JP4680882B2 - Traffic information processing apparatus and traffic information display apparatus - Google Patents

Description

The present invention relates to a technology for processing traffic information such as traffic jams and travel times, and a technology for receiving and outputting the processed traffic information.

Patent Document 1 is known as a technique for estimating travel time from other information for a link without link travel time information (hereinafter referred to as “unprovided link”). With this technology,
The average vehicle speed of the link is calculated from the congestion degree information included in the external information. Then, the supplement information of the unprovided link is obtained from the calculated average vehicle speed. Further, the travel time of the unprovided link is estimated from the average vehicle speed for each link stored in advance for each time zone.

Patent Document 2 is known as a technique for obtaining the reliability of the predicted travel time value. In this technique, travel time data up to the current time of a road section including the corresponding road is collected, a pattern having a similar travel time is searched from a travel time storage table collected in the past, and a travel time storage value N hours ahead is stored. Is the estimated travel time. This process is repeated multiple times to obtain a plurality of candidate travel time prediction values, the mode value of the candidate value is determined as the travel time prediction value, and the reliability of the travel time prediction value is determined based on the distribution of the candidate value distribution. Find the degree.

JP-A-7-129893 JP 2002-260142 A

The technique described in Patent Document 1 is premised on application to a vehicle route guidance device. But,
The traffic information is updated every moment, and if the traffic information received in the past is included, both the storage capacity and the processing amount become enormous. In general, in a vehicle route guidance device that has insufficient storage capacity and processing performance, it is difficult to perform processing for estimating travel time of unprovided links in real time. Also,
It is inefficient to perform the same processing with each vehicle route guidance device.

Further, the technique described in Patent Document 2 has a problem in terms of convenience. For example, even if the prediction error Ws that is within the probability S is obtained, the Ws may not be in the practical range. For example, the prediction error Ws with a probability S within 90% for a predicted travel time value of 20 minutes is 100 minutes, and so on.
The present invention has been made in view of the above circumstances, and an object of the present invention is to process traffic information without imposing a burden on a device mounted on a car or the like. In addition, VICS traffic information and other traffic information that does not necessarily have high reliability and stability are appropriately statistically processed, and high-accuracy traffic information and reliability information are provided for more links including unprovided links. It is to provide.

In the present invention, traffic information used in a traffic information display device is created by a traffic information processing device. The traffic information processing apparatus is provided with traffic information acquisition means for obtaining traffic information including information on travel time of each link constituting a road on a map, and information on travel time provided by the traffic information acquisition means. For an unprovided link that has not been made, a supplement means for calculating traffic information relating to travel time is provided by an estimation complement process.

Here, the traffic information processing apparatus may include an accumulation unit that accumulates traffic information obtained by the traffic information obtaining unit, and a statistical unit that statistically processes past traffic information accumulated by the accumulation unit. .

Further, the traffic information processing apparatus of the present invention is a traffic information acquisition means for acquiring traffic information including information relating to travel time of each link constituting a road on a map from the outside, and a traffic acquired by the traffic information acquisition means. And an abnormal value determining means for determining data having an abnormality from the information.
The abnormal value determining means has a function of determining that data having a traffic congestion occurrence rate in a certain period is not less than a predetermined value is abnormal, and traffic having a large deviation compared to other traffic information in a plurality of days in the same time zone. A function for determining that the information is abnormal, and when the travel time and traffic jam information in a certain period are compared and one of them changes within the normal range but the other shows a constant value, the traffic jam information data At least one of the functions of determining that an error is detected.

Further, the traffic information processing apparatus of the present invention has traffic information acquisition means for acquiring traffic information including information on travel time of each link constituting the road on the map from the outside, and the traffic information acquisition means includes: Accumulating means for accumulating the obtained traffic information. And a link travel time probability calculating means for calculating a probability distribution related to the travel time of each link, and a probability distribution related to the travel time of each link calculated by the link travel time probability calculating means. A probability for a specific travel time range using a route travel time probability calculating means for calculating a probability distribution related to the travel time of a specific route, and a probability distribution relating to the travel time of the specific route calculated by the route travel time probability calculating means. Means for calculating.

Further, the traffic information display device of the present invention uses a means for obtaining information relating to the probability distribution relating to the travel time of each link, which is created by the traffic information processing device, and a probability distribution relating to the travel time of each link. A route travel time probability calculating means for calculating a probability distribution relating to a travel time of a specific route composed of links, a setting means for setting a travel time range or a travel time probability of the specific route, and the setting means, When the travel time range of the specific route is set, using the probability distribution regarding the travel time of the specific route, the probability that the travel time of the specific route is the travel time range set by the setting means is calculated, By setting means,
When the travel time probability of the specific route is set, a travel time range that falls within the travel time probability set by the setting means is calculated using the probability distribution related to the travel time of the specific route. And a reliability display means for displaying a result calculated by the reliability calculation means.

According to the present invention, the traffic information is processed by the traffic information processing device, so that the processing load of the traffic information display device mounted on a car or the like can be reduced.

Hereinafter, an embodiment of the present invention will be described with reference to the drawings. FIG. 1 is a schematic diagram of a traffic information system to which an embodiment of the present invention is applied. The traffic information system of the present embodiment includes a user terminal 200, a communication network 103, a traffic information processing device 107, and a traffic information providing center 100 that provides traffic information such as a VICS center. The user terminal 200 includes a communication network IF unit (IF represents an interface; the same applies hereinafter) 201, an information processing unit 202, a user IF unit 203, a storage device 204, and a display unit 205. Information processing unit 20
2 receives various types of traffic information from the traffic information processing apparatus 107 via the communication network IF unit 201 and the communication network 103, and stores the received traffic information in the storage device 204. In addition, a user request is received via the user IF unit 203, traffic information is appropriately processed according to the request content, and displayed on the display unit 205. Note that the user terminal 200 is not necessarily installed in the vehicle.

The traffic information processing apparatus 107 includes a communication network IF unit 112, a user management unit 113, a route search unit 114, a map DB (DB represents a database; the same applies hereinafter) 126, and a traffic information management unit 116. . The communication network IF unit 112 mediates each unit constituting the traffic information processing apparatus 107 and the user terminal 200 via the communication network 103. For example, when the communication network 103 is a WWW, the communication network IF unit 112 may include a CGI (Comm
on Gate Interface). The user management unit 113 registers and edits user information. The route search unit 114 uses a map data or the like based on information on the departure place (current location) and destination, or the departure location (present location), destination and waypoints sent from the user, and routes such as the Dijkstra method. The route from the vehicle position to the destination is calculated using a search method. When the user terminal side has a route search function, the route search unit 114 is not essential for the traffic information processing apparatus 107.

In the map DB 126, for each mesh area obtained by dividing the map into a plurality of parts, a mesh area identification code (mesh ID) and link data of each link constituting a road included in the mesh area are registered / registered. Managed. Link data includes link identification code (link ID), coordinate information of two nodes (start node, end node) constituting the link, attribute information of roads such as national roads, prefectural roads, regulation speed, link length / width , Information on travel speed for each congestion degree, link IDs (link IDs) of links connected to the two nodes, and the like. The map data also includes information on major intersections and information on map components other than the roads included in the corresponding mesh area (name, type, coordinate information, etc.).

The traffic information management unit 116 includes a traffic information receiving unit 130, an accumulated traffic information DB 180, a traffic information processing unit 132, a processed traffic information DB 133, and a distribution information creation unit 137. The traffic information receiving unit 130 receives traffic information such as traffic volume, traffic jam, travel time, regulation / failure information, parking space empty / full information, intersection signal information, etc., which are periodically sent from the traffic information providing center 100. . The accumulated traffic information DB 180 registers and manages various types of traffic information received from the traffic information receiving unit 130. FIG. 2 shows an example of traffic information registered and managed by the accumulated traffic information DB 180. The accumulated traffic information DB 180 manages traffic information for each collection date (registration date) 1821. In addition, traffic information is managed for each link ID 1822. The traffic information includes information 1824 related to the link travel time (travel speed) and information 1825 related to the traffic jam such as the traffic jam degree and the length of the traffic jam. The accumulated traffic information DB 180 also manages information such as the day type 1846 to which the information collection date 1821 belongs. The types of day types include weekday and holiday classifications, classifications for each day of the week, or classifications that take into account general user behavior patterns, for example,
Examples include weekday / holiday day, weekday day, weekday all day, holiday first day, holiday middle day, holiday all day, etc. In addition to the above, classification may be made in consideration of the weather.

The traffic information processing unit 132 performs processing such as deletion of an abnormal value (singular value) in the accumulated traffic information DB 180, appropriate supplement processing for a link without information, or statistical processing. Each specific processing will be described later.

The processed traffic information DB 133 manages various traffic information created by the traffic information processing unit 132, and includes a real-time traffic information DB 135, a statistical traffic information DB 134, and a predicted traffic information DB 136 that stores traffic information related to future traffic conditions. Have.
The real-time traffic information DB 135 manages current traffic information for each link. The statistical traffic information DB 134 converts traffic information created by statistical processing into day types, links, time (
Manage every time). The predicted traffic information DB 136 manages traffic information related to future traffic conditions for each day type, each link, and each time (time zone).

In response to a request from the user terminal 200, the distribution information creation unit 137 processes the traffic information DB1.
33 is formed into a predetermined format to create distribution information, and the created information is transmitted to the user terminal.

Next, a process for creating processed traffic information performed by the traffic condition processing unit 132 will be described. First,
Real-time traffic information creation processing will be described with reference to the flowchart of FIG. When creating real-time traffic information, the traffic information processing unit 132 first reads the latest traffic information with reference to the information collection date 1821 (S1100). Next, the traffic information processing unit 132 determines whether or not the read traffic information is abnormal (unique) (S1101). For example, a link travel time corresponding to a high speed exceeding the regulation speed is included, or a link travel time exceeding a predetermined value or a very low speed link travel time corresponding to a predetermined speed or less is included. Then, it is determined that the read traffic information is abnormal. Alternatively, if the link travel time and traffic information are not consistent, for example, if the link travel time is significantly different from the link travel time obtained by converting to the speed based on the traffic congestion level, both traffic information is regarded as abnormal. You may make it determine. If it is determined as an abnormal value, the traffic information processing unit 132 deletes the traffic information determined as abnormal from the accumulated traffic information DB 180 and does not use it in the subsequent processing (S1102). Above S110
The processing of 1 and S1102 is performed on the traffic information of all links of the latest traffic information managed in the accumulated traffic information DB 180 (S1103).

Next, the traffic information processing unit 132 determines whether significant travel time information is provided for each link (S1104). Here, the significant travel time information is travel time information that is not determined to be abnormal by the abnormal value determination and remains in the accumulated traffic information DB 180. Then, for a link for which significant travel time information is not provided (also referred to as “unprovided link”), an estimation complementing process (a specific processing method will be described later) is performed (S1105). The processes of S1104 to S1105 are performed for all links (S1107). Through the above processing, real-time traffic information is created. Then, the traffic information processing unit 132 stores the created real-time traffic information in the real-time traffic information DB 135. If this process is executed by the traffic information providing center 100 in accordance with a cycle in which traffic information is newly registered, the latest real-time traffic information can be held.

Here, the estimation complementing process S1105 will be described. Even if there is no significant link travel time information in the link to be estimated and supplemented, the travel time of the unprovided link can be estimated and supplemented from other available traffic information (alternative traffic information). Hereinafter, the estimation complementing process will be described with reference to the flowchart of FIG.

(A) First, the traffic information processing unit 132 determines whether travel time is included in the past traffic information for an unprovided link (S1500). If it is included (Yes in S1500)
s) The traffic information processing unit 132 refers to the information collection date 1821 and applies the past link travel time closest to the current time as the travel time of the unprovided link (S1503). However, this is not applied when significant travel time information cannot be obtained unless it goes back in the past for a predetermined time or more (for example, 1 hour or more). In addition, when there are a plurality of significant travel times by going back to the past to a predetermined time, a value averaged by weighting in order from the newest may be applied.

(B) When travel time is not included in unprovided links in past traffic information (S15
00, No), the traffic information processing unit 132 determines whether the traffic information of the unprovided link includes traffic jam information (S1501). If it is included (Yes in S1501), the traffic information processing unit 132 uses the travel time (movement speed) corresponding to each congestion degree for each predetermined road type, and the unprovided link congestion degree and its congestion The travel time of the link is calculated from the length of (S
1504). At this time, if there is a section with unknown traffic congestion on the unprovided link, the traffic congestion degree of the section with unknown traffic congestion is regarded as normal. Or, as shown in FIG. 5, when the degree of traffic congestion in the same link 400 is known (congestion length 401: 300 m, congestion length 402: 200 m, normal length 4
03: 250 m), the traffic information processing unit 132 first obtains the length ratio of the congestion degree. Then, the length of each traffic jam is multiplied by the length of the traffic jam unknown section 404 to obtain the traffic jam length for each traffic jam. In FIG. 5, when the congestion degree unknown section (250 m) is assigned to the length of each congestion degree, the congestion length is 100 m, the congestion length is 67 m, and the normal length is 83 m. As described above, since the degree of congestion and the length thereof are obtained for the section with unknown degree of congestion, the travel time of the unprovided link can be calculated.

(C) When traffic information of unprovided links does not include traffic jam information (No in S1501)
The traffic information processing unit 132 determines whether or not significant travel time is included in the traffic information of the link around the unprovided link (for example, within a predetermined distance such as within 2 km) (S1502).
If included (Yes in S1502), the traffic information processing unit 132 selects a specific link from the links around the unprovided link, and calculates the travel time of the unprovided link from the travel time of the selected link (S1505). ). Here, from the viewpoint of estimation accuracy, it is important which link should be selected. Therefore, a link selection method will be described with reference to a virtual road network diagram example of FIG. R1 represents national road 1, prefecture 1 represents prefectural road 1, city 1 represents city road 1, and the like. Moreover, although the arrow lines 410-418 and 420-427 are shown along the national highway No. 1 and the prefectural road No. 1, this represents the presence or absence of significant travel time information, and the solid line arrows 410-418 are shown. A link where significant travel time information exists is indicated, and broken arrows 420 to 427 indicate links where no significant travel time information exists. Here, the traffic information processing unit 132 selects an appropriate link from the links having significant travel time information in the vicinity for 420 to 427 which are broken arrows having no significant travel time information. Will be described.

The traffic information processing unit 132 first selects (i) a link that is on the same route as the unprovided link (for example, National Route 1) from the links around the unprovided link. Of the plurality of selected links, the traffic information processing unit 132 (ii) determines whether the main intersection (43
0 to 433) is selected with the smallest number of times. The main intersection may be an intersection with a large change in traffic conditions, for example, a traffic condition change point such as a traffic jam bottleneck, or an intersection where main lines such as prefectural roads, national roads, and expressways intersect. Good. At this time, a plurality of links may be selected by providing a priority order in ascending order of the number of times crossing the main intersections (430 to 433). If a link is not selected in (i), (ii) is selected for all links around unprovided links. Next, the traffic information processing unit 132 selects a link that is closest to the unprovided link from among the selected links. However, links that are directly connected, or links that are in a reverse direction (opposite lane) are not selected for links that are close to each other. At this time, a plurality of links may be selected by setting priorities in order of increasing distance from the unprovided link. In addition, whether it is the same route, whether it is a main intersection, or whether a link is directly connected can be determined by examining link data and intersection information in map data. When a plurality of links are selected with priorities, the traffic information of the selected links is weighted and averaged in order of preference and used to calculate the travel time of the target link.

According to the link selection method described above, the link 411 is selected with the highest priority in order to supplementally estimate the travel time of the link 420 in FIG. 410 is then selected. Also,
The link 412 is selected for the link 421 and the link 413 is selected for the link 422 with the highest priority. For the link 423, the link 414 and the link 415 are selected with the same priority. In this case, the average value of the traffic information of both is used for calculating the travel time of the link 423. Similarly, for link 424 and link 425, link 416 is
For the link 426 and the link 427, the link 417 is selected with the highest priority. As described above, the traffic information processing unit 132 appropriately selects the link around the unprovided link, and calculates the travel time of the unprovided link using the travel time of the selected link.

(D) When there is no link having significant travel time information around an unprovided link (S1502)
No), the traffic information processing unit 132 has the same mesh as an unprovided link (for example, the same national highway),
Links with the same road attributes such as the same route, the same road type, and the same direction are extracted from the map DB 126. For the extracted link, the travel time is searched from the accumulated traffic information DB 131 to obtain the average travel speed. The travel time of the unprovided link is obtained from the average travel speed and the link length of the unprovided link (S1506).

Next, statistical traffic information creation processing will be described with reference to the flowchart of FIG. First, the traffic information processing unit 132 refers to the collection date and time 1821 and the day type 1826 from the traffic information stored in the accumulated traffic information DB 180, thereby obtaining traffic information for a specified period (for example, weekdays of the past half year). Read (S1200). In the above-described real-time traffic information creation process, it is only necessary to read out the latest traffic information. However, in this process, the traffic information processing unit 132 performs multiple times on a plurality of days to be processed (normally, all 24 hours). Hours)
Read traffic information. The designated period is set in advance according to the usage of the statistical traffic information.

Next, the traffic information processing unit 132 determines whether the traffic information is abnormal (unique) for each link from the read traffic information (S1201). As an abnormal value determination method, similar to the method in the above-mentioned real-time traffic information creation process, when an ultra-high-speed or ultra-low-speed link travel time is included, or when the congestion degree and the travel time are inconsistent, Can be adopted. Further, the presence / absence of abnormality may be determined by comparing with the traffic information of other days having the same day type 1826. Specifically, when the congestion occurrence time (ratio) in a day is greater than or equal to a predetermined value (for example, 5 hours or more), the traffic information for the entire day is determined to be abnormal, or traffic information for multiple days in the same time zone The value is significantly different from the others (the deviation is remarkably large)
In some cases, there is a method for determining an abnormality.

The traffic information processing unit 132 deletes the traffic information determined to be abnormal from the accumulated traffic information DB 180 and does not use it in the subsequent processing (S1202). The processes of S1201 and S1202 are performed for all the traffic information of the links within the specified period (S1203).

Next, the traffic information processing unit 132 performs statistical processing such as averaging processing on the basis of the traffic information that has not been deleted in the abnormal information deletion processing (S1202), and performs the time (time) Statistical traffic information such as travel time (travel speed) and traffic congestion level is created for each band. At this time, the traffic information processing unit 132 obtains a probability distribution (probability density function 440) regarding the link travel time as shown in FIG. 8 for each day type, each link, and each time (time zone) (S1206).

Next, the traffic information processing unit 132 refers to the created statistical traffic information and determines whether or not significant travel time information is provided for each link (S1204). For links that have not been provided with significant travel time information, the travel time is estimated and supplemented from the traffic information of other links in the same way as the real-time traffic information creation process, and the obtained traffic information is replaced with statistical traffic information. (S1205). The estimation complement method can be performed in the same manner as the estimation complement processing in the real-time traffic information creation processing. In addition, when calculating travel time about the time (target time) where link travel time is not provided, time (time zone) when link travel time is provided within a predetermined time (for example, 5 hours) before and after the target time. Find out if there is. If provided, the link travel time is set as the travel time of the target time. The predetermined time is set in advance in a time range in which there is no significant change in traffic conditions. Above S1204-S
The process of 1206 is performed for all times (S1208). This will give you the full time of the link (
Travel time for (time zone) is obtained. Further, the above processes of S1204 to S1208 are performed for all links (S1209). Thereby, the statistical traffic information in a wide area is completed. If this processing flow is executed at a predetermined timing such as every month, every season, or every year, it is possible to provide stable statistical traffic information without impairing the freshness of the information.

  Next, a process for creating predicted traffic information will be described.

When creating predicted traffic information for a specific link (target link), first, the traffic information processing unit 132 calculates the travel time Td ′ (t) of the latest target link at the current time t from the real-time traffic information DB 135. read out. Next, the travel time Td (t) of the target link at the current time t and the travel time Td (t + n) in the near future t + n after the elapse of a predetermined time to be predicted are searched from the statistical traffic information DB 136. Then, Td (t + n)
(T) / Td (t) is multiplied by the estimated travel time Td ′ (t
+ N). By performing the above processing for each link, a predicted traffic information DB 136 for the near future in a wide area can be created. The above processing flow is applied to the traffic information providing center 1
If it is executed in accordance with the period updated from 00 (usually 5 minutes), it is possible to provide the predicted traffic information to the user more quickly and efficiently.

Next, an example in which the travel time of a specific route composed of a plurality of links is calculated using the link travel time (statistical travel time) stored in the statistical traffic information DB 134 will be described. Consider the case of FIG. 9 as a simple example of a road network. A to E in the figure are intersections, 460 to 46
3 represents a link. Further, it is assumed that the link length of each link 460 to 463, the statistical travel time and the statistical travel speed for each time zone are as shown in FIGS. 10 (A) and 10 (B). 10: 0 in the figure
0 means a statistical travel time or a statistical travel speed at a time from 10:00 to less than 10:05. The statistical travel speed is obtained from the statistical travel time and link length in each time zone. Calculation of statistical travel time from intersection A to intersection E will be described. 10:00
： If you leave the intersection A at 00: 72 seconds to cross the link 460 (average speed is 30
km / h) is expected. Time 10:01 when this link 461 will be reached
: 12 is not yet 10:05, so the predicted travel speed of the next link 461 is 10:
Adopted 25 km / h of 00. Therefore, the travel time required to pass through the link 461 is 144 seconds, and the total travel time from the intersection A is 216 seconds. Similarly, the travel time required to pass through the link 462 is calculated as 82 seconds (total 298 seconds). Since the travel time required to pass through the last link 463 is 173 seconds (total 471 seconds), it is necessary to switch to a speed of 10:05 along the way. In other words, since the first 2 seconds after entering the link 463, a speed of 10:00 (25 km / h) is adopted, the travel distance between them is about 1
It is calculated that it takes approximately 285 seconds to adopt a 10:05 speed (15 km / h) for 4 m and then the remaining distance 1186 m. Eventually, the travel time required to pass through the link 463 is calculated as 287 seconds (total 585 seconds). From the above, 10:00: 00
The estimated time of arrival at the intersection E is 10:09:45, and the traveling condition of the entire route is as shown by a graph 464 in FIG. Similarly, time 10: 05: 0
The traveling situation when the intersection A is departed from 0 is as shown in the graph 465 of FIG.
The statistical travel time is calculated as 759 seconds and the estimated arrival time is 10:17:39.

Next, as an example of utilizing the probability distribution of the link travel time, an example of calculating the probability distribution related to the travel time of a specific route composed of a plurality of links will be described. In the road network of FIG. 9, an example of obtaining a probability distribution regarding the travel time of the route AE from the intersection A to the intersection E will be described. Similarly to the above, the probability distribution at each time of each link taking into account the passage of time while traveling from the time of departure from the intersection A can be known by referring to the statistical traffic information DB 134. Travel times X1, X2, X3 of links 460, 461, 462, 463
, The probability f for X4 is f460 (X1), f461 (X2), f462 (X3), respectively.
), F463 (X4), and the probability f as shown in FIG. 8 according to X1, X2, X3, and X4
Also takes various values. Here, the travel times of the links 460, 461, 462, and 463 are x1, x2, x3, and x4, respectively (the travel time X of the route AE is x1 + x2 + x3 + x4).
The probability f (X) is expressed by the following equation if the probability distribution of each link travel time is independent of each other.
f (X) = f460 (x1) .f461 (x2) .f462 (x3) .f463 (x4)
... (Equation 1)
By calculating this for all possible combinations of X1, X2, X3, and X4 and adding the same X, a probability density function f (X) relating to the travel time X of the route AE can be obtained. . Then, using the probability density function f (X), an expected value E of travel time relating to the route AE, a standard deviation σ, and the like can be obtained. Further, as shown in FIG. 12, the probability density function 47
By using 0, the probability that the travel time X is included in the range of E ± ΔX can be obtained by the ratio of the area 471 of the hatched portion in the area surrounded by the probability density function 470 and the X axis. By changing this ΔX (difference from E), probabilities P (ΔX) relating to travel time in various ranges can be obtained.

As described above, the utilization example of the link travel time or the utilization example of the probability distribution related to the travel time has been described. However, even if the processing associated with these examples is performed by the traffic information processing device 107,
You may go on.

Next, in the case where the average travel time E, travel time range E ± ΔX, and probability P (ΔX) related to the travel time range of a specific route (target route) are displayed on the user terminal 200, the flowchart of FIG. 13 is used. I will explain.

First, the information processing unit 202 performs various settings related to the display of travel time (S1400).
Setting items include travel time range and travel time probability (corresponding to probability P for travel time range)
There is. The travel time range is a travel time width indicating the display width of the travel time (equivalent to twice the above ΔX).
May be obtained and set by the equation: E ± ΔX. At this time, the information processing unit 30
2 displays a radio button 480 on the screen 140 of the display unit 205 for selecting which index of the travel time width and the travel time probability is to be preferentially displayed. Reference numerals 481 to 483 of the screen 140 are setting value candidate buttons for each setting item.

Next, the information processing unit 202 calculates the travel time probability for the target route (average travel time), its probability distribution, its expected value, and the travel time probability for the set travel time range. To request. The traffic information processing apparatus 107 calculates these values by the method described above, and then transmits them to the information processing unit 202 of the user terminal 200 (S1401).
). However, the information processing unit 202 may calculate these values by itself. Next, the information processing unit 202 determines whether or not the calculation result satisfies a predetermined condition (S
1402). This condition is set as the maximum travel time width (for example, 60 minutes) and the lower limit value (for example, 40%) of the travel time probability. When these conditions are exceeded, the reliability of information is low.

For example, as a first example, when a very low probability that a travel time probability of 20 minutes is calculated for an average travel time of 45 minutes and a travel time range of 40 to 50 minutes with respect to a set value of a travel time width of 10 minutes, The lower limit of the time probability (for example, 40%) is reached, and the above condition is not satisfied. As a second example, an average travel time of 5% is set for a set value of 90% of travel time probability.
When a very wide travel time range of 5 minutes and a travel time range of 90% with a travel time probability of 10 to 100 minutes is calculated, the maximum travel time width (for example, 60 minutes) is exceeded and the condition is not satisfied. As a third example, when the travel time width is set to 30 minutes and the average travel time value is 10 minutes, the travel time range is -5 minutes to 25 minutes. That is, the minimum value may be calculated with a value of 0 or less. Even in this case, the condition is not satisfied. Similarly, the condition is not satisfied even when the maximum value of the travel range exceeds a predetermined value (for example, 10 hours).
As described above, when the condition is not satisfied, the information processing unit 202 automatically changes the travel time width or the travel time probability so as to satisfy the above condition (S1403).

For example, in the first example, since the set value of the travel time width of 10 minutes has led to a low reliability result, the travel time width is changed to an appropriate value (for example, 20 minutes). In the second example, the setting value of 90% travel time probability led to a low reliability result.
The travel time probability is changed to an appropriate value (for example, 70%). Further, as in the third example, when the minimum value of the travel time range is 0 or less, the travel time range is defined only by the upper limit value such as the maximum value or less (for example, 25 minutes or less). Further, when the maximum value exceeds a predetermined value, it is defined only by the lower limit value such as more than the minimum value of the travel time range (for example, 550 minutes or more). And
Calculation processing S1401 is performed based on the changed setting value, and S1401 to S1401 are satisfied until the above condition is satisfied.
S1403 is repeated. However, if a result satisfying the above condition is not obtained even if the process is repeated a predetermined number of times, the process ends as no solution. Then, the finally obtained result is output to the display unit 205 (characters and graphics), a speaker (speech), or the like (S1404).

Display examples of the display unit 205 are shown in FIGS. In FIG. 15A, 490
Is the average travel time (average travel time) or expected travel time, 493 is the travel time range, 493
Is the travel time probability. In FIG. 15B, reference numeral 496 denotes an example in which only the upper limit value is displayed because the minimum value of the travel time range is 0 or less. Further, in FIG. 15C, reference numeral 497 is an example showing that no solution satisfying the above-mentioned conditions was obtained and there was no solution as a result. The travel time range and travel time probability values may be displayed as a stacked bar graph or a pie chart. Thereby, the user can grasp intuitively even during driving.

In addition, information such as travel times (route information) regarding a plurality of routes may be displayed. In this case, the order of displaying the route information may be arranged from the top in the order of a predetermined route type (for example, the shortest time). Route, highway priority, general road priority), or travel time may be displayed in descending order (in order of the expected arrival time). Further, the range of travel time or the range of expected arrival time and its probability may be displayed, and the order in which the route information is displayed may be displayed in order of increasing travel time expectation value or high probability. Further, the specific route and the route information may be superimposed on the map.

  Heretofore, an example of the embodiment of the present invention has been described.

According to the present embodiment, even if the traffic information received from the outside does not necessarily have sufficient reliability and stability quality and the amount of information, the link is not provided by statistically processing the traffic information. It is possible to generate highly accurate real-time traffic information, statistical traffic information, and predicted traffic information including a highly practical travel time range and its probability for more links including

In addition, according to the present embodiment, by displaying the travel time range and the probability regarding the route, the user can intuitively know the width of the arrival time and the frequency thereof, making it easy to make a travel plan. A good traffic information display device can be provided.

In addition, this invention is not limited to said embodiment, A various deformation | transformation is possible within the range of the summary. For example, the statistical traffic information DB may be stored in a storage medium such as a CD, DVD, memory card, or hard disk. Further, when the user terminal 200 displays traffic information, the traffic information that is estimated and supplemented among the traffic information is changed in display color, etc.
You may make it display distinguishing from the traffic information which is not complemented.

The traffic information display device of the present invention is a traffic information processing device that creates traffic information used in the traffic information display device, and obtains traffic information including information related to travel time of a link from the outside. Complementing means for calculating traffic information related to travel time by an estimation complementing process for an unprovided link for which information related to travel time is not provided by the traffic information acquiring means. Calculates an average travel speed of all links or links having the same road attribute as the unprovided link in the predetermined area where the unprovided link exists, and the calculated average travel speed is set as the travel speed of the unprovided link. The travel time of the unprovided link may be calculated.

Here, the traffic information processing apparatus has storage means for storing the traffic information acquired by the traffic information acquisition means, and statistical means for statistically processing past traffic information stored by the storage means. Predicting travel time after elapse of a predetermined time of a specific link using the current traffic information obtained by the means, the traffic information statistically processed by the statistical means, and the traffic information calculated by the complement means You may have a means.

Further, the traffic information display device forms traffic information obtained by the traffic information obtaining means and traffic information calculated by the complementing means into a predetermined format in response to a request from the traffic information display device. You may have a means to transmit with respect to an information display apparatus.

Furthermore, the traffic information display method of the present invention is a traffic information processing method performed by a traffic information processing apparatus that creates traffic information used in the traffic information display apparatus, and includes traffic information including information related to travel time of a link. A step of obtaining from the outside, and a complementing step of calculating traffic information relating to travel time by an estimation complementing process for an unprovided link for which information relating to travel time is not provided by the traffic information obtaining step. There may be.

FIG. 1 is a diagram illustrating an example of a configuration of a traffic information processing apparatus. FIG. 2 is a diagram illustrating how the accumulated traffic information DB manages traffic information. FIG. 3 is a flowchart showing the flow of real-time traffic information creation processing. FIG. 4 is a flowchart showing a flow of complement processing. FIG. 5 is a diagram for explaining a complementary processing method for an unknown section related to the degree of congestion that constitutes a link. FIG. 6 is a road network diagram for explaining a method of complementing the travel time of unprovided links from the travel time of surrounding links. FIG. 7 is a flowchart showing the flow of statistical traffic information creation processing. FIG. 8 shows an example of a probability distribution related to link travel time. FIG. 9 is a road network diagram for explaining an example of utilizing link travel time. FIG. 10 is a diagram for explaining a route travel time prediction method. FIG. 10A shows a statistical travel time for each link and time zone. FIG. 10B shows a statistical travel speed for each link and time zone. FIG. 11 is a diagram illustrating a traveling situation in the middle of a route, which is an example for explaining a route travel time prediction method. FIG. 12 is a diagram for explaining a method for obtaining the probability of route travel time from a probability density function. FIG. 13 is a flowchart showing a flow of processing for displaying the probability related to route travel time on the user terminal. FIG. 14 shows an example of a travel time display setting screen. FIG. 15 is a display screen example of travel time and probability.

Explanation of symbols

DESCRIPTION OF SYMBOLS 100 ... Traffic information provision center, 103 ... Communication network, 107 ... Traffic information processing apparatus, 116 ...
Traffic information management unit 180 ... Accumulated traffic information DB 132 ... Traffic information processing unit 133 ...
Processing traffic information DB, 200 ... user terminal

Claims (5)

A traffic information processing method of a traffic information processing system that creates statistical traffic information,
The traffic information processing system includes a storage unit that stores traffic information, and a traffic information processing device that includes a processing unit that performs processing related to travel time using the traffic information stored in the storage unit.
The storage unit
Obtaining traffic information including information on travel time for each link that makes up the road on the map from outside, and accumulating the obtained traffic information,
The processing unit of the traffic information processing apparatus
A step to read out the stored traffic information for each time slot to create a statistical traffic information,
Using the traffic information for each read time zone, calculating a probability distribution related to travel time for each time zone of each link;
Calculating a probability distribution related to travel time of a specific route composed of a plurality of links, using a probability distribution related to travel time for each time zone of each link;
A step Cormorant line travel time range or travel time setting of the probability of the specific path,
When the travel time range of the specific route is set, using the probability distribution regarding the travel time of the specific route, calculating the probability that the travel time of the specific route will be the set travel time range;
When the travel time probability of the specific route is set, the travel time range within which the travel time of the specific route falls within the set travel time probability is calculated using a probability distribution related to the travel time of the specific route ; ,
The traffic information processing method characterized by implementing . The traffic information processing system further includes a traffic information display device including a processing unit, and the processing unit of the traffic information display device includes:
The travel calculated by the traffic information processing method according to claim 1, wherein the travel time of the specific route falls within the set travel time range or the travel time of the specific route falls within the set travel time probability a step to obtain information about time range,
Displaying the obtained probability or the travel time range ;
The traffic information display method characterized by implementing . The traffic information display method according to claim 2,
The processing unit of the traffic information display device
A step of changing the set travel time range or travel time probability when the calculated result does not satisfy a predetermined condition ;
The traffic information display method characterized by implementing . The traffic information display method according to claim 2,
The processing unit of the traffic information display device
When displaying traffic information for a plurality of the specific routes,
A traffic information display method characterized by displaying the route travel time in ascending order or in descending order of probability for travel time. A traffic information processing device that creates statistical traffic information,
A storage unit that obtains traffic information including information on travel time of each link constituting the road on the map from the outside, and accumulates the obtained traffic information;
A read-out unit that reads out the accumulated traffic information for each time zone for creating statistical traffic information;
A link probability distribution calculating unit that calculates a probability distribution related to travel time for each time zone of each link, using the traffic information for each read time zone;
A path probability distribution calculating unit that calculates a probability distribution related to a travel time of a specific route composed of a plurality of links, using a probability distribution related to a travel time for each time zone of each link;
A setting unit for setting a travel time range or a travel time probability of the specific route;
When the travel time range of the specific route is set, a probability calculation unit that calculates the probability that the travel time of the specific route falls within the set travel time range using a probability distribution related to the travel time of the specific route;
When a travel time probability of the specific route is set, a time range for calculating a travel time range within which the travel time of the specific route falls within the set travel time probability using a probability distribution related to the travel time of the specific route A calculation unit;
A traffic information processing apparatus comprising:

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