Vehicle route guidance device based on predicted route deviation

Abstract

A vehicle route guidance device includes a processor configured to predict a deviation point when route guidance is performed, and a storage device configured to store data and algorithms executed by the processor. The processor is configured to calculate a deviation possibility score using at least one of a first score based on an overlapping section between a previous route and a subsequent route with respect to the deviation point, a second score based on road grades of the previous and subsequent routes, and a third score based on estimated times of arrival of the previous and subsequent routes when a route deviation occurs during the route guidance.

Description

[0001] Cross-reference to related applications

[0002] This application claims priority and benefit to Korean Patent Application No. 10-2020-0145551, filed on November 3, 2020, the entire contents of which are incorporated herein by reference. Technical Field

[0003] This invention relates to a vehicle route guidance device, and more particularly to a technique for predicting deviations from the route and providing guidance during route guidance. Background Technology

[0004] The description in this section provides only background information in relation to the present invention and may not constitute prior art.

[0005] Generally, devices used to provide route guidance services (e.g., navigation) can receive the vehicle's current driving position from Global Positioning System (GPS) satellites and display the vehicle's location on a map, while simultaneously outputting the map corresponding to the vehicle's driving position on its screen. Thus, the driver can immediately see the vehicle's driving situation and can be easily guided to unfamiliar roads. Recently, drivers can use user devices such as smartphones to download applications for route guidance services and receive these services.

[0006] In devices with this type of navigation service, route deviation may occur during route guidance. This deviation may occur due to confusion from users unfamiliar with driving, due to road characteristics such as busy intersections, or due to the driver randomly choosing a route that is better than the guided line.

[0007] There is a need for technologies that predict deviations and provide guidance when they occur. However, in existing technologies, it is difficult to collect information about deviation points and to perform deviation point analysis because it is impossible to distinguish between intentional deviations and general deviations. Summary of the Invention

[0008] One aspect of the present invention provides a vehicle route guidance device for calculating a deviation probability score to predict deviations and provide warnings about deviations.

[0009] Another aspect of the present invention provides a vehicle route guidance device for adjusting the map matching time period according to the number of deviations and immediately recalculating the route when a deviation occurs to provide route guidance.

[0010] Another aspect of the present invention provides a vehicle route guidance device for identifying deviation types and providing personalized route guidance for each deviation type.

[0011] The technical problems solved by this invention are not limited to those mentioned above, and those skilled in the art will clearly understand any other technical problems not mentioned herein through the following description.

[0012] According to one aspect of the invention, a vehicle route guidance device may include a processor for predicting deviation points during route guidance and a storage device for storing data and algorithms executed by the processor. The processor may calculate a deviation probability score when a deviation from the route occurs during route guidance using one of the following: a score based on the overlapping segments between the original route before and after the deviation relative to the deviation point; a score based on the road class of the routes before and after the deviation; and a score based on the estimated arrival time before and after the deviation.

[0013] In one implementation, the processor can provide a deviation warning when the deviation from the possible score is greater than or equal to a predetermined score.

[0014] In one implementation, when the overlap between the original route before deviation and the route after deviation is long, the processor can determine that the deviation is intentional.

[0015] In one implementation, the processor can subtract the sum of the road grades of the segments of the original route from the sum of the road grades of the segments of the deviated route, and can calculate a score based on road grades by dividing the resulting difference by the sum of the road grades of the segments of the original route.

[0016] In one implementation, the processor can determine that the vehicle deliberately deviated when the sum of the road grades of the segments of the deviated route is less than the sum of the road grades of the segments of the original route.

[0017] In one implementation, the processor can calculate a score based on the estimated arrival time by dividing the value obtained by subtracting the estimated arrival time of the original route from the estimated arrival time of the deviated route by the estimated arrival time of the original route.

[0018] In one implementation, the processor can calculate the deviation probability score by summing the scores based on the overlapping segments between the original route before and after the deviation, the road class of the routes before and after the deviation, and the estimated arrival time before and after the deviation.

[0019] In one implementation, the processor may assign predetermined weights to each of the following: a score based on the overlapping segments between the original route before and after the deviation, a score based on the road class of the routes before and after the deviation, and a score based on the estimated arrival time before and after the deviation.

[0020] According to another aspect of the invention, a vehicle route guidance device may include a processor that predicts deviation points during route guidance and a storage device that stores data and algorithms executed by the processor. When a route deviation occurs during route guidance, the processor may correct the map matching score used for route recalculation based on the number of deviations at the deviation points.

[0021] In one implementation, the processor can calculate the frequency by dividing the number of deviations at the deviation point by the total number of route searches.

[0022] In one implementation, the processor can use the original map score and frequency to lower the map matching score.

[0023] In one implementation, by lowering the map matching score, the processor can immediately recalculate the route when a deviation occurs shortly after the deviation point.

[0024] According to another aspect of the invention, a vehicle route guidance device may include a processor that predicts deviation points during route guidance and a storage device that stores data and algorithms executed by the processor. When a route deviation occurs during route guidance, the processor can classify the deviation for each individual based on the road type before and after the deviation point.

[0025] In one implementation, the processor can assign weights to each deviation scenario for each person and can guide the user along a different route while providing route guidance corresponding to each person's deviation scenario.

[0026] In one implementation, the processor can increase the weight of each deviation scenario for each person as the number of deviations at the deviation point increases.

[0027] Further applicability will become apparent from the description provided herein. It should be understood that the description and specific examples are intended for illustrative purposes only and are not intended to limit the scope of the invention. Attached Figure Description

[0028] To provide a better understanding of the invention, various forms of the invention will now be described by way of example with reference to the accompanying drawings, in which:

[0029] The above and other objects, features and advantages of the present invention will become more apparent from the following specific embodiments, taken in conjunction with the accompanying drawings:

[0030] Figure 1 This is a block diagram illustrating the configuration of a vehicle system that includes a vehicle route guidance device in some forms of the invention;

[0031] Figure 2 and Figure 3This is an illustration of an exemplary screen used in some forms of the invention for calculating possible deviation scores, predicting deviations, and providing route guidance;

[0032] Figure 4 This is an illustration of an exemplary screen used in some forms of the invention to describe an example of adjusting map matching time periods based on the number of deviations and an example of identifying deviation types and providing personalized route guidance for each deviation type;

[0033] Figure 5 This is a flowchart illustrating a vehicle route guidance method in some forms of the present invention;

[0034] Figure 6 This is a flowchart illustrating a vehicle route guidance method in some forms of the present invention; and

[0035] Figure 7 This is a flowchart illustrating a vehicle route guidance method in some forms of the present invention.

[0036] The illustrations described herein are for illustrative purposes only and are not intended to limit the scope of the invention in any way. Detailed Implementation

[0037] The following description is exemplary in nature only and is not intended to limit the invention, application, or use. It should be understood that throughout the drawings, corresponding reference numerals indicate similar or corresponding parts and features.

[0038] In the following, some embodiments of the invention will be described in detail with reference to exemplary illustrations. When adding reference numerals to components in each illustration, it should be noted that identical or equivalent components are designated by the same numerals even if shown in other illustrations. Furthermore, in describing embodiments of the invention, detailed descriptions of known features or functions will be omitted to avoid unnecessarily obscuring the essential points of the invention.

[0039] In describing components according to embodiments of the present invention, terms such as first, second, "A", "B", (a), (b), etc., may be used. These terms are intended only to distinguish one component from another, and they do not limit the nature, order, or sequence of the constituent components. Unless otherwise defined, all terms used herein (including technical or scientific terms) shall have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. Such terms, as defined in commonly used dictionaries, shall be interpreted as having a meaning equivalent to that in the context of the relevant technical field and shall not be interpreted as having an idealized or overly formal meaning unless expressly defined in this application as having such a meaning.

[0040] In the following text, reference will be made to Figures 1 to 7The embodiments of the present invention will be described in detail.

[0041] Figure 1 This is a block diagram illustrating the configuration of a vehicle including a vehicle route guidance device according to an embodiment of the present invention.

[0042] refer to Figure 1 The vehicle system according to an embodiment of the present invention may include a vehicle route guidance device 100, a sensing device 200, and a global positioning system (GPS) receiver 300.

[0043] The vehicle route guidance device 100 according to an embodiment of the present invention can be implemented in a vehicle. In this case, the vehicle route guidance device 100 can be integrated with the control unit in the vehicle, or it can be implemented as a separate device connected to the control unit of the vehicle via a separate connection device.

[0044] The vehicle route guidance device 100 can identify and store deviation points during route guidance. It can calculate a deviation probability score using at least one of the following: a score based on the overlap between the original route before and after the deviation; a score based on the road class of the routes before and after the deviation; and a score based on the estimated arrival time before and after the deviation. It can provide a deviation warning when the deviation probability score is greater than or equal to a threshold. In this case, the threshold can be preset using stored experimental values.

[0045] The vehicle route guidance device 100 can identify and store deviation points in the route, correct the map matching score based on the number of deviations at the deviation points, and perform a quick route recalculation when a deviation occurs later at the deviation point, because the map matching interval is shortened due to the downward correction of the map matching score.

[0046] The vehicle route guidance device 100 can identify and store deviation points in the route. When a deviation occurs at a deviation point, it can classify the deviation situation for each person according to the road type before and after the deviation, and can assign weights based on the number of deviations for each deviation situation for each person, so as to guide the user along the route with fewer deviations.

[0047] Therefore, the vehicle route guidance device 100 may include a communication device 110, a storage device 120, an interface 130, and a processor 140.

[0048] The communication device 110 can be a hardware device implemented through various electronic circuits to send and receive signals via a wireless or wired connection. This wireless or wired connection can utilize in-vehicle network communication technologies to transmit and receive information. As examples, in-vehicle network communication technologies may include Controller Area Network (CAN) communication, Local Internet (LIN) communication, flex-ray communication, etc.

[0049] Furthermore, the communication device 100 can communicate with servers, infrastructure, other vehicles, etc., outside the vehicle via wireless internet technology or short-range communication technology. Wireless internet technology can include wireless local area network (WLAN), Wi-Fi, Wi-Fi, WiMAX, etc. Short-range communication technology can include Bluetooth, ZigBee, ultra-wideband (UWB), RFID, IrDA, etc.

[0050] As an example, the communication device 110 can perform vehicle-to-vehicle communication using the sensing device 200, GPS receiver 300, etc. Furthermore, the communication device 110 can receive traffic information from traffic centers or other external locations outside the vehicle, and can also receive traffic information from vehicles or infrastructure surrounding the vehicle.

[0051] The storage device 120 can store the sensing results of the sensing device 200 and the data, algorithms, etc. necessary for the operation of the processor 140.

[0052] As an example, storage device 120 can store map information for vehicle route guidance. The map information may include general map information or high-precision map information including lane information.

[0053] In addition, the storage device 120 may include at least one type of storage medium such as flash memory, hard disk memory, micro memory, card memory (e.g., security digital (SD) card or extreme digital (XD) card), random access memory (RAM), static RAM (SRAM), read-only memory (ROM), programmable ROM (PROM), electrically erasable PROM (EEPROM), magnetic RAM (MRAM), magnetic disk and optical disk.

[0054] Interface 130 may include an input device for receiving control commands from a user and an output device for outputting the operating status, operating results, etc., of the vehicle route guidance device 100. Interface 130 may be implemented independently as a head-up display (HUD), cluster, audio-video navigation (AVN), human-machine interface (HMI), user settings menu (USM), etc.

[0055] The input device may include buttons, as well as a mouse, joystick, jogshuttle, stylus, etc. Additionally, the input device may include soft keys implemented on the display.

[0056] The output device may include a display, and may also include a voice output device such as a speaker. In this case, when a touch sensor such as a touch film, touch pad, or touch panel is incorporated into the display, the display operates as a touchscreen, and can be implemented with the input and output devices integrated together. As an example, the output device may output information about vehicle routes to the destination and lane departure warning lights.

[0057] In this case, the display may include at least one of liquid crystal display (LCD), thin film transistor-LCD (TFT-LCD), organic light-emitting diode (OLED) display, flexible display, field emission display (FED), and three-dimensional (3D) display.

[0058] The processor 140 can be electrically connected to the communication device 110, the storage device 120, the interface 130, etc., and can electrically control the various components. The processor 140 can be a circuit that executes software instructions and can perform various data processing and calculations described below.

[0059] The processor 140 can process signals transmitted between the various components of the vehicle route guidance device 100. The processor 140 can be, for example, an electronic control unit (ECU), a microcontroller unit (MCU), or another sub-controller loaded into the vehicle.

[0060] The processor 140 can store the deviation point in the storage device 120 when a deviation occurs during route guidance, and can calculate the deviation probability score using at least one of the following: the score of the overlapping section between the original route before the deviation and the route after the deviation; the score of the road class of the routes before and after the deviation; and the score of the estimated arrival time before and after the deviation.

[0061] Furthermore, the processor 140 can provide a deviation warning when the deviation score is greater than or equal to a predetermined threshold. In this case, the threshold can be preset experimentally.

[0062] When the overlap between the original route before deviation and the route after deviation is relatively long, the processor 140 can determine that the deviation is intentional. When the overlap between the original route before deviation and the route after deviation is relatively short, the processor 140 can determine that the vehicle has mistakenly deviated from the original route. Therefore, the processor 140 can provide a deviation warning when the vehicle arrives at the deviation point later to prevent the vehicle from mistakenly deviating from the original route.

[0063] The processor 140 can calculate the score A based on the number of overlapping segments between the original route and the deviated route, as shown in Equation 1 below.

[0064] [Formula 1]

[0065] A = 100 - (Number of overlapping road segments / Total number of road segments * 100)

[0066] In this situation, when the overlap between the original route before deviation and the deviated route after deviation is long, that is, when the score A based on the number of overlapping road segments is high, the processor 140 can determine that the probability of intentional deviation is high. Furthermore, when the overlap is short, the processor can determine that the deviation is an unintentional deviation caused by reasons such as driving inexperience.

[0067] The processor 140 can subtract the sum of the road grades of the segments of the original route from the sum of the road grades of the segments of the deviated route, and can calculate a score based on road grades by dividing the resulting difference by the sum of the road grades of the segments of the original route. Furthermore, when the road grades of the segments of the deviated route are less than the sum of the road grades of the segments of the original route, the processor 140 can determine that the vehicle intentionally deviated from the route.

[0068] The processor 140 can calculate the score B based on the road class (road type) used before the merging point immediately following the deviation point, as shown in Equation 2.

[0069] [Equation 2]

[0070] B = (Sum of road grades of all deviated sections - Sum of road grades of all sections of the original route (central route)) * 100 / Sum of road grades of all sections of the original route

[0071] exist Figure 2 In this process, processor 140 can calculate score B based on road type, using the sum of the road grades of the deviation route from deviation point D1 to rendezvous point M1 and the original route 201 immediately preceding deviation point D1. For example, the grades can be determined in the following order: expressway, urban expressway, national highway, state-run provincial highway, provincial highway, arterial road 1, arterial road 2, arterial road 3, other road 1, other road 2, backside road, ferry route, etc. Expressways can be set as the highest grade.

[0072] In this scenario, the processor 140 can use the difference in road class to digitize whether a vehicle is intentionally deviating from its route. That is, when using a lower road class, the vehicle route guidance device 100 can determine that the probability of a vehicle intentionally deviating from its route is higher.

[0073] The processor 140 can calculate the score C based on the estimated time of arrival (ETA) as shown in Equation 3 below.

[0074] [Formula 3]

[0075] C = (ETA after deviation - Original ETA) * 100 / ETA before deviation

[0076] The processor 140 can calculate the score based on the ETA by dividing the value obtained by subtracting the ETA of the route before the deviation from the ETA of the route after the deviation by the ETA of the route before the deviation.

[0077] When the ETA after deviation increases, that is, when the score C based on the ETA increases, the processor 140 can determine that the probability of the vehicle deviating from the route due to driver error is high. Therefore, the vehicle route guidance device 100 can calculate the deviation probability score by adding up the score A based on the number of overlapping road segments, the score B based on the road grade, and the score C based on the ETA.

[0078] Furthermore, the processor 140 can assign weights to each of the following: a score A based on the number of overlapping road segments, a score B based on road grade, and a score C based on ETA. These weights can be multiplied by each score to calculate possible deviations from the target score. In this case, the weights can be preset using experimental values ​​or through user selection.

[0079] Thus, the processor 140 can assign predetermined weights to each of the following: a score based on the overlapping segments between the original route before and after the deviation, a score based on the road class of the routes before and after the deviation, and a score based on the estimated arrival time before and after the deviation.

[0080] The processor 140 can calculate the deviation score by adding together the score of the overlapping segments between the original route before and after the deviation, the score of the road class of the routes before and after the deviation, and the score of the estimated arrival time before and after the deviation.

[0081] Figure 2 and Figure 3 This illustration shows an exemplary screen for calculating possible deviation scores, predicting deviations, and providing route guidance according to an embodiment of the present invention.

[0082] like Figure 2 As shown, when there is an original route and a deviated route, for example, when the number of overlapping road segments between the original route and the deviated route is 325 and the total number of road segments is 387, the fraction A based on the number of overlapping road segments is 100-(325 / 387)*100, which is 16.02.

[0083] Furthermore, when the sum of the road grades of the deviated sections is 1564 and the sum of the road grades of the sections of the original route (central route) is 1342, the road grade score B is (1564-1342)*100 / 1342, which is 16.54.

[0084] When the deviation from the original ETA is 42 minutes and the original ETA is 35 minutes, the score C of the ETA is (42 minutes after deviation - 35 minutes initially) * 100 / 35, which is 20.

[0085] Therefore, when the weight of score A based on overlapping road segments is set to 0.3, the weight of score B based on road grade is set to 0.2, and the weight of score C based on ETA is set to 0.5, the possible deviation score is {(16.02)*0.3}+{(16.54)*0.2}+{20*0.5}, which is 4.81+3.31+10, and finally 18.12.

[0086] refer to Figure 3 Since the score is calculated based on the number of overlapping road segments from deviation point D2 to rendezvous point M2 as 100 - (number of overlapping road segments / number of search road segments before deviation) * 100, for example 100 - (199 / 208) * 100, the deviation probability score is 4.33.

[0087] Since the score for road class is calculated as (sum of road classes of the deviated route - sum of road classes of the center route (original route)) * 100 / sum of road classes of the center route, for example (901-995) * 100 / 995, the possible deviation score is -9.45.

[0088] For example, the score based on the difference in ETA is (29 minutes after deviation - 32 minutes initially) * 100 / 32, which is -9.38.

[0089] Therefore, the weight used to prevent deviation is {(4.33)*0.3}+{(﹣9.45)*0.2}+{﹣9.38*0.5}=1.30-1.89-4.69=﹣5.28=0. In this case, since the weight cannot be negative, when the weight is negative, it can be replaced with "0".

[0090] The processor 140 can predict deviation points during route guidance and can correct the map matching score based on the number of deviations at the deviation points, as shown in Equation 4 below.

[0091] [Formula 4]

[0092] i) Frequency = (Number of deviations / Total number of searches using the corresponding interval) * 100

[0093] ii) Correction = Original map matching score * {(100 - frequency) / 100}

[0094] Processor 140 can calculate the frequency by dividing the number of deviations at the deviation point by the total number of route searches. Processor 140 can use the original map matching score and frequency to lower the map matching score. Therefore, by lowering the map matching score, processor 140 can immediately recalculate the route when a deviation occurs later at the deviation point.

[0095] Map matching is a method for obtaining the current position of a vehicle in an applied navigation mode. This method can obtain the current position by comparing the current position calculated from sensor data with map data, and correct the current position of the vehicle indicated on the map in the area included in the detailed map.

[0096] The lower the map matching score, the shorter the time it takes to obtain the current position while comparing it with the map data, which is calculated from sensor data. Therefore, the vehicle route guidance device 100 can reduce the map matching score when the vehicle passes through points with the highest deviation frequency, and can immediately perform deviation search when deviation occurs, so as to respond quickly to route deviation.

[0097] Figure 4 This is an illustration of an exemplary screen showing an example of adjusting map matching time periods based on the number of deviations according to an embodiment of the present invention, and an example of identifying deviation types and providing personalized route guidance for each deviation type.

[0098] like Figure 4 As shown, for example, when the number of deviations at deviation point D3 is 118 within 6 months, since the frequency is (number of deviations / total number of searches using the corresponding road segment) * 100, (118 / 2569) * 100 = 4.59.

[0099] Therefore, since the map matching score is the original map matching score (e.g., 59) * {(100 - frequency) / 100}, i.e., 59 * (0.95) = 56.2919, the map matching score is lower than the existing map matching score.

[0100] When a deviation occurs at the deviation point, the processor 140 can classify the deviation situation for each person based on the road type before and after the deviation.

[0101] The deviations are shown in Table 1 below.

[0102] [Table 1]

[0103]

[0104] Based on route guidance corresponding to each person's deviation scenarios, processor 140 can assign weights to each deviation scenario for each person to guide the user along another route. In other words, in the case of highway-general road-highway (i.e., scenario 1), and when the number of deviations is higher than 10, processor 140 can generate a driving route consisting of highways and guide the user along that driving route.

[0105] Furthermore, as the number of deviations at the deviation point increases, the processor 140 can increase the weight of each deviation scenario for each person.

[0106] Figure 1 The sensing device 200 may include one or more sensors, each sensor measuring obstacles around the vehicle, distance to the obstacles, and / or relative speed of the obstacles.

[0107] The sensing device 200 may have multiple sensors to sense objects outside the vehicle and obtain information about the object's position, speed, direction of movement, and / or type (e.g., vehicle, pedestrian, bicycle, motorcycle, etc.). For this purpose, the sensing device 200 may include ultrasonic sensors, radar, cameras, laser scanners and / or angular radar, light detection and ranging (LiDAR), acceleration sensors, yaw rate sensors, torque sensors and / or wheel speed sensors, steering angle sensors, etc.

[0108] Figure 1 The GPS receiver 300 can receive GPS signals and provide the received GPS signals to the vehicle route guidance device 100. Therefore, the vehicle route guidance device 100 can identify the vehicle's location.

[0109] Figure 5 This is a flowchart illustrating a vehicle route guidance method according to an embodiment of the present invention. (Reference) Figure 5 In S101, the vehicle route guidance device 100 can generate a route to the destination to begin route guidance.

[0110] In S102, when the vehicle deviates from the guided route while driving, the vehicle route guidance device 100 can store the deviation point.

[0111] In S103, the vehicle route guidance device 100 can calculate the deviation probability score for each deviation point. In this case, the deviation probability score for each deviation point may include a comparison score of each segment attribute (for each segment type) before / after the deviation, a comparison score of the segment ETA before / after the deviation, a score of the number of overlapping segments before / after the deviation, etc.

[0112] In S104, the vehicle route guidance device 100 can determine whether the deviation probability score is greater than or equal to a predetermined reference value, in order to determine whether to provide deviation guidance. When the deviation probability score is greater than or equal to the predetermined reference value, in S105, the vehicle route guidance device 100 can provide deviation warning guidance.

[0113] Therefore, embodiments of the present invention can predict the possibility of deviation to provide a warning, thereby preventing the vehicle from deviating unintentionally and increasing system reliability.

[0114] In the following text, reference will be made to Figure 6 A vehicle route guidance method according to another embodiment of the present invention will be described in detail. Figure 6 This is a flowchart illustrating a vehicle route guidance method according to another embodiment of the present invention. Figure 6 The document discloses an example of adjusting the map matching time period based on the amount of deviation at the deviation point and immediately recalculating the route when a deviation occurs to provide route guidance.

[0115] In the following text, it is assumed that... Figure 1 The vehicle route guidance device 100 performs Figure 6 The process. Furthermore, in describing... Figure 6 At that time, the operation described as being performed by the device can be understood as being controlled by the processor 140 of the vehicle route guidance device 100.

[0116] refer to Figure 6 In S201, the device can generate a route to the destination to begin route guidance.

[0117] In S202, the device can store the deviation point when the vehicle deviates from the guided route while driving.

[0118] In S203, the device can store the number of deviations (deviation frequency). For example, whenever the vehicle deviates from the same deviation point, the device can increment the deviation count by "1" to store the increased number of deviations.

[0119] In S204, the device can adjust the map matching score based on the number of deviations. In this case, as the number of deviations increases, the device can determine that the probability of a deviation is higher.

[0120] In other words, in S205, the device can reduce the map matching score as the number of deviations increases, so as to immediately identify the deviation and recalculate the route when a deviation occurs.

[0121] In S205, the device can detect the deviation point and determine whether the vehicle has deviated from the deviation point based on the number of deviations.

[0122] Thus, the apparatus according to another embodiment of the present invention can adjust the map matching score according to the number of deviations, and can quickly detect deviations when the vehicle deviates later to perform a fast route recalculation.

[0123] In the following text, reference will be made to Figure 7 A detailed description of a vehicle route guidance method according to another embodiment of the present invention is given. Figure 7 This is a flowchart illustrating a vehicle route guidance method according to another embodiment of the present invention. Figure 7 The document discloses examples of identifying deviation types at deviation points and providing personalized route guidance for each deviation type.

[0124] In the following text, it is assumed that... Figure 1 The vehicle route guidance device 100 performs Figure 7 The process. Furthermore, in describing... Figure 7 At that time, the operation described as being performed by the device can be understood as being controlled by the processor 140 of the vehicle route guidance device 100.

[0125] refer to Figure 7 In S301, the device can generate a route to the destination to begin route guidance.

[0126] In S302, when a vehicle deviates from the guided route while driving, the device can store the deviation point for each route.

[0127] In S303, the device can define deviation scenarios.

[0128] In S304, the device can classify the situations in which the vehicle frequently deviates from its course for each individual. In S305, the device can assign route weights and guide the user along a different route when providing route guidance for each individual's situation.

[0129] When the route is scenario 1 (highway-general road-highway), vehicle A frequently uses the deviation route that only uses the highway. Therefore, the device can increase the weight of the corresponding scenario once when the deviation occurs for the first time, and can guide the user without following scenario 1 (highway-general road-highway) when the route is similar.

[0130] In addition, the device can manipulate weights to prevent situation 1 when currently searching the central route, and the device can increase the weight for the vehicle's user whenever the vehicle deviates.

[0131] Therefore, the current weight at the deviation point is the original weight plus (number of deviations). If the original weight is 300, then 300 + 10 (times) = 310.

[0132] Here, because excessive weighting could lead to abnormal routes, the device will not assign more than twice the original weight. Furthermore, if the user wishes, the device can initialize weights for each individual and each scenario.

[0133] Thus, the apparatus according to another embodiment of the invention can define each deviation scenario, classify the corresponding deviation scenarios for each person, and assign weights to the corresponding scenarios when searching for later routes to guide the user along another route.

[0134] Therefore, embodiments of the present invention can improve route guidance quality by collecting and analyzing deviation points, perform rapid route recalculation by identifying frequently deviating sections in advance, and generate customized routes through route planning by taking into account individual deviation scenarios.

[0135] Therefore, the method operations or algorithms described in conjunction with the embodiments disclosed herein can be directly implemented in hardware or software modules or combinations thereof executed by a processor. Software modules may reside in storage media (i.e., memory and / or storage devices), such as RAM, flash memory, ROM, EPROM, EEPROM, registers, hard disks, removable disks, and CD-ROMs.

[0136] An exemplary storage medium can be coupled to a processor, and the processor can read information from the storage medium and record information on the storage medium. Alternatively, the storage medium can be integrated with the processor. The processor and storage medium can reside in an integrated circuit (ASIC). The ASIC can reside within the user terminal. In another scenario, the processor and storage medium can reside as separate components in the user terminal.

[0137] This technology can improve route guidance quality by collecting and analyzing deviation points, perform rapid route recalculation by identifying frequently deviating sections in advance, and generate customized routes through route planning by taking into account individual deviation scenarios.

[0138] In addition, various effects can be provided directly or indirectly through the present invention.

[0139] In the foregoing, although the invention has been described with reference to exemplary embodiments and accompanying drawings, the invention is not limited thereto, and various modifications and alterations can be made to the invention by those skilled in the art without departing from the spirit and scope of the invention as claimed in the following claims.

[0140] Therefore, exemplary embodiments of the present invention are provided to explain the spirit and scope of the invention, and not to limit it, so that the spirit and scope of the invention are not limited by the embodiments. The scope of the invention should be interpreted based on the accompanying drawings, and all technical concepts equivalent to the scope of the claims should be included within the scope of the invention.

Claims

1. A vehicle route guidance device, comprising: A storage device configured to store deviation points when a vehicle deviates from a guide route while driving; and The processor is configured to calculate the possible deviation score for each deviation point; The processor is configured as follows: The deviation probability score is calculated using a first score based on the overlapping segments between the original route before and after the deviation, a second score based on the road class of the routes before and after the deviation, and a third score based on the estimated arrival time before and after the deviation; and A deviation alert is provided when the deviation score is greater than or equal to the predetermined score. The processor is configured as follows: The deviation score is calculated by adding the first score, the second score, and the third score.

2. The vehicle route guidance device according to claim 1, wherein The processor is configured as follows: When the overlapping section after deviation is longer than the predetermined section, the deviation is determined to be intentional.

3. The vehicle route guidance device according to claim 1, wherein The processor is configured as follows: Subtract the sum of the road grades of the segments before the deviation from the sum of the road grades of the segments after the deviation; and Divide the difference by the sum of the road grades of the segments of the original route, and calculate the resulting value as a score based on the road grade.

4. The vehicle route guidance device according to claim 1, wherein The processor is configured as follows: When the sum of the road grades of all segments of the deviated route is less than the sum of the road grades of all segments of the original route, it is determined that the vehicle deliberately deviated.

5. The vehicle route guidance device according to claim 1, wherein, The processor is configured as follows: The score based on the estimated arrival time is calculated by dividing the estimated arrival time of the original route by the estimated arrival time of the original route.

6. The vehicle route guidance device according to claim 1, wherein, The processor is configured as follows: Predetermined weights are assigned to each of the first score, the second score, and the third score.

7. The vehicle route guidance device according to claim 1, in, The processor is also configured to: When a route deviation occurs during route guidance, the map matching score used for route recalculation is corrected based on the number of deviations at the deviation points.

8. The vehicle route guidance device according to claim 7, wherein, The processor is configured as follows: The frequency is calculated by dividing the number of deviations at the deviation point by the total number of route searches.

9. The vehicle route guidance device according to claim 8, wherein, The processor is configured as follows: The map matching score is lowered using the original map matching score and the frequency.

10. The vehicle route guidance device according to claim 9, wherein, The processor is configured as follows: By lowering the map matching score, the route is recalculated immediately when a deviation occurs shortly after the deviation point.

11. The vehicle route guidance device according to claim 1, in, The processor is also configured to: When a route deviation occurs during route guidance, the deviation situation for each person is classified according to the type of road before and after the deviation point.

12. The vehicle route guidance device according to claim 11, wherein, The processor is configured as follows: Assign a weight to each deviation scenario for each person, and guide the user along a different route when providing route guidance corresponding to each person's deviation scenario.

13. The vehicle route guidance device according to claim 12, wherein, The processor is configured as follows: As the number of deviations at the deviation point increases, the weight of each deviation scenario for each person is increased.

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