WO2011046185A1 - Dispositif embarqué, dispositif de génération de données de déplacement, et système d'information embarqué - Google Patents

Dispositif embarqué, dispositif de génération de données de déplacement, et système d'information embarqué Download PDF

Info

Publication number
WO2011046185A1
WO2011046185A1 PCT/JP2010/068083 JP2010068083W WO2011046185A1 WO 2011046185 A1 WO2011046185 A1 WO 2011046185A1 JP 2010068083 W JP2010068083 W JP 2010068083W WO 2011046185 A1 WO2011046185 A1 WO 2011046185A1
Authority
WO
WIPO (PCT)
Prior art keywords
data
driver
travel
traffic information
characteristic data
Prior art date
Application number
PCT/JP2010/068083
Other languages
English (en)
Japanese (ja)
Inventor
憲一郎 山根
淳輔 藤原
Original Assignee
クラリオン株式会社
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by クラリオン株式会社 filed Critical クラリオン株式会社
Publication of WO2011046185A1 publication Critical patent/WO2011046185A1/fr

Links

Images

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
    • G01C21/34—Route searching; Route guidance
    • G01C21/3453—Special cost functions, i.e. other than distance or default speed limit of road segments
    • G01C21/3492—Special cost functions, i.e. other than distance or default speed limit of road segments employing speed data or traffic data, e.g. real-time or historical
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/09—Arrangements for giving variable traffic instructions
    • G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
    • G08G1/0968—Systems involving transmission of navigation instructions to the vehicle
    • G08G1/096805—Systems involving transmission of navigation instructions to the vehicle where the transmitted instructions are used to compute a route
    • G08G1/096827—Systems involving transmission of navigation instructions to the vehicle where the transmitted instructions are used to compute a route where the route is computed onboard
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/09—Arrangements for giving variable traffic instructions
    • G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
    • G08G1/0968—Systems involving transmission of navigation instructions to the vehicle
    • G08G1/096855—Systems involving transmission of navigation instructions to the vehicle where the output is provided in a suitable form to the driver
    • G08G1/096866—Systems involving transmission of navigation instructions to the vehicle where the output is provided in a suitable form to the driver where the complete route is shown to the driver

Definitions

  • the present invention relates to an in-vehicle device, a travel characteristic data generation device, and an in-vehicle information system.
  • In-vehicle devices typified by navigation systems are required to provide route guidance that avoids delays due to traffic jams, etc., so that drivers can arrive at their destinations more quickly.
  • the in-vehicle device performs guidance along the route searched by the Dijkstra method using traffic information, particularly travel time information for each road section (called a link) as a cost.
  • the travel time information expresses the travel time of the average driver
  • the accuracy is not necessarily high depending on the travel characteristics related to the driving tendency of each driver.
  • Patent Document 1 is one of the prior arts that attempts to improve the accuracy of travel time information by taking into account the driving characteristics of individual drivers.
  • the future road conditions (travel time, etc.) of the link are estimated, and the driving speed when each driver drives the vehicle under the estimated road condition is estimated as the preferred driving speed of each driver.
  • a technique for estimating the travel time of each link using the link distance and the estimated preference driving speed is described.
  • Patent Document 2 is also one of the prior arts that attempts to improve the accuracy of travel time information by taking into account the driving characteristics of individual drivers.
  • data obtained by measuring the traveling state of a vehicle is accumulated as traveling history information, and traffic information on the route is predicted based on the traveling history information and traffic information.
  • a technique for predicting an arrival time at an arbitrary point is disclosed.
  • none of the above known techniques can correct the travel time information with high accuracy in a situation where there is no driving history data of the driver or there is not a sufficient amount of driving history data. This means that when the driver uses the in-vehicle device that obtains the travel history data for the first time or when using it for the first time, none of the above-described known techniques is sufficiently effective. Furthermore, even after a lot of travel history data is acquired by the in-vehicle device, the preferred driving speed cannot be acquired for a road on which the driver has not traveled so far, so that none of the above known techniques can be applied.
  • the Dijkstra method described above is a method for searching for a route from a departure place to a destination based on travel time information of a road section (link).
  • a road section in which travel time information is not corrected, a road section that is generally free of traffic congestion such as a residential road in a residential area or a road section with a small amount of traffic, and a route searched by the Dijkstra method, This is because it may be an unnatural route including many of these road sections.
  • An object of the present invention is to solve such a problem and to correct travel time information with high accuracy in consideration of estimated travel characteristics even in a situation where there is not enough travel history data for each driver. .
  • the vehicle-mounted device is mounted on a vehicle and stores a traffic information data and map data used for route search, and a destination based on the traffic information data and the map data.
  • a traffic information data and map data used for route search, and a destination based on the traffic information data and the map data.
  • Communication means for receiving driving characteristic data for each attribute classification from the driving characteristic data generating device, and traffic information correction means for correcting traffic information data using the attribute characteristic driving characteristic data of the attribute classification to which the driver of the vehicle corresponds
  • the route search means searches for a recommended route using the traffic information data corrected by the traffic information correction means.
  • the in-vehicle device of the first aspect is based on a driver profile including driver attribute information, travel history data that is travel data for each driver, and travel history data based on the driver profile.
  • Data classification means for classifying drivers for each driver, and driving characteristic data for each driver to be corrected for each attribute classification using travel history data and traffic information data classified for each driver registered in the driver profile
  • Driving characteristic data generating means and the traffic information correcting means corrects the traffic information data using the attribute classification-specific traveling characteristic data or the driver-specific traveling characteristic data.
  • the travel characteristic data generating means is configured such that the travel history data classified for each driver is recorded more than the first predetermined number.
  • driving characteristic data for each driver for use in correcting traffic information data is generated, and when the driving characteristic data is less than the first predetermined number and greater than the second predetermined number, the driving characteristic data for each driver based on the driving characteristic data for each attribute classification Generate generate.
  • the driver profile includes the user ID of each driver
  • the travel history data includes the link number of the road link that has traveled
  • the travel on the road link The data classification means classifies the travel history data for each user ID based on the user ID included in the driver profile information, and the travel characteristic data generation means is classified. Based on the amount of travel history data for each user ID, a method for generating driver-specific travel characteristic data is determined.
  • the travel characteristic data generating means has the travel history data classified for each driver being less than the first predetermined number and greater than the second predetermined number.
  • the travel time data or the average speed of each link is compared between the travel history data and the traffic information data of the driver, and a difference obtained by subtracting the traffic information data from the travel history data is obtained.
  • the driving characteristic data for each attribute classification of the minimum attribute classification is obtained as driving characteristic data for each driver.
  • a driving characteristic data generating apparatus is a driving characteristic data generating apparatus that generates driving characteristic data for correcting traffic information data using driving history data of a plurality of drivers, and relates to driver attributes.
  • Driver profile that includes information, travel history data that accumulates travel data for each driver, data classification means that classifies travel history data for each predetermined attribute classification based on the driver profile, and travel classified for each attribute
  • a travel characteristic data generating means for generating travel characteristic data for each attribute classification for correcting the traffic information data for each attribute classification using the history data is provided.
  • the driver profile includes the user ID of each driver, and at least one of birth date, gender, license acquisition date, and cumulative driving distance.
  • the travel history data includes the link number of the travel and either the travel time or the average speed of the link, and in the data classification means, the attribute classification is information included in the driver profile and the travel history data. To be determined.
  • the driving characteristic data generating means compares the driving history data for each attribute classification of the driver with the travel time for each link in the traffic information data, A difference obtained by subtracting the traffic information from the travel history data is obtained, and an average value of the difference is obtained as travel characteristic data for each attribute classification for correcting the traffic information data of each link for each attribute classification.
  • An in-vehicle information system includes an in-vehicle device according to any one of claims 1 to 5, a traveling characteristic data generation device according to any one of claims 6 to 8, Consists of a data communication device and a communication network that connect the travel characteristic data generation device and the in-vehicle device.
  • the driving characteristic data is generated by the attribute classification based on the driving history data of another driver belonging to the same attribute classification as the driver.
  • Traffic information data can be appropriately corrected by obtaining it from the device and applying it. Further, by generating or selecting appropriate attribute classification-specific travel characteristic data according to the collection status of the driver's travel history data, the traffic information data can be appropriately corrected in consideration of the driver's driving characteristics.
  • FIG. 1 is a configuration diagram of an in-vehicle information system according to an embodiment of the present invention.
  • the in-vehicle information system 1 in FIG. 1 includes a travel characteristic data generation device 10, an automobile 13 equipped with the in-vehicle device 11 and the data communication device 12, and a communication network 14.
  • the in-vehicle device 11 is connected to the travel characteristic data generation device 10 via the communication network 14.
  • the travel characteristic data generation device 10 includes a driver attribute classification condition 100, a data classification unit 101, a travel history database 102, a travel characteristic data generation unit 103 by attribute classification, a reference traffic information database 104, a travel characteristic data 105 by attribute classification, and a driver.
  • a profile 106 is provided.
  • the driving characteristic data generation device 10 has a function of classifying individual drivers into attributes and generating driving characteristic data obtained by analyzing driving history data of various drivers based on the attributes.
  • the travel characteristic data generation device 10 is a computer device such as a personal computer (PC), a workstation, a server, a large computer, etc., and its hardware configuration includes a CPU, memory, HDD, DVD drive, display, keyboard, mouse, and the like. Composed.
  • the travel characteristic data generation device 10 is connected to the in-vehicle device 11 via the communication network 14.
  • the travel characteristic data generation device 10 receives travel history data for each driver from the in-vehicle device 11 and accumulates the travel history data in the travel history database 102.
  • working characteristic data generation apparatus 10 is explained in full detail behind.
  • the in-vehicle device 11 calculates a recommended route to the destination using map data, traffic information, and the like, and performs guidance based on the recommended route.
  • the in-vehicle device 11 has a function of accumulating travel history data of the automobile 13.
  • a functional block diagram of the in-vehicle device 11 is shown in FIG.
  • the in-vehicle device 11 includes a destination setting unit 110, a traffic information correction unit 111, a reference traffic information database 112, travel characteristics data 113 by attribute classification, a route search unit 114, a search database 115, A route guidance unit 116, a travel history storage unit 117, a travel history database 118, and a map database 119 are provided. Each part shown in FIG. 2 will be described in detail later.
  • the in-vehicle device 11 includes, as hardware configurations, an arithmetic processing unit 40, a display 41, a data storage device 42, a voice input / output device 43, an input device 44, a wheel speed sensor 45, a geomagnetic sensor 46, a gyroscope.
  • a sensor 47, a GPS (Global Positioning System) receiving device 48, and an in-vehicle LAN (Local Area Network) device 49 are provided.
  • GPS Global Positioning System
  • LAN Local Area Network
  • the in-vehicle device 11 is connected to the travel characteristic data generation device 10 via the communication network 14.
  • the in-vehicle device 11 accesses the traveling characteristic data generation device 10 in response to a request from the user via the input device 44, receives the traveling characteristic data by attribute classification from the traveling characteristic data generation device 10, and receives this by the attribute classification Stored in the travel characteristic data 113.
  • the in-vehicle device 11 transmits the driving history data of the driver from the driving history database 118 to the driving characteristic data generation device 10.
  • the data communication device 12 is connected to the in-vehicle device 11 via a communication I / F (interface) 50 and includes a modem for connecting to the communication network 14.
  • the data communication device 12 may be, for example, a communication modem that supports PHS (registered trademark) (Personal Handyphone System), DSRC (Dedicated Short Range Communication), cellular communication, short-range wireless LAN communication, or the like. It corresponds to a cellular phone or a data communication card with a built-in modem.
  • the in-vehicle device 11 can be connected to the communication network 14 by the data communication device 12 and further connected to the traveling characteristic data generation device 10 via the communication network 14.
  • the arithmetic processing unit 40 is a central unit that performs various processes.
  • One of the processes is a positioning process for calculating the current location of the automobile 13 based on information output from various sensors such as the wheel speed sensor 45, the geomagnetic sensor 46, the gyro sensor 47, and the GPS receiver 48.
  • the arithmetic processing unit 40 is a map database in which map data necessary for displaying a map around the current location on the display 41 is stored in the data storage device 42 based on the information on the current location calculated by the positioning process. A process of reading from 119 is performed.
  • the arithmetic processing unit 40 performs processing for displaying a mark (icon) indicating the current location together with the surrounding map on the display 41. Furthermore, the arithmetic processing unit 40 performs a process of searching for a recommended route connecting the destination set by the user and the current location (departure location) using the map database 119 or the like stored in the data storage device 42. The arithmetic processing unit 40 uses the voice input / output device 43 and the display 41 to perform processing for guiding the user along the recommended route. Each function of FIG. 2 is also processed by the arithmetic processing unit 40.
  • the display 41 is a unit that displays an image under the control of the arithmetic processing unit 40, and includes a CRT (Cathode Ray Ray Tube) or a liquid crystal display. Signals between the arithmetic processing unit 40 and the display 41 are generally connected by RGB signals or NTSC (National Television System Committee) signals.
  • CTR Cathode Ray Ray Tube
  • NTSC National Television System Committee
  • the data storage device 42 includes an optical storage medium such as a CD-ROM and a DVD-ROM, a magnetic storage medium such as a hard disk, a storage medium such as a nonvolatile semiconductor memory, and a reading / writing device thereof.
  • the data storage device 42 stores a reference traffic information database 112, attribute classification-specific travel characteristic data 113, a search database 115, a travel history database 118, and a map database 119, and a destination setting POI.
  • Various data such as (Point of Interests) data is also stored.
  • the map data format shown in FIG. 3 is an example in the case where map data is managed as secondary mesh information that is data in units of secondary mesh, and each “secondary mesh code” that is a mesh code of a secondary mesh.
  • the link information of each link constituting the road included in the mesh area is included.
  • the link information includes “start point coordinates” that are the coordinate information of the start node constituting each link for each “link number”, “end point coordinates” that are the coordinate information of the end node, and road type information including each link.
  • link length which is information indicating the length of each link
  • regulated speed which is information indicating the speed limit of each link
  • two nodes, a start node and an end node of each link Each contains a pointer to the link to be connected.
  • the voice input / output device 43 converts the message to the user generated by the arithmetic processing unit 40 into a voice signal and outputs it. Further, the voice input / output device 43 recognizes the voice uttered by the user and transfers the content to the arithmetic processing unit 40.
  • the input device 44 is a device that receives an instruction from the user, and includes a hard switch such as a scroll key or a scale change key, a joystick, a touch panel pasted on the display 41, a microphone for voice input, and the like.
  • the various sensors such as the wheel speed sensor 45, the geomagnetic sensor 46, and the gyro sensor 47 and the GPS receiver 48 are used by the in-vehicle device 11 to detect the current location (vehicle position).
  • the wheel speed sensor 45 measures the travel distance from the product of the wheel circumference and the measured number of rotations of the wheel, and further measures the angle bent from the difference in the number of rotations of the paired wheels.
  • the geomagnetic sensor 46 detects the earth's magnetic field and detects the direction in which the moving body is facing.
  • the gyro sensor 47 is composed of an optical fiber gyro, a vibration gyro, or the like, and detects an angle of rotation of the sensor.
  • the GPS receiver 48 receives a signal from a GPS satellite, and measures the distance between the mobile body and the GPS satellite and the rate of change of the distance with respect to three or more satellites to thereby determine the current position, traveling speed, Measure the heading and current time.
  • the in-vehicle LAN device 49 is a device for connecting to the in-vehicle LAN provided in the automobile 13 on which the in-vehicle device 11 is mounted.
  • Various information flowing through the in-vehicle LAN for example, door opening / closing information, light lighting state information , Receive engine status and failure diagnosis results.
  • Driver attribute classification condition 100 is a condition for classifying individual drivers into attributes based on the driving characteristics of the driver. It is desirable that drivers classified into the same attribute based on the driver attribute classification condition 100 have similar driving characteristics.
  • the driver attribute classification condition 100 is based on factors such as the number of years that have passed since obtaining a license and the cumulative driving distance after obtaining a license, and the age at which the body's reaction speed may be affected. It is determined in consideration of factors such as weather and brightness at the driving point. For example, consider a first example in which the driving characteristics of a driver are classified by age.
  • the younger age group is less than 30 years old
  • the attribute class is 1, 30 years old and younger than 50 years is attribute class 2, 50 years old and younger is less than 65 years old
  • the attribute classification is 3, 65.
  • elderly people over age are divided into attribute classification 4.
  • a rule for classifying drivers from attribute classification 1 to attribute classification 4 based on their age is the driver attribute classification condition 100.
  • As another method of classification other than age there may be a method related to the skill level of driving such as the number of years since the license is obtained and the cumulative driving distance after the license is obtained.
  • the driver attribute classification condition 100 may include a gender condition that may reflect a difference in action range. For example, when the classification according to the sex condition is added to the first example, the classification is, for example, a male under 30 years old, a female under 30 years old, a male between 30 and 50 years old, a female between 30 and 50 years old, and so on. It becomes a combination. Further, the driver attribute classification condition 100 may take into account road surface conditions (dry, wet, frozen) or weather (sunny, rain, snow).
  • the driver attribute classification condition 100 may take into account outdoor brightness (bright, dark) and time zones (morning, noon, evening). For example, when the classification according to the outdoor brightness is added to the first example, the outdoor situation under 30 years old is bright, the outdoor condition under 30 years is dark, the outdoor condition between 30 and 50 years old is bright, 30 It is a combination of classifications such as the situation where the outdoors is over 50 years old and under 50 years old.
  • the driver attribute classification condition 100 is stored as a data file in a data storage device such as an HDD (not shown) provided in the traveling characteristic data generation device 10.
  • the travel history database 102 stores travel history data collected from the travel history database 118 for each of the one or more automobiles 13 by the travel characteristic data generation device 10 via the data communication device 12 and the communication network 14. Similar to the driver attribute classification condition 100, the travel history database 102 is also stored in the data storage device.
  • FIG. 4 shows an example of the data format of the travel history data. A method for generating the travel history data will be described in detail in the description of the travel history storage unit 117 of the in-vehicle device 11.
  • the driver profile 106 is data including information on individual drivers.
  • the data of the driver profile 106 is stored as a data file in a data storage device such as an HDD in the driving characteristic data generation device 10 as with the driver attribute classification condition 100.
  • FIG. 5 shows an example of the data format of the driver profile 106.
  • the driver profile 106 shown in FIG. 5 is a driver ID (identical to that included in the driving history data) that is an ID for identifying each driver, the date of birth of each driver, gender, license acquisition date, cumulative driving distance. Consists of By referring to these pieces of information, each driver can be classified into attributes.
  • the driver profile 106 is created from information provided when a user who has purchased the in-vehicle device 11 performs user registration through a website or a postcard.
  • the data classification unit 101 classifies the travel history data 102 into attributes based on the driver attribute classification condition 100 and the driver profile 106. Details of the processing of the data classification unit 101 will be described later together with the processing flow.
  • the reference traffic information database 104 traffic information data used as a reference when judging the tendency of the attributed travel history data classified by the data classification unit 101 is stored as reference traffic information data.
  • the reference traffic information data is, for example, travel time data for each link provided from a traffic information center, statistical travel time data obtained by statistically processing the provided link travel time according to day of the week or time zone, and the like.
  • the reference traffic information data beta 104 is stored as a data file in a data storage device such as an HDD in the driving characteristic data generation device 10 as with the driver attribute classification condition 100.
  • FIG. 6 shows an example of the data format of the reference traffic information data.
  • the reference traffic information data in FIG. 6 includes a link number, a link length, and a reference travel time.
  • the attribute classification-specific travel data generation unit 103 compares the travel history data classified by the data classification unit 101 with the reference traffic information data having the same link number stored in the reference traffic information database 104, thereby obtaining a travel history.
  • the tendency of the data with respect to the reference traffic information data is analyzed, and the attribute characteristic-specific traveling characteristic data 105 which is a parameter for correcting the reference traffic information data is generated.
  • FIG. 7 shows an example of the data format of the travel characteristic data 105 classified by attribute classification.
  • the attribute characteristic-specific traveling characteristic data includes correction parameters for each link in each of the attributes 81 to 84 that can be classified by the driver attribute classification condition 100.
  • the correction parameter is a value for correcting the reference traffic information data.
  • the reference travel time which is the reference value in the reference traffic information data in FIG. 6, is the travel time [second] for each link
  • the correction parameter is also the amount [second] for correcting the travel time for each link.
  • the correction parameter is positive, the reference travel time increases due to the correction. If the correction parameter is negative, the reference travel time is reduced by the correction.
  • the traveling characteristic data generation device 10 generates the attribute characteristic-specific traveling characteristic data 105 which is a correction parameter for each attribute classification.
  • This attribute classification-specific traveling characteristic data 105 is transmitted to the in-vehicle device 11 via the communication network 14.
  • the in-vehicle device 11 receives the attribute classification-specific travel characteristic data 105 and stores it in the data storage device 42 as attribute-classification-specific travel characteristic data 113.
  • the in-vehicle device 11 uses the attribute-specific traveling characteristic data 113 based on the traveling history data of another driver belonging to the same attribute classification as that driver for the link in which the traveling history data of the driver of the automobile 13 does not exist.
  • the destination setting unit 110 is an HMI (Human Machine Interface) for setting a destination by the user operating the in-vehicle device 11.
  • HMI Human Machine Interface
  • the reference traffic information database 112 is a database equivalent to the reference traffic information database 104 in the travel characteristic data generation device 10.
  • the reference traffic information database 112 may download, for example, the reference traffic information database 104 of the travel characteristic data generation device 10 via the data communication device 12 and the communication network 14, or via FM multiplex broadcasting, DSRC or beacon communication. You may produce
  • the reference traffic information data 104 held in the travel characteristic data generation device 10 may be temporarily stored in a storage medium such as a DVD-ROM and copied or moved to the in-vehicle device 11 by a reading device (not shown).
  • the attribute classification-specific traveling characteristic data 113 is data equivalent to the attribute classification-specific traveling characteristic data 105 in the traveling characteristic data generation apparatus 10.
  • the attribute characteristic-specific traveling characteristic data 105 may be downloaded from the traveling characteristic data generation apparatus 10 via the data communication device 12 and the communication network 14, or may be downloaded to a storage medium such as a DVD-ROM.
  • the attribute classification-specific traveling characteristic data 105 may be temporarily stored, read by a reading device (not shown), and copied or moved to the in-vehicle device 11.
  • the traffic information correction unit 111 performs a process of correcting the reference traffic information data 112 using the attribute classification-specific traveling characteristic data 113.
  • search database 115 data other than the map data whose format is shown in FIG. 3 among the data used for route search and guidance is stored as search data.
  • search data is stored for each mesh code representing an area identification ID.
  • information on road structures (name, type, coordinate information, etc.) other than roads included in each mesh region, information on rivers, lakes, seas, etc. in addition to green zones and mountainous areas are also included. include.
  • the route search unit 114 is set by the current location obtained from the GPS receiver 48 or the departure point set by the user and the destination setting unit 110 with reference to the map database 119, the search database 115, the reference traffic information database 112, and the like. Search for the optimal route (recommended route) connecting the destination.
  • the route guidance unit 116 refers to the map database 119 and the like, and guides the user along the recommended route obtained by the route search unit 114 using the voice input / output device 43 and the display 41.
  • the travel history accumulating unit 117 includes various data of the map database 119, various information of the wheel speed sensor 45, the geomagnetic sensor 46, the gyro sensor 47, and the position information of the vehicle 13 measured by the GPS receiver 48, and the interior of the vehicle. Based on data from outside the in-vehicle device 11 obtained via the LAN device 49, travel history data is generated, the travel history data is stored in the travel history database 118, and output to the travel characteristic data generation device 10.
  • the travel history data generated by the travel history storage unit 117 follows the data format shown in FIG.
  • the generation process of the travel history data shown in the format of FIG. 4 will be described.
  • the data column in each row in FIG. 4 is called one record.
  • a travel history is recorded as data for each driver, for each link traveled, and for each date and time that passed the link.
  • Driver ID is obtained by referring to the driver ID number uniquely assigned to each vehicle-mounted device 11 stored in the data storage device 42.
  • an ID number corresponding to each driver may be referred to.
  • the “passing date and time” is the date and time when the automobile 13 passed the link, and is information in units of one second obtained from the GPS receiver 48 of the in-vehicle device 11. It is assumed that the automobile 13 passes the link when the automobile 13 passes either the link start node or the end node. It is unified for all records whether the start node or the end node is considered to have passed the link. In the following, the date and time when the link has passed the start node is recorded.
  • the “link number” is the current location of the vehicle 13 obtained from the latitude / longitude information obtained at a frequency of once or less per second from the wheel speed sensor 45, the geomagnetic sensor 46, the gyro sensor 47, and the GPS receiver 48 of the in-vehicle device.
  • the position information is specified by matching each coordinate in the link including the start node and the end node of the link included in the map database 119 stored in the data storage device 42.
  • Link length is included in the map data and can be referenced using the corresponding link number as a key.
  • the “link travel time” can be calculated from the difference between the end node passage date and time and the start node passage date and time by specifying the passage date and time of the start node and end node of the link. This value is also data in units of one second like the passage date and time. Instead of the link travel time, the link average speed obtained using the link travel time and the link length may be recorded in the travel history data.
  • “Road surface condition” and “outdoor brightness” are values obtained from the outside of the in-vehicle device 11 via the in-vehicle LAN device 49 of the in-vehicle device 11.
  • the road surface state is recognized from an in-vehicle camera and an image recognition device provided in the automobile 13, and outdoor brightness is obtained from an illuminance sensor provided in the automobile 13.
  • the travel history database 118 that accumulates the travel history data of the automobile 13 in record units in this way is collected in the travel characteristic data generation device 10 via the data communication device 12 and stored as the travel history database 102.
  • the driving characteristic data generation device 10 reads a data file of the driver attribute classification condition 100 from a data storage device (not shown).
  • the driving characteristic data generation device 10 reads the driver profile 106 from the data storage device.
  • the travel characteristic data generation device 10 reads travel history data from the travel history database 102 and reads reference traffic information data from the reference traffic information database 104 (step S51).
  • the travel characteristic data generation device 10 classifies the travel history data read in step S51 by the data classification unit 101 based on the driver attribute classification condition 100 and the driver profile 106 read in step S51.
  • the driver attribute classification condition 100 is the above-mentioned younger age group under 30 years old, the attribute class 1, 30 years old and younger than 50 years old attribute class 2, 50 years old and younger than 65 years old attribute class 3, 65 years old and older An example of using an age-based classification rule that divides the demographic group into attribute classification 4 will be described.
  • the driver profile 106 has the contents shown in FIG. 5 and the travel history data 102 is the data shown in FIG.
  • the travel characteristic data generation device 10 classifies all the records in the travel history database 102 into attributes based on the driver attribute classification condition 100 (step S52).
  • the travel characteristic data generation device 10 compares all records in the travel history database 102 classified into attributes with the reference traffic information data read in step S51 in the attribute classification-specific travel characteristic data generation unit 103. Thus, the tendency of each record with respect to the reference traffic information data is analyzed, and a correction parameter is generated.
  • the correction parameters are stored as attribute classification-specific traveling characteristic data 105 (step S53).
  • the travel time Tb of the reference traffic information is subtracted from the link travel time Th of the travel history data for all data of the same attribute classification in the same link, as shown in Equation 1 below.
  • the average value Ta of each difference (Th ⁇ Tb) is used as a correction parameter for correcting the reference traffic information data.
  • i is a data suffix in a certain link
  • n is the number of data of a link to be processed.
  • the attribute classification travel characteristic data generation unit 103 obtains the correction parameter using the travel time of the link, such as the travel time of the link history of the travel history data and the reference travel time of the reference traffic information data.
  • the average speed at the link is used as the reference value as the traffic information data
  • the average speed for each link is used instead of the travel time in Equation 1.
  • the correction parameter Ta is once generated for each link, but the parameters generated for each link are aggregated in a predetermined unit such as an area or a road type, and an average value thereof is calculated for each aggregation unit. May be used as a correction parameter.
  • a predetermined unit such as an area or a road type
  • an average value thereof is calculated for each aggregation unit.
  • an area-related code secondary mesh code
  • road type highway, general road, etc.
  • the destination is set by the HMI operation on the voice input / output device 43 or the input device 44 by the user in the destination setting unit 110 (step S 61).
  • the destination is a method of inputting a cursor moved on the map display screen as a destination, a method of selecting from a list of destinations (POI) after selecting a genre in a destination search menu, or a telephone number. This is set by a method of setting a destination by a search specifying an address or the like.
  • the in-vehicle device 11 reads the reference traffic information data from the reference traffic information database 112 in the traffic information correction unit 111, and reads the travel characteristic data 113 by attribute classification from the data storage device 42 (step S62). And the vehicle equipment 11 correct
  • the traffic information correction unit 111 corrects the reference traffic information data in the reference traffic information database 112.
  • the correction parameter for each driver attribute classification based on the driving characteristic data 113 according to attribute classification is Ta and the reference traffic information data based on the reference traffic information database 112 is Tb
  • the corrected reference traffic information data Tb ′ is expressed by the following (Equation 2). It is expressed as
  • the driving history data is based on the driving history data.
  • the traffic parameter Tb based on the reference traffic information data held in the reference traffic information database 112 by the traffic information correction unit 111 is obtained by obtaining the correction parameter Ta in the travel characteristic data 105 according to the attribute classification from the travel characteristic data generation device 10.
  • the corrected traffic information data Tb ′ with high accuracy can be obtained.
  • the correction parameter Ta in the attribute classification-specific travel characteristic data 113 is described as being generated for each link, but as described above, the attribute characteristic-specific travel characteristic data generated for each link. 113 may be aggregated in a predetermined unit such as area or road type, and an average value thereof may be used as a correction parameter in driving characteristic data by attribute classification for each aggregation unit.
  • the correction obtained for each aggregation unit Parameters (travel characteristic data) can be collectively applied to the reference traffic information data of the links corresponding to the respective aggregation units.
  • the in-vehicle device 11 uses the route searching unit 114 to determine the position information measured by the wheel speed sensor 45, the geomagnetic sensor 46, the various sensors of the gyro sensor 47, and the GPS receiver 48 of the in-vehicle device 11 as described above.
  • the search data 115 an optimum route (recommended route) that connects the current location of the vehicle 13 obtained from each of the data, or the starting point set by the user and the destination set by the destination setting unit 110 is referred to. ) Is searched (step S64).
  • the corrected traffic information data Tb ′ the shortest time route when the travel time is the cost of the link is calculated as a recommended route by the Dijkstra method.
  • the in-vehicle device 11 creates guidance data necessary for guidance from the map data stored in the data storage device 42 based on the recommended route information searched by the route search unit 114 in the route guidance unit 116.
  • This guidance data includes major intersections, intersections with complex structures, or enlarged views of intersections that need to turn right or left (referred to as guidance intersections), and detailed route information from entry to exit of the guidance intersection, Or the distance information etc. to the guidance intersection are included.
  • route guidance is performed according to the current location that is sequentially obtained (step S65).
  • the in-vehicle device 11 displays the distance from the current location to the nearest guidance intersection on the display 41 or notifies by voice. In addition, if there is a guided intersection within a predetermined distance from the current location, the in-vehicle device 11 sequentially updates the distance to the guided intersection displayed on the display 41, and "the intersection is left in the future 500m" Is guided in the direction of travel. Further, the in-vehicle device 11 calculates the total travel time to the destination by calculating the sum of the travel time of each link constituting the calculated recommended route. And the vehicle equipment 11 calculates the arrival time to the destination from the present time and the total travel time.
  • the in-vehicle device 11 calculates a value based on two types of travel times before and after the correction for the estimated arrival time at the destination.
  • FIG. 10 is a display example of the display 41 at the time of route guidance in step S65.
  • 90 indicates the current position
  • 91 indicates the current date and time
  • 92 indicates the destination set by the user in the destination setting unit 110
  • 93 indicates the recommended route calculated by the route search unit 114.
  • 94 is the estimated arrival time at the destination.
  • “standard” is a value before correction, that is, a value calculated based on the reference traffic information data
  • “correction” is corrected by the travel characteristic data 113 by attribute classification. It is a value calculated based on the traffic information. Thereby, the user can know what the correction result by the attribute classification of the driver is compared with the reference value.
  • the in-vehicle device 11 uses the travel history storage unit 117 to store various data such as map data stored in the data storage device 42 and various sensors such as the wheel speed sensor 45, the geomagnetic sensor 46, and the gyro sensor 47 as described above.
  • the travel history data is generated by measuring and processing the travel data of the vehicle from the value measured during the travel and the positioning information measured by the GPS receiver 48 to generate travel history data. (Step S66).
  • the travel history data accumulated in the travel history database 118 is transmitted to the travel characteristic data generation device 10 via the communication network 14.
  • the process of the travel history accumulating unit 117 is the process from step S61 to S65. Regardless, it is executed periodically.
  • the in-vehicle device 11 uses the attribute characteristic-specific traveling characteristic data 105 generated from the traveling history data of another driver belonging to the same attribute classification as the driver even when the driving history data of the driver does not exist, as the driving characteristic data generation device. 10 and the reference traffic information data 112 is corrected to obtain highly accurate corrected traffic information. Then, by the minimum cost route search using the corrected traffic information with high accuracy, it becomes possible to perform high-quality route guidance that avoids traffic congestion more reliably.
  • the in-vehicle device 11 has a driving characteristic by attribute classification based on the driving history data of another driver belonging to the same attribute classification as the driver even when the driving history data of the driver is not sufficiently present.
  • the accuracy of the traffic information is improved by applying the data 105 and correcting the reference traffic information data in the reference traffic information database 112. This is effective in situations where the driver has just started using the vehicle-mounted device 11 that acquires travel history data for the first time or when using it for the first time.
  • This idea is based on the idea that the driving characteristics of a driver are similar to the driving characteristics of another driver belonging to the same attribute classification. However, since the driving characteristics of the driver do not necessarily match, In a situation where the driving history data of the driver is sufficiently present after repeated use, it is considered that the accuracy is higher when the reference traffic information data is corrected using the driving history data of each driver.
  • the reference traffic information data of all roads including the untraveled road is corrected based on the respective travel history data. To consider the driving characteristics of the driver.
  • the traveling characteristic data generation device 10 in the second embodiment of the present invention is the same as that in the first embodiment.
  • FIG. 11 shows a functional block diagram of the in-vehicle device 1011 in the second embodiment.
  • the in-vehicle device 1011 generates the driving characteristic data of the driver based on the accumulated driving history data for each driver in addition to the functions of the in-vehicle device 11 described in the first embodiment. It has a function.
  • the in-vehicle device 1011 has a configuration in which attribute-specific traveling characteristic data 120, a driver profile 121, a data classification unit 122, and a driver-specific traveling characteristic data generation unit 123 are added to the in-vehicle device 11.
  • the attribute characteristic-specific travel characteristic data 120 is a parameter for correcting the reference traffic information for each attribute class as in the case of the attribute characteristic-specific travel characteristic data 105 in the travel characteristic data generation device 10, but here, the travel history for each individual driver. It also includes correction parameters generated from the data.
  • the attribute classification-specific travel characteristic data 120 is obtained from the travel characteristic data generation device 10 as in the first embodiment, and also stores correction parameters generated by the driver-specific travel characteristic data generation unit 123.
  • the driver profile 121 is data including information on individual drivers, like the driver profile 106 in the travel characteristic data generation device 10 of the first embodiment. Note that in the second embodiment, it is sufficient that the driver can be identified, so there is no problem even if there is no information other than the driver ID.
  • the data classification unit 122 performs processing for classifying the travel history data 118 based on the driver ID registered in the driver profile 121. Further, a process for determining the amount of travel history data for each classified driver ID by a predetermined method is also performed. This processing result is used in the driver-specific travel characteristic data generation unit 123. Details of the processing will be described later together with the processing flow.
  • the driving characteristic data generation unit 123 for each driver compares the driving history data for each driver ID classified by the data classification unit 122 with the reference traffic information data 112 or the driving characteristic data 120 for each attribute classification, thereby The tendency with respect to the reference traffic information data 112 is analyzed, and the attribute characteristic-specific traveling characteristic data 120 that is a parameter for correcting the reference traffic information data 112 is generated and output.
  • the data format of the attribute characteristic-specific traveling characteristic data 120 is the same as that in the first embodiment. Details of the processing will be described later together with the processing flow.
  • the in-vehicle device 1011 uses the data classification unit 122 to select a driver from the driver profile 121 that should generate the attribute characteristic-specific traveling characteristic data 120 (step S71).
  • the driver may be selected by the user by the HMI from the driver list displayed on the display 41 of the in-vehicle device 1011 or automatically selected in the ascending order of the driver ID registered in the driver profile 121. Also good.
  • the driver is not registered in the driver profile 121, it is assumed that the user newly registers by the HMI displayed on the display 41.
  • the in-vehicle device 1011 reads various data necessary for processing, such as the reference traffic information data 112, the travel history data 118, and the travel characteristic data 120 by attribute classification, from the data storage device 42 (step S72).
  • the in-vehicle device 1011 identifies the driver ID of the user profile 121 for the driver selected in step S71.
  • the in-vehicle device 1011 searches the travel history data 118 and extracts a data record corresponding to the driver ID (step S73). For example, when a driver whose driver ID is “1” is selected, a record of data whose driver ID is “1” is stored when the record of the driving history shown in FIG. (First two lines of data) are extracted.
  • the in-vehicle device 1011 analyzes the amount of travel history data extracted in the process of step S73. First, the in-vehicle device 1011 obtains the number of records of the travel history data extracted in the process of step S73. Next, the in-vehicle device 1011 compares the number of records with two threshold values ( ⁇ 1, ⁇ 2), and determines the value of the data amount determination value.
  • the threshold values ⁇ 1 and ⁇ 2 are both positive numbers and have a relationship of ⁇ 1> ⁇ 2. If the number of records is greater than ⁇ 1, it is determined that there is a sufficient amount of travel history data for the driver selected in step S71, and 1 is given as the data amount determination value.
  • step S74 If the number of records is equal to or less than ⁇ 1 and greater than ⁇ 2, it is determined that there is not a sufficient amount of travel history data for the driver selected in step S71, but a minimum amount of travel history data exists. Given. If the number of records is ⁇ 2 or less, it is determined that there is no minimum amount of travel history data for the driver selected in step S71, and 3 is given as the data amount determination value (step S74).
  • classification may be performed for each item included in the record, and determination may be made based on the number of each classification.
  • the number of records extracted in the process of step S73 is the number of “dry” records, the number of “wet” records, and the number of “freeze” records.
  • the number of records of each classification is compared with the above-described threshold value to determine the data amount determination value.
  • the data amount determination values for all road surface conditions may be the same or different data amount determination values. The same applies to the case where the records extracted in step S73 are classified by the value of “outdoor brightness”.
  • the in-vehicle device 1011 proceeds to the processing of step S75 because the travel history data amount is sufficient when 1 or 2 is given as the data amount determination value in the processing of step S74, and 3 is given as the data amount determination value. Sometimes it is determined that the amount of travel history data is not sufficient, and the process is terminated. The same applies when the data amount determination value is given for each value of “road surface condition” or “outdoor brightness”.
  • step S74 when 1 is given as the data quantity determination value, the driving characteristic data generation method 1 for each driver is selected, and when 2 is given as the data quantity determination value, the driving characteristic data generation method 2 by driver is selected. Then, the driving characteristic data generation method for each driver to be executed in step S76 is determined (step S75).
  • the driver-specific travel characteristic data generation method 1 and the driver-specific travel characteristic data generation method 2 will be described in detail later.
  • the in-vehicle device 1011 generates a correction parameter for the corresponding driver according to the driving characteristic data generation method for each driver determined in step S75, and adds it to the attribute characteristic-specific driving characteristic data 120 (step S76).
  • the driving characteristic data generation method 1 for each driver since a sufficient amount of driving history data exists for the driver selected in step S71, the driving characteristics of the driver are sufficiently reflected. That is, the correction parameter Ta is calculated based on Equation 1, where Th is the link travel time in the travel history data of the driver and Tb is the reference travel time of the reference traffic information data.
  • the Ta is an average value of the difference between the driving history data of the driver and the reference traffic information data, and is a value representing the driving characteristics of the driver.
  • the driving characteristic of the driver since the driver selected in step S71 is not sufficient but there is a minimum amount of driving history data, the driving characteristic of the driver should be sufficiently reflected.
  • the driving characteristic data by attribute classification having the closest attribute to the driving characteristic of the driver is selected. Specifically, first, the correction parameter Ta is once calculated for each link using Equation 1 with Th as the link travel time in the travel history data of the driver and Tb as the reference travel time in the reference traffic information data. Operating characteristics. Next, reference is made to the attribute classification-specific traveling characteristic data Ta ′ j for each attribute classification already stored in the attribute classification-specific traveling characteristic data 120.
  • Ta ′ j is a correction parameter for each link generated by the travel characteristic data generation device 10 from, for example, the travel history data of the driver of the age group j.
  • the degree of deviation ⁇ j between the attribute classification j and the driving characteristics of the driver is calculated according to the following expression 3.
  • k is a link that exists in common in Ta and Ta ′ j
  • m is the number of data of all the links that exist in common.
  • the in-vehicle device 1011 obtains the divergence degree for all the age groups j, and among them, the attribute classification of the age group J indicating the minimum value of the divergence degree is regarded as the closest driving characteristic for this driver. Accordingly, in this case, Ta ′ J is the attribute characteristic-specific traveling characteristic data to be selected.
  • the attribute characteristic-specific traveling characteristic data Ta and Ta ′ J are once generated for each link. However, as described in the first embodiment, they are generated for each link.
  • the attribute characteristic-specific travel characteristic data may be aggregated in a predetermined unit such as an area or road type, and the average value thereof may be used as attribute classification-specific travel characteristic data of each aggregation unit.
  • correction parameters driver-specific travel characteristic data obtained in each aggregation unit can be collectively applied to the traffic information of links belonging to the aggregation unit.
  • the in-vehicle device 1011 determines whether all users registered in the driver profile 121 have been processed (step S77). If all the users have not been processed, the process returns to step S71 to perform the process. If the processing for all users has been completed, this processing ends.
  • the in-vehicle device 1011 can calculate the correction parameter representing the driving characteristic of the driver of the automobile 13 as the driving characteristic data for each driver, and updates the driving characteristic data 120 for each attribute classification with the correction parameter. be able to. Also, by referring to the updated attribute classification-specific traveling characteristic data 120, the reference traffic information data 112 can be more appropriately corrected as in the first embodiment, and more appropriately connecting the departure place and the destination. The recommended route can be calculated.
  • driving characteristics data for each attribute classification is generated or selected according to the collection status of the driving history data of the driver, and the driving characteristics of each driver are taken into consideration. It is possible to correct the reference traffic information data in the reference traffic information database 112, thereby obtaining highly accurate corrected traffic information data. And, by the shortest time route search using the corrected traffic information with high accuracy, it becomes possible to perform high-quality route guidance that avoids traffic congestion more reliably.
  • the driving characteristic data generation device, the in-vehicle device, and the in-vehicle information system according to the present invention improve the accuracy of traffic information by correcting the traffic information data in consideration of the driving characteristics of individual drivers.
  • a vehicle navigation system such as a car navigation system installed in an automobile, or a route guidance system including an in-vehicle apparatus and a server.
  • the present invention can be applied.

Landscapes

  • Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Navigation (AREA)

Abstract

La présente invention concerne un dispositif embarqué équipé: d'un moyen de stockage qui assure le stockage de données d'information de circulation et de données cartographiques qui sont utilisées pour une recherche d'itinéraire ; d'un moyen de recherche d'itinéraire qui recherche un itinéraire recommandé depuis un point de départ jusqu'à un point de destination sur la base de données de circulation et de données cartographiques ; d'un moyen de communication de données qui reçoit, à partir d'un dispositif de génération de données de caractéristiques de déplacement, des données de caractéristiques de déplacement de catégorie d'attributs par catégorie d'attributs pour corriger l'information de circulation par rapport à chaque catégorie d'attributs prédéterminée, les données de caractéristiques de déplacement de catégorie d'attributs par catégorie d'attributs étant obtenues par classification de données d'historique de déplacement concernant une pluralité d'autres conducteurs selon des catégories d'attributs basés sur les attributs des conducteurs ; et d'un moyen de correction d'information de circulation qui corrige les données d'information de circulation au moyen des données de caractéristiques de déplacement de catégorie d'attributs par catégorie d'attributs concernant une catégorie d'attributs correspondant au conducteur d'un véhicule, le moyen de recherche d'itinéraire utilisant les données d'information de de circulation corrigées par le moyen de correction d'information de circulation comme données d'information de circulation.
PCT/JP2010/068083 2009-10-14 2010-10-14 Dispositif embarqué, dispositif de génération de données de déplacement, et système d'information embarqué WO2011046185A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
JP2009236781A JP2011085431A (ja) 2009-10-14 2009-10-14 走行特性データ生成装置，車載装置及び車載情報システム
JP2009-236781 2009-10-14

Publications (1)

Publication Number Publication Date
WO2011046185A1 true WO2011046185A1 (fr) 2011-04-21

Family

ID=43876234

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/JP2010/068083 WO2011046185A1 (fr) 2009-10-14 2010-10-14 Dispositif embarqué, dispositif de génération de données de déplacement, et système d'information embarqué

Country Status (2)

Country Link
JP (1) JP2011085431A (fr)
WO (1) WO2011046185A1 (fr)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2013250167A (ja) * 2012-05-31 2013-12-12 Pioneer Electronic Corp 距離計測装置、距離補正方法、距離補正プログラム、および記録媒体
CN112513950A (zh) * 2018-08-27 2021-03-16 日立汽车系统株式会社 更新系统和电子控制装置

Families Citing this family (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
TWI428249B (zh) * 2011-08-23 2014-03-01 Ind Tech Res Inst 車載裝置及其行車輔助系統與行車輔助資訊提供方法
US10160458B2 (en) 2015-06-02 2018-12-25 Mitsubishi Electric Corporation Driving characteristic measurement apparatus
JP6506142B2 (ja) * 2015-09-01 2019-04-24 本田技研工業株式会社 ナビサーバおよびナビシステム
US11313692B2 (en) * 2015-09-01 2022-04-26 Honda Motor Co., Ltd. Navigation server and navigation system
CN113707824A (zh) * 2015-12-25 2021-11-26 株式会社半导体能源研究所 化合物、发光元件、显示装置、电子设备及照明装置
JPWO2017213064A1 (ja) * 2016-06-09 2019-05-16 日本電気株式会社 車両制御システム、車両制御方法およびプログラム
JP7102320B2 (ja) * 2018-11-15 2022-07-19 株式会社日立製作所 データ管理システムおよび方法
FR3096860B1 (fr) * 2019-06-03 2022-04-22 Psa Automobiles Sa Procédé et dispositif de communication d’informations relatives à un ou plusieurs trajets

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2008217121A (ja) * 2007-02-28 2008-09-18 Toyota Motor Corp 情報提供装置
JP2009042051A (ja) * 2007-08-08 2009-02-26 Xanavi Informatics Corp 経路探索方法、経路探索システムおよびナビゲーション装置

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2008217121A (ja) * 2007-02-28 2008-09-18 Toyota Motor Corp 情報提供装置
JP2009042051A (ja) * 2007-08-08 2009-02-26 Xanavi Informatics Corp 経路探索方法、経路探索システムおよびナビゲーション装置

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2013250167A (ja) * 2012-05-31 2013-12-12 Pioneer Electronic Corp 距離計測装置、距離補正方法、距離補正プログラム、および記録媒体
CN112513950A (zh) * 2018-08-27 2021-03-16 日立汽车系统株式会社 更新系统和电子控制装置

Also Published As

Publication number Publication date
JP2011085431A (ja) 2011-04-28

Similar Documents

Publication Publication Date Title
WO2011046185A1 (fr) Dispositif embarqué, dispositif de génération de données de déplacement, et système d'information embarqué
US7590488B2 (en) Route condition evaluation method and apparatus for navigation system
US8694242B2 (en) Traveling information creating device, traveling information creating method and program
JP4773823B2 (ja) 交通状況予測方法およびその装置ならびにプログラム
US9965950B2 (en) Method and apparatus for classifying a traffic jam from probe data
US8296062B2 (en) Method for displaying traffic information and navigation system
US8706408B2 (en) Navigation system and route search method
JP5096396B2 (ja) 交通情報管理サーバー、ナビゲーション端末及び方法
US11022457B2 (en) Method, apparatus, and computer program product for lane-level route guidance
US20090234572A1 (en) Surrounding Search Data Generating System, Surrounding Search System, Surrounding Search Data Generating Method, Surrounding Search Method, and Navigation Apparatus
US7477990B2 (en) Navigation apparatus
US20040039523A1 (en) Navigation system and program for navigation system setup
JP2007178126A (ja) 走行リンク特定システム
JP5892004B2 (ja) 経路探索システム、経路探索装置、経路探索方法及びコンピュータプログラム
US10982969B2 (en) Method, apparatus, and computer program product for lane-level route guidance
US10497256B1 (en) Method, apparatus, and system for automatic evaluation of road closure reports
US11537944B2 (en) Method and system to generate machine learning model for evaluating quality of data
JP2009216400A (ja) ナビゲーション装置、及びナビゲーションプログラム
JP3894017B2 (ja) ナビゲーションシステム、ナビゲーションプログラム及び快速道路情報作成方法
JP2010151477A (ja) ナビゲーションシステム
JP2010026803A (ja) 渋滞予測装置、経路探索装置、渋滞予測方法、経路探索方法、渋滞予測プログラム、経路探索プログラムおよびコンピュータに読み取り可能な記録媒体
JP4761582B2 (ja) 経路探索システム、経路探索サーバおよび経路案内方法
US20090105936A1 (en) Route guidance apparatus, route guidance method, route guidance program and computer-readable recording medium
JP4466362B2 (ja) 交通状況提供システム及び交通状況提供方法
JP2007086087A (ja) 情報表示システム

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 10823453

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 10823453

Country of ref document: EP

Kind code of ref document: A1