CN115127568A

CN115127568A - Navigation method and device

Info

Publication number: CN115127568A
Application number: CN202110329885.XA
Authority: CN
Inventors: 刘建琴
Original assignee: Huawei Technologies Co Ltd
Current assignee: Huawei Technologies Co Ltd
Priority date: 2021-03-26
Filing date: 2021-03-26
Publication date: 2022-09-30
Also published as: WO2022199562A1

Abstract

The application discloses a navigation method and a navigation device, which relate to the technical field of automatic driving and comprise the following steps: the method comprises the steps that a first terminal device receives navigation information, wherein the navigation information comprises one or more of map information, position information of a dynamic event, influence information of the dynamic event and time information of the dynamic event; wherein, the influence information of the dynamic event comprises the influence range of the dynamic event; and the first terminal equipment carries out navigation according to the map information and the navigation information. The application provides an accurate and automatic driving-oriented dynamic event representation method, which is beneficial to realization of automatic driving.

Description

Navigation method and device

Technical Field

The application relates to the technical field of automatic driving, in particular to a navigation method and a navigation device.

Background

An automatic vehicle (Self-steering automatic vehicle) is also called an unmanned vehicle, a computer-driven vehicle or a wheeled mobile robot, and is an intelligent vehicle for realizing unmanned driving through a computer system. The automatic driving automobile depends on the cooperation of artificial intelligence, visual calculation, radar, positioning system and map system, so that the motor vehicle may be operated automatically and safely by computer without any active operation of human. Electronic map systems are used as tools for car navigation, and the accuracy and precision of maps are crucial to the safety of automatic driving cars. The actual road condition is often changed, and if the map used by the automobile is not updated timely, a relatively great potential safety hazard is brought to the safety of the automatic driving automobile.

Unlike static elements in a map, dynamic information or dynamic events generally need associated spatial information to accurately reflect the Location range information of the occurrence of the dynamic events, and we call this Location mapping of the dynamic events as Location Reference, i.e., the Location mapping of the dynamic events.

In the prior art, the characterization modes of dynamic events (such as traffic accidents and traffic jams) are mainly an absolute geographic characterization mode and a predefined ID identification mode.

However, the definition and characterization of the dynamic events in the prior art are mainly human-oriented and do not support automatic driving-oriented machines.

Disclosure of Invention

The embodiment of the application provides a navigation method and a navigation device, the navigation method provides a dynamic event representation mode for an automatic driving-oriented machine, and the accuracy of expression of dynamic events is improved, so that the automatic driving function is better realized.

In a first aspect, the present application provides a navigation method, including: the method comprises the steps that a first terminal device receives navigation information, wherein the navigation information comprises one or more of map information, position information of a dynamic event, influence information of the dynamic event and time information of the dynamic event; wherein, the influence information of the dynamic event comprises the influence range of the dynamic event; and the first terminal equipment carries out navigation according to the map information and the navigation information.

It can be seen that, in the embodiment of the present application, the influence information and the time information of the dynamic event are introduced into the navigation information to characterize the dynamic event, where the influence information of the dynamic event includes an influence range of the dynamic event, and the precise description of the dynamic event is realized by the above characterization mode of the dynamic event, and the characterization mode is easy to be recognized by a machine, so that the method can be applied to the technical field of automatic driving to realize the function of automatic driving.

In a possible implementation manner, the influence information of the dynamic event further includes a map element list, and the method further includes: the first terminal equipment detects the map elements in the map element list to obtain the detection result of the map elements, and sends the detection result to the server or the second terminal equipment so as to update the navigation information and the map; wherein the map is derived based on the map information.

It can be seen that, in the embodiment of the present application, the influence information of the dynamic event further includes a map element list, and when the terminal device receives the map element list, the terminal device can be triggered to detect the attributes corresponding to the map elements in the map element list, so as to obtain the detection result of the map elements; for example, when the map element is a lane line, the corresponding attribute may include a lane line color and a lane line width. When the terminal device is an automatic driving vehicle, different dynamic events can trigger different behaviors of the automatic driving vehicle, for example, a vehicle sensor and/or a vehicle-mounted camera is used for collecting related data, a detection result of a map element is obtained, and the detection result is sent to a server or a second terminal device to update the map, so that the real-time update of the map is realized; the server is ensured to send the updated map to the vehicle end next time, so that the vehicle end can better realize the function of automatic driving.

In a possible implementation manner, the sending the detection result to the server or the second terminal device includes: and 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 equipment sends the detection result to the server or the second terminal equipment.

It can be seen that, in the embodiment of the present application, 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 terminal device is triggered to send the detection result to the server, so as to implement update of the map element by the server, that is, the map is updated according to the actual situation, and it is ensured that the subsequent terminal device receives the latest map, and when the terminal device is an autonomous vehicle, the autonomous function is better implemented.

In a possible embodiment, the influence information of the dynamic event further includes at least one of a localization influence factor and a perception influence factor, and the method further includes: the first terminal device determines the confidence degree of the detection result according to at least one of the positioning influence factor, the perception influence factor and the time information of the dynamic event, and sends the confidence degree of the detection result to the server or the second terminal device, wherein the confidence degree of the detection result is used for representing the confidence degree of the detection result.

It can be seen that, in the embodiment of the present application, the influence information of the dynamic event further includes at least one of a positioning influence factor and a sensing influence factor, and the confidence of the detection result, that is, the credibility of the detection result, is determined by at least one of the positioning influence factor, the sensing influence 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, the updated map is more accurate, it is ensured that the subsequent terminal device receives the accurate map, and when the terminal device is an automatically-driven vehicle end, the function of automatic driving is better achieved.

In a possible implementation manner, the above-mentioned perceptual influence factor is used to characterize the influence degree of the dynamic event on the detection process of the map element; the positioning influence factor is used for representing the influence degree of the dynamic event on the positioning of the terminal equipment.

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 influence degree of the dynamic event on the detection process, so that the confidence degree of the detection result is determined by using the perception influence factor and the positioning influence factor, and the accuracy degree of the detection result can be accurately reflected, so that the subsequent server can adaptively update the map based on the confidence degree.

In a possible implementation manner, the determining, by the first terminal device, the confidence of the detection result according to at least one of the positioning impact factor, the perceptual impact factor, and the time information of the dynamic event includes: and when the process of detecting the map elements in the map element list by the first terminal equipment is within the predicted duration of the dynamic event, determining the confidence degree of the detection result according to the positioning influence factor and/or the perception influence factor.

It can be seen that, in the embodiment of the present application, when the process of detecting the map elements in the map element list by the terminal device is within the expected duration of the dynamic event, that is, when the dynamic event is still continuing, the dynamic event may have a certain influence on the detection process of the terminal device, so that 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, and when the subsequent terminal device is an automatically-driven vehicle end, the function of automatic driving is better achieved by receiving the updated map.

In one possible implementation, the time information of the dynamic event includes one or more of a start time of the dynamic event, an expected duration of the dynamic event, and an expected end time of the dynamic event.

It can be seen that, in the embodiment of the present application, the time information of the dynamic event may assist the first terminal device in determining whether the detection process of the first terminal device is under the influence of the dynamic event, so as to determine whether the confidence of the detection result needs to be determined by using the sensing influence factor and the positioning influence factor corresponding to the dynamic event, so as to obtain an accurate confidence result, and facilitate a subsequent server to accurately update the map.

In a possible embodiment, the values of the localization impact factors and the perception impact factors are predefined quantization values.

It can be seen that, in the embodiment of the present application, the values of the positioning impact factors and the sensing impact factors are predefined quantized values, and the quantized sensing impact factors and the positioning impact factors can be more easily identified and processed by a machine, so that the data structure supports an automatic driving-oriented machine, and is beneficial to realizing an automatic driving function.

In a possible embodiment, the influence information of the dynamic event further includes lane passable state information.

It can be seen that, in the embodiment of the present application, the influence information of the dynamic event further includes lane passable state information, and the lane passable state information may be all or part of lane passable state information within the influence range of the dynamic event. By introducing the passable lane state information into the navigation information, when the terminal equipment is an automatic driving vehicle end, decision and path planning can be carried out in advance according to the passable lane state, so that an effective automatic driving function is realized.

In a possible embodiment, the navigation information further includes semantic information characterizing the dynamic event.

It can be seen that, in the embodiment of the present application, when the terminal device is an automatic driving vehicle end, semantic information facing a human driver is retained in the navigation information, so that when an automatic driving vehicle is taken over manually, the semantic information contained in the navigation information can be used for navigation, thereby implementing compatibility between automatic driving and manual driving.

In a possible embodiment, the influence range of the dynamic event includes position information of the dynamic event.

It can be seen that, in the embodiment of the present application, since the influence range of the dynamic event is greater than or equal to the range included in the position information of the dynamic event, and the influence range of the dynamic event has a reference value for the automatic driving vehicle end in performing the path planning, the embodiment of the present application assists the automatic driving vehicle end in planning the optimal driving path by introducing the influence range of the dynamic event into the navigation information, thereby implementing an effective automatic driving function.

In one possible embodiment, the navigation messages corresponding to different dynamic events have the same transmission format.

It can be seen that, in the embodiment of the present application, the navigation information corresponding to different dynamic events can adopt the same transmission format for data transmission, so that the data interaction between the terminal device and the server is more efficient, the terminal device can quickly receive the navigation information of the dynamic events, and accurate navigation is realized according to the navigation information.

In a second aspect, the present application provides a navigation method, comprising: the server sends navigation information to the terminal equipment, wherein the navigation information comprises one or more of map information, position information of the dynamic event, influence information of the dynamic event and time information of the dynamic event; the influence information of the dynamic event comprises one or more of a map element list, a positioning influence factor, a perception influence factor, an influence range of the dynamic event and lane traffic state information; the server receives a detection result and the confidence coefficient of the detection result of the terminal equipment for detecting the map elements in the map element list, and updates the map and the navigation information according to the detection result and the confidence coefficient of the detection result; the map is obtained based on map information, and the confidence degree of the detection result is used for representing the accuracy degree of the detection result.

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, position information of the dynamic event, influence information of the dynamic event, and time information of the dynamic event, and the influence information of the dynamic event includes various related information easily recognized by the machine, so as to implement accurate information indication of the dynamic event, so that the terminal device can quickly and accurately process and make decisions and perform navigation after receiving the navigation information; when the terminal equipment is an automatic driving vehicle end, the automatic driving function can be effectively realized by the vehicle end conveniently. Meanwhile, the server can receive the detection results and the corresponding confidence degrees sent by different terminal devices, and analyze and process the received detection results and the confidence degrees to realize accurate updating of the map and the navigation information, so that subsequent terminal devices can receive accurate navigation information, and accurate navigation of the terminal devices is facilitated.

In a possible implementation manner, the above-mentioned perception impact factor is used for characterizing the degree of impact of the dynamic event on the detection process of the map element; the positioning influence factor is used for representing the influence degree of the dynamic event on the positioning of the terminal equipment.

It can be seen that, in the embodiment of the present application, the sensing impact factor and the positioning impact factor are used to characterize the impact degree of the dynamic event on the detection process, so that after the server sends the sensing impact factor and the positioning impact factor to the terminal device, the terminal device can determine the confidence of the detection result by using the sensing impact factor and the positioning impact factor, thereby accurately reflecting the accuracy of the detection result.

In a possible embodiment, the values of the localization impact factors and the perception impact factors are predefined quantized values.

In one possible embodiment, the influencing information of the dynamic event also includes lane passable status information.

It can be seen that, in the embodiment of the present application, the vehicle-to-passable status information may be all or part of lane passable status information within the influence range of the dynamic event. By introducing the passable lane state information into the navigation information sent by the server, when the terminal equipment is an automatic driving vehicle end, the terminal equipment can make a decision and plan a path in advance according to the passable lane state, so that an effective automatic driving function is realized.

It can be seen that, in the embodiment of the present application, the navigation information sent by the server to the center device further includes semantic information representing a dynamic event, and when the terminal device is an autonomous driving vehicle, semantic information facing a human driver is retained in the navigation information, so that when the autonomous driving vehicle is taken over manually, the semantic information included in the navigation information can be used for navigation, thereby implementing compatibility between autonomous driving and manual driving.

The beneficial effects of the two embodiments are the same as those of the corresponding embodiment of the first aspect, and are not described herein again.

In a third aspect, the present application provides a navigation device comprising means for performing the method of the first aspect.

In a fourth aspect, the present application provides a navigation device comprising means for performing the method of the second aspect.

In a fifth aspect, the present application provides a terminal device comprising a processor and a memory, the processor and the memory being interconnected, wherein the memory is configured to store a computer program comprising program instructions, and the processor is configured to invoke the program instructions to perform the method according to any of the first aspect.

In a sixth aspect, the present application provides a server comprising a processor and a memory, the processor and the memory being interconnected, wherein the memory is used for storing a computer program comprising program instructions, and the processor is configured to invoke the program instructions to perform the method according to any one of the second aspects.

In a seventh aspect, the present application provides a computer readable storage medium storing a computer program for execution by a processor to implement the method of any one of the first or second aspects.

Drawings

The drawings used in the embodiments of the present application are described below.

Fig. 1 is an architecture diagram of a system to which a navigation method is applied in an embodiment of the present application;

FIG. 2 is a schematic diagram of a scenario of a dynamic event in an embodiment of the present application;

FIG. 3 is a flow chart illustrating a navigation method according to an embodiment of the present application;

FIG. 4 is a diagram illustrating a data structure of navigation information according to an embodiment of the present application;

FIG. 5 is a driving scene diagram of an automatic driving vehicle end in the embodiment of the present application;

FIG. 6 is a flow chart illustrating another navigation method in an embodiment of the present application;

FIG. 7 is a schematic structural diagram of a navigation device in an embodiment of the present application;

FIG. 8 is a schematic structural diagram of another navigation device in the embodiment of the present application;

fig. 9 is a schematic hardware structure diagram of an apparatus in an embodiment of the present application.

Detailed Description

The embodiments of the present application are described below with reference to the drawings. The map mentioned in the embodiment of the present application may be a high-precision map, or may be a conventional navigation map, which is not specifically limited in the present application.

The following description will exemplarily describe a scenario in which the embodiment of the present invention is applicable.

For example, the navigation method provided by the application can be applied to the field of automatic driving. In the field of autonomous driving, navigation is usually performed with the aid of high-precision maps. The high-precision map can describe the road more accurately, clearly and comprehensively, and can reflect various dynamic events in the road in real time, so that a plurality of pre-judging spaces can be provided for vehicles, driving planning can be performed in advance, and the driving stability and economy are ensured. In addition, the high-precision map can help the vehicle to reduce the calculated amount, when the vehicle needs to pass through the intersection, the vehicle needs to sense the state of the front signal lamp in advance, and the high-precision map can help the vehicle to be positioned in the specific area where the signal lamp is located, so that the calculated amount of full-range scanning identification is effectively reduced. With the continuous development of the fields of automatic driving, intelligent auxiliary driving, traffic networking and the like, high-precision maps gradually become tools for better serving the fields.

The navigation method provided by the application can also be applied to other fields, and is not limited to the automatic driving field introduced above.

In order to better realize the function of automatic driving, various dynamic events influencing the driving of the vehicle need to be expressed into a high-precision map so that the vehicle can sense the dynamic events, but at present, in the field of automatic driving, no uniform industry standard exists to represent navigation information corresponding to the dynamic events, so that the application provides a feasible and effective navigation method.

Optionally, the navigation method provided by the present application may be implemented in a server, a road side unit, a vehicle-mounted terminal device (for example, a vehicle or a processing device or unit in the vehicle), or a handheld terminal device (for example, a mobile phone), where the road side unit, the vehicle-mounted terminal device, and the handheld terminal device are collectively referred to as a terminal device in the present application.

For ease of understanding, reference may be made to fig. 1, which is a diagram illustrating a system architecture used by the navigation method provided herein. The system architecture may include a server 100, a vehicle 101, a roadside unit 102, and the like. The server 100 may include one or more servers, and a plurality of servers may form a server cluster. The server 100 may implement mutual communication with the vehicle 101 and the road side unit 102 through a network, and the road side unit 102 may also implement interactive communication with the vehicle 101.

The server 100 may interactively communicate with other devices to obtain information required by a high-precision map, for example, the server 100 may interactively communicate with a device such as a server of a traffic bureau to obtain traffic information, and for example, the server 100 may interactively communicate with a device such as a server of a weather bureau to obtain weather information, and the like. The vehicle 101 may be an autonomous vehicle, a semi-autonomous vehicle, or may also be a general vehicle, or the like.

If the navigation method provided by the present application is implemented in the server 100, the vehicle 101 may interact with the server 100 to obtain a high-precision map in the latest state. Alternatively, the server 100 may send the high-precision map of the latest state to the roadside unit 102, and the vehicle 101 and the roadside unit 102 acquire the map interactively.

If the navigation method provided by the present application is implemented in the roadside unit 102, the roadside unit 102 may acquire the latest information of various dynamic events from the server 100, and update the high-precision map based on the latest information, and then the vehicle 101 may interact with the roadside unit 102 to acquire the latest high-precision map.

If the navigation method provided by the present application is implemented in the vehicle 101, the vehicle 101 may obtain the latest information of various dynamic events from the server 100, and perform corresponding actions based on the latest information, so as to update the high-precision map for use.

It should be noted that the system architecture shown in fig. 1 is only an example, and as long as the system architecture to which the navigation method provided by the present application can be applied is within the protection scope of the present application, the present application does not limit the specific system architecture used.

The dynamic events in the present application may include some or all of the following events:

weather conditions: dynamic events such as air temperature conditions, air pressure conditions, humidity conditions, sunny days, cloudy days, windy conditions, haze conditions, rain conditions, lightning conditions, snow conditions, frost conditions, lightning conditions, or hail conditions may be included.

Road covering situation or road surface environment: dynamic events such as water accumulation, snow accumulation, icing or breakage of road coverage may be included.

Road adhesion coefficient case: refers to the condition of the adhesion between the road and the vehicle tires, the greater the adhesion the less likely the vehicle will slip.

Road visibility situation: which may refer to the visible distance condition due to haze or light, etc.

Temporary point of interest (POI) case: dynamic events such as non-fixed points of interest, temporary available parking spaces, temporary available charging piles or temporary public service points can be included.

And (4) recommending information conditions: dynamic events such as user point of interest recommendations or trip suggestion recommendations may be included.

Road traffic conditions: dynamic events may include traffic accidents, traffic control, road construction, or accident prone locations.

The traffic flow situation is as follows: the number of traffic flows in each road may be included, and the like.

The traffic light state: dynamic events such as traffic light phase state, semantic information, timing data or working state may be included.

Vehicle obstacle: the type of vehicle causing the obstacle, motion information, vehicle door information, control information, driving behavior prediction information, or the like may be included.

Other obstacles: all obstacles other than vehicle obstacles may be included.

Risk early warning condition: information such as risk category (collision risk, landslide risk, etc. in each direction), risk level or avoidance advice, etc. may be included.

Cooperative driving conditions: the vehicle cooperation guiding information can be vehicle cooperation guiding information, and comprises lane merging cooperation, steering cooperation, special vehicle avoidance or parking and warehousing cooperation and the like.

And (3) path planning condition: it may refer to a planned route of a driving path or the like made according to the existing road conditions.

Road network topology change condition: the temporary drivable route change caused by the road traffic incident can be represented by a road route, a geometric expression change or an attribute change of a lane line and the like.

The above exemplarily introduces some dynamic events applied to the high-precision map, and in practical applications, the expression granularity of the dynamic events may be finer, for example, for a dynamic event of a weather state, when actually expressed in the high-precision map, the dynamic events may be expressed by events such as raining, snowing, or sunny days, and optionally, may be expressed by a specific event such as heavy rain, medium rain, light rain, and the like. By updating the tables in real time for the dynamic events to the high-precision map, various dynamic conditions in the road can be provided for the objects using the high-precision map such as vehicles in real time, and powerful references are provided for further route planning and behavior prediction. It should be noted that, the dynamic events actually used in the high-precision map are not limited to the above events, and the application does not limit the specific dynamic events and the number.

Referring to fig. 2, fig. 2 is a scene schematic diagram of a dynamic event according to an embodiment of the present disclosure. As shown in fig. 2, the dynamic event shown in fig. 2 is a construction-type event, and navigation information corresponding to the dynamic event, which is sent to the terminal device by the server in the prior art, will be described below with reference to fig. 2. The representation manner of the navigation information corresponding to the construction type event shown in fig. 2 may be: starting from a position 1km away from the driving direction of the vehicle, narrowing a lane within a range of 3.5km in the same direction; starting at a distance of 2km from the driving direction of the vehicle, lanes within a range of 1.5km in the same direction are closed. At this time, the characterization mode of the construction dynamic event mainly faces to human drivers and is easy to understand by the drivers.

Referring to fig. 3, fig. 3 is a flowchart illustrating a navigation method 300 according to an embodiment of the present disclosure. As shown in fig. 3, the method 300 includes steps S310 and S320. The method 300 is applied to the first terminal device side.

Step S310, the first terminal equipment receives navigation information, wherein the navigation information comprises one or more of map information, position information of a dynamic event, influence information of the dynamic event and time information of the dynamic event; wherein, the influence information of the dynamic event comprises the influence range of the dynamic event.

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

For example, the data structure of the navigation information of the dynamic event may be as shown in fig. 4, that is, the navigation information of the dynamic event may include map information, location information of the dynamic event, influence information of the dynamic event, and time information of the dynamic event; the position information of the dynamic event refers to the position of the dynamic event in the map, and the position information of the dynamic event is represented by using map elements in the map. For example, the method for representing the location information of the dynamic event may be: and a splash is positioned on the fifth road and 200 meters away from the second traffic signal lamp within 1 meter of radius.

Alternatively, 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, posts, fences, trees, flower beds, and buildings.

Optionally, the map may be a high-precision map, which is not specifically limited in this application.

Optionally, the first terminal device may receive the navigation information from a server or a second terminal device; the first terminal device may 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, a tablet, and the like); the second terminal device may be a terminal device with a communication function, such as a vehicle-mounted terminal device, or a road side unit, or a handheld terminal device.

And step S320, the first terminal equipment navigates according to the map information and the navigation information.

Specifically, the first terminal device obtains a map based on the map information, and plans a reasonable travel route for the terminal device according to the position information of the dynamic event in the map, the influence 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-driving vehicle, the vehicle can automatically plan a reasonable driving route according to the received navigation information, so that the influence of a dynamic event on driving of a vehicle end is avoided, and the driving time is saved. Specifically, when the time when the vehicle end receives the navigation information is within the expected duration of the dynamic event time information, it indicates that the dynamic event continues to exist, and at this time, the optimal driving route of the vehicle can be planned according to the influence range of the dynamic event and/or the position information of the dynamic event. And when the influence range of the dynamic event is equal to the range contained in the position information of the dynamic event, planning the driving route of the vehicle according to the influence range of the dynamic event or the position information of the dynamic event.

The map acquired by the first terminal device comprises corresponding map elements and corresponding attributes of the map elements.

Alternatively, when the map information contains a map, the first terminal device may directly acquire the map from the map information; when the map information includes a map version number corresponding to a desired map, the first terminal device may download a map corresponding to the map version number from the server.

It can be seen that, in the embodiment of the present application, the influence information of the dynamic event further includes a map element list, and when the first terminal device receives the map element list, the first terminal device may be triggered to detect the attribute corresponding to the map element in the map element list, so as to obtain the detection result of the map element. When the first terminal device is an autonomous vehicle, different dynamic events can trigger different behaviors of the autonomous vehicle, for example, a vehicle sensor and/or a vehicle-mounted camera is used for collecting related data, a detection result of a map element is obtained, and the detection result is sent to a server or a second terminal device to update the map, so that the map is updated in real time; the server is ensured to send the updated map to the first terminal device and the second terminal device next time, so that the vehicle can better realize the function of automatic driving.

In a possible implementation manner, the influence information of the dynamic event further includes a map element list, and the method further includes: the first terminal device detects the map elements in the map element list to obtain 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.

Specifically, the detection result includes attributes such as size, shape, color, and position of the map element in the map element list. When the first terminal device is a vehicle end, map elements in the map element list can be detected through vehicle-mounted devices such as a vehicle-mounted radar and/or a vehicle-mounted camera, and attributes such as size, shape and color of the map elements are obtained. It should be understood that the corresponding attributes may be different for different map elements, for example, when the map element is a lane line, the corresponding attributes may include a lane line color and width.

Optionally, the map elements in the map acquired by the first terminal device include map elements in the map element list.

Optionally, the first terminal device may determine the real-time position of the map element through a satellite positioning system, a vehicle-mounted radar, and/or a vehicle-mounted camera, where the detection result includes real-time position information of some or all map elements in the map element list. The satellite Positioning System may be a Global Positioning System (GPS), a galileo System, a glonass System, or a beidou System, which is not specifically limited in this application.

In a possible implementation manner, the sending the detection result to the server includes: and 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 equipment sends the detection result to the server or the second terminal equipment.

Specifically, when one or more of the attributes such as the size, shape, color, and position of the map element in the detection result are different from the corresponding attribute of the map element in the map, the first terminal device transmits 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 may forward the detection result to the server directly or forward the detection result to the server through other terminal devices.

Optionally, after receiving the detection result, the server may update the map according to the detection result, and the following embodiment will specifically describe an update process of the map and the navigation information.

Alternatively, the map elements included in the map element list may include a part of the map elements in the influence range of the dynamic event, all of the map elements in the influence range of the dynamic event, or map elements outside the influence range of the dynamic event.

In a possible embodiment, the influence information of the dynamic event further includes at least one of a localization influence factor and a perception influence factor, and the method further includes: and the terminal equipment determines the confidence coefficient of the detection result according to at least one of the positioning influence factor, the perception influence factor and the time information of the dynamic event, and sends the confidence coefficient of the detection result to the server or the second terminal equipment, wherein the confidence coefficient is used for representing the confidence degree of the detection result.

In one possible embodiment, 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 influence factor is used for representing the influence degree of the dynamic event on the positioning of the terminal equipment.

Optionally, the perception influence factor is larger when the influence degree of the dynamic event on the map element detection process of the first terminal device is larger, and the perception influence factor is smaller when the influence degree of the dynamic event on the map element detection process of the first terminal device is smaller; the larger the influence degree of the dynamic event on the self-positioning of the first terminal equipment is, the larger the positioning influence factor is, and the smaller the influence degree of the dynamic event on the self-positioning of the first terminal equipment is, the smaller the positioning influence factor is.

Alternatively, for different dynamic events, their corresponding perceptual and localization impact factors may be predefined quantized values, as shown in tables 1 and 2 below.

It should be understood that other corresponding relations may also be used to represent the relationship between the influence degree of the dynamic event on the map element detection process of the terminal device and the perception influence factor, or to represent the relationship between the influence degree of the dynamic event on the self-positioning of the terminal device and the positioning influence factor, which is not specifically limited in this application. For example, the perception influence factor is smaller when the dynamic event has a greater influence on the map element detection process performed by the terminal device, or the positioning influence factor is smaller when the dynamic event has a greater influence on the self-positioning of the terminal device.

Optionally, the time information of the dynamic event includes one or more of a start time of the dynamic event, a predicted duration of the dynamic event, and a predicted end time of the dynamic event.

Alternatively, table 1 and table 2 may be template examples of the perception impact factor and the localization impact factor corresponding to two types of dynamic events, namely, predefined traffic congestion and weather conditions, respectively.

Degree of traffic congestion	Perception influence factor	Localization of influence factors
			Severe severity of disease	4.0	2.0
Medium and high grade	2.0	1.5
			Slight, it is a little	1.0	1.0

Table 1: perception influence factor and positioning influence factor template corresponding to traffic jam event

Weather conditions	Perception influence factor	Localization of influence factors
			Heavy rain	4.0	2.0
Medium rain	3.0	1.5
			Light rain	2.0	1.0
Clear and clear	1.0	1.0

Table 2: perception influence factor and positioning influence factor template corresponding to weather event

Please refer to table 1, where table 1 shows a perception impact factor and a positioning impact factor template corresponding to a traffic congestion event. As shown in table 1, the congestion level of a traffic congestion event may include three types: severe congestion, moderate congestion, and light congestion. Traffic congestion events of different congestion degrees may correspond to different perception impact factors and localization impact factors. As can be seen from table 1, the more serious the traffic congestion is, the larger the corresponding perception influence factor and positioning influence factor are, that is, when the dynamic event occurs, the larger the influence of the dynamic event on the process of map element detection performed by the terminal device is, and the larger the influence on the terminal device for acquiring the position information of the terminal device is; on the contrary, the smaller the traffic congestion degree is, the smaller the corresponding perception influence factor and positioning influence factor are, that is, when the dynamic event occurs, the smaller the influence of the dynamic event on the process of map element detection of the terminal device is, and the smaller the influence on the terminal device for acquiring the position information of the terminal device is.

Please refer to table 2, table 2 shows the perception impact factor and the positioning impact factor template corresponding to the weather event. As shown in table 2, the weather conditions may include four categories: heavy rain, medium rain, light rain and clear. Different weather may correspond to different perception impact factors and localization impact factors. As can be seen from table 2, when the rainfall is large, the corresponding perception influence factor and positioning influence factor are larger; when the rainfall is small or clear, the corresponding perception influence factor and the corresponding positioning influence factor are smaller.

It should be understood that tables 1 and 2 are only specific examples of the perceptual impact factors and the positioning impact factors corresponding to the two types of dynamic events given in the embodiment of the present application, and the perceptual impact factors and the positioning impact factors corresponding to other dynamic events may be defined with reference to the formats in tables 1 and 2, or may be characterized by using templates in other formats, which is not specifically limited in this application. For example, the perception impact factor and the localization impact factor corresponding to different dynamic events may be characterized by letters or other format data.

Optionally, the weather-like events may also include fog, haze, snow, hail, and the like.

In a possible implementation manner, the determining, by the first terminal device, the confidence of the detection result according to at least one of the positioning impact factor, the perceptual impact factor, and the time information of the dynamic event includes: and when the process of detecting the map elements in the map element list by the first terminal device is within the predicted duration of the dynamic event, determining the confidence degree of the detection result according to the positioning influence factor and/or the perception influence factor.

Optionally, when the detection process of the detection result is within the predicted duration of the dynamic event, a discount factor may be determined according to the perceptual influence factor and/or the localization influence factor of the dynamic event, and the initial confidence coefficient is multiplied by the discount factor to obtain the confidence coefficient of the detection result; the initial confidence may be predefined, and this is not specifically limited in this application.

For example, when the current dynamic event is a severe traffic jam shown in table 1, the perceptual impact factor and the localization impact factor of the dynamic event at this time are 4.0 and 2.0, respectively; the initial confidence of the detection result is 1.0, and the discount factor may be calculated in a manner of 1/(4.0+2.0) ═ 0.17, where the confidence of the detection result is 0.17. Under the calculation mode of the confidence coefficient of the detection result, the closer the confidence coefficient of the detection result is to 1, the higher the accuracy of the detection result is; the closer to 0, the lower the accuracy of the detection result. It should be understood that other ways of determining the discount factor may be used by those skilled in the art, and the application is not limited thereto.

Alternatively, different levels may be used to characterize the confidence of the detection results. And determining the confidence of the detection result according to one or more of the positioning influence factor, the perception influence factor and the time information of the dynamic event. Table 3 is a schematic diagram of the detection result confidence level classification, and the confidence level classification method is designed based on the perception influence factor and the positioning influence factor templates shown in tables 1 and 2. As shown in table 3, according to the difference between the sum of the perception impact factor and the positioning impact factor of the dynamic event, the confidence of the detection result can be divided into 5 levels, which are respectively a first level, a second level, a third level, a fourth level and a fifth level; the higher the confidence level, the higher the accuracy of the detection result, and the lower the confidence level, the lower the accuracy of the detection result. For example, when the dynamic event is a light rain in the weather event shown in table 2, the sum of the perception impact factor and the localization impact factor at this time is 3. Referring to table 3, it can be seen that: when the dynamic event occurs, the confidence level of the detection result is four levels, that is, the confidence at this time is four levels of confidence.

Table 3: confidence level division table

It should be understood that, for the perception impact factor and localization impact factor templates shown in table 1 and table 2, a person skilled in the art may also use other ways to determine the confidence of the detection result, and this is not specifically limited in the embodiment of the present application. In addition, when the skilled person uses other templates of the perception impact factor and the localization impact factor, the confidence of the detection result can be determined in a corresponding manner, which is not specifically limited in this application.

In a possible embodiment, when multiple independent dynamic events exist simultaneously, the navigation information corresponding to the multiple independent dynamic events may respectively include corresponding perception impact factors and/or positioning impact factors. When the detection process of the map element is within the predicted duration of the plurality of independent dynamic events, the confidence of the detection result can be determined according to the perception influence factors and/or the positioning influence factors of the plurality of dynamic events at the same time.

In one possible implementation, the content contained in its impact information may be different for different dynamic events. For example, when the dynamic event is a construction-type event, the influence information may include an influence range of the dynamic event, a passable lane state within the influence range, and a map element list; when the dynamic event is a weather event, the influence information of the dynamic event can comprise the influence range of the dynamic event, the passable state of the lane in the influence range and a perception influence factor; when the dynamic event is a safety early warning event, the influence information of the dynamic event can include the influence range of the dynamic event, the passable lane state in the influence range, a map element list, a perception influence factor and a positioning influence factor.

It can be seen that, in the embodiment of the application, different dynamic event influence information formats and contents are set for different types of dynamic events, and for each dynamic event, only the content related to the dynamic event needs to be set in the navigation information, so that the data structure is simplified, and the data transmission efficiency between the terminal device and the server is effectively improved.

Optionally, in the embodiment of the present application, the navigation information corresponding to different dynamic events may be defined in a uniform data format, that is, the content items included in the navigation information corresponding to different dynamic events are the same, which is not specifically limited in the embodiment of the present application.

Specifically, the influence range of the dynamic event is greater than or equal to the range included in the position information of the dynamic event. For example, when the dynamic event is a construction-type event, such as a partial lane closing on a road, the specific location information of the dynamic event may be a section of construction road identified by a roadblock as shown in fig. 2; however, the road construction may cause a long distance between the whole road and other roads adjacent to or intersecting with the road to be congested, and at this time, the influence range of the construction type event is the whole range in which traffic congestion occurs, and the range is larger than the range included in the position information of the dynamic event. Optionally, the influence range of the dynamic event may be a circular area with a radius of N and a position of the dynamic event as a center of a circle, where N is a positive number; the influence range of the dynamic event may also be other predefined ranges, which is not specifically limited in this application.

In a possible embodiment, the influence information of the dynamic event further includes lane passable state information. The lane passable state information is used for describing a passable state of one or more lanes contained in each road in the dynamic event influence range, namely whether the lanes in the dynamic event influence range can normally pass or not. For example, 0 may represent that the lane is not passable, and 1 may represent that the lane is passable; when the influence range of the dynamic event includes a road (road number: 857) as shown in fig. 2, the road shown in fig. 2 includes three lanes (lane 1, lane 2 and lane 3, respectively), and the passable state information of the lane corresponding to the road may be: 857-1-0, 857-2-1, 857-3-1; wherein 857-1-0 represents that the first lane on the road 857 is not passable, and 857-2-1 and 857-3-1 represent that the second lane and the third lane on the road 857 are passable, respectively. It should be understood that those skilled in the art may also use other ways to characterize the influence range of the dynamic event, including whether the lane can normally pass through, and the application is not limited thereto. Further, when a certain section of the lane is not accessible, the information representing the accessible state of the lane may further include specific position information of the inaccessible section in the lane.

Optionally, the first terminal device receiving the navigation information may be an automobile, a vehicle-mounted terminal device, a handheld terminal device (such as a mobile phone), or a road side unit in fig. 1, which is not specifically limited in this application.

In a possible implementation, the navigation information may further include semantic information characterizing the dynamic event.

Specifically, when the first terminal device is a vehicle end, in consideration of the possibility that the vehicle in the automatic driving process considers to take over, the semantic information representing the dynamic event is also retained in the navigation information, so that a certain degree of backward compatibility (i.e., manual driving) of the automatic driving vehicle is realized. The semantic information is information that can be understood by the driver, such as voice information or text information.

In one possible embodiment, the navigation messages corresponding to different dynamic events have the same transmission format. The navigation information of different dynamic events is transmitted by adopting the same transmission format, so that the data transmission efficiency between the first terminal device and the server or the second terminal device can be improved. When the first terminal equipment is the vehicle end, the data receiving time delay during automatic driving of the vehicle end can be effectively reduced, and therefore the automatic driving performance of the vehicle end is improved.

In a possible embodiment, the first terminal device may send the detection result and the confidence level of the detection result to a plurality of second terminal devices; each second terminal device can directly send the detection result and the confidence of the detection result to the server or forward the detection result and the confidence 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 may perform corresponding update on the map and the navigation information according to the received detection result and the confidence of the detection result, and perform navigation by using the updated map; the process of the second terminal device performing corresponding update on the map and the navigation information may refer to a corresponding process in the server in the embodiment described in fig. 6, which is not described herein again.

Referring to fig. 5, fig. 5 is a driving scene diagram of an automatic traveling vehicle according to an embodiment of the present disclosure. At this time, the autonomous vehicle in the figure is the first terminal device in the above embodiment; the second terminal device may be a road side unit, or a handheld terminal device, or a vehicle-mounted terminal device within a certain range of the first terminal device. As shown in fig. 5, the dynamic event is heavy rain, and the position information of the dynamic event included in the navigation information may be the whole city where the current vehicle is located; the dynamic event start time, the predicted duration, and the predicted end time included in the time information of the dynamic event may be time T1, 24 hours, and time T2, respectively; the influence information of the dynamic event may include a perception influence factor, a positioning influence factor, lane passable status information, a map element list, and an influence range of the dynamic event.

The perception influence factor and the positioning influence factor of the dynamic event can adopt a predefined template shown in table 2; the lane passable state information may include passable states of four lanes of the road 1, the road 2, the road 3, and the road 4 shown in fig. 5; the map element list may contain trees 1, lane lines 1, gas stations, traffic lights, shown in FIG. 5; the range of influence of the dynamic event may be equal to the range of this rainfall.

After the vehicle receives the navigation information from the server or the second terminal device, downloading a map corresponding to the map version number from the server, marking the position and the influence range of the dynamic event on the map, and navigating according to the received navigation information; meanwhile, the map elements in the map element list are detected by the vehicle-mounted equipment, and when the detected map element attributes are changed compared with the attributes of the corresponding map elements in the map, the detection results and the confidence degrees of the detection results are sent to the server or the second terminal equipment.

Referring to fig. 6, a flow chart of another navigation method 600 according to an embodiment of the present application is shown. As shown in fig. 6, the method 600 includes steps S610 and S620. The method 600 is applied on the server side.

Step S610, the server sends navigation information to the terminal equipment, wherein the navigation information comprises one or more of map information, position information of the dynamic event, influence information of the dynamic event and time information of the dynamic event; the influence information of the dynamic event comprises one or more of a map element list, a positioning influence factor, a perception influence factor, an influence range of the dynamic event and lane traffic state information.

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

Specifically, the navigation information sent by the server is the same as the navigation information received by the terminal device in the embodiment of fig. 3, and is not described herein again.

The terminal device may be a terminal device with a communication function or a terminal device with a navigation function (i.e., 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 road side unit in fig. 1.

Step S620, the server receives the detection result and the confidence coefficient of the detection result of the terminal equipment for detecting the map elements in the map element list, and updates the map and the navigation information according to the detection result and the confidence coefficient of the detection result; the map is obtained based on map information, and the confidence of the detection result is used for representing the accuracy of the detection result.

Specifically, the above determination process of the map element detection result and the detection result confidence may refer to the description in the embodiment of fig. 3, and is not repeated here.

Alternatively, when the map information contains a map, the terminal device may directly acquire the map from the map information; when the map information includes a map version number corresponding to a desired map, the terminal device may download a map corresponding to the map version number from the server.

The map acquired by the terminal equipment comprises corresponding map elements and corresponding attributes of the map elements.

Optionally, the updating the map and the navigation information according to the detection result and the confidence level of the detection result may include: for updating a certain map element on a map, in the confidence level of the detection results and the detection results sent by other terminal devices received by the server, when a plurality of detection results sent by the terminal devices with a preset proportion are the same and the confidence levels of the plurality of detection results are all greater than or equal to a preset threshold value, the server can update the attribute of the corresponding map element in the map according to the detection results sent by the terminal devices with the preset proportion; for the navigation information updating, the server may determine whether the predicted duration, the predicted end time, the lane passable state, and the like of the dynamic event change according to the detection result of the terminal device with the preset ratio, and when the predicted duration, the predicted end time, the lane passable state, and the like change, update the corresponding content in the navigation information.

In one possible implementation, the perception impact factor is used to characterize the degree of impact of the dynamic event on the detection process of the map element; the positioning influence factor is used for representing the influence degree of the dynamic event on the positioning of the terminal equipment.

In a possible embodiment, the navigation information further comprises semantic information characterizing the dynamic event.

In one possible embodiment, the influence range of the dynamic event contains the position information of the dynamic event.

Specifically, the specific content and the data transmission format included in the navigation information correspond to those described in the embodiment shown in fig. 3, and are not described herein again.

Referring to fig. 7, fig. 7 is a schematic structural diagram of a navigation device 700 according to an embodiment of the present application. As shown in fig. 7, the apparatus 700 comprises: a receiving unit 701, a decision unit 702, a detecting unit 703 and a sending unit 704.

A receiving unit 701, configured to receive navigation information, where the navigation information includes one or more of a map, location information of a dynamic event, influence information of the dynamic event, and time information of the dynamic event; wherein, the influence information of the dynamic event comprises the influence range of the dynamic event.

A decision unit 702, configured to perform navigation according to the map and the navigation information.

In a possible implementation, the influence information of the dynamic event further includes a map element list, and the apparatus 700 further includes: a detecting unit 703, configured to detect a map element in the map element list to obtain a detection result of the map element; a sending unit 704, configured to receive and send the detection result to the server or the second terminal device, so as to update the map and the corresponding navigation information.

In a possible implementation, the sending unit 704 is specifically configured to: and when the attribute of the map element in the detection result is different from the attribute of the corresponding map element in the map, sending the detection result to the server.

In a possible implementation manner, the influence information of the dynamic event further includes one or more of a localization influence factor and a perception influence factor, and the decision unit 702 is further configured to determine a confidence of the detection result according to one or more of the localization influence factor, the perception influence factor, and the time information of the dynamic event; a sending unit 704, configured to send a confidence level of the detection result to the server, where the confidence level is used to characterize a confidence level of the detection result; the perception influence factor is used for representing the influence degree of the dynamic event on the detection process of the map element; the positioning influence factor is used for representing the influence degree of the dynamic event on the positioning of the terminal equipment.

In a possible embodiment, the decision unit 702 is specifically configured to, in terms of determining the confidence level of the detection result according to one or more of the localization impact factor, the perception impact factor and the time information of the dynamic event: and when the process of detecting the map elements in the map element list by the terminal equipment is within the predicted duration of the dynamic event, determining the confidence degree of the detection result according to the positioning influence factor and/or the perception influence factor.

In a possible embodiment, the influencing information of the dynamic event also includes lane passable status information.

Referring to fig. 8, fig. 8 is a schematic structural diagram of another navigation device 800 according to an embodiment of the present application. As shown in fig. 8, the navigation device 800 includes: a transmitting unit 801, a receiving unit 802, and an updating unit 803.

A sending unit 801, 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, influence information of the dynamic event, and time information of the dynamic event; the influence information of the dynamic event comprises one or more of a map element list, a positioning influence factor, a perception influence factor, an influence range of the dynamic event and lane traffic state information;

a receiving unit 802, configured to receive a detection result and a confidence of the detection result, where the detection result is obtained by a terminal device detecting a map element in a map element list;

an updating unit 803, configured to update the map and the navigation information according to the detection result and the confidence level of the detection result; and the confidence of the detection result is used for representing the accuracy of the detection result.

In one possible embodiment, the navigation information further includes semantic information characterizing the dynamic event.

Fig. 9 is a schematic diagram illustrating a hardware structure of an apparatus 900 provided in the present application, where the apparatus may be the navigation device 700 or the navigation device 800 in the method according to the above embodiment. The apparatus 900 comprises: a processor 901, a memory 902, and a communication port 903. The processor 901, communication port 903, and memory 902 may be interconnected or interconnected through a bus 904.

Illustratively, the memory 902 is used for storing computer programs and data of the device 900, and 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), etc.

In the case of implementing the embodiment shown in fig. 9, software or program codes necessary for performing the functions of all or part of the units in fig. 9 are stored in the memory 902.

In the case of implementing the embodiment of fig. 9, if software or program codes required for functions of partial units are stored in the memory 902, the processor 901 may cooperate with other components (such as the communication port 903) to implement other functions (such as functions of receiving data) described in the embodiment of fig. 9, in addition to calling the program codes in the memory 902 to implement partial functions.

The number of the communication ports 903 may be multiple, and may be used for supporting the device 900 to communicate, such as to receive or transmit data or signals.

Illustratively, 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, transistor logic, a hardware component, or any combination thereof. A processor may also be a combination of computing functions, e.g., a combination of one or more microprocessors, a digital signal processor and a microprocessor, or the like. The processor 901 may be configured to read the program stored in the memory 902 to perform the method described in fig. 3 or fig. 6 and the method described in the possible embodiment. For example, for the embodiment in fig. 3, the communication port 903 may perform the following operations:

receiving navigation information; the navigation information includes one or more of map information, location information of the dynamic event, influence information of the dynamic event, and time information of the dynamic event; wherein, the influence information of the dynamic event comprises the influence range of the dynamic event; the operation of receiving may be an operation in step S310 shown in fig. 3.

The processor 901 may perform the following operations:

navigating according to the map and the navigation information; the operation in this step may be the operation in step S320 shown in fig. 3.

For specific operations and advantages performed by the apparatus 900 shown in fig. 9, reference may be made to the description of the method described in fig. 3 or fig. 6 and possible embodiments thereof, which are not described herein again.

An embodiment of the present application further provides an apparatus, which includes a processor, a communication port and a memory, and is configured to perform the method described in any one of the foregoing embodiments and possible embodiments thereof.

In one possible embodiment, the device is a Chip or System on a Chip (SoC).

Embodiments of the present application further provide a computer-readable storage medium, where a computer program is stored, and the computer program is executed by a processor to implement the method described in any one of the above embodiments and possible embodiments thereof.

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 of the above embodiments and possible embodiments thereof will be executed.

Embodiments of the present application further provide a computer program, which when executed on a computer, will enable the computer to implement the method described in any one of the above embodiments and possible embodiments thereof.

The terms "first," "second," and the like in this application are used for distinguishing between similar items and items that have substantially the same function or similar functionality, and it should be understood that "first," "second," and "nth" do not have any logical or temporal dependency or limitation on the number or order of execution. It will be further understood that, although the following description uses the terms first, second, etc. to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another.

It should also be understood that, in the embodiments of the present application, the sequence numbers of the respective processes do not mean the execution sequence, and the execution sequence of the respective processes should be determined by the functions and the inherent logic thereof, and should not constitute any limitation to the implementation process of the embodiments of the present application.

It will be further understood that the terms "comprises," "comprising," "includes," and/or "including," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.

It should also be appreciated that reference throughout this specification to "one embodiment," "an embodiment," "one possible implementation" means that a particular feature, structure, or characteristic described in connection with the embodiment or implementation is included in at least one embodiment of the present application. Thus, the appearances of the phrases "in one embodiment" or "in an embodiment" or "one possible implementation" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

Finally, it should be noted that: the above embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A method of navigation, the method comprising:

the method comprises the steps that a first terminal device receives navigation information, wherein the navigation information comprises one or more of map information, position information of a dynamic event, influence information of the dynamic event and time information of the dynamic event; wherein the influence information of the dynamic event comprises the influence range of the dynamic event;

and the first terminal equipment carries out navigation according to the map information and the navigation information.

2. The method of claim 1, wherein the impact information of the dynamic event further comprises a list of map elements, the method further comprising:

the first terminal device detects the map elements in the map element list to obtain detection results of the map elements;

sending the detection result to a server or a second terminal device to update the navigation information and the map; wherein the map is derived based on the map information.

3. The method of claim 2, wherein the sending the detection result to the server or the second terminal device comprises:

and 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.

4. The method of claim 2 or 3, wherein the impact information of the dynamic event further comprises at least one of a localization impact factor and a perception impact factor, the method further comprising:

and the first terminal equipment determines the confidence degree of the detection result according to at least one of the positioning influence factor, the perception influence factor and the time information of the dynamic event, and sends the confidence degree of the detection result to the server or the second terminal equipment, wherein the confidence degree of the detection result is used for representing the credibility degree of the detection result.

5. The method of claim 4, wherein the perceptual impact factor is used to characterize a degree of impact of the dynamic event on a detection process of the map element; the positioning influence factor is used for representing the influence degree of the dynamic event on the positioning of the first terminal device.

6. The method according to claim 4 or 5, wherein the determining, by the first terminal device, the confidence of the detection result according to at least one of the positioning impact factor, the perceptual impact factor and the time information of the dynamic event comprises:

and when the process of detecting the map elements in the map element list by the first terminal device is within the predicted duration of the dynamic event, determining the confidence degree of the detection result according to the positioning influence factor and/or the perception influence factor.

7. The method of any of claims 1 to 6, wherein the time information of the dynamic event comprises one or more of a start time of the dynamic event, an expected duration of the dynamic event, and an expected end time of the dynamic event.

8. The method according to any of claims 4 to 6, wherein the values of the localization impact factors and the perception impact factors are predefined quantized values.

9. The method according to any one of claims 1 to 8, characterized in that the influence information of the dynamic event further comprises lane passable status information.

10. The method according to any one of claims 1 to 9, wherein the navigation information further comprises semantic information characterizing the dynamic event.

11. The method according to any one of claims 1 to 10, wherein the dynamic event's range of influence contains location information of the dynamic event.

12. The method according to any one of claims 1 to 11, wherein the transmission formats of the navigation messages corresponding to different dynamic events are the same.

13. A method of navigation, the method comprising:

the method comprises the steps that a server sends navigation information to a terminal device, wherein the navigation information comprises one or more of map information, position information of a dynamic event, influence information of the dynamic event and time information of the dynamic event; the influence information of the dynamic event comprises one or more of a map element list, a positioning influence factor, a perception influence factor, an influence range of the dynamic event and lane traffic state information;

the server receives a detection result and the confidence coefficient of the detection result of the terminal equipment for detecting the map elements in the map element list, and updates the navigation information and the map according to the detection result and the confidence coefficient of the detection result; the map is obtained based on the map information, and the confidence of the detection result is used for representing the accuracy of the detection result.

14. The method of claim 13, wherein the perceptual impact factor is used to characterize a degree of impact of the dynamic event on a detection process of the map element; and the positioning influence factor is used for representing the influence degree of the dynamic event on the positioning of the terminal equipment.

15. The method of claim 13 or 14, wherein the time information of the dynamic event comprises one or more of a start time of the dynamic event, an expected duration of the dynamic event, and an expected end time of the dynamic event.

16. The method according to any of the claims 13 to 15, characterized in that the values of the localization impact factor and the perception impact factor are predefined quantized values.

17. The method according to any one of claims 13 to 16, the influence information of the dynamic event further comprising lane passable status information.

18. The method according to any one of claims 13 to 17, wherein the navigation information further comprises semantic information characterizing the dynamic event.

19. The method according to any one of claims 13 to 18, wherein the dynamic event's range of influence contains location information of the dynamic event.

20. The method according to any one of claims 13 to 19, wherein the transmission formats of the navigation messages corresponding to different dynamic events are the same.

21. A navigation device, characterized in that the device comprises:

a receiving unit, configured to receive navigation information, where the navigation information includes one or more of map information, location information of a dynamic event, influence information of the dynamic event, and time information of the dynamic event; wherein the influence information of the dynamic event comprises the influence range of the dynamic event;

and the decision unit is used for navigating according to the map information and the navigation information.

22. The apparatus of claim 21, wherein the impact information of the dynamic event further comprises a list of map elements, the apparatus further comprising:

the detection unit is used for detecting the map elements in the map element list to obtain the detection result of the map elements;

the sending unit is used for sending the detection result to a server or terminal equipment so as to update the navigation information and the map; wherein the map is derived based on the map information.

23. The apparatus according to claim 22, wherein the sending unit is specifically configured to:

and when the attribute of the map element in the detection result is different from the attribute of the corresponding map element in the map, sending the detection result to the server or the terminal equipment.

24. The apparatus according to claim 22 or 23, wherein the impact information of the dynamic event further comprises at least one of a localization impact factor and a perception impact factor,

the decision unit is further configured to determine a confidence of the detection result according to at least one of the positioning impact factor, the perception impact factor, and the time information of the dynamic event;

the sending unit is further configured to send a confidence level of the detection result to the server or the terminal device, where the confidence level of the detection result is used to characterize a credibility of the detection result.

25. The apparatus of claim 24, wherein the perceptual impact factor is configured to characterize a degree of impact of the dynamic event on a detection process of the map element; the positioning influence factor is used for representing the influence degree of the dynamic event on the positioning of the navigation device.

26. The apparatus according to claim 24 or 25, wherein in said determining a confidence level of the detection result according to one or more of the localization impact factor, the perceptual impact factor and the temporal information of the dynamic event, the decision unit is specifically configured to:

when the process of detecting the map elements in the map element list by the navigation device is within the predicted duration of the dynamic event, determining the confidence degree of the detection result according to the positioning influence factor and/or the perception influence factor.

27. The apparatus of claim 26, wherein the time information of the dynamic event comprises one or more of a start time of the dynamic event, an expected duration of the dynamic event, and an expected end time of the dynamic event.

28. The apparatus according to any of the claims 24 to 26, wherein the values of the localization impact factor and the perception impact factor are predefined quantized values.

29. The apparatus of any one of claims 21 to 28, wherein the influence information of the dynamic event further comprises lane passable status information.

30. The apparatus according to any of claims 21 to 29, wherein the navigation information further comprises semantic information characterizing the dynamic event.

31. The apparatus according to any one of claims 21 to 30, wherein the range of influence of the dynamic event comprises location information of the dynamic event.

32. The apparatus according to any one of claims 21 to 31, wherein the transmission formats of the navigation messages corresponding to different dynamic events are the same.

33. A navigation device, characterized in that the device comprises:

a sending unit, configured to send navigation information to a terminal device, where the navigation information includes one or more of map information, location information of a dynamic event, and influence information of the dynamic event and time information of the dynamic event; the influence information of the dynamic event comprises one or more of a map element list, a positioning influence factor, a perception influence factor, an influence range of the dynamic event and lane traffic state information;

a receiving unit, configured to receive a detection result obtained by detecting, by the terminal device, a map element in the map element list and a confidence level of the detection result;

the updating unit is used for updating the navigation information and the map according to the detection result and the confidence coefficient of the detection result;

the map is obtained based on the map information, and the confidence of the detection result is used for representing the accuracy of the detection result.

34. The apparatus of claim 33, wherein the perceptual impact factor is configured to characterize a degree of impact of the dynamic event on a detection process of the map element; and the positioning influence factor is used for representing the influence degree of the dynamic event on the positioning of the terminal equipment.

35. The method of claim 33 or 34, wherein the time information of the dynamic event comprises one or more of a start time of the dynamic event, an expected duration of the dynamic event, and an expected end time of the dynamic event.

36. The method of any one of claims 33 to 35, wherein the values of the localization impact factors and the perception impact factors are predefined quantization values.

37. The method of any one of claims 33 to 36, the dynamic event impact information further comprising lane passable status information.

38. The apparatus according to any of claims 33-37, wherein the navigation information further comprises semantic information characterizing the dynamic event.

39. The apparatus of any one of claims 33 to 38, wherein the dynamic event's range of influence comprises location information of the dynamic event.

40. The apparatus according to any one of claims 33 to 39, wherein the transmission formats of the navigation messages corresponding to different dynamic events are the same.

41. A terminal device, characterized in that it comprises a processor and a memory, said processor and memory being interconnected, wherein said memory is adapted to store a computer program comprising program instructions, said processor being configured to invoke said program instructions to perform the method according to any one of claims 1 to 12.

42. A server, characterized in that it comprises a processor and a memory, said processor and memory being interconnected, wherein said memory is used for storing a computer program comprising program instructions, said processor being configured for invoking said program instructions for performing the method according to any one of claims 13 to 20.

43. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program which is executed by a processor to implement the method of any one of claims 1 to 12 or 13 to 20.