JP2008164910A - Information processor, program, and information processing method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To present information which is more useful, related to user's driving. <P>SOLUTION: An information processor is provided with a recording means (steps 44 and 45) of recording information specifying a place moved to in a predetermined data sampling section and data of a predetermined item possibly changing at each movement, while making them correspond to identification information for identification at each movement each time a user moves in the predetermined data sampling section; a specifying means of receiving specification of the contents of the data of the predetermined item or the contents of the identification information; and a display means (step 43) of displaying a movement locus, based on the information corresponding to the contents, specified by the specifying means in movement place specification information recorded by the recording means. <P>COPYRIGHT: (C)2008,JPO&INPIT

Description

  The present invention relates to an information processing apparatus that displays a movement locus based on past movement records, a program that causes a computer to operate as each unit in the information processing apparatus, and an information processing method in the information processing apparatus.

  2. Description of the Related Art Conventionally, in a navigation apparatus, in order to perform a route search with good accuracy, learning about what route actually traveled is performed. Furthermore, there are cases where the vehicle speed variation pattern is learned and the learning result is reflected in the route search.

  For example, in the technique described in Patent Document 1, when the recommended route obtained by the route search is different from the route actually traveled by the user, the estimated required time for the recommended route and the route actually traveled Compared with the time required, if the latter is shorter, the route actually traveled is learned, and the learned route is reflected in the next route search.

  Further, in the technique described in Patent Document 2, a route to a destination is searched, a user specifies a travel route from a plurality of routes that can be searched, and each route that is not specified by the user is The position of the vehicle when traveling virtually, that is, the virtual vehicle position is calculated based on the vehicle speed fluctuation pattern of the vehicle, and presented to the user traveling on the specified travel route. Thereby, the user can compare the progress of the vehicle for each route and the arrival time at the destination. As a result, when the next route from the same departure point to the destination is traveled, it is possible to determine which route should be selected to reach the destination in the shortest time.

  The learning performed by comparing the recommended route with the actual travel route is considered to include route learning and parameter learning. Route learning has a learning effect on frequently used routes. For example, if the route is used only once, the learning effect cannot be confirmed. The technique of Patent Document 1 described above is a technique for performing route learning, and the technique of Patent Document 2 is considered to be a technique for performing parameter learning.

JP 2006-64563 A JP 2004-28825 A

  However, the above-described conventional route learning technology compares the estimated required time for the recommended route with the actual required time for the actually traveled route. It does not compare time required. When the recommended route is actually traveled, the travel may be performed in a shorter time than the expected time by the navigation device.

  In addition, route learning is effective for frequently used routes, but guidance for recommended routes is not necessary for frequently traveled routes. Rather, it is desirable to present data that can reduce the time required for actual travel.

  In addition, according to the conventional parameter learning technique described above, even if a driver's habit, for example, the above-described vehicle speed fluctuation pattern is learned and reflected in the route search, the number of parameters and the complexity of the processing are compared. , The effect can not be expected so much. For example, even if a driver who has a sudden start or stop as a vehicle speed fluctuation pattern arrives at the destination earlier than the expected time of the recommended route, it is doubtful whether it will arrive early enough to greatly affect the whole. Confirmation of this is considered difficult.

  In the case of parameter learning, it can be considered that the learning effect can be confirmed for the frequently used route. Therefore, the comparison with the above-described virtual host vehicle position is likely not to be expected so much because the user can easily estimate the frequently used route. Such a comparison is effective only when a plurality of routes are hit in the route search.

  An object of the present invention is to make it possible to present more effective information regarding a user's driving in a navigation device in view of the problems of the conventional technology.

  In order to achieve this object, the information processing apparatus according to the first aspect of the present invention, every time a predetermined data collection section is moved, information for specifying a moved location in the section, and a predetermined value that can be changed for each movement. Recording means for recording item data in association with identification information for identifying each movement, designation means for designating data contents of the predetermined item or contents of the identification information, and recording by the recording means Display means for displaying a movement trajectory based on information corresponding to the content designated by the designation means among the designated movement location specifying information.

  Here, as the information processing device, for example, a navigation device, a personal computer equipped with a GPS receiver, and a GPS mobile phone are applicable. The movement corresponds to movement due to traveling of a vehicle on which the apparatus is mounted or movement due to walking of a user carrying the apparatus. Examples of the predetermined items that may vary with each movement include “weather”, “temperature”, “traveling time”, and “presence of traffic jam”. As the identification information, for example, the date and number of times of movement (first time, second time, etc.) are applicable.

  As data corresponding to the specified content, for example, data corresponding to this specification when “the data content of the item“ traveling time ”is the maximum” is specified (collected in the second time in FIG. 5 described later). Data) and data corresponding to this designation when the content of the data of the item “weather” is designated as “clear” (data collected for the first time in FIG. 5 described later). The data corresponding to the content of the specified distinction information corresponds to, for example, data recorded at the time of the third movement when “third time” is specified. The designation by the designation means can be performed in combination. For example, the data content of “weather” can be specified as “clear” and the data content of “traffic jam” can be specified as “none”.

  In this configuration, when the data collection section is moved, the movement location specifying information and data on the predetermined item are recorded. At this time, identification information for identifying these data for each movement is recorded. Thereafter, when the content of the data of the predetermined item or the content of the identification information is designated, the movement trajectory is displayed based on the data corresponding to the designated content. The user can consider a more preferable movement trajectory based on the specified contents and the movement trajectory.

  In the information processing apparatus according to a second invention, in the first invention, the movement location specifying information is data of each movement position for every predetermined time, and the display means displays a mark indicating the movement position on a map Thus, the movement trajectory is displayed. Here, as the fixed time, for example, the timing at which the vehicle position in the navigation device is updated corresponds.

  In the information processing device according to a third invention, in the first or second invention, the movement location specifying information is data of each movement position for every predetermined time, and the display means moves the data collection section. A moving position at a time corresponding to the current time when a predetermined point on the data collection section is used as a reference among the moving positions in the moving part specifying information corresponding to the content specified by the specifying means The movement trajectory is displayed by displaying a mark indicating the current position together with the mark indicating the current position on the map. As the predetermined point, for example, the start point of the data collection section, the start point of each route element constituting each route of the data collection section, and the start point of each section element constituting each route element are applicable.

  The information processing device according to a fourth invention is the information processing apparatus according to any one of the first to third inventions, wherein the movement location specifying information is at each branch point in each route from the start point to the end point of the data collection section. It is information indicating whether or not each divided route element is used for movement, and the display means displays the movement trajectory by displaying the use frequency for each route element. To do. Here, the information indicating whether or not each route element is used for movement corresponds to, for example, whether or not the section element included in each route element is recorded. For example, the fact that there is a record for section A in FIG. 5 means that a root element including section A has been used. Further, the fact that there are three records for the section A means that the root element including the section A has been used three times.

  An information processing device according to a fifth invention is the information processing device according to any one of the first to fourth information processing devices, wherein each route is divided at each branch point in each route from the start point to the end point of the data collection section. The element is composed of one or more section elements, and the recording means records the data of the predetermined item for each section element.

  The information processing apparatus according to a sixth aspect of the present invention is the information processing apparatus according to any one of the first to fifth aspects, wherein a predetermined one of the predetermined items is calculated based on a data value recorded a plurality of times. A value is handled as a part of the data of the predetermined item. Here, the predetermined item among the predetermined items corresponds to, for example, “travel time” which is an item of time required for travel. Examples of the predetermined calculated value include a maximum value, a minimum value, an average value, and a standard deviation. In this case, the calculated maximum value and minimum value are also the data values of the item “traveling time”.

  An information processing apparatus according to a seventh invention is characterized in that, in any one of the first to sixth inventions, the information processing apparatus further comprises editing means for deleting or invalidating a part of the data recorded by the recording means. .

  A program according to an eighth invention is characterized by causing a computer to operate as each means in the information processing apparatus according to any one of the first to sixth inventions. The concept of computer includes various embedded devices.

  The information processing device according to the ninth aspect of the invention relates to information for specifying a moved position in the section and data of a predetermined item that can vary for each movement, every time the recording means moves in the predetermined data collection section. Is recorded in association with identification information for identifying each movement, a designation unit accepts designation of data content of the predetermined item or the content of the identification information, and a display unit And a display step of displaying a movement trajectory based on information corresponding to the content designated by the designation means among the movement location specifying information recorded by the recording means.

  According to the present invention, since the movement trajectory is displayed based on the recorded movement location identification information corresponding to the content of the data of the specified predetermined item or the content of the identification information, the user designates Based on the contents and the movement trajectory, it is possible to consider a more preferable movement trajectory.

  In addition, when the movement location specifying information is data of each movement position at a certain time, the movement locus is displayed by displaying a mark indicating the movement position on the map. By setting the movement position to each current position at the timing when the own vehicle position in the navigation device is updated, for example, a detailed movement locus can be displayed. Thereby, for example, it is possible to perform a detailed consideration as to which lane to travel.

  In addition, when the moving part specifying information is data of each moving position for every fixed time, when moving the data collection section, among the moving positions in the moving part specifying information, a predetermined value on the data collecting section Since the mark indicating the moving position at the time corresponding to the current time when the point is used as a reference is displayed on the map together with the mark indicating the current position, the current moving position that changes momentarily and the same in the past Compared with the movement position in real time, it can be used to improve the movement trajectory.

  In addition, when the movement location specifying information is information indicating whether or not each route element is used for movement, the movement trajectory is displayed by displaying the use frequency for each route element. By sharing the information recorded by multiple users, each user can grasp which root element is being used well by other users and use it as a reference when selecting the root element to be used. it can.

  Also, when each route element delimited by each branch point in each route from the start point to the end point of the data collection section is composed of one or more section elements, data of a predetermined item is recorded. Since it is performed for each section element, the travel locus can be considered based on the recorded contents for each section element and the travel locus.

  In addition, for a predetermined item among the predetermined items, a predetermined calculated value calculated based on a data value recorded a plurality of times is handled as a part of the data of the predetermined item. For the “travel time”, which is a time item, the maximum value, minimum value, average value, standard deviation, etc. of the recorded data are specified by the specifying means, and the travel locus is displayed using the corresponding movement location specifying information. Can be made.

  In addition, since the editing means for deleting or invalidating part of the data recorded by the recording means is provided, the data recorded under an abnormal situation such as under construction is deleted and recorded under the abnormal situation. It is possible to prevent the reference data from being referred to.

  FIG. 1 is a block diagram showing a configuration of a navigation apparatus according to an embodiment of the present invention. As shown in the figure, the navigation device includes a control unit 11 that performs necessary information processing and control of each part of the device, a current position detection unit 12 that detects a current position of a vehicle on which the device is mounted, and map data necessary for navigation. A map data unit 13 for storing information, a storage unit 14 for storing programs necessary for information processing, processing results, etc., a voice output unit 15 for outputting necessary information by voice, a map for navigation, and various information and operations. A display unit 16 for displaying necessary information and the like, and an operation unit 16 for performing operation input to the control unit 11 are provided.

  The current position detection unit 12 acquires the current position by GPS or inertial navigation. The storage unit 14 includes a hard disk device, a RAM, a ROM, and the like. The operation unit 17 includes a touch panel provided on the display unit 16 and can perform operation input by touch.

  In this configuration, the control unit 11 accepts setting of a section in which predetermined data is to be collected, and collects the predetermined data when the vehicle travels in the data collection section. The collection of the predetermined data is performed on the route actually traveled regardless of whether there are a plurality of routes in the data collection section or whether the travel route is a route deviating from the recommended route.

  FIG. 2 is a flowchart showing processing for accepting the setting of the data collection section in the navigation device. When the process is started, the control unit 11 first accepts designation of the start point of the data collection section to be set in step 21. This designation can be accepted by, for example, accepting a touch of a position desired to be a starting point on the displayed map or a selection from each position already registered as a starting point. . Next, in step 22, the designation of the end point of the data collection section is accepted in the same manner.

  Next, in step 23, an input of a name set for the data collection section is accepted. Next, in step 24, it is determined whether or not the same name as the input name exists in the name of the data collection section that has already been set. If it is determined that it exists, the process returns to step 23 to prompt the user to input another name again. If it is determined that the same name does not exist, the process proceeds to step 25, where the designated start point and end point are subdivided and set as a data collection section composed of the subdivided section elements. The subdivision is performed by dividing the start point and the end point for each point where an intersection has passed, a road type has changed, or a certain distance has occurred. Thereby, the setting of the data collection section is completed. A plurality of data collection sections can be set.

  FIG. 3 shows an example of the data collection section set by the process of FIG. In the figure, 31 is the start point of the data collection section, 32 is the end point of the data collection section, and 33 is an intersection that divides the data collection section. In this data collection section, the name “from home to company” is set. This data collection section is composed of a section A that is a section element from the start point 31 to the intersection 33 and a section B that is a section element from the intersection 33 to the end point 32. In this case, the same route as the route having the home as the departure point and the company as the destination is set as the data collection section. That is, the departure point of this route is designated as the start point 31 (step 21), and the destination is designated as the end point 32 (step 22).

  FIG. 4 is a flowchart showing a data collection process for a data collection section in the navigation device. When the process is started, the control unit 11 first waits at step 41 to reach the start point of any data collection section. When arrival at the start point is detected, the process proceeds to step 42, and it is determined whether or not already collected data exists for the data collection section. If it is determined that there is no data, the process proceeds to step 44 as it is.

  If it is determined in step 42 that the collected data already exists, the process proceeds to step 43, and on the condition that the vehicle position is updated every fixed time, the past vehicle The display position is updated, and the process proceeds to step 44. When updating, the vehicle mark that has been displayed until then may be left displayed as a travel locus according to the user's selection. The past vehicle mark is a vehicle mark when traveling in the past in the data collection section currently being traveled. The past own vehicle mark is displayed on the assumption that the start point of the current data collection section that is currently running is used as a reference and that the start point departs at the same time as the current run. Therefore, the user can immediately recognize whether the vehicle is behind or ahead of the past by comparing the current and past vehicle mark positions. Note that the current vehicle mark is updated every time the vehicle position is updated regardless of the presence of past collection data.

  The data used for displaying the past vehicle mark is based on the point information collected for the currently collected data collection section in step 45 described later. As the data used for displaying the past vehicle mark, the point information collected during any past driving may be used as it is, and the average or maximum value of each point information collected during each past driving. Alternatively, the deviation value of each point information collected during each past run may be considered. The control unit 11 can accept designation of which data is used. For example, the user can display a past vehicle mark based on the spot information collected when the time required for the data collection section currently running is the shortest.

  In step 44, predetermined data is collected for each of the section elements in the traveling data collection section. The predetermined data corresponds to data that can be acquired, such as travel date and time, weather, temperature, travel time, and traffic conditions for the section element. Record the number of passengers as necessary. In the next step 45, the spot information is recorded on condition that the vehicle position is updated every fixed time. The point information is information on the current position at the time of updating the own vehicle position. As a result, the travel locus is recorded. Based on this travel locus, the past vehicle mark update display in step 43 is performed.

  Next, at step 46, it is determined whether or not the vehicle has arrived at the end point in the traveling data collection section. If it is determined that it has not arrived, the process returns to step 42 and the processes of steps 42 to 45 are repeated. If it is determined that it has arrived, the process proceeds to step 47, and the data acquired in steps 44 and 45 is registered in the database. Thereby, the data collection process ends. When the number of data collection for each data collection section is equal to or greater than the predetermined number, the control unit 11 calculates the maximum value, minimum value, average value, deviation value, etc. for the possible data items, and the calculation result Is stored.

  The control unit 11 has a function of displaying the data collected in step 44 described above. That is, the control unit 11 displays a list of names of the respective data collection sections set by the process of FIG. When any name is selected from this list, the data collected in step 44 is displayed for the data collection section of the selected name.

  FIG. 5 shows an example of this display. This example is for the data collection section in which the name “from home to company” illustrated in FIG. 3 is set. In FIG. 5, for the sections A and B constituting the data collection section, the items “running day”, “weather”, “temperature”, “traveling time”, and “traffic jam” are 1 to 3 The data collected during each run is shown. In addition, regarding the “travel time”, values of “maximum”, “minimum”, “average”, and “deviation” for the three travels 1 to 3 are shown for the section A and the section B. Similar values for the entire data collection section are shown in the “section A + B” column.

  The control unit 11 has a function of accepting editing of data to be displayed in this way. Editing that deletes the collected data, for example, in units of number of times or sections can be accepted. Therefore, for example, if the data about the section B collected on October 20 in the display shown in FIG. 5 is collected under a shortage such as road construction, the user Data can be deleted. In this case, the control unit 11 resets the “maximum”, “minimum”, “average”, and “deviation” values for the section B based on the edited data. However, the data for the third “section A + B” is blank because it cannot be calculated.

  According to the example of FIG. 5, it can be seen that it takes about 34 minutes to reach the office from the home, and it takes about 37 minutes even when it is slow. However, for such data, the data collection section is a route that is used every morning at the same time zone, so the driver is aware of the congestion, including the degree of congestion. In addition, it has also been observed that the arrival time tends to be slow because the field of view is narrower on a rainy day than on a clear day and attention to slipping is necessary. In order to make the information useful for the user, it is necessary to use it in combination with the point information collected in step 45 described above or in combination with the route search function.

  Therefore, the traveling locus can be displayed based on the spot information collected in step 45 of FIG. That is, the control unit 11 displays the travel locus based on the spot data collected in step 45 for the data collection section of the designated name or the data collection section currently running by a predetermined operation on the operation unit 16. I do. When data collection has been performed twice or more for the target data collection section, designation of the number of times and designation of the type of data to be used are accepted, and display according to the designation is performed. For example, an average value, a maximum value, or a minimum value corresponds to the type of data to be used. Or you may enable it to designate the data to be used with a weather or temperature. That is, the point information that can be specified by the items and the contents as illustrated in FIG. 5 can be used.

  The travel locus is displayed on the map as shown in FIG. Reference numeral 34 in FIG. 3 is a mark indicating a travel locus. The control unit 11 specifies a range in the travel locus displayed on the map, points of the enlargement center point, further specifies an enlargement ratio, and accepts an operation for scrolling the display, and enlarges and displays the travel locus according to the operation. Or change the display position. You may make it increase an enlargement rate, whenever it points. That is, the user can observe a desired travel locus portion at a desired magnification.

  FIG. 6 shows an enlarged portion of a section in the data collection section of FIG. In the figure, 61 is a two-lane road that is one-way in the direction of arrow A, 62 is a pedestrian road provided along the two-lane road 61, and 63 is a run based on the point information recorded in step 45 of FIG. It is a trajectory. In this section, referring to the travel locus 63, it can be seen that the vehicle traveled in the right lane of the two-lane road 61. This is because the left lane with many confluences was avoided.

  Based on the display of such a travel locus, the following operational suggestions can be obtained. For example, when trying to collect data while driving on the two-lane road 61 on various days of the weather and trying to display the driving trajectory, it is faster to drive on the left lane only on rainy days. I can know that. This is presumed to be due to the car traveling in the right lane in the rain when caring for pedestrians on the pedestrian road 62, the umbrella of children on the way to school, etc. can do.

  FIG. 7 exemplifies this state, and shows a state in which the traveling locus of the two-lane road 61 during rainy weather is displayed. This figure shows a state in which a part of the section portion in FIG. 6 is further enlarged and displayed. In FIG. 7, reference numeral 71 denotes a travel locus based on the spot information collected while traveling in the right lane during rainy weather, 72 denotes a travel locus based on the spot information collected while traveling in the left lane during rainy weather, and 73 denotes each travel locus. The own vehicle mark point, 71a is a part of the traveling locus 71, and 72a is a part of the traveling locus 72.

  In the case of FIG. 7, the enlargement ratio is sufficiently larger than in the case of FIG. 6, so that the own vehicle mark points 73 constituting the traveling tracks 71 and 72 are the vehicle positions at regular intervals collected in step 45 of FIG. 4 described above. Is displayed. Since the own vehicle mark point 73 corresponds to each own vehicle position updated at regular intervals, the interval between adjacent own vehicle mark points 73 on the same traveling locus corresponds to the traveling speed at that position. .

  The travel lane portion 71a in the right lane shows a state where the pedestrian on the pedestrian road 62 is watched and is traveling so as to avoid the pedestrian. The travel lane portion 72a in the left lane indicates that the speed decreases on the front side in the traveling direction, but thereafter the speed increases. The number of the own vehicle mark points 73 constituting the traveling lane 72 of the left lane is seven, whereas the number of the own vehicle mark points 73 constituting the traveling locus 71 of the right lane is twelve. This indicates that the left lane can travel more smoothly on rainy days.

  Thus, by comparing and displaying the actual travel trajectory, it becomes clear at a glance that it is faster to travel in the left lane on a rainy day in some sections of the data collection section. Further, since the point information corresponding to the position in the traveling direction is recorded at regular intervals for the own vehicle mark point 73 constituting the traveling locus (step 45), the traveling locus by the own vehicle mark point 73 is displayed. By doing so, it is also possible to estimate the approximate time required. Also, if the vehicle mark points 73 constituting the travel locus are dense, it can be intuitively determined that the situation when the vehicle mark points 73 are collected is the cause of the delay. For example, when the vehicle mark points 73 collected on a rainy day are denser than the vehicle mark points 73 collected on a sunny day, it is intuitive that rain is the cause of the delay. Can do.

  In this example, the difference in speed between the left and right lanes depending on the weather was intuitive, but by always displaying the travel locus when the vehicle was able to travel at the fastest speed, the user can There is a high possibility that it will be possible to easily find a room for improving the required time. For example, even if you depart quickly depending on the time of day, you can easily know that you have encountered the peak of commuting and school rush hours and no improvement in the required time. This is because it is possible to easily find which section is behind the fastest travel locus. Therefore, the user can obtain information for generally facilitating improvement of driving by displaying the traveling locus and considering the situation when the point information constituting the traveling locus is collected.

  As shown in FIG. 5, the control unit 11 can easily obtain a deviation value for the item “traveling time”, so that the average value is “optimal”, “slightly early / slow”, “ Several types of data such as “early / late” may be calculated, and based on these data, several types of data corresponding to these data may be displayed simultaneously as past vehicle marks in the processing of step 43 described above. .

  Further, the control unit 11 searches for a plurality of routes from the start point to the end point of the data collection section to be set at the time of subdivision in step 25 of FIG. 2, and subdivides each route element constituting each route. You may make it set the area element which carried out. In this case, when traveling in the data collection section, data collection in FIG. 4 is performed for each section element constituting the traveled route element.

  In this case, when the collected data is shared by a plurality of users, based on the shared data, the control unit 11 displays a usage frequency diagram showing the usage frequency for each route element as shown in FIG. Can do. In the figure, 81 is the start point of the data collection section, 82 is the end point, 83a to 83g are route elements constituting each route from the start point 81 to the end point 82, and 84 is the past of each route element 83a to 83f. It is an icon which shows the use frequency of. Each of the root elements 83a to 83g is composed of at least one section element.

  In FIG. 8A, icons 84 are displayed based on all data collected by the process of FIG. In FIG. 8B, an icon 84 is displayed based on only data collected in fine weather and in FIG. 8C in rainy weather. The control unit 11 is as shown in FIGS. 8A to 8C in response to an instruction accompanied by designation of the name of the data collection section by the user and whether to use all data or only data in fine weather or rainy weather. A figure can be displayed.

  In this way, for a desired data collection section, by displaying the past usage frequency for each route element for each situation at the time of data collection such as weather, the user can, for example, experience traveling in the data collection section for the first time. Even in the case of a certain salesman, a route similar to that selected by an experienced person can be selected according to the situation such as the weather during driving.

  The past use frequency for each of the route elements 83a to 83f indicated by the icon 84 is calculated based on the data collected by the process of FIG. That is, based on the data as illustrated in FIG. 5 collected for each section element constituting each route element 83a to 83f, the number of times the data collection of FIG. 4 is performed for each route element 83a to 83f is aggregated. Based on the counting result, the usage frequency of each of the route elements 83a to 83f can be obtained.

  As described above, in FIG. 8A, as the usage frequency indicated by the icon 84, the usage ratios of the route elements 83a to 83f obtained using all the data regardless of the weather are displayed. In this case, for example, if a certain root element is the section A in the example of FIG. 5, the data collection for the section A has been performed three times, so the total result for the root element is “3”. Moreover, in FIG.8 (b), the utilization rate of each route element 83a-83f is displayed using only the data at the time of fine weather. In this case, since the data collection in the situation where the “weather” for the section A is “clear” is performed once, the total result for the route element is “1”. In FIG.8 (c), the utilization rate of each route element 83a-83f is displayed using only the data at the time of rainy weather. In this case, since the data collection in the situation where the “weather” for the section A is “clear” is performed once, the total result for the route element is “1”. Based on the tabulation results obtained in this way, the usage frequency for each route element is obtained.

  The icon 84 is like a bar meter indicating the usage frequency. The use frequency is indicated as the use ratio of each route element with respect to all route elements coming out from each branch point in the route from the start point 81 to the end point 82. That is, the sum of the utilization ratios of the route elements coming out from one branch point is 1. The utilization ratio is indicated by the ratio of the black portion to the entire bar, where 1 is the case where the entire bar of each icon 84 is black. Therefore, for example, the length of the icon 84a and the icon 84b added to the two route elements 83a and 83b coming from the start point 81 which is also a branch point in FIG. One length. And since the length of the black part of the icon 84a is longer than the length of the black part of the icon 84b, it turns out that the root element 83a is used more frequently than the root element 83b.

  According to the example of FIG. 8, for example, it is considered that a route with a good view is used in fine weather, and a route with a poor view that can avoid wind and rain in rainy weather is reflected. In such a case, for example, even if the user is the first salesman to pass the route from the start point 81 to the end point 82, the weather frequency can be displayed by referring to the usage frequency diagram as shown in FIG. Depending on the situation, it is possible to select a safe route that has been selected by many experienced persons in the past. For example, when it rains, the route elements 83a, 83c, and 83g may be selected so as to trace the frequent route elements with reference to FIG. 8C based on data collected in the rain. As for the root element 83g, only this root element has come out of the branch point and the usage rate is 1, so the display of the icon 84 is omitted.

  Note that the above-described use frequency can also be used when performing a route search with the start point of the data collection section as the start point and the end point as the destination point. That is, conventionally, when performing a route search, a recommended route is searched in consideration of the “distance” and “time” from the departure point to the destination, but in addition to “distance” and “time”, “ Route search can also be performed in consideration of "weather" and the like.

  For example, if the weather at the time of route search is fine weather, it is possible to give priority to a route composed of route elements that are frequently used based on data collected during fine weather. For example, in the case of the route illustrated in FIG. 8 described above, the route configured by the route elements 83b and 83f that are frequently used in the fine weather shown in FIG. Further, “road type” is added as a data collection item by the processing of FIG. 4, and a route search can be performed in consideration of the set “frequency for each road type”. For example, if the frequency of a highway is set as “frequency for each road type”, a route element passing through the highway can be prioritized.

  According to the present embodiment, it is possible to provide appropriate data for improving the driving efficiency as exemplified in FIGS. 5 to 8 based on the driving record data collected by the processing of FIG. This point is consistent with the fact that there is no need for guidance by a navigation device on a frequently used route, and in many cases it is often asked how efficiently the vehicle can travel.

  In addition, since data related to the traveling environment such as weather is collected at the time of data collection in FIG. 4, analysis data considering the traveling environment can be provided based on the collected data. For example, the analysis data can be provided separately for each traveling environment, such as displaying the traveling trajectory and the usage frequency of each route element separately in the case of fine weather and in the case of rainy weather. The collected data can also be used for estimation of a required time based on a weather forecast, search for a recommended route, and the like.

  In addition, since the past vehicle mark and the current vehicle mark are displayed at the same time based on the start point of the data collection section (step 43), the current traveling state in the data collection section is displayed at the same timing. Compared with past driving in Japan, it can be used to improve driving. In addition, the data collected by standardizing the collected data by calculating the average value or the actual travel value of the collected data as it is and the current travel locus are displayed at the same time. Can be easily found.

  In addition, since data is collected for each section element obtained by subdividing the data collection section for each intersection or the like, the collected and accumulated data is displayed in other cases, for example, in the use frequency screen display as shown in FIG. It can be used easily. In addition, since it is considered that the user likes a route that is frequently used, when performing route search in the data collection section, as shown in FIG. 8 above, the number of uses for each route element 83a to 83f. By summing up and presenting the frequency of use, the route suitable for the user's preference can be immediately proposed.

  In addition, collecting data on frequently used routes and presenting the analysis results to the driver in this way requires the driver to standardize the driving tendency. That is, as shown in FIG. 8, even when a plurality of routes can be proposed, the driver's habit is corrected and optimized by the driver selecting a route that is frequently used. For example, a user who places importance on safe driving will drive carefully regardless of which of the proposed routes, but on the other hand, only a slight improvement in fuel efficiency will be required for frequently used routes. Therefore, the user who thinks that the effect is large is considered to inevitably standardize the driving tendency in the direction of lower fuel consumption by selecting a route that can travel at a constant speed. Moreover, since the driving tendency can be standardized by performing display based on the collected data in this way, complicated processing such as learning becomes unnecessary.

  In addition, by exchanging the collected data among each user in the group and sharing it, typical characteristics of the group, for example, characteristics that tend to pass through a narrow road forcibly even with large cars, If it is a nursing care vehicle, it can grasp | ascertain the characteristic that there exists a tendency which invades from the route which is easy to get on and off. Therefore, an objective evaluation for such characteristics can be performed as a group. In the case of a route service vehicle or the like, it is important to evaluate and improve whether or not the group characteristics are correct, and the present invention is considered to be effective.

  In addition, since the collected data can be edited, data that deviates from the standard and should not be referenced to form the standard is collected under special driving conditions such as during road construction. In such a case, such data can be deleted or invalidated. When data is collected again under the same special driving environment, the special driving environment is also distinguished based on the data collected under such a driving environment. You may make it show like 8. FIG.

  In addition, since “weather” and “road type” exist as data items to be collected, when searching for routes, in addition to the conventional “distance” and “time” search conditions, “weather” and “by road type” Route search using the “frequency” as a search condition.

  Note that the present invention is not limited to the above-described embodiment, and can be implemented with appropriate modifications. For example, in the above description, the example in which the present invention is implemented for a navigation device has been described. Instead, the present invention is implemented for a combination of a personal computer and a GPS receiver or a GPS mobile phone. Also good.

  In addition, since the GPS mobile phone often manages the map information by the base station, if the data collected at the time of running or walking can be collected from the GPS mobile phone by the process as shown in FIG. In addition to information, a standardized route can be provided by many users in consideration of conditions such as weather.

It is a block diagram which shows the structure of the navigation apparatus which concerns on one Embodiment of this invention. It is a flowchart which shows the process which accepts the setting of a data collection area in the navigation apparatus of FIG. It is a figure which shows an example of the data collection area set by the process of FIG. It is a flowchart which shows the data collection process in the navigation apparatus of FIG. It is a figure which shows an example of the display of the data collected by the data collection process of FIG. It is a figure which shows a mode that a part in the data collection area of FIG. 3 was expanded and displayed. It is a figure which shows a mode that a part of display of FIG. 6 was expanded and displayed. It is a figure which shows an example of the usage frequency figure which shows the usage frequency about each route element displayed by the apparatus of FIG.

Explanation of symbols

11: control unit, 12: position detection unit, 13: map data unit, 14: storage unit, 15: audio output unit, 16: operation unit, 17: display unit, 31: start point, 32: end point, 33: Intersection, 34: Mark, 61: Two-lane road, 62: Pedestrian road, 63, 71, 72: Traveling locus, 71a, 72a: Part of the traveling locus, 73: Own vehicle mark point, 81: Start point, 82: End point, 83a to 83g: Route element, 84, 84a, 84b: Icon.

Claims (9)

Each time a predetermined data collection section is moved, information for identifying a moved portion in the section and data of a predetermined item that can vary for each movement are associated with identification information for identifying each movement. Recording means for recording,
Designating means for accepting designation of data content of the predetermined item or content of the identification information;
An information processing apparatus comprising: display means for displaying a movement locus based on information corresponding to the content designated by the designation means among the movement location specifying information recorded by the recording means. The movement location specifying information is data of each movement position for every fixed time,
The information processing apparatus according to claim 1, wherein the display unit displays the movement locus by displaying a mark indicating the movement position on a map. The movement location specifying information is data of each movement position for every fixed time,
When the display means is moving in the data collection section, a reference is made to a predetermined point on the data collection section among the movement positions in the movement location specifying information corresponding to the content designated by the designation means. The display of the movement trajectory is performed by displaying a mark indicating a movement position at a time corresponding to the current time on the map together with a mark indicating the current position. Information processing device. The movement location specifying information is information indicating whether each route element delimited by each branch point in each route from the start point to the end point of the data collection section is used for movement,
The information processing apparatus according to claim 1, wherein the display unit displays the movement trajectory by displaying a usage frequency for each route element. Each route element delimited by each branch point in each route from the start point to the end point of the data collection section is composed of one or two or more section elements,
5. The information processing apparatus according to claim 1, wherein the recording unit records the data of the predetermined item for each section element. 6.   6. The predetermined item of each predetermined item, wherein a predetermined calculated value calculated based on a data value recorded a plurality of times is handled as a part of the data of the predetermined item. The information processing apparatus according to any one of claims.   The information processing apparatus according to claim 1, further comprising an editing unit that deletes or invalidates a part of the data recorded by the recording unit.   A program for operating a computer (including an embedded device) as each means in the information processing apparatus according to claim 1. Each time the recording means moves in a predetermined data collection section, information for identifying the moved location in the section and data for a predetermined item that can vary for each movement are identified for each movement. A recording step of recording in association with information;
A designation step for accepting designation of data content of the predetermined item or content of the identification information;
The display means comprises a display step of displaying a movement locus based on information corresponding to the content designated by the designation means among the movement location identification information recorded by the recording means. Processing method.

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