Route planning method, navigation method, system, and vehicle used in driving training scene

Abstract

To provide a route planning method, a navigation method, a system, and a vehicle used in a driving training scene.SOLUTION: A route planning method 100 comprises: a road difficulty classification step 102 of classifying and marking roads at different driving execution difficulties on the basis of static and dynamic attributes regarding the roads; and a route planning setting step 104 of setting a planing route for a driving training scene on the basis of driving desired by a user. A navigation method 200 comprises: a navigation service step 202 of providing a route guidance to a user through voice broadcasting and / or moving image displaying on the basis of the route planned by the method 100, and a driving feedback step 204 of providing a feedback to the user after completion of the process.SELECTED DRAWING: Figure 5

Description

Technical Field

[0001] The present invention relates to the technical field of road traffic, and particularly to a route planning method, a navigation method and system, and a vehicle used in a driving practice scene.

Background Art

[0002] As navigation systems and autonomous driving technologies continue to grow, how to plan the optimal route has become an important and mainstream issue. Currently, in route planning for navigation systems or autonomous vehicles, how to use GPS information, map information, and sensing information from in-vehicle sensors to plan the optimal route has become the focus of research.

[0003] In the prior art, as a relatively common route planning method, two or three alternative routes are provided and the user is allowed to select during navigation. Different route plans are usually based on factors such as the total distance of the route, whether to pass through highway sections, the number of toll booths in the route, the number of traffic signals in the route, and the traffic congestion situation in the route.

[0004] The different driving routes provided by conventional navigation systems or vehicles have very limited selectivity and are almost the same for almost all users, so they cannot meet the needs of users for customizing and selecting special routes. Also, after the user selects the corresponding route, the interaction is very limited or almost non-existent. Furthermore, in the navigation systems of the prior art, the user can choose their own preferences, such as highway priority, distance priority, time priority, etc., to perform route planning and navigation, but such choices are still very rough and general. Therefore, people using conventional navigation systems or vehicles equipped with navigation systems cannot realize special route planning and selection for specific scenes (such as driving practice scenes for novice drivers or drivers with little experience) without other information.

[0005] In the prior art, in a known general route planning method, the user has to set a "starting point" and an "ending point" or "waypoints", and the fundamental desire is to "reach" the ending point or waypoints. However, for the special requirements for the route in the driving practice scene of novice drivers or drivers with little experience, that is, not taking "reaching" as the fundamental purpose, not having to set an "ending point", and taking "driving duration", "driving practice difficulty", "driving scene", etc. as fundamental and core requirements, it cannot be satisfied.

Summary of the Invention

Problems to be Solved by the Invention

[0006] In order to solve the above problems existing in the prior art, the present invention provides an intelligent route planning and navigation service for the user to use in the driving practice scene, thereby providing a route planning method, a navigation method, a system, and a vehicle that do not require a prior investigation of road conditions and road areas to find an appropriate navigation route.

Means for Solving the Problems

[0007] According to a first aspect of the present invention, there is provided a route planning method for use in a driving practice scene, including a road difficulty classification step of classifying and marking the road with different levels of driving practice difficulty based on static and dynamic attributes of the road, and a route planning setting step of setting a planned route for the driving practice scene based on the user's desired driving practice.

[0008] According to a second aspect of the present invention, there is provided a navigation method for use in a driving practice scene, including a navigation service step of providing guidance on the planned route to the user by voice broadcast and / or video display using the guiding method of a virtual driving instructor based on the route planned by the above route planning method.

[0009] According to a third aspect of the present invention, there is provided a route planning system for a driving practice scene, including a road difficulty classification unit that classifies and marks the road with different levels of driving practice difficulty based on static and dynamic attributes of the road, and a route planning setting unit that sets a planned route for the driving practice scene based on a user's desired driving practice.

[0010] According to a fourth aspect of the present invention, there is provided a navigation system for a driving practice scene, including a navigation service unit that provides guidance on the planned route to the user by voice broadcast and / or video display using a virtual driving instructor's guidance method based on the route planned by the above route planning system.

[0011] According to a fifth aspect of the present invention, there is provided a vehicle including the above route planning system for a driving practice scene and the above navigation system for a driving practice scene.

Advantages of the Invention

[0012] The route planning method, navigation method, system, and vehicle according to the present invention achieve the following beneficial technical effects.

[0013] 1. It provides intelligent route planning and navigation services for a specific driving practice scene, eliminating the need for manual pre-investigation of road conditions and road areas to find an appropriate navigation route, and saving the time for the user to use for route preparation or selection.

[0014] 2. For the special requirements of users who do not take "reaching the end point" as the core purpose in specific driving practice scenarios, customized route planning and navigation services are provided to focus on solving specific navigation requirements such as driving duration, driving practice difficulty, and driving scenarios.

[0015] 3. For specific driving practice scenarios, based on the static and dynamic attributes of roads from map data, all roads are classified and marked with different levels of driving practice difficulty. Also, by planning routes based on users' desired driving practices, the special needs for route planning and navigation services in the driving practice scenarios of novice drivers and drivers with little experience are met.

[0016] 4. For specific driving practice scenarios, more complete and enjoyable navigation services and driving feedback services are provided through immersive and interactive guides during the driving practice journey, and feedback similar to interactive games after the driving practice journey.

[0017] 5. By flexibly using various classification methods to pre-classify and mark road and lane data, the needs of users for route planning and selection in other specific scenarios or required situations can be met.

Brief Description of the Drawings

[0018]

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Embodiments for Carrying out the Invention

[0019] Hereinafter, in order for those skilled in the art to better understand the technical aspects of the present invention, the technical aspects of the embodiments of the present invention will be clearly and completely described with reference to the drawings. Needless to say, the described embodiments are only some of the embodiments of the present invention, not all of them. Based on the embodiments disclosed in this application, all other embodiments obtained by those skilled in the art without making inventive efforts shall fall within the protection scope of the present invention.

[0020] It should be noted that the terms "including", "having" and any variations thereof in the specification, claims and drawings of the present invention are intended to cover those that are included without exclusivity. For example, a process, system, product or device including a series of steps or units is not necessarily limited to those steps or units clearly listed, and may also include other steps or units not clearly listed or specific to these processes, systems, products or devices.

[0021] In the present invention, unless otherwise specified, the quantifiers "one" and "a" do not exclude the scene where there are multiple elements.

[0022] Also, as a supplementary note here, in the embodiments of the present invention, from the viewpoints of clarity and conciseness, only some parts or components may be shown. However, those skilled in the art should understand that according to the teachings of the present invention, necessary parts or components may be added according to the needs of specific scenarios. Also, unless otherwise specified, the features of different embodiments of the present invention can be combined with each other.

[0023] Moreover, the numbers of the steps of each method of the present invention do not limit the execution order of the steps of the foregoing method. Unless otherwise specified, the steps of each method may be executed in a different order.

[0024] Hereinafter, with reference to the drawings and specific embodiments, the route planning method, navigation method, system, and vehicle used in the driving practice scene provided by the present invention will be described in more detail. Through the following description, the advantages and features of the present invention will become clearer. It should be noted that all the drawings are shown in a very simplified form and do not use any completely accurate dimensional relationships, but are only used for conveniently and clearly explaining the embodiments of the present invention.

[0025] First, refer to FIG. 1, FIGS. 13A to 13F, and FIGS. 15A to 15D. FIG. 1 shows a route planning method 100 used in a driving practice scene according to a first embodiment of the present invention. The route planning method 100 is implemented by the vehicle-side navigation system of the vehicle or by a combination of the vehicle-side navigation system of the vehicle and a cloud-side server connected thereto, and includes the following steps 102 to 104.

[0026] In road difficulty classification step 102, roads are classified and marked with different levels of driving practice difficulty based on static and dynamic attributes of the roads from map data. The classification and marking of roads by driving practice difficulty are used as basic input data for route planning and navigation route calculation. Here, the static and dynamic attributes of the roads include, but are not limited to, at least one of the number of intersections in the road, the complexity of the road topology (e.g., how many roads are connected to one road), the presence or absence of a road median strip (to separate oncoming vehicles and to separate unprotected pedestrians, cyclists or motorbike riders, rickshaws, etc. in the same direction), dynamic traffic information (traffic volume, traffic congestion situation), the speed limit of the road, etc. For specific examples of the static and dynamic attributes of the roads, refer to FIGS. 13A to 13F. As shown in FIGS. 13A to 13F, the static and dynamic attributes of the roads include, but are not limited to, the number of intersections I in the road, the complexity of the road topology C, the presence or absence of a road median strip Z, dynamic traffic information D, the speed limit of the road including the speed limit CL of urban roads or the speed limit HL of highways, etc.

[0027] In route planning setting step 104, a planned route for the driving practice scene is set based on the user's desired driving practice. Here, the user's desired driving practice includes, but is not limited to, at least one of the driving duration, the starting point of the route, the via points, the level of the desired driving practice difficulty and the corresponding percentage, the percentage of the desired driving scene, etc. For an example of the input display of the user's desired driving practice information, refer to FIGS. 15A to 15D. FIG. 15A exemplarily shows the driving duration input by the user. FIG. 15B exemplarily shows the starting point, destination and via points of the route input by the user (in other situations, the user may only input the starting point and via points of the route and set the destination during the journey). FIG. 15C exemplarily shows the level of the desired driving practice difficulty input by the user and the corresponding percentage (for example, the levels of the desired driving practice difficulty are easy E, medium M and hard H, and the corresponding percentages are that easy E accounts for 30%, medium M accounts for 50%, and hard H accounts for 20%). FIG. 15D exemplarily shows the percentage of the desired driving scene input by the user (for example, urban roads account for 70% and highways account for 30%).

[0028] Refer to FIGS. 2 and 14. FIG. 2 shows the first type of road difficulty classification step 102A in the route planning method 100 shown in FIG. 1. The first type of road difficulty classification step 102A includes the following steps 1022 to 1028.

[0029] In the preset difficulty coefficient setting step 1022, a plurality of corresponding preset difficulty coefficients are set for different static or dynamic attributes of the road. For example, the preset difficulty coefficient for a straight road, or a road or lane with very little traffic volume is set to 1, and the preset difficulty coefficient for a narrow road, or a curve with a curvature value greater than the first preset value (for example, 0.004 m^-1), or a road where the number of lanes changes by more than the second preset value (for example, the number of lanes changes from two to one) is set to 3, and the preset difficulty coefficient for a road where one passes unprotected with oncoming vehicles, or a circular intersection with multiple exits, or a road with a large number of electric vehicles / bicycles, or a road without pedestrian protection facilities is set to 5. Of course, those skilled in the art can understand that depending on the specific operation situation, the plurality of preset difficulty coefficients may be made using different setting criteria.

[0030] In the total difficulty score generation step 1024, a total difficulty score for each road section is generated based on a plurality of preset difficulty coefficients. For example, the total difficulty score for a narrow, highly curved, and unprotected passing road is 3 (preset difficulty coefficient for a narrow road) + 3 (preset difficulty coefficient for a curve with a curvature value greater than the first preset value) + 5 (preset difficulty coefficient for an unprotected passing road) = 11.

[0031] In the driving practice difficulty level determination step 1026, the level of the driving practice difficulty for each road section is determined according to the interval in which the total difficulty score of each road section exists. For example, the level of the driving practice difficulty corresponding to the interval 0 - 3 in which the total difficulty score exists is easy E, the level of the driving practice difficulty corresponding to the interval 3 - 9 in which the total difficulty score exists is medium M, and the level of the driving practice difficulty corresponding to the interval >9 in which the total difficulty score exists is hard H. Of course, those skilled in the art can understand that depending on the specific operation situation, the level of the driving practice difficulty may be made using different setting criteria.

[0032] In classification and marking step 1028, each road section is classified and marked according to the level of driving practice difficulty of the road corresponding to each section. For example, on the navigation map, each road section is marked with different colors corresponding to different levels of driving practice difficulty. For a specific example of classifying and marking roads with different levels of driving practice difficulty, refer to FIG. 14. As shown in FIG. 14, different levels of driving practice difficulty include three levels: easy E, medium M, and hard H, and are marked with corresponding different colors on the navigation map. For example, the easy level E is marked in green in the figure, the medium level M is marked in yellow in the figure, and the hard level H is marked in red in the figure.

[0033] FIG. 3 shows a flowchart of the second type of road difficulty classification step 102B in the route planning method 100 shown in FIG. 1. The difference between the second type of road difficulty classification step 102B and the first type of road difficulty classification step 102A is that the second type of road difficulty classification step 102B further includes a user customization step 1030 between the preset difficulty coefficient setting step 1022 and the total difficulty score generation step 1024. In the user customization step 1030, the user can customize one or more of a plurality of preset difficulty coefficients to overwrite the corresponding preset difficulty coefficients set in the preset difficulty coefficient setting step 1022. For example, if user A considers that the scene of "unprotected passing with oncoming vehicles", which is a dynamic attribute of the road, is relatively simple, the preset difficulty coefficient of this dynamic attribute of the road set in the preset difficulty coefficient setting step 1022 can be customized from 5 to 3 to overwrite the preset difficulty coefficient set in the preset difficulty coefficient setting step 1022.

[0034] FIG. 4 shows a flowchart of the route planning setting step 104 in the route planning method 100 shown in FIG. 1. Specifically, the route planning setting step 104 includes the following steps 1042 to 1048.

[0035] In the prior setting step 1042 of the desired driving practice priority, the user pre-sets one or more types of desired driving practice priorities through the vehicle-side navigation system, and stores them in the processor of the vehicle-side navigation system or the cloud-side server connected to the vehicle-side navigation system.

[0036] In the driving practice requirement input step 1044, for the driving practice scenario, the user inputs one or more specific numerical values among one or more types of desired driving practices, and the specific numerical values represent the driving practice requirements for the user's driving practice scenario.

[0037] In the planned route calculation step 1046, based on the priority of one or more types of desired driving practices pre-set by the user and one or more specific numerical values among one or more types of desired driving practices input by the user, the vehicle-side navigation system or the cloud-side server connected thereto calculates the corresponding route and provides the calculation result (in this embodiment, the calculation result is displayed on the display screen of the navigation system, but of course, it can also be replaced or combined with other methods such as voice playback). The calculation result indicates the ratio of the calculated corresponding route meeting the user's driving practice requirements (for example, meeting 100% or 80%) and / or whether each specific numerical value in the driving practice requirements is met (for example, the driving duration is met, the starting point of the route is met, the via point is not met, the desired road difficulty and the corresponding percentage are met, the percentage of the desired driving scenario is not met, etc.).

[0038] In the planned route determination step 1048, based on the calculation result, the user determines whether to accept the calculated corresponding route as the planned route set for the driving practice scene. If the user accepts, the vehicle-side navigation system starts navigation. If the user does not accept, it returns to the driving practice requirement input step 1044, and the user re-enters the specific numerical values after modification for one or more of one or more types of desired driving practices in the driving practice scene. The subsequent steps 1046-1048 are then executed.

[0039] Refer to FIGS. 5, 6 and 16. FIG. 5 shows a navigation method 200 used in a driving practice scene according to a second embodiment of the present invention. The navigation method 200 is implemented by the vehicle-side navigation system of the vehicle, or by a combination of the vehicle-side navigation system of the vehicle and a cloud-side server connected thereto, and includes the following steps 202 to 204.

[0040] In the navigation service step 202, based on the route planned by the route planning method 100, the navigation system provides guidance on the planned route to the user by using the guiding method of the virtual driving instructor through voice broadcast and / or video display. The guiding method of the virtual driving instructor includes, but is not limited to, the following content of voice broadcast and / or video display. For example, 1. Guidance on the front scene or correct driving behavior "Please note that there will be a difficult road ahead. Please get well prepared and challenge it.", "Please note that the number of lanes will change when passing the current traffic signal. Please observe the target lane in advance.", "Please note that you will enter a roundabout 500 meters ahead. When driving in the roundabout, please observe the traffic signal in front of the vehicle carefully.", "200 meters ahead is the entrance and exit of the industrial park. There may be vehicles or pedestrians entering and leaving, so please slow down and observe carefully.", "It is now rush hour in the evening. There are many vehicles and pedestrians at the intersection ahead, so please slow down and avoid them.", "The number of lanes ahead will decrease, so please change lanes in advance.",

[0041] 2. Guide on Encouraging Correct Behavior or Pointing out Incorrect Behavior Regarding the Traveled Scene (Simulating an Instructor) "At the left-turn intersection we just passed, you immediately slowed down and yielded or stopped. Great response!", "At the left-turn intersection we just passed, you didn't look at the vehicle on the right. Please pay attention next time.", "Keep it up! You're already halfway through today's driving practice. Stay focused and keep going like this.", "Today's driving practice time has already reached one hour. If you feel tired, look for the nearest parking lot. Don't drive while overworked.",

[0042] In driving feedback step 204, after the driving route of the route is completed, the vehicle-side navigation system provides various driving feedbacks similar to an interactive game to the user. The driving feedback includes, but is not limited to, congratulations at the end of the practice journey (including seat vibration, sound effects, and ambient lighting effects to create a congratulatory atmosphere), statistics on the total driving distance of the journey, statistics on the total journey time, and subsequent driving practice route advice.

[0043] Figure 6 shows a flowchart of driving feedback step 204. Driving feedback step 204 includes the following steps 2042 to 2046.

[0044] In the achievement calculation step 2042, the achievement score R is calculated from the formula R = (A × X) - (B × Y), and then obtained and displayed. In the formula, A is the total score of the driving practice difficulty of the road, X is the driving distance of correct driving in the driving journey, B is the coefficient of incorrect / dangerous driving (which may be preset by the user or the cloud-side server. For example, the danger coefficient of frequent fine-tuning of steering control is 1, the danger coefficient of driving in a lane for a long time is 1, the danger coefficient of not starting immediately at a green light is 1, the danger coefficient of not immediately reducing speed at a red light is 2, the danger coefficient of not applying the brake immediately resulting in too close a distance to the following vehicle is 2, the danger coefficient of not using the turn signal when steering is 2, the danger coefficient of applying an emergency brake when not observing the traffic flow immediately when passing through an intersection is 3, the danger coefficient of getting scratches is 5, etc.), and Y is the driving distance of incorrect driving in the driving journey.

[0045] In the dangerous behavior analysis step 2044, data on dangerous behaviors in the driving journey (such as videos of dangerous behaviors captured by an in-vehicle camera or vehicle-side data of dangerous behaviors collected by other types of sensors, etc.) are recorded, and the type and severity of dangerous behaviors are analyzed (the analysis criteria may be preset by the user or the cloud-side server), and the analysis results are provided (for example, they may be displayed on the display screen of the vehicle-side navigation system).

[0046] In the driving feedback providing step 2046, based on the achievement score and the analysis results, subsequent driving practice route advice is generated (for example, advising the user to increase or decrease the difficulty coefficient of a specific route section, increase the ratio of the section where dangerous behaviors occur in the subsequent driving practice route, etc.), and the vehicle-side navigation system provides the user with driving feedback including the subsequent driving practice route advice.

[0047] The recorded data on dangerous behaviors may be stored in the cloud-side server and pushed to other users with driving practice requirements for them to refer to.

[0048] FIG. 16 shows a specific example of driving feedback. As shown in FIG. 16, the driving feedback includes the total driving distance of the trip (e.g., 88 km in the figure), the total time of the trip (e.g., 3.3 hours in the figure), and subsequent driving practice route advice (e.g., "The speed control in the intersection scene is not smooth, and neither the acceleration start nor the deceleration braking and stopping are immediate. Therefore, more urban intersection scenes will be planned in the future navigation route! Keep up the good work!" in the figure).

[0049] In one or more embodiments, the route planning method 100 and the navigation method 200 can be combined to obtain a route planning and navigation method for use in a driving practice scene.

[0050] Refer to FIGS. 7, 13A - 13F, and 15A - 15D. FIG. 7 shows a route planning system 300 for use in a driving practice scene according to a third embodiment of the present invention. The route planning system 300 is realized by a vehicle - side navigation system of the vehicle, or by a combination of the vehicle - side navigation system of the vehicle and a cloud - side server connected thereto, and includes the following.

[0051] A road difficulty classification unit 302 classifies and marks all roads with different levels of driving practice difficulty based on static and dynamic attributes of roads from map data. The classification and marking of roads by driving practice difficulty are used as basic input data for intelligent automatic route planning and navigation route calculation. Here, the static and dynamic attributes of roads include, but are not limited to, the number of intersections in the route, the complexity of the road topology (e.g., how many roads are connected to one road), the presence or absence of a road median strip (to separate oncoming vehicles and separate unprotected pedestrians, cyclists or motorbike riders, rickshaws, etc. moving in the same direction), dynamic traffic information (traffic volume, traffic congestion situation), the speed limit of the route, etc. For specific examples of the static and dynamic attributes of roads, refer to FIGS. 13A to 13F. As shown in FIGS. 13A to 13F, the static and dynamic attributes of roads include, but are not limited to, the number of intersections I in the route, the complexity of the road topology C, the presence or absence of a road median strip Z, dynamic traffic information D, the speed limit L of the route (e.g., the speed limit CL of urban roads or the speed limit HL of highways).

[0052] A route planning setting unit 304 sets a planned route for a driving practice scene based on a user's desired driving practice. Here, the user's desired driving practice includes, but is not limited to, the duration of driving, the departure location of the route, the via locations, the level of desired driving practice difficulty and the corresponding percentage, the percentage of the desired driving scene, etc. For an example of the input display of the user's desired driving practice information, refer to FIGS. 15A to 15D. FIG. 15A illustratively shows the duration of driving input by the user. FIG. 15B illustratively shows the departure location, destination, and via locations of the route input by the user (in other situations, the user may only input the departure location and via locations of the route and set the destination during the journey). FIG. 15C illustratively shows the level of desired driving practice difficulty and the corresponding percentage input by the user (for example, the levels of desired driving practice difficulty are easy E, medium M, and hard H, and the corresponding percentages are that easy E accounts for 30%, medium M accounts for 50%, and hard H accounts for 20%). FIG. 15D illustratively shows the percentage of the desired driving scene input by the user (for example, urban roads account for 70% and highways account for 30%).

[0053] Refer to FIGS. 8 and 14. FIG. 8 shows a first type of road difficulty classification unit 302A in the route planning system 300 shown in FIG. 7. The first type of road difficulty classification unit 302A includes the following.

[0054] The preset difficulty coefficient setting unit 3022 sets a plurality of corresponding preset difficulty coefficients for different static or dynamic attributes of the road. For example, the preset difficulty coefficient of a straight road or a road / lane with very little traffic volume is set to 1, and the preset difficulty coefficient of a narrow road or a curve with a curvature value greater than the first preset value (e.g., 0.004 m^-1) or a road / lane where the number of lanes changes by more than the second preset value (e.g., the number of lanes changes from two to one) is set to 3. The preset difficulty coefficient of a road where there is unprotected passing with oncoming vehicles or a circular intersection with multiple exits or a road with a large number of electric vehicles / bicycles or a road without pedestrian protection facilities is set to 5. Of course, those skilled in the art can understand that depending on the specific operating situation, the plurality of preset difficulty coefficients may be made using different setting criteria.

[0055] The total difficulty score generation unit 3024 generates a total difficulty score for each road section based on a plurality of preset difficulty coefficients. For example, the total difficulty score of a narrow, highly curved, and unprotected passing road is 3 (preset difficulty coefficient of a narrow road) + 3 (preset difficulty coefficient of a curve with a curvature value greater than the first preset value) + 5 (preset difficulty coefficient of an unprotected passing road) = 11.

[0056] The driving practice difficulty level determination unit 3026 determines the level of driving practice difficulty for each road section according to the range in which the total difficulty score of each road section exists. For example, the level of driving practice difficulty corresponding to the range 0 - 3 in which the total difficulty score exists is easy E, the level of driving practice difficulty corresponding to the range 3 - 9 in which the total difficulty score exists is medium M, and the level of driving practice difficulty corresponding to the range >9 in which the total difficulty score exists is hard H. Of course, those skilled in the art can understand that depending on the specific operating situation, the level of driving practice difficulty may be made using different setting criteria.

[0057] Classification and marking unit 3028 classifies and marks each road section according to the level of driving practice difficulty of each road section. For example, in a navigation map, each road section is marked with different colors corresponding to different levels of driving practice difficulty. For specific examples of classifying and marking roads with different levels of driving practice difficulty, refer to FIG. 14. As shown in FIG. 14, different levels of driving practice difficulty include three levels: easy E, medium M, and hard H, and are marked with corresponding different colors in the navigation map. For example, the easy level E is marked in green in the figure, the medium level M is marked in yellow in the figure, and the hard level H is marked in red in the figure.

[0058] FIG. 9 shows the second type of road difficulty classification unit 302B in the route planning system 300 shown in FIG. 7. The difference between the second type of road difficulty classification unit 302B and the first type of road difficulty classification unit 302A is that the second type of road difficulty classification unit 302B further includes a user customization unit 3030 that allows the user to customize one or more of a plurality of preset difficulty coefficients to overwrite the corresponding preset difficulty coefficients set by the preset difficulty coefficient setting unit 3022. For example, if user A considers that the dynamic attribute of the road "unprotected passing with oncoming vehicles" is a relatively simple scenario, the user can customize the preset difficulty coefficient of the dynamic attribute of the corresponding road set by the preset difficulty coefficient setting unit 3022 from 5 to 3 and overwrite the preset difficulty coefficient set by the preset difficulty coefficient setting unit 3022.

[0059] Of course, based on different user needs, variations of each of the above embodiments may be implemented. For example, in the road difficulty classification step 102 or the road difficulty classification unit 302 (including 302A and 302B), in addition to the driving practice difficulty, road driving styles (comfortable, sporty, energy-saving, etc.), road environments (three or more lanes, two lanes, one lane, etc.), road landscape compositions (more street trees, more flower installations, etc.), one or more of other special road conditions (requiring more left turns or requiring more right turns) are used to classify and mark all roads.

[0060] FIG. 10 is a block diagram of the configuration of the route planning setting unit 304 in the route planning system 300 shown in FIG. 7. The route planning setting unit 304 includes the following.

[0061] A desired driving practice priority pre-setting unit 3042 that allows a user to pre-set the priority of one or more types of desired driving practices by means of a vehicle-side navigation system and store it in a cloud-side server.

[0062] A driving practice requirement input unit 3044 that allows a user to input one or more specific numerical values of one or more types of desired driving practices for a driving practice scene, and the specific numerical values represent the driving practice requirements for the user's driving practice scene.

[0063] The planned route calculation unit 3046 calculates a corresponding route based on one or more types of priorities of desired driving practices preset by the user and one or more specific numerical values of one or more types of desired driving practices input by the user, and provides a calculation result. (In this embodiment, the calculation result is displayed on the display screen of the navigation system. Of course, it can also be replaced or combined with other methods such as voice playback.) The calculation result indicates the ratio of the calculated corresponding route meeting the user's driving practice requirements (for example, meeting 100% or 80%) and / or whether each specific numerical value in the driving practice requirements is met (for example, the driving duration is met, the starting point of the route is met, the waypoint is not met, the desired driving difficulty and the corresponding percentage are met, the percentage of the desired driving scene is not met, etc.).

[0064] The planned route determination unit 3048 determines whether to let the user accept the calculated corresponding route as the planned route set for the driving practice scene based on the calculation result. When the user accepts, the vehicle-side navigation service unit 306 starts the navigation service. When the user does not accept, the user re-enters the specific numerical values after modifying one or more of one or more types of desired driving practices in the driving practice scene through the driving practice requirement input unit 3044.

[0065] Refer to FIGS. 11, 12, and 16. FIG. 11 shows a navigation system 400 used in a driving practice scene according to the fourth embodiment of the present invention. The navigation system 400 includes a navigation service unit 402 that provides guidance on the planned route to the user by voice broadcast and / or video display using the guidance method of a virtual driving instructor based on the route planned by the route planning system 300. The guidance method of the virtual driving instructor includes, but is not limited to, the following content of voice broadcast and / or video display. For example, 1. Guidance on the upcoming scene or correct driving behavior "Please be aware that there will be a difficult road ahead. Prepare well and challenge it bravely.", "Please note that the number of lanes will change after passing the current traffic signal. Observe the target lane in advance.", "Please be aware that you will enter a roundabout 500 meters ahead. When driving in the roundabout, observe the traffic signal in front of the vehicle carefully.", "200 meters ahead is the entrance and exit of the industrial park. There may be vehicles or pedestrians entering and leaving, so slow down and observe carefully.", "It is currently the evening rush hour, and there are many vehicles and pedestrians at the intersection ahead. Please slow down and avoid them.", "The number of lanes ahead will decrease, so please change lanes in advance.", 2. Guide for rewarding correct behavior or pointing out incorrect behavior regarding the completed scene (simulating an instructor) "At the left-turn intersection you passed just now, you immediately slowed down and yielded or stopped. Great response!", "At the left-turn intersection you passed just now, you didn't look at the vehicle on the right. Please pay attention next time.", "Keep it up! You're already halfway through today's driving practice. Concentrate on driving and keep it up like this.", "Today's driving practice time has already reached one hour. If you feel tired, look for the nearest parking lot. Don't drive when over-fatigued.",

[0066] The driving feedback unit 404 provides various feedbacks similar to an interactive game to the user by the navigation system after the driving journey is completed. The driving feedback includes, but is not limited to, celebration at the end of the practice journey (including seat vibration, sound effects, environmental lighting effects to create a celebratory atmosphere), statistics of the total driving distance of the journey, statistics of the total journey time, and advice on the subsequent driving practice route, etc.

[0067] FIG. 12 shows a configuration block diagram of the driving feedback unit 404. The driving feedback unit 404 includes the following.

[0068] An achievement calculation unit 4042 that calculates the achievement score R from the formula R = (A×X) - (B×Y), obtains it, and displays it. In the formula, A is the total score of the driving practice difficulty of the road, X is the driving distance of correct driving in the driving journey, B is the coefficient of incorrect / dangerous driving (which may be preset by the user or the cloud-side server. For example, the danger coefficient of frequent fine-tuning of steering control is 1, the danger coefficient of driving in a lane for a long time is 1, the danger coefficient of not starting immediately at a green signal is 1, the danger coefficient of not immediately reducing speed at a red signal is 2, the danger coefficient of not applying the brake immediately resulting in the distance to the following vehicle being too close is 2, the danger coefficient of not turning on the blinker when steering is 2, the danger coefficient of applying an emergency brake because the traffic flow was not observed immediately when passing through an intersection is 3, the danger coefficient of scratches occurring is 5, etc.), and Y is the driving distance of incorrect driving in the driving journey.

[0069] A dangerous behavior analysis unit 4044 that records data on dangerous behaviors in the driving journey (such as videos of dangerous behaviors taken by an in-vehicle camera or vehicle-side data on dangerous behaviors collected by other types of sensors), analyzes the type and severity of the dangerous behaviors (the analysis criteria may be preset by the user or the cloud-side server), and provides the analysis results (for example, it may be displayed on the display screen of the vehicle-side navigation system).

[0070] A driving feedback providing unit 4046 that generates subsequent driving practice route advice based on the achievement score and the analysis results (for example, advises the user to increase or decrease the difficulty coefficient of a specific route section, increase the ratio of the section where dangerous behaviors occur in the subsequent driving practice route, etc.), and provides the user with driving feedback including the subsequent driving practice route advice.

[0071] The data of the recorded dangerous behaviors may be stored in the cloud-side server and pushed to other users who require driving practice for reference.

[0072] For specific examples of driving feedback, refer to FIG. 16. As shown in FIG. 16, the driving feedback includes the total travel distance of the journey (e.g., 88 km in the figure), the total travel time of the journey (e.g., 3.3 hours in the figure), and subsequent driving practice route advice (e.g., "The speed control at intersection scenes is not smooth, and neither the acceleration start nor the deceleration brake and stop are immediate. Therefore, more urban intersection scenes will be planned in the future navigation route! Keep up the good work!").

[0073] In one or more embodiments, the route planning system 300 and the navigation system 400 can be combined to obtain a route planning and navigation system for use in driving practice scenes.

[0074] In one or more embodiments, the route planning system 300 and the navigation system 400 may be integrated into the vehicle-side navigation system of the vehicle, or integrated into the vehicle-side navigation system of the vehicle and the connected cloud-side server.

[0075] The present invention also provides a vehicle (not shown) including the above-mentioned route planning system 300 and navigation system 400.

[0076] It can be understood that the above specific embodiments are only exemplary embodiments for explaining the principle of the present invention and do not limit the protection scope of the present invention. Also, it will be apparent to those skilled in the art that various changes, combinations, partial combinations, and replacements may be made based on design requirements and other factors. Any changes, equivalent substitutions, improvements, etc. made without departing from the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Explanation of Reference Signs

[0077] 100 Route Planning Method 102 Road Difficulty Classification Step 102A Road Difficulty Classification Step 102B Road Difficulty Classification Step 104 Route Planning Setting Step 200 Navigation Method 202 Navigation Service Step 204 Driving Feedback Step 300 Route Planning System 302 Road Difficulty Classification Unit 302A Road Difficulty Classification Unit 302B Road Difficulty Classification Unit 304 Route Planning Setting Unit 306 Vehicle-Side Navigation Service Unit 400 Navigation System 402 Navigation Service Unit 404 Driving Feedback Unit 1022 Preset Difficulty Coefficient Setting Step 1024 Total Difficulty Score Generation Step 1026 Difficulty Level Determination Step 1028 Mark Step 1030 User Customization Step 1042 Priority Pre-Setting Step 1044 Driving Practice Requirement Input Step 1046 Planned Route Calculation Step 1048 Planned Route Determination Step 2042 Achievement Score Calculation Step 2044 Hazardous Behavior Analysis Step 2046 Driving Feedback Provision Step 3022 Preset Difficulty Coefficient Setting Unit 3024 Total Difficulty Score Generation Unit 3026 Difficulty Level Determination Unit 3028 Mark Unit 3030 User Customization Unit 3042 Driving Practice Priority Presetting Unit 3044 Driving Practice Requirement Input Unit 3046 Planned Route Calculation Unit 3048 Planned Route Determination Unit 4042 Achievement Calculation Unit 4044 Dangerous Behavior Analysis Unit 4046 Driving Feedback Providing Unit

Claims

1. A route planning method (100) for use in a driving practice scene, comprising: A road difficulty classification step (102) of classifying and marking the road with different levels of driving practice difficulty based on static and dynamic attributes of the road; A route planning setting step (104) of setting a planned route for the driving practice scene based on the user's desired driving practice. The route planning method (100) is characterized by the above.

2. The road difficulty classification step (102) includes: A preset difficulty coefficient setting step (1022) of setting a plurality of corresponding preset difficulty coefficients for different static and dynamic attributes of the road; A total difficulty score generation step (1024) of generating a total difficulty score for each road section based on the plurality of preset difficulty coefficients; A difficulty level determination step (1026) of determining the level of driving practice difficulty of each road section according to the interval where the total difficulty score of each road section exists; A classification and marking step (1028) of classifying and marking each road section according to the level of driving practice difficulty of each road section. The route planning method according to claim 1 is characterized by the above.

3. The road difficulty classification step (102) further includes a user customization step (1030) between the preset difficulty coefficient setting step (1022) and the total difficulty score generation step (1024), in which the user can customize one or more of the plurality of preset difficulty coefficients to overwrite the corresponding preset difficulty coefficients set in the preset difficulty coefficient setting step (1022). The route planning method according to claim 2 is characterized by the above.

4. The route planning setting step (104) includes: A priority presetting step (1042) of the user presetting the priority of one or more types of desired driving practices through the vehicle-side navigation system of the vehicle and storing it in the processor of the vehicle-side navigation system or the cloud-side server connected to the vehicle-side navigation system. For the driving practice scene, the user inputs one or more specific numerical values among the one or more types of desired driving practices, and the specific numerical values represent a driving practice requirement input step (1044) for the user's driving practice requirement for the driving practice scene. Based on the priority of the one or more types of desired driving practices preset by the user and the one or more specific numerical values input for the one or more types of desired driving practices, the processor of the vehicle-side navigation system or the cloud-side server calculates a corresponding route and provides a calculation result. The calculation result is a planned route calculation step (1046) that indicates the ratio of the calculated corresponding route meeting the user's driving practice requirement and / or whether each specific numerical value in the driving practice requirement is satisfied. Based on the calculation result, the user determines whether to accept the calculated corresponding route as the planned route set for the driving practice scene. When the user accepts, the vehicle-side navigation system starts a navigation service. When the user does not accept, it returns to the driving practice requirement input step (1044), and the user re-enters the specific numerical values after modification for one or more of the one or more types of desired driving practices in the driving practice scene. This includes a planned route determination step (1048). The route planning method according to claim 1 is characterized by this.

5. The static and dynamic attributes of the road include, but are not limited to, the number of intersections in the road, the complexity of the road and lane topology, the presence or absence of a median strip, dynamic traffic information, the speed limit of the road, etc. The route planning method according to any one of claims 1 to 4 is characterized by this.

6. The different levels of driving practice difficulty include three levels: easy, medium, and difficult. In the road difficulty classification step (102), on the navigation map displayed by the vehicle-side navigation system of the vehicle, the road is marked with different colors corresponding to the different levels of driving practice difficulty. The route planning method according to any one of claims 1 to 4 is characterized by this.

7. In the road difficulty classification step (102), in addition to the driving practice difficulty, the road is classified and marked based on one or more of the road driving style, road environment, road landscape composition, and other special road conditions. The route planning method according to any one of claims 1 to 4, characterized in that.

8. The desired driving practice includes, but is not limited to, one or more of the driving duration, the departure point of the route, the transit point, the level of the desired driving practice difficulty and the corresponding percentage, the percentage of the desired driving scene, etc. The route planning method according to any one of claims 1 to 4, characterized in that.

9. A navigation method (200) used for a driving practice scene, Based on the route planned by the route planning method (100) according to any one of claims 1 to 8, using the guiding method of a virtual driving instructor, by voice broadcast and / or video display, a navigation service step (202) for providing guidance on the planned route to the user is included. The navigation method (200) is characterized in that.

10. After the navigation service step (202), after the driving journey of the route is completed, the navigation method (200) further includes a driving feedback step (204) for providing various feedbacks similar to an interactive game to the user by the vehicle-side navigation system of the vehicle. The navigation method according to claim 9, characterized in that.

11. The driving feedback step (204) is A step of calculating and obtaining and displaying the achieved result R from the formula R=(A×X)-(B×Y), where A is the total score of the driving practice difficulty of the road, X is the driving distance of correct driving in the driving journey, B is the wrong / dangerous driving coefficient, and Y is the driving distance of wrong driving in the driving journey. An achieved result calculation step (2042); Recording data on dangerous behaviors in the driving journey, analyzing the type and severity of the dangerous behaviors, and providing an analysis result. A dangerous behavior analysis step (2044); Based on the achieved results and the analysis results, generate subsequent driving practice route advice, and provide driving feedback including the subsequent driving practice route advice to the user by the vehicle-side navigation system of the vehicle. This is a driving feedback providing step (2046), and the navigation method according to claim 10 is characterized by including this step.

12. In the driving feedback providing step (2046), the data of the recorded dangerous behaviors is stored in a cloud-side server connected to the vehicle-side navigation system of the vehicle, and pushed to other users with driving practice requirements for them to refer to. The navigation method according to claim 11 is characterized by this.

13. A route planning system (300) used for a driving practice scene, A road difficulty classification unit (302) that classifies and marks the roads with different levels of driving practice difficulty based on static and dynamic attributes of the roads, A route planning setting unit (304) that sets a planned route for the driving practice scene based on the user's desired driving practice. The route planning system (300) is characterized by including this.

14. The road difficulty classification unit (302) A preset difficulty coefficient setting unit (3022) that sets a corresponding plurality of preset difficulty coefficients for different static or dynamic attributes of the road, A total difficulty score generation unit (3024) that generates a total difficulty score for each road section based on the plurality of preset difficulty coefficients, A difficulty level determination unit (3026) that determines the level of driving practice difficulty of each road section according to the interval where the total difficulty score of each road section exists, A classification and marking unit (3028) that classifies and marks each road section at the level of driving practice difficulty of each road section. The route planning system according to claim 13 is characterized by including this.

15. The road difficulty classification unit (302) further includes a user customization unit (3030) that allows the user to customize one or more of the plurality of preset difficulty coefficients to overwrite the corresponding preset difficulty coefficients set by the preset difficulty coefficient setting unit (3022). The route planning system according to claim 14 is characterized by this.

16. The route planning setting unit (304) includes: a desired driving practice priority pre-setting unit (3042) that allows the user to pre-set the priority of one or more types of desired driving practices by means of the vehicle-side navigation system of the vehicle and stores it in a cloud-side server connected to the vehicle-side navigation system; a driving practice requirement input unit (3044) that allows the user to input one or more specific numerical values among the one or more types of desired driving practices for the driving practice scene, where the specific numerical values represent the driving practice requirements of the user for the driving practice scene; a planned route calculation unit (3046) that calculates a corresponding route based on the priority of the one or more types of desired driving practices pre-set by the user and the one or more specific numerical values among the one or more types of desired driving practices input by the user, and provides a calculation result, where the calculation result indicates the ratio of the calculated corresponding route meeting the driving practice requirements of the user and / or whether each of the specific numerical values in the driving practice requirements is met; a planned route determination unit (3048) that allows the user to determine whether to accept the calculated corresponding route as the planned route set for the driving practice scene based on the calculation result, and when the user accepts, the navigation service unit (306) starts the navigation service, and when the user does not accept, the user re-enters the specific numerical values after modifying one or more of the one or more types of desired driving practices for the driving practice scene by means of the driving practice requirement input unit (3044). The route planning system according to claim 13, characterized by comprising the above.

17. The static and dynamic attributes of the road include, but are not limited to, the number of intersections in the road, the complexity of the road and lane topology, the presence or absence of a median strip, dynamic traffic information, the road speed limit, etc. The route planning system according to any one of claims 13 to 16, characterized by this.

18. The different levels of driving practice difficulty include three levels: easy, medium, and difficult. The road difficulty classification unit (302) further marks the roads in different colors corresponding to the different levels of driving practice difficulty on the navigation map displayed by the vehicle-side navigation system of the vehicle. The route planning system according to any one of claims 13 to 16, characterized in that.

19. The road difficulty classification unit (302) further classifies and marks the road based on one or more of the driving style, road environment, road landscape composition, and other special road conditions in addition to the driving practice difficulty. The route planning system according to any one of claims 13 to 16, characterized in that.

20. The desired driving practice includes, but is not limited to, one or more of the driving duration, the departure place of the route, the via place, the level of the desired driving practice difficulty and the corresponding percentage, the percentage of the desired driving scene, etc. The route planning system according to any one of claims 13 to 16, characterized in that.

21. A navigation system (400) used for driving practice scenes, Based on the route planned by the route planning system (300) according to any one of claims 13 to 20, using the guiding method of a virtual driving instructor, a navigation service unit (402) that provides guidance on the planned route to the user by voice broadcast and / or video display is included. The navigation system (400) is characterized in that.

22. After the driving journey of the route is completed, the navigation system (400) further includes a driving feedback unit (404) that provides various feedbacks similar to an interactive game to the user by the vehicle-side navigation system of the vehicle. The navigation system according to claim 21, characterized in that.

23. The driving feedback unit (404) An achievement calculation unit (4042) that calculates an achievement result R from the formula R = (A × X) - (B × Y), obtains it, and displays it, where A is the total score of the driving practice difficulty of the road, X is the driving distance of correct driving in the driving process, B is an incorrect / dangerous driving coefficient, and Y is the driving distance of incorrect driving in the driving process. A dangerous behavior analysis unit (4044) that records data on dangerous behaviors in the driving process, analyzes the types and severities of the dangerous behaviors, and provides an analysis result. A driving feedback providing unit (4046) that generates subsequent driving practice route advice based on the achievement result and the analysis result, and provides driving feedback including the subsequent driving practice route advice to the user. The navigation system according to claim 22, characterized by comprising the above.

24. The driving feedback providing unit (4046) further stores the recorded data on the dangerous behaviors in a cloud-side server connected to the vehicle-side navigation system of the vehicle, and pushes it to other users who have a driving practice requirement for reference. The system according to claim 23, characterized by comprising the above.

25. A vehicle comprising a route planning system (300) used in the driving practice scene according to any one of claims 13 to 20 and a navigation system (400) used in the driving practice scene according to any one of claims 21 to 24.

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