Navigation method and device

Abstract

This application discloses a navigation method and apparatus relating to the field of autonomous driving technology, comprising: a first terminal device receiving navigation information, the navigation information including one or more of map information, location information of a dynamic event, impact information of the dynamic event, and time information of the dynamic event; wherein the impact information of the dynamic event includes the impact range of the dynamic event; and the first terminal device performing navigation based on the map information and navigation information. This application provides a precise and autonomous driving-oriented dynamic event representation method, which facilitates the implementation of autonomous driving.

Description

Technical Field

[0001] The present application relates to the field of autonomous driving technology, and in particular to a navigation method and device. Background Art

[0002] Autonomous vehicles (also known as self-piloting automobiles, driverless cars, computer-driven cars, or wheeled mobile robots) are intelligent vehicles that utilize computer systems to achieve autonomous driving. They rely on artificial intelligence, visual computing, radar, positioning systems, and mapping systems to enable computers to operate the vehicle safely and automatically without any human intervention. Electronic map systems are essential for vehicle navigation, and the accuracy and precision of these maps are crucial to the safety of autonomous vehicles. Road conditions are constantly changing, and failure to keep updated maps can pose significant safety risks to autonomous vehicles.

[0003] Unlike static elements in a map, dynamic information or events usually need to be associated with spatial information to accurately reflect the location range of their occurrence. We call this location mapping of dynamic events LocationReference, that is, the location mapping of dynamic events.

[0004] In the prior art, dynamic events (such as traffic accidents and traffic jams) are mainly represented by two methods: absolute geographical representation and predefined ID identification.

[0005] However, the definition and representation of dynamic events in the above-mentioned prior art are mainly oriented towards humans and do not support machines oriented towards autonomous driving. Summary of the Invention

[0006] An embodiment of the present application provides a navigation method and device, which provides a dynamic event representation method for a machine for autonomous driving, improves the accuracy of the expression of dynamic events, and thus better realizes the autonomous driving function.

[0007] In a first aspect, the present application provides a navigation method, which includes: a first terminal device receives navigation information, the above navigation information includes one or more of map information, location information of dynamic events, impact information of dynamic events and time information of dynamic events; wherein the impact information of dynamic events includes the impact range of dynamic events; the first terminal device navigates according to the map information and navigation information.

[0008] It can be seen that in the embodiment of the present application, the impact information and time information of dynamic events are introduced into the navigation information to characterize the dynamic events, wherein the impact information of the dynamic events includes the impact range of the dynamic events. The above-mentioned characterization method of dynamic events is used to achieve accurate description of the dynamic events, and the characterization method is easy to be recognized by the machine, so that it can be applied to the field of autonomous driving technology to realize the function of autonomous driving.

[0009] In a feasible implementation, the impact information of the above-mentioned dynamic event also includes a list of map elements, and the above-mentioned method also includes: the first terminal device detects the map elements in the map element list, obtains the detection results of the map elements, and sends the detection results to the server or the second terminal device to update the navigation information and map; wherein, the map is obtained based on the map information.

[0010] It can be seen that in the embodiment of the present application, the impact information of the dynamic event also includes a list of map elements. When the terminal device receives the list of map elements, it can trigger the terminal device to detect the corresponding attributes of the map elements in the list of map elements to obtain the detection results of the map elements; wherein, for different map elements, the corresponding attributes may be different. For example, when the map element is a lane line, the corresponding attributes may include the color and width of the lane line. When the terminal device is an autonomous driving vehicle, different dynamic events can trigger different behaviors of the autonomous driving vehicle, such as using vehicle sensors and / or on-board cameras to collect relevant data, obtain the detection results of the map elements, and send the detection results to the server or the second terminal device to update the map, thereby realizing real-time update of the map; ensuring that the server sends the updated map to the vehicle next time, so that the vehicle can better realize the function of autonomous driving.

[0011] In a feasible implementation, the sending of the detection result to the server or the second terminal device includes: when the attribute of the map element in the detection result is different from the attribute of the corresponding map element in the map, the first terminal device sends the detection result to the server or the second terminal device.

[0012] It can be seen that in the embodiment of the present application, when the attributes of the map elements in the detection results are different from the attributes of the corresponding map elements in the above-mentioned map, the terminal device is triggered to send its detection results to the server, thereby enabling the server to update the map elements, that is, update the map according to the actual situation, and ensure that subsequent terminal devices receive the latest map. When the terminal device is the vehicle end of an autonomous driving vehicle, the autonomous driving function can be better realized.

[0013] In a feasible embodiment, the impact information of the above-mentioned dynamic event also includes at least one of a positioning impact factor and a perception impact factor. The above-mentioned method also includes: the first terminal device determines the confidence of the detection result based on at least one of the positioning impact factor, the perception impact factor and the time information of the dynamic event, and sends the confidence of the detection result to the server or the second terminal device. The confidence of the detection result is used to characterize the credibility of the detection result.

[0014] It can be seen that in the embodiment of the present application, the impact information of the dynamic event also includes at least one of the positioning impact factor and the perception impact factor. The confidence of the detection result, that is, the credibility of the detection result, is determined by at least one of the positioning impact factor, the perception impact factor and the time information of the dynamic event, and the confidence is sent to the server, so that the server can update the map according to the confidence of the detection result and the detection result, so that the updated map is more accurate, ensuring that subsequent terminal devices receive accurate maps, and better realizing the function of autonomous driving when the terminal device is an autonomous driving vehicle.

[0015] In a feasible implementation, the perception impact factor is used to characterize the degree of influence of a dynamic event on the detection process of a map element; the positioning impact factor is used to characterize the degree of influence of a dynamic event on the terminal device's positioning of itself.

[0016] It can be seen that in the embodiment of the present application, the perception influence factor and the positioning influence factor are used to characterize the degree of influence of dynamic events on the detection process. Therefore, the perception influence factor and the positioning influence factor are used to determine the confidence of the detection result, which can accurately reflect the accuracy of the detection result, so that the subsequent server can adaptively update the map based on the confidence.

[0017] In a feasible implementation, the first terminal device determines the confidence of the detection result based on at least one of the positioning influence factor, the perception influence factor, and the time information of the dynamic event, including: when the process of the first terminal device detecting the map elements in the map element list is within the expected duration of the dynamic event, determining the confidence of the detection result based on the positioning influence factor and / or the perception influence factor.

[0018] It can be seen that in an embodiment of the present application, when the process of the terminal device detecting the map elements in the map element list is within the expected duration of the dynamic event, that is, when the dynamic event is still ongoing, the dynamic event will have a certain impact on the detection process of the terminal device. Therefore, the confidence of the detection result is determined according to the positioning influence factor and / or the perception influence factor, so that the subsequent server accurately updates the map according to the confidence of the detection result and the detection result. When the subsequent terminal device is the vehicle end of the autonomous driving, the autonomous driving function is better realized by receiving the updated map.

[0019] In a feasible implementation manner, the time information of the dynamic event includes one or more of the start time of the dynamic event, the expected duration of the dynamic event, and the expected end time of the dynamic event.

[0020] It can be seen that in the embodiment of the present application, the time information of the dynamic event can assist the first terminal device in determining whether the detection process of the first terminal device is under the influence of the dynamic event, thereby deciding whether it is necessary to use the perception influence factor and positioning influence factor corresponding to the dynamic event to determine the confidence of the detection result, and obtain accurate confidence results, so as to facilitate the subsequent server to accurately update the map.

[0021] In a feasible implementation manner, the values ​​of the positioning influence factor and the perception influence factor are predefined quantitative values.

[0022] It can be seen that in the embodiment of the present application, the values ​​of the positioning influence factor and the perception influence factor are predefined quantitative values. Since the quantized perception influence factor and positioning influence factor can be more easily recognized and processed by the machine, the data structure supports machines for autonomous driving and is conducive to realizing the function of autonomous driving.

[0023] In a feasible implementation manner, the impact information of the above-mentioned dynamic event also includes lane passability status information.

[0024] As can be seen, in this embodiment of the present application, the dynamic event impact information also includes lane availability information, which can include all or part of the lane availability information within the dynamic event's impact range. By incorporating lane availability information into navigation information, when the terminal device is an autonomous vehicle, decisions and path planning can be made in advance based on lane availability, thereby achieving effective autonomous driving capabilities.

[0025] In a feasible implementation manner, the navigation information further includes semantic information representing dynamic events.

[0026] It can be seen that in the embodiment of the present application, when the terminal device is an autonomous driving vehicle, by retaining semantic information for human drivers in the navigation information, when the autonomous driving vehicle is manually taken over, the semantic information contained in the above navigation information can be used for navigation, thereby achieving compatibility between autonomous driving and manual driving.

[0027] In a feasible implementation manner, the impact range of the dynamic event includes location information of the dynamic event.

[0028] It can be seen that in the embodiment of the present application, since the impact range of the dynamic event is greater than or equal to the range contained in the location information of the dynamic event, and the impact range of the dynamic event is more valuable for the autonomous driving vehicle side when performing path planning, the embodiment of the present application assists the autonomous driving vehicle side in planning the optimal driving path by introducing the dynamic event impact range in the navigation information, thereby realizing effective autonomous driving function.

[0029] In a feasible implementation manner, the transmission format of navigation information corresponding to different dynamic events is the same.

[0030] It can be seen that in the embodiment of the present application, the navigation information corresponding to different dynamic events can be transmitted using the same transmission format, thereby making the data interaction between the terminal device and the server more efficient, and the terminal device can quickly receive the navigation information of the dynamic event, thereby achieving accurate navigation based on the navigation information.

[0031] In a second aspect, the present application provides a navigation method, which includes: a server sending navigation information to a terminal device, the navigation information including map information, location information of dynamic events, impact information of dynamic events and time information of dynamic events; the impact information of dynamic events includes one or more of a map element list, a positioning impact factor, a perception impact factor, an impact range of dynamic events and lane traffic status information; the server receives the detection results and the confidence of the detection results of the terminal device for the map elements in the map element list, and updates the map and navigation information based on the detection results and the confidence of the detection results; wherein, the map is obtained based on the map information, and the confidence of the detection result is used to characterize the accuracy of the detection result.

[0032] It can be seen that in the embodiment of the present application, the navigation information sent by the server to the terminal device includes one or more of map information, location information of dynamic events, impact information of dynamic events, and time information of dynamic events, and the impact information of dynamic events includes a variety of relevant information that is easy for the machine to recognize, so as to achieve accurate information indication of dynamic events, so that the terminal device can quickly and accurately process and make decisions after receiving the navigation information, and navigate; when the terminal device is an autonomous driving vehicle, it can facilitate the vehicle to effectively realize the function of autonomous driving. At the same time, the server can receive the detection results and corresponding confidence levels sent by different terminal devices, and analyze and process the received detection results and confidence levels to achieve accurate updates of the map and navigation information, so that subsequent terminal devices can receive accurate navigation information, which is conducive to accurate navigation of the terminal devices.

[0033] In a feasible implementation, the perception impact factor is used to characterize the degree of influence of a dynamic event on the detection process of a map element; the positioning impact factor is used to characterize the degree of influence of a dynamic event on the terminal device's positioning of itself.

[0034] It can be seen that in the embodiment of the present application, the perception influence factor and the positioning influence factor are used to characterize the degree of influence of dynamic events on the detection process. Therefore, after the server sends the perception influence factor and the positioning influence factor to the terminal device, the terminal device can use them to determine the confidence of the detection result, thereby accurately reflecting the accuracy of the detection result.

[0035] In a feasible implementation manner, the values ​​of the positioning influence factor and the perception influence factor are predefined quantitative values.

[0036] It can be seen that in the embodiment of the present application, the values ​​of the positioning influence factor and the perception influence factor are predefined quantitative values. Since the quantized perception influence factor and positioning influence factor can be more easily recognized and processed by the machine, the data structure supports machines for autonomous driving and is conducive to realizing the function of autonomous driving.

[0037] In a feasible implementation manner, the impact information of the dynamic event also includes lane passability status information.

[0038] As can be seen, in this embodiment of the present application, the vehicle-to-vehicle drivability status information can be the drivability status information of all or part of the lanes within the dynamic event's impact range. By incorporating lane drivability status information into the navigation information sent by the server, when the terminal device is an autonomous vehicle, decisions and path planning can be made in advance based on the lane drivability status, thereby achieving effective autonomous driving functionality.

[0039] In a feasible implementation manner, the navigation information further includes semantic information representing dynamic events.

[0040] It can be seen that in the embodiment of the present application, the navigation information sent by the server to the central device also includes semantic information representing dynamic events. When the terminal device is an autonomous driving vehicle, by retaining the semantic information for human drivers in the navigation information, when the autonomous driving vehicle is manually taken over, the semantic information contained in the above navigation information can be used for navigation, thereby achieving compatibility between autonomous driving and manual driving.

[0041] In a feasible implementation manner, the impact range of the dynamic event includes location information of the dynamic event.

[0042] In a feasible implementation manner, the transmission format of navigation information corresponding to different dynamic events is the same.

[0043] The beneficial effects of the above two embodiments are the same as those of the corresponding embodiments of the first aspect, and will not be repeated here.

[0044] In a third aspect, the present application provides a navigation device, which includes a module for executing the method in the first aspect.

[0045] In a fourth aspect, the present application provides a navigation device, which includes a module for executing the method in the second aspect.

[0046] In a fifth aspect, the present application provides a terminal device comprising a processor and a memory, the processor and the memory being connected to each other, wherein the memory is used to store a computer program, the computer program comprising program instructions, and the processor is configured to call the above-mentioned program instructions and execute a method as described in any one of the above-mentioned first aspects.

[0047] In a sixth aspect, the present application provides a server comprising a processor and a memory, the processor and the memory being connected to each other, wherein the memory is used to store a computer program, the computer program comprising program instructions, and the processor is configured to call the above-mentioned program instructions and execute a method as described in any one of the above-mentioned second aspects.

[0048] In a seventh aspect, the present application provides a computer-readable storage medium storing a computer program, which is executed by a processor to implement the method in any one of the first or second aspects above. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The following is an introduction to the drawings used in the embodiments of this application.

[0050] Figure 1This is an architecture diagram of a system used in a navigation method according to an embodiment of the present application;

[0051] Figure 2 This is a schematic diagram of a scene of a dynamic event in an embodiment of the present application;

[0052] Figure 3 This is a flowchart of a navigation method in an embodiment of the present application;

[0053] Figure 4 This is a schematic diagram of the data structure of navigation information in an embodiment of the present application;

[0054] Figure 5 This is a driving scene diagram of an automatically driving vehicle in an embodiment of the present application;

[0055] Figure 6 is a flowchart of another navigation method in an embodiment of the present application;

[0056] Figure 7 is a structural diagram of a navigation device in an embodiment of the present application;

[0057] Figure 8 is a schematic structural diagram of another navigation device in an embodiment of the present application;

[0058] Figure 9 This is a schematic diagram of the hardware structure of a device in an embodiment of the present application. DETAILED DESCRIPTION

[0059] The following describes the embodiment of the present application in conjunction with the accompanying drawings in the embodiment of the present application. The map mentioned in the embodiment of the present application can be a high-precision map or a conventional navigation map, and the present application does not make specific restrictions on this.

[0060] The following is an illustrative introduction to scenarios to which the embodiments of the present invention are applicable.

[0061] For example, the navigation method provided by the present application can be applied to the field of autonomous driving. In the field of autonomous driving, navigation is usually carried out with the help of high-precision maps. High-precision maps provide a more accurate, clear and comprehensive description of the road, and can reflect various dynamic events on the road in real time, thereby giving the vehicle a lot of room for pre-judgment, enabling driving planning in advance, and ensuring the smoothness and economy of driving. In addition, high-precision maps can help vehicles reduce the amount of calculation. When a vehicle needs to pass through an intersection, it needs to perceive the status of the traffic light ahead in advance. At this time, the high-precision map can help it locate the specific area where the traffic light is located, thereby effectively reducing the amount of calculation for full-range scanning and recognition. With the continuous development of fields such as autonomous driving, intelligent assisted driving and traffic networking, high-precision maps have gradually become a tool to better serve these fields.

[0062] The navigation method provided in this application can also be applied to other fields, not limited to the autonomous driving field introduced above.

[0063] In order to better realize the function of autonomous driving, it is necessary to express various dynamic events that affect vehicle driving in high-precision maps so that the vehicle can perceive these dynamic events. However, in the field of autonomous driving, there is currently no unified industry standard to characterize the navigation information corresponding to dynamic events. Therefore, this application provides a feasible and effective navigation method. This navigation method designs a set of data structures that are easy for machines to recognize, and uses this data structure to characterize the relevant information of dynamic events, so as to better meet the needs of autonomous driving.

[0064] Optionally, the navigation method provided in the present application can be implemented in a server, a roadside unit, a vehicle-mounted terminal device (such as a vehicle or a processing device or unit in a vehicle) or a handheld terminal device (such as a mobile phone). The roadside unit, vehicle-mounted terminal device and handheld terminal device are collectively referred to as terminal devices in this application.

[0065] For easier understanding, see Figure 1 , Figure 1 The following diagram illustrates an exemplary system architecture for the navigation method provided herein. The system architecture may include a server 100, a vehicle 101, and a roadside unit 102. The server 100 may include one or more servers, and multiple servers may form a server cluster. The server 100 may communicate with the vehicle 101 and the roadside unit 102 via a network. Furthermore, the roadside unit 102 may also communicate with the vehicle 101.

[0066] The server 100 can communicate with other devices to obtain information required for high-precision maps. For example, the server 100 can communicate with a server of a transportation bureau to obtain traffic information. For another example, the server 100 can communicate with a server of a meteorological bureau to obtain weather information. The vehicle 101 can be an autonomous vehicle, a semi-autonomous vehicle, or a regular vehicle.

[0067] If the navigation method provided in this application is implemented in the server 100, the vehicle 101 can interact with the server 100 to obtain the latest high-precision map. Alternatively, the server 100 can send the latest high-precision map to the roadside unit 102, and the vehicle 101 can interact with the roadside unit 102 to obtain it.

[0068] If the navigation method provided in this application is implemented in the roadside unit 102, then the roadside unit 102 can obtain the latest information of various dynamic events from the server 100 and update the high-precision map based on this latest information. Then the vehicle 101 can interact with the roadside unit 102 to obtain the latest high-precision map.

[0069] If the navigation method provided in this application is implemented in vehicle 101, then vehicle 101 can obtain the latest information of various dynamic events from server 100, and take corresponding actions based on the latest information, thereby updating the high-precision map for use.

[0070] It should be noted that Figure 1 The system architecture shown is only an example. As long as the system architecture can be applied to the navigation method provided in this application, it is within the scope of protection of this application. This application does not limit the specific system architecture used.

[0071] The dynamic events in this application may include some or all of the following events:

[0072] Weather conditions: may include temperature conditions, air pressure conditions, humidity conditions, sunny days, cloudy days, windy conditions, foggy conditions, rainy conditions, lightning conditions, snowy conditions, frosty conditions, thunder conditions, hail and other dynamic events.

[0073] Road cover conditions, also known as road environment, can include dynamic events such as water accumulation, snow accumulation, ice or damage to the road cover.

[0074] Road adhesion coefficient: refers to the adhesion between the road and the vehicle tires. The greater the adhesion, the less likely the vehicle is to slip.

[0075] Road visibility conditions: may refer to the visible distance conditions caused by haze or light, etc.

[0076] Temporary point of interest (POI) situations: These may include non-fixed POIs, dynamic events such as temporarily available parking spaces, temporarily available charging stations, or temporary public service points.

[0077] Recommended information: This may include dynamic events such as user interest point recommendations or itinerary suggestions.

[0078] Road traffic conditions: may include dynamic events such as traffic accidents, traffic control, road construction or accident-prone areas.

[0079] Traffic flow conditions: may include the amount of traffic on each road, etc.

[0080] Traffic light status: This can include dynamic events such as traffic light phase status, semantic information, timing data, or working status.

[0081] Vehicle obstacles: may include the type of vehicle causing the obstacle, motion information, headlight and door information, control information, or driving behavior prediction information.

[0082] Other obstacles: can include all obstacles except vehicle obstacles.

[0083] Risk warning situation: may include information such as risk type (collision risk in various directions, landslide risk, etc.), risk level or avoidance suggestions.

[0084] Collaborative driving situation: This refers to vehicle collaborative guidance information, including lane merging collaboration, steering collaboration, special vehicle avoidance, or parking collaboration.

[0085] Path planning situation: It may refer to the planned route of the driving path made according to the existing road conditions, etc.

[0086] Road network topology changes: This refers to temporary changes in drivable routes caused by road traffic incidents, which can be manifested as changes in the geometric expression or attributes of road lines and lane lines.

[0087] The above examples exemplify some of the dynamic events applied to high-precision maps, and in actual applications, the expression granularity of dynamic events can be finer. For example, for the dynamic event of weather conditions, when actually expressed in a high-precision map, it can be expressed as events such as rain, snow, or sunny days. Optionally, it can be expressed as a specific event such as heavy rain, moderate rain, or light rain. By updating these dynamic events in real-time and expressing them in high-precision maps, various dynamic conditions on the road can be provided in real time to objects using high-precision maps, such as vehicles, providing a powerful reference for further route planning and behavior prediction. It should be noted that the dynamic events actually used in high-precision maps are not limited to the above-mentioned events, and this application does not limit the specific dynamic events and their quantity.

[0088] See Figure 2 , Figure 2 A schematic diagram of a dynamic event scenario provided in an embodiment of the present application. Figure 2 As shown, Figure 2 The dynamic events shown are construction events. Figure 2 To describe the navigation information corresponding to the dynamic event sent by the server to the terminal device in the prior art. Figure 2 The navigation information for the construction event shown might be represented as follows: lane narrowing starting at 1 km in the direction of travel and within a 3.5 km radius; lane closure starting at 2 km in the direction of travel and within a 1.5 km radius. This dynamic construction event representation is primarily targeted at human drivers and is easily understood by them.

[0089] See Figure 3 , Figure 3 FIG. 3 is a flow chart of a navigation method 300 provided in an embodiment of the present application. Figure 3 As shown, the method 300 includes step S310 and step S320. The method 300 is applied to the first terminal device side.

[0090] In step S310, the first terminal device receives navigation information, which includes one or more of map information, location information of dynamic events, impact information of dynamic events, and time information of dynamic events; wherein the impact information of dynamic events includes the impact range of the dynamic events.

[0091] Optionally, the map information included in the above navigation information may be a map directly used for navigation or a map version number corresponding to the required map, which is not limited in this application.

[0092] For example, the data structure of the navigation information of a dynamic event can be as follows: Figure 4 As shown, the navigation information for a dynamic event can include map information, location information, impact information, and time information. The location information for a dynamic event refers to the location of the dynamic event within the map, and is represented using map elements within the map. For example, the location information for a dynamic event can be represented as follows: On Fifth Avenue, 200 meters from the second traffic light, there is spillage within a 1-meter radius.

[0093] Optionally, the map elements may be one or more standard map elements such as roads, lane lines, parking spaces, tunnels, bridges, signal signs, traffic lights, railways, intersection areas and platforms, or non-standard map elements such as crosswalks, stop lines, speed bumps, pillars, fences, trees, flower beds and buildings.

[0094] Optionally, the above map can be a high-precision map, which is not specifically limited in this application.

[0095] Optionally, the above-mentioned first terminal device can receive the above-mentioned navigation information from a server or a second terminal device; wherein, the first terminal device can be a terminal device with a navigation function, for example, a vehicle-mounted terminal device or a handheld terminal device (such as a mobile phone, tablet, etc.); the second terminal device can be a terminal device with a communication function, such as a vehicle-mounted terminal device, or a roadside unit, or a handheld terminal device, etc.

[0096] Step S320: The first terminal device performs navigation according to the map information and navigation information.

[0097] Specifically, the first terminal device obtains a map based on the above-mentioned map information, and plans a reasonable route for the terminal device according to the location information of the dynamic event in the map, the impact range of the dynamic event in the map, and the time information of the dynamic event. For example, when the first terminal device is an automatically driven vehicle, the vehicle can automatically plan a reasonable driving route based on the above-mentioned navigation information received, thereby avoiding the impact of the dynamic event on the vehicle's driving and saving driving time. Specifically, when the moment when the vehicle receives the navigation information is within the expected duration in the dynamic event time information, it means that the dynamic event continues to exist. At this time, the optimal driving route of the vehicle can be planned based on the impact range of the dynamic event and / or the location information of the dynamic event. When the impact range of the dynamic event is greater than the range included in the location information of the dynamic event, the vehicle's driving route is planned according to the impact range of the dynamic event. When the impact range of the dynamic event is equal to the range included in the location information of the dynamic event, the vehicle's driving route is planned according to the impact range of the dynamic event or the location information of the dynamic event.

[0098] The map acquired by the first terminal device includes corresponding map elements and corresponding attributes of the map elements.

[0099] Optionally, when the above-mentioned map information contains a map, the first terminal device can directly obtain the map from the map information; when the above-mentioned map information contains a map version number corresponding to the required map, the first terminal device can download the map corresponding to the above-mentioned map version number from the server.

[0100] It can be seen that in the embodiment of the present application, the impact information of the dynamic event also includes a list of map elements. When the first terminal device receives the list of map elements, it can trigger the first terminal device to detect the corresponding attributes of the map elements in the list of map elements to obtain the detection results of the map elements. When the first terminal device is an autonomous vehicle, different dynamic events can trigger different behaviors of the autonomous vehicle, such as using vehicle sensors and / or on-board cameras to collect relevant data, obtain detection results of map elements, and send the detection results to the server or the second terminal device to update the map, thereby achieving real-time update of the map; ensuring that the server sends the updated map to the first terminal device and the second terminal device next time, so that the vehicle can better realize the autonomous driving function.

[0101] In a feasible implementation, the impact information of the above-mentioned dynamic events also includes a list of map elements, and the method also includes: the first terminal device detects the map elements in the map element list, obtains the detection results of the map elements, and sends the detection results to the server or the second terminal device to update the map and corresponding navigation information.

[0102] Specifically, the detection results include attributes such as the size, shape, color, and position of the map elements in the map element list. When the first terminal device is a vehicle, the map elements in the map element list can be detected using onboard equipment such as an onboard radar and / or an onboard camera to obtain attributes such as the size, shape, and color of the map elements. It should be understood that different map elements may have different corresponding attributes. For example, when the map element is a lane line, its corresponding attributes may include the lane line color and width.

[0103] Optionally, the map elements in the map acquired by the first terminal device include map elements in the above map element list.

[0104] Optionally, the first terminal device may determine the real-time location of the map element through a satellite positioning system, a vehicle-mounted radar, and / or a vehicle-mounted camera, and other on-board equipment. That is, the detection result includes the real-time location information of some or all of the map elements in the map element list. The satellite positioning system may be the Global Positioning System (GPS), the Galileo system, the GLONASS system, or the BeiDou system, and this application does not specifically limit this.

[0105] In a feasible implementation manner, the sending of the detection result to the server includes: when an attribute of a map element in the detection result is different from an attribute of a corresponding map element in the map, the first terminal device sending the detection result to the server or the second terminal device.

[0106] Specifically, when one or more of the attributes of a map element in the detection result, such as size, shape, color, and position, differs from the corresponding attribute of the map element in the map, the first terminal device sends the detection result of the map element to the server or the second terminal device. When the first terminal device sends the detection result to the second terminal device, the second terminal device can forward the detection result to the server directly or through another terminal device.

[0107] Optionally, after receiving the above detection results, the server may update the map according to the above detection results. The following embodiments will specifically introduce the process of updating the map and navigation information.

[0108] Optionally, the map elements included in the map element list may include some map elements within the influence range of the dynamic event, all map elements within the influence range of the dynamic event, or map elements outside the influence range of the dynamic event.

[0109] In a feasible embodiment, the impact information of the dynamic event also includes at least one of a positioning impact factor and a perception impact factor, and the method also includes: the terminal device determines the confidence of the detection result based on at least one of the positioning impact factor, the perception impact factor and the time information of the dynamic event, and sends the confidence of the detection result to the server or the second terminal device, and the confidence is used to characterize the credibility of the detection result.

[0110] In a feasible implementation, the perception impact factor is used to characterize the degree of influence of a dynamic event on the detection process of a map element; the positioning impact factor is used to characterize the degree of influence of a dynamic event on the terminal device's positioning of itself.

[0111] Optionally, the greater the impact of the dynamic event on the map element detection process of the first terminal device, the greater the perception impact factor, and the smaller the impact of the dynamic event on the map element detection process of the first terminal device, the smaller the perception impact factor; when the greater the impact of the dynamic event on the first terminal device's own positioning, the greater the positioning impact factor, and the smaller the impact of the dynamic event on the first terminal device's own positioning, the smaller the positioning impact factor.

[0112] Optionally, for different dynamic events, their corresponding perception impact factors and positioning impact factors may be predefined quantized values, as shown in Table 1 and Table 2 below.

[0113] It should be understood that other corresponding relationships may be used to characterize the relationship between the degree of impact of a dynamic event on the terminal device's map element detection process and the perception impact factor, or to characterize the relationship between the degree of impact of a dynamic event on the terminal device's self-positioning and the positioning impact factor, and this application does not impose specific limitations on this. For example, when the degree of impact of a dynamic event on the terminal device's map element detection process is greater, the perception impact factor is smaller, or when the degree of impact of a dynamic event on the terminal device's self-positioning is greater, the positioning impact factor is smaller.

[0114] Optionally, the time information of the dynamic event includes one or more of the start time of the dynamic event, the expected duration of the dynamic event, and the expected end time of the dynamic event.

[0115] Optionally, Table 1 and Table 2 may be template examples of perception influencing factors and positioning influencing factors corresponding to two predefined dynamic events, namely, traffic congestion and weather conditions.

[0116] Traffic congestion level Perceived Impact Factor Positioning impact factor serious 4.0 2.0 medium 2.0 1.5 slight 1.0 1.0

[0117] Table 1: Templates of perception impact factors and positioning impact factors corresponding to traffic congestion events

[0118] Weather conditions Perceived Impact Factor Positioning impact factor heavy rain 4.0 2.0 moderate rain 3.0 1.5 light rain 2.0 1.0 sunny 1.0 1.0

[0119] Table 2: Templates of perception and positioning impact factors corresponding to weather events

[0120] Please refer to Table 1, which is a template of perception impact factors and positioning impact factors corresponding to traffic congestion events. As shown in Table 1, the congestion levels of traffic congestion events can include three categories: severe congestion, moderate congestion and slight congestion. Traffic congestion events with different congestion levels can correspond to different perception impact factors and positioning impact factors. It can be seen from Table 1 that the more severe the traffic congestion level, the greater the corresponding perception impact factor and positioning impact factor, that is, when the dynamic event occurs, the greater the impact of the dynamic event on the process of map element detection by the terminal device, and the greater the impact on the terminal device obtaining its own location information; conversely, the smaller the traffic congestion level, the smaller the corresponding perception impact factor and positioning impact factor, that is, when the dynamic event occurs, the smaller the impact of the dynamic event on the process of map element detection by the terminal device, and the smaller the impact on the terminal device obtaining its own location information.

[0121] Please refer to Table 2, which shows the templates for the perception and positioning impact factors corresponding to weather events. As shown in Table 2, weather conditions can be classified into four categories: heavy rain, moderate rain, light rain, and clear weather. Different weather conditions correspond to different perception and positioning impact factors. As can be seen from Table 2, when rainfall is heavy, the corresponding perception and positioning impact factors are larger; when rainfall is light or clear weather occurs, the corresponding perception and positioning impact factors are smaller.

[0122] It should be understood that Tables 1 and 2 are only specific examples of the perception impact factors and positioning impact factors corresponding to two types of dynamic events provided in the embodiments of this application. The perception impact factors and positioning impact factors corresponding to other dynamic events can be defined with reference to the formats of Tables 1 and 2, or represented using templates in other formats. This application does not impose specific limitations on this. For example, the perception impact factors and positioning impact factors corresponding to different dynamic events can be represented using letters or other data formats.

[0123] Optionally, weather events may also include fog, haze, snow, and hail.

[0124] In a feasible implementation, the first terminal device determines the confidence of the detection result based on at least one of the positioning influence factor, the perception influence factor, and the time information of the dynamic event, including: when the process of the first terminal device detecting the map elements in the map element list is within the expected duration of the dynamic event, determining the confidence of the detection result based on the positioning influence factor and / or the perception influence factor.

[0125] Optionally, when the detection process of the above-mentioned detection results is within the expected duration of a dynamic event, a discount factor can be determined based on the perception impact factor and / or positioning impact factor of the dynamic event, and the discount factor can be multiplied by the initial confidence to obtain the confidence of the detection result; wherein, the above-mentioned initial confidence can be predefined, and this application does not make specific limitations on this.

[0126] For example, when the current dynamic event is the severe traffic congestion shown in Table 1, the perception impact factor and positioning impact factor of the dynamic event are 4.0 and 2.0 respectively; the initial confidence of the detection result is 1.0, and the discount factor can be calculated as 1 / (4.0+2.0)=0.17, and the confidence of the detection result is 0.17. Under this method of calculating the confidence of the detection result, the closer the confidence of the detection result is to 1, the higher the accuracy of the detection result; the closer it is to 0, the lower the accuracy of the detection result. It should be understood that those skilled in the art may also use other methods to determine the above-mentioned discount factor, and this application does not make specific limitations on this.

[0127] Optionally, different levels can be used to characterize the confidence of the detection results. The confidence of the detection result is determined based on one or more of the positioning influence factor, the perception influence factor, and the time information of the dynamic event. Table 3 shows a schematic diagram of the classification of the detection result confidence levels. This confidence level classification method is designed based on the perception influence factor and positioning influence factor templates shown in Tables 1 and 2. As shown in Table 3, based on the sum of the perception influence factor and the positioning influence factor of the dynamic event, the confidence of the detection result can be divided into five levels: level 1, level 2, level 3, level 4, and level 5. The higher the confidence level, the more accurate the detection result, and the lower the confidence level, the lower the accuracy of the detection result. For example, when the dynamic event is light rain, one of the weather events shown in Table 2, the sum of the perception influence factor and the positioning influence factor is 3. Referring to Table 3, it can be seen that when this dynamic event occurs, the confidence level of the detection result is level 4, that is, the confidence level at this time is level 4.

[0128]

[0129] Table 3: Confidence level classification table

[0130] It should be understood that for the perception influencing factors and positioning influencing factor templates shown in Tables 1 and 2, those skilled in the art may also use other methods to determine the confidence level of the above-mentioned detection results, and the embodiments of this application do not specifically limit this. In addition, when those skilled in the art use other perception influencing factors and positioning influencing factor templates, they may use corresponding methods to determine the confidence level of the detection results, and this application does not specifically limit this.

[0131] In one feasible implementation, when multiple independent dynamic events occur simultaneously, the navigation information corresponding to each of the multiple independent dynamic events may include corresponding perception influence factors and / or positioning influence factors. When the map element detection process falls within the expected duration of the multiple independent dynamic events, the confidence level of the detection result may be determined based on the perception influence factors and / or positioning influence factors of the multiple dynamic events simultaneously.

[0132] In one feasible implementation, the content included in the impact information for different dynamic events may be different. For example, when the dynamic event is a construction event, its impact information may include the impact range of the dynamic event, the lane accessibility status within the impact range, and a list of map elements; when the dynamic event is a weather event, its impact information may include the impact range of the dynamic event, the lane accessibility status within the impact range, and the perception impact factor; when the dynamic event is a safety warning event, its impact information may include the impact range of the dynamic event, the lane accessibility status within the impact range, a list of map elements, the perception impact factor, and the positioning impact factor.

[0133] It can be seen that in the embodiment of the present application, by setting different dynamic event impact information formats and contents for different types of dynamic events, for each dynamic event, only the content related to it needs to be set in its navigation information, thereby simplifying the data structure and effectively improving the data transmission efficiency between the terminal device and the server.

[0134] Optionally, the embodiment of the present application may define the navigation information corresponding to different dynamic events into a unified data format, that is, the navigation information corresponding to different dynamic events contains the same content items, which is not specifically limited in the embodiment of the present application.

[0135] In a feasible implementation manner, the impact range of the dynamic event includes location information of the dynamic event.

[0136] Specifically, the impact range of the dynamic event is greater than or equal to the range contained in the location information of the dynamic event. For example, when the dynamic event is a construction event, such as the closure of some lanes on the road, the specific location information of the dynamic event can be as follows: Figure 2 The example shows a section of road under construction marked with a roadblock. However, this road construction may cause congestion for a significant portion of the entire road, as well as for other roads adjacent to or intersecting it. In this case, the impact range of the construction event is the entire congestion area, which is larger than the range included in the dynamic event's location information. Optionally, the dynamic event's impact range can be a circular area centered at the dynamic event's location with a radius of N, where N is a positive number. The dynamic event's impact range can also be other predefined ranges, which are not specifically limited in this application.

[0137] In a feasible implementation, the above-mentioned dynamic event impact information also includes lane passability status information. Lane passability status information is used to describe the passability status of one or more lanes contained in each road within the dynamic event impact range, that is, whether the lanes within the dynamic event impact range are passable normally. For example, 0 can be used to represent a lane that is not passable and 1 can be used to represent a lane that is passable; when the dynamic event impact range includes Figure 2 If you are on the road shown (Road No. 857), Figure 2 The road shown contains three lanes (lane 1, lane 2, and lane 3), and the lane passability status information corresponding to the road can be: 857-1-0, 857-2-1, 857-3-1; among which, 857-1-0 represents that the first lane on road 857 is impassable, and 857-2-1 and 857-3-1 represent that the second lane and the third lane on road 857 are passable, respectively. It should be understood that those skilled in the art may also use other methods to characterize the impact range of dynamic events, including whether the lanes are passable normally, and this application does not limit this. Furthermore, when part of a lane is impassable, the information characterizing the passability status of the lane may also include the specific location information of the impassable section in the lane.

[0138] Optionally, the first terminal device receiving the navigation information may be a car, a vehicle-mounted terminal device, a handheld terminal device (such as a mobile phone) or a Figure 1 The roadside unit in this application is not specifically limited to this.

[0139] In a feasible implementation manner, the above navigation information may further include semantic information representing dynamic events.

[0140] Specifically, when the first terminal device is a vehicle, given the possibility of vehicle takeover during autonomous driving, the navigation information will also retain semantic information representing dynamic events, thereby achieving a certain degree of backward compatibility for autonomous vehicles (i.e., manual driving). The semantic information is information that can be understood by the driver, such as voice information or text information.

[0141] In one feasible implementation, the navigation information corresponding to different dynamic events uses the same transmission format. Transmitting navigation information for different dynamic events using the same transmission format can improve data transmission efficiency between the first terminal device and the server or second terminal device. When the first terminal device is a vehicle, this can effectively reduce data reception latency during autonomous driving, thereby improving the performance of the vehicle-side autonomous driving.

[0142] In a feasible implementation, the first terminal device can send the detection result and the confidence level of the detection result to multiple second terminal devices; wherein, each second terminal device can directly send the detection result and the confidence level of the detection result to the server or forward it to the server through other terminal devices. Further, optionally, when the second terminal device is a handheld terminal device or a vehicle-mounted terminal device, the second terminal device can update the map and navigation information accordingly based on the received detection result and the confidence level of the detection result, and use the updated map for navigation; wherein, the process of the second terminal device updating the map and navigation information accordingly can be referred to below. Figure 6 The corresponding process in the server in the described embodiment will not be repeated here.

[0143] See Figure 5 , Figure 5 This is a driving scene diagram of an autonomous vehicle provided in an embodiment of the present application. In this case, the autonomous vehicle in the diagram is the first terminal device in the above embodiment; the second terminal device can be a roadside unit within a certain range of the first terminal device, or a handheld terminal device, or a vehicle-mounted terminal device. Figure 5 As shown, the dynamic event is heavy rain, and the location information of the dynamic event contained in the navigation information can be the entire city where the current vehicle is located; the start time, expected duration and expected end time of the dynamic event contained in the time information of the dynamic event can be T1, 24 hours and T2 respectively; the impact information of the dynamic event can include perception impact factor, positioning impact factor, lane passability status information, map element list and the impact range of the dynamic event.

[0144] Among them, the perception influencing factors and positioning influencing factors of dynamic events can adopt the predefined templates shown in Table 2; the lane passability status information can include Figure 5 The traversable status of the four lanes of Road 1, Road 2, Road 3 and Road 4 shown in the figure; the map element list can contain Figure 5 The tree 1, lane line 1, gas station, and traffic light shown in the figure; the impact range of the dynamic event can be equal to the range of this rainfall.

[0145] After the vehicle receives the above navigation information from the server or the second terminal device, it downloads the map corresponding to the map version number from the server, marks the location and impact range of the dynamic event on the map, and navigates according to the received navigation information; at the same time, the map elements in the map element list are detected using the on-board equipment. When the attributes of the detected map elements change compared with the attributes of the corresponding map elements in the map, the detection results and the confidence level of the detection results are sent to the server or the second terminal device.

[0146] See Figure 6, a flowchart of another navigation method 600 provided in an embodiment of the present application. Figure 6 As shown, the method 600 includes step S610 and step S620. The method 600 is applied to the server side.

[0147] In step S610, the server sends navigation information to the terminal device, where the navigation information includes map information, location information of dynamic events, impact information of dynamic events, and time information of dynamic events; the impact information of dynamic events includes one or more of a list of map elements, a positioning impact factor, a perception impact factor, an impact range of dynamic events, and lane traffic status information.

[0148] Optionally, the above map information may be a map directly used for navigation or a map version number corresponding to the required map, which is not limited in this application.

[0149] Specifically, the navigation information sent by the server is Figure 3 The navigation information received by the terminal device in the embodiment is the same and will not be repeated here.

[0150] The terminal device may be a terminal device with a communication function or a terminal device with a navigation function (ie, a first terminal device or a second terminal device), for example, a vehicle-mounted terminal device, a handheld terminal device (such as a mobile phone) or a Figure 1 Roadside unit in.

[0151] In step S620, the server receives the detection results and the confidence levels of the detection results of the terminal device on the map elements in the map element list, and updates the map and navigation information based on the detection results and the confidence levels of the detection results; wherein the map is obtained based on the map information, and the confidence levels of the detection results are used to characterize the accuracy of the detection results.

[0152] Specifically, the above map element detection results and the process of determining the confidence level of the detection results can be found in Figure 3 The description in the embodiments will not be repeated here.

[0153] Optionally, when the map information contains a map, the terminal device can directly obtain the map from the map information; when the map information contains a map version number corresponding to the required map, the terminal device can download the map corresponding to the map version number from the server.

[0154] The map acquired by the terminal device includes corresponding map elements and corresponding attributes of the map elements.

[0155] Optionally, the above-mentioned updating of the map and navigation information based on the detection results and the confidence of the detection results may include: for the update of a certain map element on the map, when the server receives the detection results and the confidence of the detection results sent by other terminal devices, when multiple detection results sent by a preset proportion of terminal devices are the same, and the confidence of the multiple detection results are greater than or equal to a preset threshold, the server may update the attributes of the corresponding map element in the map according to the detection results sent by the terminal devices of the preset proportion; for the update of navigation information, the server may determine whether the expected duration, expected end time and lane passability of the dynamic event have changed based on the detection results of the above-mentioned preset proportion of terminal devices, and when they have changed, update the corresponding content in the navigation information.

[0156] In a feasible implementation, the perception impact factor is used to characterize the degree of influence of a dynamic event on the detection process of a map element; the positioning impact factor is used to characterize the degree of influence of a dynamic event on the terminal device's positioning of itself.

[0157] In a feasible implementation manner, the values ​​of the positioning influence factor and the perception influence factor are predefined quantitative values.

[0158] In a feasible implementation manner, the navigation information further includes semantic information representing dynamic events.

[0159] In a feasible implementation manner, the impact range of the dynamic event includes location information of the dynamic event.

[0160] In a feasible implementation manner, the transmission format of navigation information corresponding to different dynamic events is the same.

[0161] Specifically, the specific content and data transmission format of the above navigation information are the same as Figure 3 The descriptions in the illustrated embodiments are the same and will not be repeated here.

[0162] See Figure 7 , Figure 7 FIG. 7 is a structural diagram of a navigation device 700 provided in an embodiment of the present application. Figure 7 As shown, the apparatus 700 includes: a receiving unit 701 , a decision unit 702 , a detection unit 703 and a sending unit 704 .

[0163] The receiving unit 701 is used to receive navigation information, which includes one or more of a map, location information of a dynamic event, impact information of the dynamic event, and time information of the dynamic event; wherein the impact information of the dynamic event includes the impact range of the dynamic event.

[0164] The decision unit 702 is configured to perform navigation according to the map and navigation information.

[0165] In a feasible embodiment, the impact information of the dynamic event also includes a list of map elements, and the above-mentioned device 700 also includes: a detection unit 703, which is used to detect the map elements in the map element list to obtain the detection results of the map elements; a sending unit 704, which is used to send and receive the detection results to the server or the second terminal device to update the map and the corresponding navigation information.

[0166] In a feasible implementation, the sending unit 704 is specifically configured to send the detection result to the server when the attribute of the map element in the detection result is different from the attribute of the corresponding map element in the map.

[0167] In a feasible embodiment, the impact information of the dynamic event also includes one or more of the positioning impact factor and the perception impact factor. The decision unit 702 is further used to determine the confidence of the detection result based on one or more of the positioning impact factor, the perception impact factor and the time information of the dynamic event; the sending unit 704 is further used to send the confidence of the detection result to the server, and the confidence is used to characterize the credibility of the detection result; wherein, the perception impact factor is used to characterize the impact of the dynamic event on the detection process of the map element; the positioning impact factor is used to characterize the impact of the dynamic event on the terminal device when positioning itself.

[0168] In a feasible embodiment, in terms of determining the confidence of the detection result based on one or more of the positioning influence factor, the perception influence factor and the time information of the dynamic event, the decision unit 702 is specifically used to: when the process of the terminal device detecting the map elements in the map element list is within the expected duration of the dynamic event, determine the confidence of the detection result based on the positioning influence factor and / or the perception influence factor.

[0169] In a feasible implementation manner, the time information of the dynamic event includes one or more of the start time of the dynamic event, the expected duration of the dynamic event, and the expected end time of the dynamic event.

[0170] In a feasible implementation manner, the values ​​of the positioning influence factor and the perception influence factor are predefined quantitative values.

[0171] In a feasible implementation manner, the impact information of the dynamic event also includes lane passability status information.

[0172] In a feasible implementation manner, the impact range of the dynamic event includes location information of the dynamic event.

[0173] In a feasible implementation manner, the transmission format of navigation information corresponding to different dynamic events is the same.

[0174] See Figure 8 , Figure 8 This is a structural diagram of another navigation device 800 provided in an embodiment of the present application. Figure 8 As shown, the navigation device 800 includes a sending unit 801 , a receiving unit 802 and an updating unit 803 .

[0175] The sending unit 801 is configured to send navigation information to a terminal device, where the navigation information includes one or more of a map, location information of a dynamic event, impact information of the dynamic event, and time information of the dynamic event; the impact information of the dynamic event includes one or more of a map element list, a positioning impact factor, a perception impact factor, an impact range of the dynamic event, and lane traffic status information;

[0176] The receiving unit 802 is configured to receive a detection result of a terminal device detecting a map element in a map element list and a confidence level of the detection result;

[0177] The updating unit 803 is configured to update the map and navigation information according to the detection result and the confidence level of the detection result; wherein the confidence level of the detection result is used to represent the accuracy of the detection result.

[0178] In a feasible implementation manner, the time information of the dynamic event includes one or more of the start time of the dynamic event, the expected duration of the dynamic event, and the expected end time of the dynamic event.

[0179] In a feasible implementation, the perception impact factor is used to characterize the degree of influence of a dynamic event on the detection process of a map element; the positioning impact factor is used to characterize the degree of influence of a dynamic event on the terminal device's positioning of itself.

[0180] In a feasible implementation manner, the values ​​of the positioning influence factor and the perception influence factor are predefined quantitative values.

[0181] In a feasible implementation manner, the navigation information further includes semantic information representing dynamic events.

[0182] In a feasible implementation manner, the impact information of the dynamic event also includes lane passability status information.

[0183] In a feasible implementation manner, the impact range of the dynamic event includes location information of the dynamic event.

[0184] Figure 9FIG2 is a schematic diagram of the hardware structure of a device 900 provided in this application. The device may be the navigation device 700 or the navigation device 800 in the above-described embodiment method. The device 900 includes a processor 901, a memory 902, and a communication port 903. The processor 901, the communication port 903, and the memory 902 may be interconnected or connected via a bus 904.

[0185] Exemplarily, the memory 902 is used to store computer programs and data of the device 900. The memory 902 may include, but is not limited to, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), or portable read-only memory (CD-ROM).

[0186] In implementation Figure 9 In the case of the embodiment shown, execution Figure 9 The software or program codes required for the functions of all or part of the units in the EM700 are stored in the memory 902 .

[0187] In implementation Figure 9 In the embodiment, if the software or program code required for the functions of some units is stored in the memory 902, the processor 901 can not only call the program code in the memory 902 to implement some functions, but also cooperate with other components (such as the communication port 903) to complete the Figure 9 Other functions described in the embodiment (such as the function of receiving data).

[0188] There may be multiple communication ports 903 for supporting the device 900 to communicate, such as receiving or sending data or signals.

[0189] Exemplarily, the processor 901 may be a central processing unit, a general-purpose processor, a digital signal processor, an application-specific integrated circuit, a field programmable gate array or other programmable logic device, a transistor logic device, a hardware component, or any combination thereof. The processor may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a digital signal processor and a microprocessor, and the like. The processor 901 may be used to read the program stored in the memory 902, execute the above Figure 3 or Figure 6 The method and possible embodiments described are described. For example, Figure 3 In the embodiment, the communication port 903 can perform the following operations:

[0190] Receive navigation information; the navigation information includes one or more of map information, location information of dynamic events, impact information of dynamic events, and time information of dynamic events; wherein the impact information of dynamic events includes the impact range of dynamic events; the receiving operation may be Figure 3 The operation in step S310 is shown.

[0191] The processor 901 may perform the following operations:

[0192] Navigate based on the map and navigation information; the operations in this step can be Figure 3 The operation in step S320 is shown.

[0193] Figure 9 The specific operations and beneficial effects performed by the device 900 can be found in the above Figure 3 or Figure 6 The description of the method and its possible implementation methods will not be repeated here.

[0194] An embodiment of the present application further provides a device, which includes a processor, a communication port, and a memory. The device is configured to execute the method described in any one of the above embodiments and possible embodiments thereof.

[0195] In one possible implementation manner, the device is a chip or a system on a chip (SoC).

[0196] An embodiment of the present application further provides a computer-readable storage medium storing a computer program. The computer program is executed by a processor to implement the method described in any one of the above embodiments and possible embodiments thereof.

[0197] The embodiments of the present application further provide a computer program product. When the computer program product is read and executed by a computer, the method described in any one of the above embodiments and possible embodiments thereof will be executed.

[0198] The embodiments of the present application further provide a computer program, which, when executed on a computer, enables the computer to implement the method described in any one of the above embodiments and possible embodiments thereof.

[0199] In this application, the terms "first," "second," and the like are used to distinguish between identical or similar items having substantially the same function or effect. It should be understood that "first," "second," and "nth" do not have a logical or temporal dependency, nor do they limit the quantity or order of execution. It should also be understood that although the following description uses the terms "first," "second," and the like to describe various elements, these elements should not be limited by these terms. These terms are simply used to distinguish one element from another.

[0200] It should also be understood that in the various embodiments of the present application, the size of the serial number of each process does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0201] It will also be understood that the term “comprise” (also known as “includes,” “including,” “comprises,” and / or “comprising”) when used in this specification specifies the presence of stated features, integers, steps, operations, elements, and / or components, but does not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0202] It should also be understood that references throughout this specification to "one embodiment," "an embodiment," or "a possible implementation" mean that specific features, structures, or characteristics associated with an embodiment or implementation are included in at least one embodiment of this application. Therefore, the appearance of "in one embodiment," "in an embodiment," or "a possible implementation" throughout this specification does not necessarily refer to the same embodiment. Furthermore, these specific features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0203] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some or all of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A navigation method, characterized in that: The method comprises: The first terminal device receives navigation information, the navigation information including map information, location information of a dynamic event, impact information of the dynamic event, and time information of the dynamic event; wherein the impact information of the dynamic event includes an impact range of the dynamic event and a list of map elements, a positioning impact factor, and / or a perception impact factor; and the time information of the dynamic event includes an estimated duration of the dynamic event; The first terminal device detects the map elements in the map element list to obtain a detection result of the map element; When the process of detecting the map element in the map element list by the first terminal device is within the expected duration of the dynamic event, determining the confidence level of the detection result according to the positioning influence factor and / or the perception influence factor; wherein the confidence level of the detection result is used to represent the credibility of the detection result; The first terminal device sends the detection result and the confidence level of the detection result to the server or the second terminal device; The first terminal device performs navigation according to the map information and the navigation information.

2. The method according to claim 1, characterized in that The sending the detection result to the server or the second terminal device includes: When the attribute of the map element in the detection result is different from the attribute of the corresponding map element in the map, the first terminal device sends the detection result to the server or the second terminal device.

3. The method according to claim 2, characterized in that The perception impact factor is used to characterize the degree of influence of the dynamic event on the detection process of the map element; the positioning impact factor is used to characterize the degree of influence of the dynamic event on the first terminal device's positioning of itself.

4. The method according to any one of claims 1 to 3, characterized in that The time information of the dynamic event further includes one or more of the start time of the dynamic event and the expected end time of the dynamic event.

5. The method according to any one of claims 1 to 4, characterized in that The values ​​of the positioning impact factor and the perception impact factor are predefined quantitative values.

6. The method according to any one of claims 1 to 5, characterized in that The impact information of the dynamic event also includes lane passability status information.

7. The method according to any one of claims 1 to 6, characterized in that The navigation information also includes semantic information representing the dynamic event.

8. The method according to any one of claims 1 to 7, characterized in that The impact range of the dynamic event includes the location information of the dynamic event.

9. The method according to any one of claims 1 to 8, characterized in that The transmission format of the navigation information corresponding to different dynamic events is the same.

10. A navigation method, characterized in that: The method comprises: The server sends navigation information to the terminal device, the navigation information including map information, location information of the dynamic event, impact information of the dynamic event, and time information of the dynamic event; the impact information of the dynamic event includes a list of map elements, positioning impact factors, perception impact factors, impact range of the dynamic event, and lane traffic status information; the time information of the dynamic event includes an estimated duration of the dynamic event; The server receives a detection result of the terminal device detecting the map elements in the map element list and a confidence level of the detection result, and updates the navigation information and map based on the detection result and the confidence level of the detection result; wherein the map is obtained based on the map information, and the confidence level of the detection result is used to characterize the accuracy of the detection result.

11. The method according to claim 10, characterized in that The perception impact factor is used to characterize the degree of influence of the dynamic event on the detection process of the map element; the positioning impact factor is used to characterize the degree of influence of the dynamic event on the terminal device's positioning of itself.

12. The method according to claim 10 or 11, characterized in that The time information of the dynamic event further includes one or more of the start time of the dynamic event and the expected end time of the dynamic event.

13. The method according to any one of claims 10 to 12, characterized in that The values ​​of the positioning impact factor and the perception impact factor are predefined quantitative values.

14. The method according to any one of claims 10 to 13, characterized in that The navigation information also includes semantic information representing the dynamic event.

15. The method according to any one of claims 10 to 14, characterized in that The impact range of the dynamic event includes the location information of the dynamic event.

16. The method according to any one of claims 10 to 15, characterized in that The transmission format of the navigation information corresponding to different dynamic events is the same.

17. A navigation device, characterized in that: The device comprises: a receiving unit, configured to receive navigation information, the navigation information including map information, location information of a dynamic event, impact information of the dynamic event, and time information of the dynamic event; wherein the impact information of the dynamic event includes an impact range of the dynamic event and a list of map elements, a positioning impact factor, and / or a perception impact factor; and the time information of the dynamic event includes an estimated duration of the dynamic event; a detection unit, configured to detect the map elements in the map element list and obtain detection results of the map elements; a first decision unit, configured to determine, when the navigation device detects a map element in the map element list within an expected duration of the dynamic event, a confidence level of a detection result based on the positioning influence factor and / or the perception influence factor; wherein the confidence level of the detection result is used to represent a degree of credibility of the detection result; A sending unit, configured to send the detection result and the confidence level of the detection result to a server or a terminal device; The second decision unit is configured to perform navigation according to the map information and the navigation information.

18. The device according to claim 17, characterized in that The sending unit is specifically configured to: When the attribute of the map element in the detection result is different from the attribute of the corresponding map element in the map, the detection result is sent to the server or the terminal device.

19. The device according to claim 18, characterized in that The perception impact factor is used to characterize the degree of influence of the dynamic event on the detection process of the map element; the positioning impact factor is used to characterize the degree of influence of the dynamic event on the positioning of the navigation device itself.

20. The device according to any one of claims 17 to 19, characterized in that The time information of the dynamic event further includes one or more of the start time of the dynamic event and the expected end time of the dynamic event.

21. The device according to any one of claims 17 to 20, characterized in that The values ​​of the positioning impact factor and the perception impact factor are predefined quantitative values.

22. The device according to any one of claims 17 to 21, characterized in that The impact information of the dynamic event also includes lane passability status information.

23. The device according to any one of claims 17 to 22, characterized in that The navigation information also includes semantic information representing the dynamic event.

24. The device according to any one of claims 17 to 23, characterized in that The impact range of the dynamic event includes the location information of the dynamic event.

25. The device according to any one of claims 17 to 24, characterized in that The transmission format of the navigation information corresponding to different dynamic events is the same.

26. A navigation device, characterized in that: The device comprises: a sending unit, configured to send navigation information to a terminal device, the navigation information including map information, location information of a dynamic event, impact information of the dynamic event, and time information of the dynamic event; the impact information of the dynamic event including a list of map elements, a positioning impact factor, a perception impact factor, an impact range of the dynamic event, and lane traffic status information; and the time information of the dynamic event including an estimated duration of the dynamic event; a receiving unit, configured to receive a detection result of the terminal device detecting the map element in the map element list and a confidence level of the detection result; an updating unit, configured to update the navigation information and the map according to the detection result and the confidence level of the detection result; The map is obtained based on the map information, and the confidence level of the detection result is used to represent the accuracy of the detection result.

27. The device according to claim 26, characterized in that The perception impact factor is used to characterize the degree of influence of the dynamic event on the detection process of the map element; the positioning impact factor is used to characterize the degree of influence of the dynamic event on the terminal device's positioning of itself.

28. The device according to claim 26 or 27, characterized in that The time information package of the dynamic event further includes one or more of the start time of the dynamic event and the expected end time of the dynamic event.

29. The device according to any one of claims 26 to 28, characterized in that The values ​​of the positioning impact factor and the perception impact factor are predefined quantitative values.

30. The device according to any one of claims 26 to 29, characterized in that The navigation information also includes semantic information representing the dynamic event.

31. The device according to any one of claims 26 to 30, characterized in that The impact range of the dynamic event includes the location information of the dynamic event.

32. The device according to any one of claims 26 to 31, characterized in that The transmission format of the navigation information corresponding to different dynamic events is the same.

33. A terminal device, characterized in that: The method comprises a processor and a memory, wherein the processor and the memory are connected to each other, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is configured to call the program instructions to execute the method according to any one of claims 1 to 9.

34. A server, characterized in that: The method comprises a processor and a memory, wherein the processor and the memory are connected to each other, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is configured to call the program instructions to execute the method according to any one of claims 10 to 16.

35. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement the method of any one of claims 1 to 9 or 10 to 16.

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