up the processing efficiency. Therefore, it is necessary to pre-process the received GPS data before calculation.

Compared with existing fixed detectors and automatic detection methods: Floating vehicle technology does not need to increase road facilities, and has no negative impact on the environment; Detection information can dynamically reflect the movement of road traffic flow in real time; Wide coverage; High positioning accuracy, positioning The data includes the instantaneous speed of the traveling vehicle at the positioning time and the positioning position, which implies the changing characteristics of the road traffic flow, and when a large number of floating vehicles are running in the road network, the traffic operation status of the entire road network can be reflected in real time.

The invention utilizes the floating car technology, firstly receives the original data from the monitoring center, and then sorts the original data into a standard data format, and finally preprocesses the sorted data, filters the useless or erroneous data without any reference value, and can greatly improve the point. The matching rate reduces the abnormal situation processing and improves the effectiveness and efficiency of the floating vehicle traffic information processing.

Referring to FIG. 3, corresponding to the foregoing method embodiment, the present invention further provides a processing system based on floating car traffic information, including:

The collecting device 31 is configured to acquire original GPS data of the floating car; a sorting unit 32, configured to sort the original GPS data of the floating car acquired by the collecting device 31, and convert the data into a standard data format;

The pre-processing unit 33 is configured to pre-process the original GPS data of the floating car that is arranged by the finishing unit 32. specifically,

The collecting device 31 is configured to receive the original GPS data of the floating car from the monitoring center according to the network communication transmission protocol format.

The sorting unit 32 is configured to extract useful fields from the original GPS data of the floating car according to the floating car standard data format requirement; convert the position coordinates derived from the surveying into encrypted coordinates conforming to the state regulations; The car GPS data is saved to a different timestamp file.

The pre-processing unit 33 is configured to determine the validity of the GPS data of the floating car, filter the invalid data, and perform statistics on the number of valid data records after filtering; and output the result of the pre-processed data.

For the processing method of each device or unit in the system, refer to the above-mentioned processing method based on floating car communication information, and details are not described herein again.

It should be understood that the invention is not limited to the specific embodiments disclosed. It should be understood by those skilled in the art that any modifications, equivalents, improvements, etc. are made without departing from the spirit of the invention.

Claims

Claim

A method for processing traffic information based on floating vehicles, characterized in that it comprises:

Obtain the original GPS data of the floating car;

Pre-process the original GPS data of the finished floating car.

2. The processing method according to claim 1, wherein the acquiring the original GPS data of the floating car comprises:

According to the network communication transmission protocol format, the original GPS data of the floating car is received from the monitoring center.

3. The processing method according to claim 1, wherein the sorting the raw GPS data of the floating car into a standard data format comprises:

Extracting useful fields from the original GPS data of the floating car according to the floating car standard data format requirements;

Converting the position coordinates derived from the survey to the encrypted coordinates in accordance with the state regulations;

Save the sorted floating car GPS data to a different time stamp file.

4. The processing method according to claim 3, wherein the useful fields extracted from the original GPS data of the floating vehicle include:

Vehicle ID, vehicle ID, sample time, latitude and longitude coordinates, speed, direction, status.

The processing method according to claim 3, wherein the storing the rearranged floating vehicle GPS data into different time stamp files is specifically:

When saving the floating car GPS data, determine the interval between the start of the receiving time and the next time stamp: If the interval time is less than twice the return period, save the floating car GPS data in the next time stamp file, otherwise save it in The current timestamp in the file.

The processing method according to claim 1, wherein the preprocessing the original GPS data of the sorted floating car comprises:

Determining the validity of the floating car GPS data, filtering invalid data; Statistics on the number of valid data records after filtering;

The preprocessed data results are output.

7. The processing method according to claim 6, wherein the determining the validity of the floating vehicle GPS data comprises:

Determining whether the latitude and longitude coordinates of the GPS data are incorrect;

Determining whether the GPS data exceeds the sampling period;

Determining whether the latitude and longitude coordinates of the GPS data exceed the latitude and longitude range;

Determining whether the GPS data is beyond the range of the grid, wherein the grid range is a range in which the grid within the specified output grid extends to the outside world; and

Determine whether the status of the floating car GPS data is empty.

8. The processing method according to claim 6, wherein the counting the number of valid data records after filtering comprises:

The GPS data is sorted according to the vehicle ID, vehicle ID, and time sequence, and the GPS data record repeated for the sample time and the single GPS data record under the vehicle ID are filtered.

9. The processing method according to claim 6, wherein the outputting the preprocessed data result comprises three cases:

Case 1: If the vehicle ID and vehicle ID are consistent with the previous record, the GPS data is stored under the current vehicle ID and vehicle ID data structure, and the number of GPS data is increased by one;

Case 2: The vehicle source ID is consistent with the previous record. If the vehicle ID does not match the previous record, the number of vehicle IDs is increased by one. The reset vehicle ID is the current new vehicle ID, and the number of GPS data of the new vehicle ID is set to one. , the GPS data is stored under the data structure of the new vehicle ID;

Case 3: The source ID is inconsistent with the previous record. Then, the number of the vehicle source ID is increased by one, the reset vehicle source ID is the current new vehicle source ID, the vehicle ID is the current new vehicle ID, the number of GPS data of the new vehicle ID is set to one, and the GPS data is stored in the new vehicle source ID. , under the data structure of the new vehicle ID.

10. A processing system based on floating vehicle traffic information, characterized in that:

a collecting device for acquiring original GPS data of the floating car; a sorting unit, configured to sort the original GPS data of the floating car acquired by the collecting device, and convert the data into a standard data format;

The pre-processing unit is configured to pre-process the original GPS data of the floating car after the finishing unit is finished.

The processing system according to claim 10, wherein the collecting means is specifically configured to receive the original GPS data of the floating car from the monitoring center according to a network communication transmission protocol format.

The processing system according to claim 10, wherein the sorting unit is specifically configured to extract a useful field from the original GPS data of the floating car according to the floating car standard data format requirement; The coordinates are converted to the encrypted coordinates in accordance with the state regulations; the collected floating car GPS data is saved into different time stamp files.

The processing system according to claim 10, wherein the pre-processing unit is specifically configured to determine the validity of the GPS data of the floating car, filter the invalid data, and perform statistics on the number of valid data records after filtering; The data is preprocessed for output.