Memory driving method and intelligent navigation and control system

Abstract

A memory driving method and an intelligent navigation and control system, relating to the technical field of intelligent driving. The method comprises: when entering a route learning mode, an intelligent driving controller constructs a memory driving map on the basis of road information (S201); when the route learning mode is ended, the intelligent driving controller stores the memory driving map, and on the basis of the road information of road segments in the memory driving map, generates mapping quality grades of the road segments (S202); the intelligent driving controller synchronizes route identifiers of the memory driving map and the mapping quality grades to a navigation system (S203); when entering a memory driving mode, the navigation system plays back a target memory driving map corresponding to a target route identifier, and displays the mapping quality grades of the road segments in real time (S204); and when the memory driving mode is ended, the intelligent driving controller updates the road information and the mapping quality grade of a traveled road segment, and synchronizes the route identifier and the mapping quality grade to the navigation system (S205). By using the memory driving method and the intelligent navigation and control system, the information transparency during human-machine co-driving can be improved, and the mapping quality is improved.

Description

Method for memorizing driving and intelligent navigation and control system TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent driving, in particular to a method for memorizing driving and an intelligent navigation and control system. BACKGROUND

[0002] At present, with the development of vehicle technology, intelligent services of vehicles are becoming more and more important, and memorizing driving is a crucial part of intelligent services. The map constructed by memorizing driving route learning is overall recognized by vehicle sensors on the entire environmental information, and the recognition process is actually a process of instant positioning, mapping and storing.

[0003] Memorizing driving is strongly dependent on the route learning map construction process. When the route learning mapping accuracy is not enough, the driver cannot effectively reposition the learned route and control the vehicle when using the memorizing driving function. For a fixed memorizing driving route, subsequent route learning needs to be repeated to continuously optimize the poor mapping quality of the road section, so as to obtain a better driving experience. The more times, the better the experience, which means that the driver will have a poor experience at the early stage of a memorizing driving route. SUMMARY

[0004] Therefore, a method for memorizing driving and an intelligent navigation and control system are provided.

[0005] In a first aspect, a method for memorizing driving is provided, which is applied to an intelligent navigation and control system, the system comprising a smart driving controller, a vehicle sensor and a navigation system, and the method comprising:

[0006] After entering a route learning mode, the smart driving controller constructs a memorizing driving map according to road information collected by the vehicle sensor;

[0007] After ending the route learning mode, the smart driving controller stores the memorizing driving map, and generates a mapping quality level corresponding to each road section according to road information of each road section in the memorizing driving map;

[0008] The smart driving controller synchronizes the route identifier corresponding to the memorizing driving map and the mapping quality level of each road section to the navigation system;

[0009] After entering a memorizing driving mode, the navigation system plays back a target memorizing driving map corresponding to a target route identifier according to a target route identifier selected by a user, and displays the mapping quality level of each road section in the target memorizing driving map in real time;

[0010] After the memory driving mode is ended, the intelligent driving controller updates road information of a traveled road segment in the target memory driving map and a mapping quality level of the traveled road segment, and synchronizes a route identifier corresponding to the target memory driving map and the mapping quality level of the traveled road segment to the navigation system.

[0011] As an optional implementation, the generating of the mapping quality level corresponding to each road segment according to road information of each road segment in the memory driving map comprises:

[0012] For each road segment in the memory driving map, if each type of feature point is contained in the road information of the road segment, the mapping quality level of the road segment is a good quality level;

[0013] If each key type of feature point is contained in the road information of the road segment, but part of the ordinary type of feature point is missing, the mapping quality level of the road segment is a general quality level;

[0014] If part of the key type of feature point is missing in the road information of the road segment, the mapping quality level of the road segment is a poor quality level.

[0015] As an optional implementation, the key type of feature point comprises road grade, intersection type, lane line type, lane guide arrow, speed limit sign, zebra crossing and traffic light.

[0016] As an optional implementation, the method further comprises:

[0017] After entering the route learning mode, the intelligent driving controller sends a route start drawing request to the navigation system;

[0018] The navigation system draws a traveled route trajectory in real time, and shows the route trajectory to a user.

[0019] As an optional implementation, the method further comprises:

[0020] After the route learning mode is ended, the intelligent driving controller sends a route end drawing request to the navigation system;

[0021] The navigation system ends drawing the route trajectory.

[0022] As an optional implementation, after the intelligent driving controller synchronizes the route identifier corresponding to the memory driving map and the mapping quality level of each road segment to the navigation system, the method further comprises:

[0023] The navigation system saves the route identifier corresponding to the memory driving map, the starting point, the ending point, the route trajectory and the mapping quality level.

[0024] As an optional implementation, the method of entering the memory driving mode comprises:

[0025] The intelligent driving controller receives a target route identifier selected by a user, determines a target memory driving map corresponding to the target route identifier, and prompts the user to drive to a route of the target memory driving map;

[0026] When the vehicle is on the route of the target memory driving map, the intelligent driving controller controls the vehicle to enter the memory driving mode.

[0027] As an optional implementation, after the memory driving mode is ended, the intelligent driving controller updates road information of a traveled route segment in the target memory driving map and a mapping quality level of the traveled route segment, comprising:

[0028] If the road information of the traveled route segment contains a new feature point, the mapping quality level of the traveled route segment is updated according to the road information of the traveled route segment.

[0029] In a second aspect, an intelligent navigation and control system is provided, which comprises an intelligent driving controller, a vehicle-side sensor and a navigation system, and realizes the method of any one of the first aspect.

[0030] It should be understood that the foregoing general description and the following detailed description are only exemplary and explanatory, and cannot limit the present application. BRIEF DESCRIPTION OF DRAWINGS

[0031] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or the prior art description will be briefly introduced. Obviously, the drawings in the following description only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained without creative labor on the basis of these drawings.

[0032] FIG. 1 is a structural schematic diagram of an intelligent navigation and control system provided by an embodiment of the present application;

[0033] FIG. 2 is a flowchart of a memory driving method provided by an embodiment of the present application;

[0034] FIG. 3 is a flowchart of a mapping quality level generation method provided by an embodiment of the present application;

[0035] FIG. 4 is a flowchart of a route trajectory generation method provided by an embodiment of the present application;

[0036] FIG. 5 is a flowchart of a route trajectory ending method provided by an embodiment of the present application;

[0037] FIG. 6 is a flowchart of a method for entering a memory driving mode according to an embodiment of the present application;

[0038] FIG. 7 is a flowchart of an example of a method for memory driving according to an embodiment of the present application. DETAILED DESCRIPTION

[0039] For the purpose of clarity, technical solutions and advantages of the present application, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and should not be used to limit the present application.

[0040] The method for memory driving provided by the embodiments of the present application can be applied to an intelligent navigation and control system. As shown in FIG. 1, the intelligent navigation and control system includes a smart driving controller 110, a vehicle-end sensor 120 and a navigation system 130.

[0041] The method for memory driving provided by the embodiments of the present application will be described in detail below with reference to the accompanying drawings and embodiments. FIG. 2 is a flowchart of a method for memory driving according to an embodiment of the present application. As shown in FIG. 2, the specific steps are as follows:

[0042] In step 201, after entering the route learning mode, the smart driving controller constructs a memory driving map according to the road information collected by the vehicle-end sensor.

[0043] In implementation, after entering the route learning mode, the smart driving controller can collect road information by using the vehicle-end sensor (such as a camera and a laser radar, etc.). Through the data of these sensors, the smart driving controller can create a detailed road model, which is the “memory driving map”. The memory driving map not only records the physical characteristics of the road (such as road width, curve, slope, etc.), but also can contain dynamic information, such as traffic signs, position of traffic lights, road speed limit information, etc. In addition, this map can also record environmental changes, such as weather conditions, lighting conditions, etc. In actual application, when the vehicle enters a new route, the smart driving controller activates the route learning mode. During the driving process of the vehicle, the smart driving controller records every detail of the road in real time. For example, when driving to an intersection, the system will specially record the position of the road sign and the traffic signal.

[0044] In step 202, after ending the route learning mode, the smart driving controller stores the memory driving map, and generates the mapping quality level corresponding to each road section according to the road information of each road section in the memory driving map.

[0045] In implementation, when the route learning mode ends, the intelligent driving controller can store the constructed memory driving map. According to the completeness and accuracy of the collected road information, the mapping quality level of each road segment is evaluated. The mapping quality level reflects the accuracy and reliability of the map data. These levels can help users understand the data quality of a certain road segment, so as to decide whether further learning or data updating is needed. The quality level can be affected by various factors, such as the accuracy of sensors, environmental conditions of data collection (such as insufficient light), etc. In addition, during the memory driving process, users can understand the mapping quality level, so as to maintain focus on vehicle driving in the case of poor mapping quality, take over in time, and avoid errors or accidents. For example, the data collected at night or in rainy weather may not be clear due to light or weather reasons, and the intelligent driving controller will mark it as low quality when generating the mapping quality level. Conversely, if the data is collected in sunny and light conditions, the quality level will be higher.

[0046] As an optional implementation, FIG. 3 is a flowchart of a method for generating a mapping quality level provided by an embodiment of the present application. As shown in FIG. 3, the specific steps for generating the mapping quality level corresponding to each road segment according to the road information of each road segment in the memory driving map in step 202 are as follows:

[0047] In step 301, for each road segment in the memory driving map, if the road information of the road segment contains feature points of each type, the mapping quality level of the road segment is a good quality level.

[0048] In implementation, when constructing the memory driving map, the intelligent driving controller can evaluate the detailed information of each road segment, including various types of feature points. These feature points can include traffic signs, lane lines, road markings, and traffic light positions, etc. If all feature points of a certain road segment are recorded completely and identified accurately, the mapping quality level of the road segment will be evaluated as a good quality level. A good quality level means that the system can accurately perceive and identify all feature points of the road, which is crucial for the accuracy and safety of the autonomous driving system. High-quality map data can help the vehicle make better navigation decisions, especially in complex urban environments. For example, on a city trunk road, the vehicle-mounted sensors completely record all lane markings, traffic signals, speed limit signs, and other important road feature points. All information of the road segment is accurate and complete, and the intelligent driving controller marks it as a good quality level. This means that the navigation system can rely on these data to provide accurate guidance for the vehicle and ensure driving safety.

[0049] In step 302, if the road information of the road segment contains feature points of each key type, but some feature points of ordinary type are missing, the mapping quality level of the road segment is a general quality level.

[0050] In implementation, if the road information of a certain road segment contains key type feature points (such as traffic lights, important traffic signs, etc.), but lacks some ordinary type feature points (such as lane lines, road markings, etc.), the mapping quality level of this road segment will be rated as a general quality level. The general quality level indicates that the information of this road segment is still useful for navigation and driving, but some details are not complete enough to affect some driving scenarios, such as automatic parking or handling of complex intersections. For example, on a certain rural road, the system records the main road signs and speed limit signs, but the lane line information is incomplete due to poor road conditions or insufficient light. In this case, although the key navigation information exists, the missing details may affect the accuracy of the autonomous driving system, so the road segment is rated as a general quality level.

[0051] Step 303, if the road information of the road segment is missing some key type feature points, the mapping quality level of the road segment is a poor quality level.

[0052] In implementation, when the road information of a certain road segment is missing some key type feature points, the mapping quality level of this road segment will be rated as a poor quality level. The missing of key feature points may include traffic lights, important traffic signs, etc., which seriously affect the safety and decision-making ability of autonomous driving. The poor quality level means that the map data of this road segment is unreliable, which may cause the autonomous driving system to malfunction in some cases. For example, at a complex intersection, if the system does not accurately record the position and state of the traffic lights, or misses the key traffic signs, it will cause the system to be unable to correctly judge the driving priority or speed limit information. Due to the missing of these key feature points, the mapping quality level of this road segment is rated as a poor quality level. The system may warn the user that the navigation information of this road segment is incomplete and must be continuously improved with the use of subsequent memory driving to improve the mapping quality level of this road segment.

[0053] As an optional implementation, the key type feature points include road grade, intersection type, lane line type, lane guide arrow, speed limit sign, zebra crossing and traffic light.

[0054] Step 203, the intelligent driving controller synchronizes the route identification corresponding to the memory driving map and the mapping quality level of each road segment to the navigation system.

[0055] In implementation, the intelligent driving controller can synchronize the mapping quality levels and route identifiers of the segments in the memory driving map to the navigation system. The navigation system can provide more accurate navigation suggestions to the user based on this information. The synchronization process ensures that the navigation system has the latest map data and quality information, making it more valuable when planning paths and providing driving suggestions. Optionally, the user can decide whether to use a certain segment based on the mapping quality level when selecting a route. For example, low-quality segments may affect the performance of the autonomous driving system, so the user can choose to avoid these segments. In actual use, when the user sets a destination, the navigation system can call the memory driving map and recommend the best route for the user based on the current traffic conditions and mapping quality levels. If the mapping quality level of a certain segment is low, the system will prompt the user that there may be uncertain factors and suggest other alternative routes.

[0056] As an optional implementation, after step 203, the method further includes the following steps:

[0057] The navigation system saves the route identifier, starting point, ending point, route trajectory, and mapping quality level corresponding to the memory driving map.

[0058] In implementation, after the intelligent driving controller synchronizes the information in the memory driving map to the navigation system, the navigation system saves this data, including the route identifier, starting point, ending point, route trajectory, and mapping quality level of each segment. The route identifier is used to distinguish different routes, the starting point and ending point mark the range of the trip, and the route trajectory records the path of the vehicle in detail. These data can also help users understand and choose high-quality segments and avoid low-quality areas. In addition, saving the mapping quality level information can make the system provide safer and more reliable options in subsequent route recommendation and autonomous driving. For example, after the user completes a new route, the navigation system can record the detailed information of this route. If the user plans to drive this route again, the navigation system can use the previously saved route trajectory and mapping quality level to provide the user with relatively safe and high-quality navigation suggestions. In addition, the user can also view the mapping quality level of each segment to decide whether to relearn or update the data of certain segments.

[0059] Step 204, after entering the memory driving mode, the navigation system replays the target memory driving map corresponding to the target route identifier based on the user's selected target route identifier, and displays the mapping quality level of each segment in the target memory driving map in real time.

[0060] In implementation, after entering the memorized driving mode, the navigation system can replay the memorized driving map corresponding to the target route according to the target route identifier selected by the user. The system simultaneously displays the mapping quality level of each road segment in real time. The replay function enables the user to preview the entire trip and understand the situation of each road segment before departure. The display of the mapping quality level can help the user identify potential driving risk areas. This process is particularly useful for planning long trips or unfamiliar routes.

[0061] In an example embodiment, the user plans to travel from city A to city B. The navigation system can first display an overview of the entire trip and mark road segments that may have problems (such as low mapping quality level). The user can understand the road segment situation before departure or during travel.

[0062] Step 205, after ending the memorized driving mode, the intelligent driving controller updates the road information of the traveled road segment in the target memorized driving map and the mapping quality level of the traveled road segment, and synchronizes the route identifier corresponding to the target memorized driving map and the mapping quality level of the traveled road segment to the navigation system.

[0063] In implementation, after the memorized driving mode ends, the intelligent driving controller can update the road information and mapping quality level of the traveled road segment in the target memorized driving map. These updated data are synchronized to the navigation system again to ensure the real-time and accuracy of its data. The process of updating data can include recording new changes to the road, such as newly built traffic signs, road condition changes, etc. The synchronized navigation system can provide more reliable information for future travel, which is particularly important for urban roads that change frequently. Assuming that the vehicle passes through a road segment, the previous route learning stage did not collect the speed limit sign due to environmental reasons, or a speed limit sign is added to the road segment, the intelligent driving controller can record this change and update the road information. Subsequently, the navigation system will obtain the latest data, so that the latest speed limit information can be provided when passing through the road segment next time, improving the mapping quality level and helping the user to avoid violations.

[0064] As an optional implementation, the specific method for the intelligent driving controller to update the road information of the traveled road segment and the mapping quality level of the traveled road segment in the target memorized driving map after ending the memorized driving mode in step 205 is: if the road information of the traveled road segment contains new feature points, updating the mapping quality level of the traveled road segment according to the road information of the traveled road segment.

[0065] In implementation, after ending the memorized driving mode, the intelligent driving controller can analyze the latest road information of the traveled road sections. If it is determined that these road sections contain new feature points (such as feature points not detected before, newly built traffic signs, new road markings, and changes in road structure, etc.), the intelligent driving controller can update the mapping quality level of these road sections accordingly. The information of new feature points can improve the map accuracy and quality level of the road sections, ensuring safer and more accurate future autonomous driving and navigation. Timely updating of this information helps to keep the map up to date, thereby supporting more accurate navigation and autonomous driving decisions. The update of the mapping quality level also reflects the completeness and accuracy of the data, enabling the system to consider the latest road conditions when planning routes. In actual operation, assuming that the vehicle is traveling on a recorded route, the intelligent driving controller detects a newly added speed limit sign or a newly built pedestrian crossing. These are new feature points. The intelligent driving controller will record these new feature points and add them to the memorized driving map. The intelligent driving controller can compare the road section information before and after the update. If the new information significantly improves the completeness or accuracy of the data, the intelligent driving controller will upgrade the mapping quality level of the road section. For example, after the addition of the originally unmarked speed limit information, the complete features of the road section are complete, and the quality level can be upgraded from "general" to "good".

[0066] As an optional implementation, FIG. 4 is a flowchart of a route trajectory generation method provided by an embodiment of the present application. As shown in FIG. 4, the specific steps are as follows:

[0067] Step 401, after entering the route learning mode, the intelligent driving controller sends a route start drawing request to the navigation system.

[0068] In implementation, after entering the route learning mode, the intelligent driving controller can also record the driving route of the vehicle. To this end, the intelligent driving controller can send a request to the navigation system to start the route drawing function, so that the navigation system is ready to start recording and drawing the real-time driving trajectory of the vehicle. This process is the starting point of the entire route learning, and the purpose is to provide basic data for the memorized driving map. The navigation system not only records the driving route of the vehicle, but also synchronously collects detailed information related to the road, such as geographic coordinates, speed, road conditions, etc. These data will be used for subsequent map construction and analysis. For example, when the user drives the vehicle into a new route, the intelligent driving controller detects the new driving path and sends a "start drawing route" request to the navigation system through the vehicle-mounted communication system. After receiving the request, the navigation system immediately starts recording every movement of the vehicle, ensuring that the detailed data of the entire route is captured.

[0069] Step 402, the navigation system draws the traveled route trajectory in real time and shows the route trajectory to the user.

[0070] In implementation, after receiving the request from the intelligent driving controller, the navigation system starts to draw the driving trajectory of the vehicle in real time. This includes the current driving route of the vehicle, the passed locations and the surrounding environment. The navigation system displays these data in a graphical way on the screen, so that the user can see the driving path of the vehicle in real time. The user can intuitively see the driving route on the screen, which is convenient for real-time judgment and planning of the road conditions. At the same time, the real-time drawn route trajectory can also be used as a driving record, which is convenient for future review or analysis. In actual application, when the vehicle is driving, the navigation system displays a dynamically updated route trajectory on the screen. This trajectory shows the current position of the vehicle, the route that has been driven and the destination. The user can clearly see the road they have driven on the screen of the navigation system, which provides a visual reference for the user.

[0071] As an optional implementation, FIG. 5 is a flowchart of a route trajectory ending method provided by the embodiment of the present application. As shown in FIG. 5, the specific steps are as follows:

[0072] Step 501, after ending the route learning mode, the intelligent driving controller sends a route ending drawing request to the navigation system.

[0073] In implementation, when the route learning mode ends, the intelligent driving controller sends a "route ending drawing request" to the navigation system, and instructs the navigation system to stop recording and drawing the current route trajectory. The end of the route learning mode may be due to the user reaching the destination, the preset learning of the driving route being completed, or the user manually ending the learning mode. In actual use, assuming that the user completes the learning of a specific route (for example, a new route from home to the company), when the user reaches the destination or chooses to end the route learning mode, the intelligent driving controller sends an ending drawing request to the navigation system, so that the navigation system stops the current data recording and saves the collected information.

[0074] Step 502, the navigation system ends drawing the route trajectory.

[0075] In implementation, after receiving the "route ending drawing request" from the intelligent driving controller, the navigation system stops drawing the current route trajectory. The process of ending drawing the route trajectory can include stopping data recording, performing the last check on the collected route information and saving. The user can view the saved route trajectory later, or use these data for further analysis and optimization.

[0076] As an optional implementation, FIG. 6 is a flowchart of a method for entering the memory driving mode provided by the embodiment of the present application. As shown in FIG. 6, the specific steps for entering the memory driving mode are as follows:

[0077] Step 601, the intelligent driving controller receives the target route identifier selected by the user, determines the target memory driving map corresponding to the target route identifier, and prompts the user to drive to the route of the target memory driving map.

[0078] In implementation, after receiving the target route identifier selected by the user, the intelligent driving controller can determine the target memory driving map corresponding to the target route identifier. This map contains detailed information of the specific route that the user plans to travel. Subsequently, the intelligent driving controller provides an indication to the user to guide the user to drive the vehicle to the starting point of the target route in order to start entering the memory driving mode. This step ensures that both the user and the vehicle are on a known and well-recorded route, so that the system can more effectively provide navigation and driving assistance. Prompting the user to go to the starting point of the specific route also helps the system to confirm that the vehicle is about to enter the correct navigation area, avoiding data confusion or navigation errors caused by mistakenly entering other routes. For example, the user wants to re-drive a previously recorded route. The user selects the identifier of this route in the navigation system. After receiving the selection, the intelligent driving controller displays the starting point of this route and guides the user to drive to the starting point through navigation. When the user approaches the starting point, the intelligent driving controller can remind the user to prepare to enter the memory driving mode through voice or screen prompts.

[0079] Step 602, when the vehicle is on the route of the target memory driving map, the intelligent driving controller controls the vehicle to enter the memory driving mode.

[0080] In implementation, when the vehicle reaches the starting point or any part of the route of the target memory driving map, the intelligent driving controller can detect that the position of the vehicle has entered the range of the target route. The intelligent driving controller automatically or prompts the user to enter the memory driving mode. In this mode, the system will enable relevant automatic driving or driving assistance functions to assist the user in driving according to the data in the memory driving map. For example, after the user's vehicle reaches the starting point of the target route, the intelligent driving controller confirms that the current position matches the target memory driving map, and prompts the user to "enter the memory driving mode". The intelligent driving controller automatically takes over part of the driving task, such as keeping in a specific lane, controlling the vehicle speed, recognizing traffic signals, etc. The user can choose to accept or cancel the start of the mode. If accepted, the system will automatically drive or provide highly assisted driving according to the previously recorded map data, ensuring safe and smooth driving on the target route.

[0081] As an optional implementation, FIG. 7 is a flowchart of an example of a memory driving method provided by an embodiment of the present application. As shown in FIG. 7, the specific steps are as follows:

[0082] Step 701, the user manually drives the vehicle to start learning the driving route, the intelligent driving controller enters the route learning mode after receiving the instruction, and the road environment information is identified by the vehicle sensor to start mapping. The intelligent driving controller sends a route start drawing request to the navigation, and the navigation starts to draw the route trajectory that has been driven from the starting point in the current map interface and displays it to the user.

[0083] Step 702, the user manually drives the vehicle to the destination to end the route learning, the intelligent driving controller enters the map storage mode after receiving the instruction, and saves the built map. The intelligent driving controller sends a route end drawing request, and synchronously sends the route identifier and mapping quality level information to the navigation system. The navigation system ends the route drawing after receiving the information, and saves the route identifier, starting point, ending point, GPS trajectory information, and route mapping quality level information of the current route.

[0084] Step 703, after the user manually drives the vehicle to complete the route learning for the first time, the intelligent driving controller constructs map data according to the route surrounding environment information collected by the vehicle sensor, and judges whether the necessary road feature points of different road sections of the learning route are all collected completely in combination with the GPS trajectory information. Finally, different road section mapping quality level information is generated, such as road grade, intersection type, lane line type, lane guiding arrow, speed limit identifier, zebra crossing, and traffic light. Good quality level means that all the necessary feature points of a road section have been completely learned and collected, general quality level means that the key feature points of a road section have been learned and collected, and the missing general feature points, and poor quality level means that the key feature points of a road section are missing;

[0085] Step 704, the user selects a learned route and drives the vehicle to the route, or drives the vehicle to the learned route, and activates the memory driving after the route positioning is successful. The intelligent driving controller enters the memory driving mode. The intelligent driving controller sends a route playback request and synchronously sends the positioning successful route identifier to the navigation system. The navigation system extracts relevant route information according to the route identifier after receiving the information, and performs route playback in the current map interface, and synchronously displays the mapping quality level information of the route to the user.

[0086] Step 705, the vehicle drives to the end of the route to exit the memory driving, and the intelligent driving controller updates the map information of the route. If the missing feature points are learned and collected in the road section with general or poor quality level, the quality level of the road section is improved, and then a route mapping quality level information update request is sent to the navigation. The navigation updates the mapping quality level information of the route after receiving the information.

[0087] The embodiment of the application provides a method for memorizing driving, and the technical scheme provided by the embodiment of the application at least brings the following beneficial effects: after entering the route learning mode, the intelligent driving controller constructs a memorized driving map according to road information collected by a vehicle terminal sensor; after ending the route learning mode, the intelligent driving controller stores the memorized driving map, and generates a mapping quality level corresponding to each road section according to road information of each road section in the memorized driving map; the intelligent driving controller synchronizes the route identifier corresponding to the memorized driving map and the mapping quality level of each road section to a navigation system; after entering the memorized driving mode, the navigation system plays back a target memorized driving map corresponding to a target route identifier according to the target route identifier selected by a user, and displays the mapping quality level of each road section in the target memorized driving map in real time; after ending the memorized driving mode, the intelligent driving controller updates road information of a traveled road section and the mapping quality level of the traveled road section in the target memorized driving map, and synchronizes the route identifier corresponding to the target memorized driving map and the mapping quality level of the traveled road section to the navigation system. The application adopts a display method for memorized driving route learning and route playback of fusion navigation, so that a user can know the running state of current memorized driving in real time, and the information transparency in the human-machine co-driving process is improved. While the user uses the memorized driving navigation to play back a route, the user can check the mapping quality level information of each road section, the trust degree of the user for the memorized driving is increased, and the driving experience is improved. With repeated use of the memorized driving by the user, the mapping quality is continuously optimized and improved.

[0088] It should be understood that although each step in the flowcharts of FIGS. 2 to 7 is displayed in sequence according to the direction of the arrow, these steps are not necessarily executed in sequence according to the direction of the arrow. Unless otherwise specified herein, the execution of these steps is not strictly limited in sequence, and these steps can be executed in other sequences. Moreover, at least part of the steps in FIGS. 2 to 7 can include multiple steps or multiple stages, which are not necessarily executed at the same time, but can be executed at different times, and the execution sequence of these steps or stages is not necessarily sequential, but can be executed alternately or alternately with at least part of other steps or steps or stages in other steps.

[0089] It can be understood that the same / similar parts between each embodiment of the above method in the specification can be mutually referred to, and each embodiment mainly explains the difference from other embodiments, and the related part can be referred to the description of other method embodiments.

[0090] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer readable storage medium, and when the computer program is executed, the processes of the above-mentioned embodiments of the methods can be included. Any reference to memory, storage, databases, or other media in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration but not limitation, RAM is available in many forms such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), Synchlink DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct RAMbus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM), etc.

[0091] It should be noted that, in this paper, the relationship terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between the entities or operations. Moreover, the terms "include", "contain" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or equipment including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or equipment. Without more limitations, the element defined by the statement "including a" does not exclude the presence of other identical elements in the process, method, article or equipment including the element.

[0092] It should also be noted that the user information (including but not limited to user equipment information, user personal information, etc.) and data (including but not limited to data for display, analyzed data, etc.) involved in this application are information and data authorized by the user or authorized by all parties.

[0093] The various embodiments in the specification are described in a related manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the difference from other embodiments. In particular, the system embodiments are described simply because they are basically similar to the method embodiments, and the related parts can be referred to the part of the method embodiments.

[0094] The technical features of the above embodiments can be combined in any manner. In order to make the description simple, all possible combinations of the technical features in the above embodiments are not described, but as long as the combinations of the technical features do not exist contradictory, they should be considered as the scope of the specification.

[0095] The above embodiments only express several implementation manners of the present application, and the description is more specific and detailed, but it should not be understood as a limitation on the scope of the patent. It should be pointed out that for ordinary skilled in the art, without departing from the concept of the present application, a number of modifications and improvements can be made, which are within the scope of the present application. Therefore, the scope of the patent of the present application should be subject to the appended claims.

Claims

1. A method of memorizing a driving course, characterized by, The method is applied to an intelligent navigation and control system, the system comprising a smart driving controller, a vehicle-end sensor and a navigation system, and the method comprising: After entering a route learning mode, the smart driving controller constructs a memory driving map according to road information collected by the vehicle-end sensor; After ending the route learning mode, the smart driving controller stores the memory driving map and generates a mapping quality level corresponding to each road segment in the memory driving map according to road information of each road segment in the memory driving map; The smart driving controller synchronizes a route identifier corresponding to the memory driving map and the mapping quality level of each road segment to the navigation system; After entering a memory driving mode, the navigation system plays back a target memory driving map corresponding to a target route identifier selected by a user according to the target route identifier and displays the mapping quality level of each road segment in the target memory driving map in real time; After ending the memory driving mode, the smart driving controller updates road information of a traveled road segment in the target memory driving map and the mapping quality level of the traveled road segment and synchronizes a route identifier corresponding to the target memory driving map and the mapping quality level of the traveled road segment to the navigation system.

2. The method of claim 1, wherein, The method further comprises: After entering the route learning mode, the smart driving controller sends a route start drawing request to the navigation system; The navigation system draws a route trajectory traveled in real time and shows the route trajectory to a user. The method further comprises:

3. The method of claim 2, wherein, After ending the route learning mode, the smart driving controller sends a route end drawing request to the navigation system; 4. The method of claim 1, wherein, The navigation system ends drawing the route trajectory. After the smart driving controller synchronizes the route identifier corresponding to the memory driving map and the mapping quality level of each road segment to the navigation system, the method further comprises: The navigation system saves the route identifier, a starting point, an ending point, a route trajectory and a mapping quality level corresponding to the memory driving map.

5. The method of claim 4, wherein, The method of entering the memory driving mode comprises: The smart driving controller receives a target route identifier selected by a user, determines a target memory driving map corresponding to the target route identifier and prompts the user to drive on a route of the target memory driving map; When the vehicle is on the route of the target memory driving map, the smart driving controller controls the vehicle to enter the memory driving mode.

6. The method of claim 5, wherein, ​ ​ 7. The method of claim 1, wherein, ​ ​ ​ 8. The method of claim 6, wherein, After the end of the memory driving mode, the intelligent driving controller updates the road information of the traveled road section and the mapping quality level of the traveled road section in the target memory driving map, comprising: If the road information of the traveled road section contains new feature points, the mapping quality level of the traveled road section is updated according to the road information of the traveled road section.

9. An intelligent navigation and control system characterized by, The system comprises an intelligent driving controller, a vehicle-end sensor and a navigation system, and realizes the method according to any one of claims 1-8.

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