JPH1125130A - Collected information processing method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To reduce the number of data to be held on a center side by processing collected information from mobile terminals and to secure reliability by compressing the collected information sorted for each position attribute and each class. SOLUTION: As the mobile terminal, a probe car 10 respectively possesses various kinds of road information (such as jamming and accidents) through an on-vehicle sensor and sends it to a satellite 12. The satellite 12 transmits that information to a center 14. To the information transmitted from the probe car 10, the 'class' and 'position' are added and while using the data, the center 14 sorts (groups) the collected information. After the information is sorted based on the class and position, compression processing is performed for reducing the information quantity and securing the reliability, and the information is made into data of various classes and positions. Therefore, the format of information stored in the memory of the center 14 and provided to the other mobile terminal becomes the class, position, data and reliability.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

TECHNICAL FIELD The present invention relates to a collection information processing method,
In particular, it relates to management and processing of information sent from a plurality of mobile terminals.

[0002]

2. Description of the Related Art Japanese Patent Laying-Open No. 6-195536 discloses a system in which information about passing vehicles is transmitted from an entrance tollgate to an exit tollgate via a satellite and used for billing. In this case, the data to be transmitted has a meaning individually, and its value does not include an error. Also,
Since the number of data to be transmitted is also limited to the number of users on the toll road, the processing load on the center is not heavy.

[0003] Also, rather than in such pricing information, various information of the road (traffic congestion, accidents, CO ₂ concentration, etc.) of the car equipped with a sensor to obtain the (probe car) to collect information on the other vehicles A system to provide it is also being considered.

[0004]

However, when collecting various information from a probe car, since many vehicles travel at the same point, the same information is sent to many centers. If the data is stored as it is, the data amount becomes enormous, and the memory capacity of the center becomes insufficient. In addition, data sampled by the probe car may have variations due to the sampling environment and timing, and further includes errors of the sensor itself, so it is necessary to ensure data reliability at the center side. There is.

The present invention has been made in view of the above-mentioned problems of the prior art, and has as its object to reduce the number of data held at the center side by processing information collected from a mobile terminal and improving its reliability. It is an object of the present invention to provide a collection information processing method that can secure the information.

[0006]

According to a first aspect of the present invention, there is provided a method for processing various information collected from a mobile terminal and providing the processed information to another mobile terminal. The collected information is classified based on the location attribute and type of the information collected from the terminal, and the collected information classified for each location attribute and type is compressed.

According to a second invention, in the first invention, the compression processing sequentially overlap-compresses the collected information for a predetermined time.

In a third aspect of the present invention, in the first and second aspects, the reliability of the compression value obtained by the compression processing is calculated and attached to the compression value.

In a fourth aspect based on the first to third aspects, the position attribute used for the classification is determined based on the type.

[0010]

Embodiments of the present invention will be described below with reference to the drawings.

FIG. 1 shows a system configuration diagram of the present embodiment. A probe car (including a general vehicle) 10 as a mobile terminal is provided with various information (road congestion,
Accidents, new roads, travel time, CO ₂ concentration, NOx concentration, etc.)
Is acquired by a vehicle-mounted sensor, and the acquired information is sent to the satellite 12. The satellite 12 receives the information transmitted from each probe car 10 and transmits the information to the center 14 on the ground. The information transmitted from the probe car is provided with “type” and “position”, and the center 14 classifies (groups) the collected information using these. Specifically, (Type 1,
Data 1, data 2, data 3 at position 1), data 1, data 2, data 3 at (type 2, position 1), data 1, data 2, at (type 3, position 3)
Data 3 and the like. Then, after the classification based on the type and the position, compression processing is performed to reduce the amount of information and secure the reliability, and the data in (type 1, position 1) and the data in (type 2, position 1) data,
(Type 3, position 3). In the present embodiment, as shown in the figure, the reliability of data obtained by compressing information is also calculated and attached to the data. Therefore, the format of the information stored in the memory of the center 14 and provided to other mobile terminals is type, position, data, and reliability.

FIG. 2 shows a processing flowchart in the center 14 of this embodiment. When information is collected from the probe car 10, all information is sequentially read out to the end (S101, S105), and the type is determined (S1).
02). As described above, there are traffic jams, accidents, travel times, NOx, road surface friction coefficient μ, and the like, and the information is classified for each type. Next, the position of the information in each type is determined and classified for each position (S103). The position is
More specifically, there are links, areas, and the like in addition to Hokkaido, the Tohoku region, and the like, which are determined according to the type of information. For example, if the type of information is travel time, it is classified by link (each link number), and if it is traffic congestion information, it is classified by link (each link number). If it is NOx concentration, it is classified by area (area). Etc.). After classifying by information type and position, compression processing is performed for each classification (S104).

FIG. 3 shows a detailed flowchart of the compression processing in S104. The number n of data of information classified by type and position is counted (the initial value is n = 0) (S
201), a weighted average value ave _n of n pieces of information is

Equation 1 ave _n = (ave _n-1 * (n-1) + dat _n ) / n (1) is calculated (S202). Note that dat _n is the value of the n-th (last collected) information. Then, after calculating the average value ave _n as the compression value, the reliability relia of the compression value is calculated (S203). When an average value is used as the compression value, the reliability can be a variance or a standard deviation. Of course, as shown in FIG. 4, the number of information n (horizontal axis) and the reliability (vertical axis) have a positive correlation (the larger the number, the higher the reliability). It is also possible to use itself. Further, when a value other than the average value is adopted as the compression value, it is preferable that the reliability is determined in accordance with the value. For example, when the type of information is travel time, the maximum value of the information may be adopted as the compression processing, and the minimum value or the difference between the maximum value and the minimum value may be adopted as the reliability. The compression value is
It is also conceivable to set a certain threshold value and compress information by automatically deleting information exceeding the threshold value. In this case, the compression value is plural.

As described above, according to the present embodiment, the collected information is classified based on the type and position of the information, and the classified information is compressed and provided to other mobile terminals, so that the memory capacity of the center 14 is reduced. In addition, the reliability of the provided information can be improved by averaging processing or the like. Further, in the present embodiment, since the reliability is calculated together with the compression value and provided to other mobile terminals, each mobile terminal receiving the compression value may appropriately process the received compression value using the reliability. Possible and the system can be used more effectively.

If the old data does not make use, a weighted average for increasing the weight of the latest information can be performed as the compression processing. However, since the ratio of the old information increases with time, the reliability is high. It is difficult to obtain a compression value. Of course, it is conceivable to clear old information once and collect new information again, but if past information is collectively discarded, the reliability of the provided information temporarily decreases due to a decrease in the number of parameters. . Therefore, instead of compressing (weighting and averaging) all the information at once, it is desirable to update the information while maintaining the reliability by successively compressing the time-series collected information at predetermined time intervals and performing compression processing. .

FIG. 5 schematically shows such a compression processing method. In the figure, P is a group of certain information classified by type and position, and it is assumed that data 1, data 2,..., Data n are collected in time series. Effective time of information (depending on type, for example, road surface friction coefficient μ
Then, if T is 2 hours, then T / 2 (T /
(Or 3 or less). In the figure, the group A starts compression at a certain time, and the compressed value data A and the reliability relia. Suppose you got A. B in the figure
The group A starts the compression processing of a new information group in parallel with the group A at T / 2 after the group A starts the compression processing, and the compression value data B and the reliability relia. Suppose B is obtained. In the population of the group B, the old data 1, data 2,
Data 3 and data 4 are not included. Similarly, in the group C in the figure, the compression processing of the new information group is started in parallel with the group B after T / 2 after the group B starts the compression processing, and the compression value data C and the reliability relia. Suppose C is obtained. The old data included in the group B is not included in the population of the group C.

The information (information for a predetermined time) collected during the time 0 to T after the start of data collection is used for the compressed value data A of group A and the reliability rel. A is adopted and provided to the mobile terminal, and for the information collected during the time T３3T / 2, the value of group A is discarded and the compressed value data B of group B and the reliability relia. B was adopted and time 3T /
For 2 to 2T, the compressed value data C and relia. C is adopted. Note that, since the group A continues to process new information even after the group B starts the compression processing, some information overlaps with the group A and the group B (for example, data 5). Similarly, the B group and the C group perform compression processing in parallel, and some information overlaps with the B group and the C group.
From time T / 2 to T, the compressed value data A of the group A and the reliability relia. A and B group compressed value data B, reli
a. B exists at the same time, but at this point, the reliability of the group A is higher because the parameter is larger, and the value of the group A is adopted until the time T is exceeded. As a result, it is possible to prevent a decrease in reliability when old information is discarded and to provide a highly reliable compressed value.

Although the type, position, compression value, and reliability are calculated for each of the groups A, B, and C in FIG. 5, the type and position to be compressed are common to each group. These can be handled collectively as shown. In the figure, the type and position are common, and the compression value and reliability for each group are sequentially calculated and stored in one format.
Other mobile terminals that receive information in this format,
relia. A, relia. B, relia. What has the highest reliability among C may be adopted.

[0019]

As described above, according to the present invention,
The information collected from the mobile terminal can be processed to reduce the number of data held on the center side, and its reliability can be ensured.

[Brief description of the drawings]

FIG. 1 is a system configuration diagram of an embodiment of the present invention.

FIG. 2 is an overall processing flowchart of the embodiment.

FIG. 3 is a flowchart of a compression process according to the embodiment;

FIG. 4 is a graph showing the relationship between the number (parameter) and reliability.

FIG. 5 is an explanatory diagram illustrating a compression method according to the embodiment;

FIG. 6 is an explanatory diagram showing another compression method according to the embodiment;

[Explanation of symbols]

 10 vehicles (mobile terminals), 12 satellites, 14 centers.

Claims (4)

[Claims] 1. A method for processing various information collected from a mobile terminal and providing the processed information to another mobile terminal, wherein the collected information is classified based on a position attribute and a type of the information collected from the mobile terminal. And a compression processing of the collected information classified for each position attribute and each type. 2. The collection information processing method according to claim 1, wherein the compression processing sequentially and redundantly compresses the collected information for a predetermined time. 3. The collection information processing method according to claim 1, further comprising calculating reliability of the compression value obtained by the compression processing and attaching the reliability to the compression value. 4. The method according to claim 1, wherein a position attribute used for the classification is determined based on the type.
3. The collection information processing method according to any one of 3.