WO2020057407A1 - Vehicle navigation assistance method and system - Google Patents

Abstract

A vehicle (110) navigation assistance method and system (100). The vehicle (110) navigation assistance method comprises the steps of: acquiring road data within a predetermined range, the road data within the predetermined range comprising static and/or dynamic information about objects within the predetermined range; identifying, on the basis of the road data, one or more vehicles (110) and vehicle (110) motion information among the objects; and transmitting the vehicle (110) motion information and the road data to the one or more vehicles (110), so that the vehicles (110) perform vehicle navigation. Further disclosed are a corresponding road side sensing device (200) and a vehicle navigation system (100).

Description

Method and system for assisting vehicle navigation

This application claims priority from a Chinese patent application filed on September 21, 2018 with an application number of 201811109401.5 and an invention name of "a method and system for assisting vehicle navigation", the entire contents of which are incorporated herein by reference.

Technical field

The present invention relates to the field of vehicle navigation, and particularly to the field of using road environment data to assist vehicle navigation.

Background technique

As the automotive industry enters the Internet and smart age, sensors and computing units in the vehicle or its surroundings can provide increasingly powerful driving-related data and computing capabilities. These data and capabilities can assist in driving vehicles more effectively than before, making vehicle driving easier, smarter, and safer.

Various vehicle navigation schemes already exist. A common vehicle navigation scheme is to use the position information of a vehicle or a smart device on the vehicle. That is, first, the vehicle's position information is obtained and the road map information is obtained. The position of the vehicle is superimposed on the map information. After the destination specified by the user, the navigation plan route is determined using the vehicle position and map information. Then, as the vehicle travels, update the vehicle's position on the map and guide the vehicle to its destination based on the map features.

One problem with existing navigation methods is that even with a high-precision map, since the vehicle's position is obtained by the vehicle's GPS positioning, when the vehicle is driving at high speed, the GPS positioning accuracy is low, and it is difficult to determine the vehicle's position on the road. On which lane to drive on, lane-based positioning cannot be achieved.

Another problem with existing navigation methods is that information such as the degree of congestion on the map may be reported by vehicles on the road over a period of time. Due to the local positioning accuracy of the vehicle, the congestion on the map cannot be confirmed in lanes. Therefore, lane-based navigation planning cannot be implemented.

With the development of connected car V2X technology, a collaborative environment perception system has emerged. This system can comprehensively use the data of the vehicle and the surrounding environment for vehicle navigation. However, how to construct the environmental data and how to fuse the vehicle itself and the environmental data are the problems faced by the collaborative environment sensing system.

To this end, a new navigation system is needed that can provide lane-level navigation planning. The navigation solution does not rely on high-precision GNSS, can perform real-time navigation, and can be adjusted at any time according to real-time road conditions.

Summary of the Invention

For this reason, the present invention provides a new vehicle navigation scheme to try to solve or at least alleviate at least one of the problems existing above.

According to an aspect of the present invention, a method for assisting vehicle navigation is provided. The method includes the steps of: acquiring road data within a predetermined range, the road data including static and / or dynamic information of objects within the predetermined range; and based on the road Data, identifying one or more vehicles and vehicle motion information in each object; and sending the vehicle motion information and road data to the one or more vehicles so that the one or more vehicles perform vehicle navigation.

Optionally, in the assisted vehicle navigation method according to the present invention, the step of obtaining road data within a predetermined range includes: obtaining pre-stored static information about the predetermined range of the road; utilizing deployment in a drive test sensing device To obtain static and / or dynamic information of each object within a predetermined range; to combine the static information stored in advance with the information obtained by each sensor to generate the road data.

Optionally, in the assisted vehicle navigation method according to the present invention, the step of obtaining road data within a predetermined range further includes: receiving vehicle driving information sent by a vehicle within the predetermined range through a predetermined communication method; and combining the previously The stored static information, the information obtained by each sensor, and the received vehicle driving information are used to generate road data.

Optionally, in the assisted vehicle navigation method according to the present invention, the step of acquiring static information on a predetermined range includes: determining a geographic position of a roadside sensing device; and obtaining static information within a predetermined range of the geographical position from a server. .

Optionally, in the assisted vehicle navigation method according to the present invention, the step of identifying one or more vehicles and vehicle motion information in each object based on road data includes: determining a vehicle object belonging to the vehicle and the vehicle object based on the motion characteristics of each object, and Motion information; and an identification identifying each vehicle object.

Optionally, the assisted vehicle navigation method according to the present invention further includes the steps of: receiving a navigation request sent by a navigation vehicle within a predetermined range through a predetermined communication method; matching the navigation vehicle from the identified one or more vehicles; and responding to The navigation request sends vehicle motion information and road data of the matched navigation vehicle to the navigation vehicle for vehicle navigation.

Optionally, in the assisted vehicle navigation method according to the present invention, the communication mode includes one or more of the following: V2X, 5G, 4G, and 3G communication.

Optionally, in the assisted vehicle navigation method according to the present invention, each object includes one or more of the following objects: lane lines, guardrails, barriers, vehicles, pedestrians, and throws; static and / or dynamic information includes the following One or more of them: position, distance, speed, angular velocity, license plate, type and size, etc.

Optionally, in the method for assisting vehicle navigation according to the present invention, the sensors in the roadside sensing device include one or more of the following: millimeter-wave radar, lidar, camera, and infrared probe.

Optionally, in the assisted vehicle navigation method according to the present invention, the vehicle running information includes one or more of the following: current time, size, speed, acceleration, angular velocity, and position.

Optionally, the assisted vehicle navigation method according to the present invention further includes the steps of: after determining a vehicle matching the navigation vehicle, calculating a navigation plan for the navigation vehicle based on the vehicle motion information and road data of the matched vehicle; and calculating the calculated The resulting navigation plan is sent to the navigation vehicle.

Optionally, in the assisted vehicle navigation method according to the present invention, the navigation planning is performed using lanes on a road as a basic unit.

Optionally, the auxiliary vehicle navigation method according to the present invention further includes the steps of receiving a clock synchronization request of the navigation vehicle and performing clock synchronization.

Optionally, the assisted vehicle navigation method according to the present invention is further adapted to be executed in a roadside sensing device deployed at a road location or in a server coupled to the roadside sensing device.

According to another aspect of the present invention, a method for assisting vehicle navigation performed in a vehicle is provided. The vehicle runs on a road on which a roadside sensing device is deployed. The method includes the steps of: sending a navigation request; and receiving a response to the navigation request. The returned vehicle motion information determined by the roadside sensing device and road data of the road segment associated with the drive test sensing device; obtaining a navigation plan based on the vehicle motion information and the road data; and performing the navigation plan based on the navigation plan. Vehicle navigation.

According to yet another aspect of the present invention, a roadside sensing device is provided, which is deployed at a road position, and the device includes: a sensor group adapted to obtain static and dynamic information of objects within a predetermined range; and a storage unit adapted to The road data is stored, and the road data includes static and dynamic information of objects within a predetermined range; and a calculation unit adapted to execute the assisted vehicle navigation method according to the present invention.

According to still another aspect of the present invention, there is provided a vehicle navigation system including: a plurality of the above-mentioned roadside sensing devices, which are deployed at a side position of a road; and a vehicle, which runs on a road and performs assistance as in accordance with the present invention. Vehicle navigation method.

According to yet another aspect of the invention, a computing device is also provided. The computing device includes at least one processor and a memory storing program instructions, wherein the program instructions are configured to be executed by the at least one processor and include instructions for performing the above-described assisted vehicle navigation method.

According to still another aspect of the present invention, a readable storage medium storing program instructions is provided, and when the program instructions are read and executed by a computing device, the computing device is caused to execute the above-mentioned auxiliary vehicle navigation method.

According to the vehicle navigation scheme of the present invention, the sensing capability of the roadside sensing device is fully utilized, and a lane-based navigation method can be provided for a vehicle.

BRIEF DESCRIPTION OF THE DRAWINGS

To achieve the above and related objectives, certain illustrative aspects are described herein in conjunction with the following description and accompanying drawings, which indicate various ways in which the principles disclosed herein can be practiced, and all aspects and their equivalents are intended to be Within the scope of the claimed subject matter. The above and other objects, features, and advantages of the present disclosure will become more apparent by reading the following detailed description in conjunction with the accompanying drawings. Throughout this disclosure, the same reference numerals generally refer to the same parts or elements.

FIG. 1 shows a schematic diagram of a driving assistance system according to an embodiment of the present invention;

2 shows a schematic diagram of a roadside sensing device according to an embodiment of the present invention;

FIG. 3 shows a schematic diagram of a method for assisting vehicle navigation according to an embodiment of the present invention; and

FIG. 4 shows a schematic diagram of a method for assisting vehicle navigation according to another embodiment of the present invention.

detailed description

Hereinafter, exemplary embodiments of the present disclosure will be described in more detail with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a thorough understanding of the present disclosure, and to fully convey the scope of the present disclosure to those skilled in the art.

FIG. 1 shows a schematic diagram of a vehicle navigation system 100 according to an embodiment of the present invention. As shown in FIG. 1, the vehicle navigation system 100 includes a vehicle 110 and a roadside sensing device 200. The vehicle 110 is traveling on a road 140. The road 140 includes a plurality of lanes 150. During the process that the vehicle 110 can travel on the road 140, different lanes 150 can be switched according to the road conditions and driving targets. The roadside sensing device 200 is deployed around the road and uses various sensors to collect various information within a predetermined range around the roadside sensing device 200, especially road data related to the road.

The roadside sensing device 200 has a predetermined coverage. According to the coverage of each roadside sensing device 200 and the road conditions, a sufficient number of roadside sensing devices 200 can be deployed on both sides of the road to achieve full coverage of the entire road. Of course, according to one embodiment, instead of achieving full coverage of the entire road, the roadside sensing device 200 can be deployed at the characteristic points (turns, intersections, bifurcations) of each road to obtain the characteristics of the road Data. The invention is not limited to the specific number of roadside sensing devices 200 and the coverage of the road.

When the roadside sensing device 200 is deployed, the position of the sensing device 200 to be deployed is first calculated according to the coverage area of a single roadside sensing device 200 and the condition of the road 140. The coverage area of the roadside sensing device 200 depends at least on the arrangement height of the sensing device 200 and the effective distance sensed by the sensors in the sensing device 200. The condition of the road 140 includes the length of the road, the number of lanes 150, the curvature and slope of the road, and the like. The deployment position of the sensing device 200 may be calculated in any manner in the art.

After the deployment location is determined, the roadside sensing device 200 is deployed at the determined location. Since the data required by the roadside sensing device 200 includes motion data of a large number of objects, the clock synchronization of the roadside sensing device 200 is performed, that is, the time of each sensing device 200 is consistent with the time of the vehicle 110 and the cloud platform.

Subsequently, the location of each deployed roadside sensing device 200 is determined. Since the sensing device 200 is to provide a high-precision vehicle navigation function for the vehicle 110 traveling at high speed on the road 140, the position of the sensing device 200 must be high-precision. There are many ways to calculate the high-accuracy absolute position of the sensing device 200. According to one embodiment, a global satellite navigation system (GNSS) may be utilized to determine a high-precision position.

The roadside sensing device 200 uses its sensors to collect and sense the static conditions (lane lines 120, guardrails, barriers, etc.) and dynamic conditions (moving vehicles 110, pedestrians 130, and throws) of roads within its coverage area, and sense different sensors. The data is fused to form road data for the road. The road data includes static and dynamic information of all objects in the area covered by the sensing device 200, especially in road-related areas. The roadside sensing device 200 may then determine the individual vehicles within its coverage area and the motion information of each vehicle based on the road data.

The vehicle 110 entering the coverage area of one roadside sensing device 200 can communicate with the roadside sensing device 200. A typical communication method is the V2X communication method. Of course, mobile communication methods such as 5G, 4G, and 3G can be used to communicate with the roadside sensing device 200 through a mobile internet network provided by a mobile communication service provider. Considering that the vehicle is traveling at a fast speed, and the time delay requirement for communication is as short as possible, the V2X communication method is adopted in the general embodiment of the present invention. However, any communication method that can meet the time delay requirements required by the present invention is within the protection scope of the present invention.

The vehicle 110 may receive vehicle motion information related to the vehicle 110 and road data of the road from the roadside sensing device 200 and use these data to perform vehicle navigation.

The vehicle 110 may receive vehicle motion information related to the vehicle 110 and road data of the road in various ways. In one implementation, all the vehicles 110 entering the coverage area of the roadside sensing device 200 can automatically receive these information and data for navigation. In another implementation, the vehicle 110 may issue a navigation request, and the roadside sensing device 200 sends vehicle motion information related to the vehicle 110 and road data of the road to the vehicle 110 in response to the request, so that the vehicle 110 performs navigation.

The present invention is not limited to the specific manner in which the vehicle 110 receives the vehicle motion information and the road data of the road, and all manners that can receive the vehicle motion information and the road data of the road and perform navigation based on this are within the protection scope of the present invention. within.

Optionally, the vehicle navigation system 100 further includes a server 160. Although only one server 160 is shown in FIG. 1, it should be understood that the server 160 may be a cloud service platform composed of multiple servers. Each roadside sensing device 100 sends the sensed road data to the server 160. The server 160 may combine road data based on the position of each roadside sensing device 100 to form road data for the entire road. The server 160 may further perform processing on the road data of the road to form information required for vehicle navigation, such as the traffic status of the entire road, unexpected road sections, expected transit time, and the like.

Considering the requirements of computing power and time delay, the navigation plan may be calculated at the vehicle 110, the roadside sensing device 200, or the server 160 as needed. The navigation plan can be calculated based on the vehicle motion information of the navigation vehicle and the road data of a certain road. The computing power of the server 160 is the strongest, but data needs to be sent to the server 160 for calculation. The vehicle 110 may not have strong computing capabilities, but the real-time running information of the vehicle is used directly to calculate the navigation plan locally, so it has accurate navigation plan results. Calculating the navigation plan on the roadside sensing device 200 does not require network transmission of a large amount of data, and has the best time delay.

The present invention can choose which device to perform navigation planning calculation according to the specific situation applied. Wherever navigation planning calculations are performed, these are within the scope of the present invention.

The formed road data and vehicle motion information of the entire road may be sent to each roadside sensing device 200, or corresponding sections of roads of several roadside sensing devices 200 adjacent to a certain roadside sensing device 200 may be sent The road-related data and vehicle motion information are sent to the roadside sensing device 200. In this way, the vehicle 110 can obtain a larger range of road data from the roadside sensing device 200. Of course, the vehicle 110 may obtain road data and vehicle motion information directly from the server 160 without passing through the roadside sensing device 200.

If roadside sensing devices 200 are deployed on all roads in an area, and these roadside sensing devices 200 all send road data to the server 160, a navigation instruction for road traffic in the area can be formed at the server 160. The vehicle 110 may receive the navigation instruction from the server 160 and perform navigation accordingly.

FIG. 2 shows a schematic diagram of a roadside sensing device 200 according to an embodiment of the present invention. As shown in FIG. 2, the roadside sensing device 200 includes a communication unit 210, a sensor group 220, a storage unit 230, and a calculation unit 240.

The roadside sensing device 200 communicates with each vehicle 110 entering its coverage area in order to provide vehicle navigation services for the vehicle 110 and receive vehicle driving information of the vehicle from the vehicle 110. At the same time, the roadside sensing device 200 also needs to communicate with the server 160. The communication unit 210 provides a communication function for the roadside sensing device 200. The communication unit 210 may adopt various communication methods, including but not limited to Ethernet, V2X, 5G, 4G, and 3G mobile communication, as long as these communication methods can complete data communication with a minimum time delay. In one embodiment, the roadside sensing device 200 may use V2X to communicate with the vehicle 110 entering its coverage area, and the roadside sensing device 200 may communicate with the server 160 using, for example, a high-speed Internet.

The sensor group 220 includes various sensors, such as a radar sensor such as a millimeter-wave radar 222, a lidar 224, and an image sensor such as a camera 226 and an infrared probe 228 having a supplementary light function. For the same object, various sensors can obtain different attributes of the object. For example, radar sensors can measure object speed and acceleration, while image sensors can obtain object shape, relative angle, and so on.

The sensor group 220 uses various sensors to collect and sense the static conditions of the road (lane line 120, guardrails, barriers, etc.) and dynamic conditions (moving vehicles 110, pedestrians 130, and throws) in the coverage area, and collect and sense each sensor The data is stored in the storage unit 230.

The computing unit 240 fuses the data sensed by each sensor to form road data of the road, and also stores the road data in 234. In addition, the calculation unit 240 may further perform data analysis on the basis of road data to identify one or more vehicles and vehicle motion information therein. These data and information may be stored in the storage unit 230 so as to be transmitted to the vehicle 110 or the server 160 via the communication unit 210.

In addition, the storage unit 230 may also store various calculation models, such as a collision detection model, a license plate recognition model, a navigation planning model, and the like. These calculation models may be used by the calculation unit 240 to implement the corresponding steps in the method 300 described below with reference to FIG. 3.

FIG. 3 shows a schematic diagram of a method 300 for assisting vehicle navigation according to an embodiment of the present invention. The auxiliary vehicle navigation method 300 is adapted to be executed in the roadside sensing device 200 shown in FIG. 2 or executed in the server 160. When executed in the server 160, all relevant data generated or received by the roadside sensing device 200 need to be sent to the server 160 in order to perform related processing in the server 160.

As shown in FIG. 3, the assisted vehicle navigation method 300 starts at step S310.

In step S310, road data within a predetermined range of road positions is acquired. As described above with reference to FIG. 1, the roadside sensing device 200 is usually fixedly deployed near a certain road, and therefore has a corresponding road position. In addition, the roadside sensing device 200 has a predetermined coverage area, at least depending on the arrangement height of the sensing device 200, the effective distance for sensing by the sensors in the sensing device 200, and the like. Once the roadside sensing device 200 is deployed on the side of a road, the predetermined range of roads that the sensing device can cover can be determined according to the specific position, height, and effective sensing distance of the sensing device and the road.

The roadside sensing device 200 uses various sensors to collect and / or collect static and dynamic conditions (lane lines 120, guardrails, barriers, etc.) and dynamic conditions (moving vehicles 110, pedestrians 130, and throws) of roads in the coverage area. Perceive to obtain and store various sensor data.

As described above, the roadside sensing device 200 includes various sensors, such as a radar sensor such as a millimeter wave radar 222, a lidar 224, and an image sensor such as a camera 226 and an infrared probe 228 having a supplementary light function. For the same object, various sensors can obtain different attributes of the object. For example, radar sensors can measure object speed and acceleration, while image sensors can obtain object shape and relative angle.

In step S310, processing and fusion may be performed based on the obtained various sensor raw data, thereby forming unified road data. In one embodiment, step S310 may further include a sub-step S312. In step S312, static information about a predetermined range of road positions that is stored in advance is acquired. After the roadside sensing device is deployed at a certain location on the road, the road range covered by the sensing device is also fixed. The static information of the predetermined range can be obtained, such as the width of the road, the number of lanes, the turning radius, etc. within the range. There are many ways to obtain static information about a road. In one embodiment, the static information may be stored in the sensing device in advance when the sensing device is deployed. In another embodiment, the location information of the sensing device may be obtained first, and then a request containing the location information is sent to the server 160 so that the server 160 returns static information of the relevant road range according to the request.

Subsequently, in step S314, the original sensor data is processed according to different sensors to form perceptual data such as distance measurement, speed measurement, type, and size recognition. Then in step S316, based on the road static data obtained in step S312, in different cases, different sensor data is used as a reference, and other sensor data is used for calibration, and finally unified road data is formed.

Steps S312-S136 describe a way to obtain road data. The present invention is not limited to a specific way of fusing data from various sensors to form road data. As long as the road data contains static and dynamic information of various objects within a predetermined range of the road position, this method is within the protection scope of the present invention.

According to one embodiment, each vehicle 110 that enters the coverage area of the roadside sensing device 200 will actively communicate with the sensing device 200 through various communication methods (such as V2X). Therefore, as described in step S318, the vehicle 110 sends vehicle driving information of the vehicle to the sensing device 200. The running information of the vehicle includes running information of the vehicle during running, for example, including the current time when the running information is generated, the size, speed, acceleration, angular velocity, and position of the vehicle. The method S310 further includes step S319, in which the vehicle driving information obtained in step S318 is further integrated on the basis of the road data formed in step S316 to form new road data.

Next, in step S320, based on the road data obtained in step S310, one or more vehicles within the coverage of the sensing unit and the motion information of these vehicles are identified. The identification in step S320 includes two aspects of identification. One aspect of identification is vehicle identification, which identifies which objects in the road data are vehicle objects. Because vehicle objects have different motion characteristics, such as high speed, driving along the lane in one direction, they generally do not send collisions with other objects. A traditional classification detection model or a deep learning-based model can be constructed based on these motion features, and the constructed model can be applied to road data to determine motion features such as vehicle objects and motion trajectories of the vehicle objects in the road data.

Another aspect of identification is identifying the vehicle identification. For the identified vehicle object, its vehicle identification is further determined. One way to determine the vehicle identification is to determine the unique license plate of the vehicle, for example, through image recognition. When the license plate of the vehicle cannot be identified, another way to determine the vehicle identification may be to generate a unique mark of the vehicle by combining the size, type, location information, and driving speed of the vehicle object. This vehicle identification is the unique identification of the vehicle object in this road segment and is used to distinguish it from other vehicle objects. The vehicle identification will be used in subsequent data transmission, and will be transmitted in different roadside sensing devices on this road to facilitate overall analysis.

Subsequently, in step S330, a data request sent by a navigation vehicle 110 that desires to enter the coverage of the roadside sensing device 200 is received. Because the road data generated by the roadside sensing device 200 includes dynamic and static data of the road, navigation planning can be performed based on the road data, and the navigation vehicle 110 itself does not generate road data, so the navigation vehicle 110 needs to send a request to Roadside sensing device 200.

Subsequently, in step S340, after receiving the data request from the navigation vehicle 110, the requesting navigation vehicle 110 needs to be matched with all vehicles within the coverage area of the sensing device 200, so as to determine which is within the coverage area. The vehicle sent a data request.

Vehicle matching can be performed through a variety of matching methods, such as license plate matching, driving speed and type matching, and fuzzy location information matching. According to one embodiment, the vehicle 110 can bind the license plate information through V2X or application verification, and this license plate information can further be matched to the vehicle data of the corresponding license plate in the roadside sensing device and the server, thereby achieving license plate matching.

After determining a vehicle matching the navigation vehicle in step S340, in step S350, the vehicle motion information of the matched vehicle that has been determined in step S320 and the road data determined in step S310 are sent to the navigation vehicle 110 so that the navigation vehicle Car navigation.

It should be noted that the above steps S330 and S340 are not necessary steps of the present invention. The vehicle 110 may receive vehicle motion information related to the vehicle 110 and road data of the road in various ways. In one implementation, all the vehicles 110 entering the coverage area of the roadside sensing device 200 can automatically receive these information and data for navigation. In another implementation, the vehicle 110 may issue a navigation request, and the roadside sensing device 200 sends vehicle motion information related to the vehicle 110 and road data of the road to the vehicle 110 in response to the request, so that the vehicle 110 performs navigation. The present invention is not limited to the specific manner in which the vehicle 110 receives the vehicle motion information and the road data of the road, and all manners that can receive the vehicle motion information and the road data of the road and perform navigation based on this are within the protection scope of the present invention. within.

Therefore, in one embodiment, in step S350, one or more vehicles 110 identified in step S320 may actively send the vehicle motion information related to them and the road data of the section of road, so that these The vehicle 110 performs navigation.

In addition, optionally, after the vehicle motion information and road data are sent to the navigation vehicle 110 in step S350, in order to facilitate the navigation vehicle 110 to perform navigation, the method 300 further includes step S360. In step S360, a navigation plan is calculated for the navigation vehicle based on the vehicle motion information of the matched vehicle and the road data. Various ways in the art can be used for navigation planning, and these are all within the protection scope of the present invention. Optionally, the vehicle motion information and road data may also be sent to the cloud server 160, and the navigation plan calculation is performed on the cloud server 160, and the calculated navigation plan is obtained from the cloud server 160.

According to an embodiment of the present invention, the navigation plan is a lane-level navigation path plan (this plan can also be calculated at the vehicle end). Because the road data contains static and dynamic data related to the lane, when planning the navigation path, lane-level avoidance can also be performed according to the situation of the road (obstacles, faulty vehicles, congested lanes, accident lanes, etc.) to achieve Lane-level navigation path planning.

In addition, when planning a navigation route, the overall vehicle data can be used as a basis to seek a global optimal solution for the entire road segment. After the global optimization, the planned path of the navigation vehicle is determined.

Since the server 160 includes road data of the entire road, the server 160 may consider the global optimum of the entire road to determine the planned path of a certain navigation vehicle.

Subsequently, in step S370, the navigation plan calculated in step S360 is sent to the navigation vehicle 110 to guide the vehicle to perform navigation.

In addition, optionally, due to navigation, strict time consistency is required as much as possible. For this reason, navigation vehicles usually need to be time-synchronized with equipment that provides navigation path planning or navigation basic data (ie, vehicle motion information and road data). To this end, the method 300 also needs to receive a time synchronization request from the navigation vehicle and process it to ensure time consistency of the navigation vehicle 110, the roadside sensing device 200, and the server 160.

FIG. 4 shows a schematic diagram of a method 400 for assisting vehicle navigation according to another embodiment of the present invention. The vehicle navigation method 400 is adapted to be performed in a vehicle 110 and the vehicle 110 is traveling on a road on which a roadside sensing device 200 is deployed. The method 400 includes step S410. In step S410, a navigation request is transmitted. The navigation request may be sent to the roadside sensing device 200 or the server 160. Both the sensing device 200 and the server 160 store the vehicle motion information of each vehicle within the coverage area of the sensing device and the road data of the associated road segment, so both can process the navigation request.

Subsequently, in step S420, the vehicle motion information determined by the roadside sensing device and the road data of the road segment associated with the drive test sensing device returned in response to the navigation request of step S410 are received. The specific method for calculating vehicle motion information and road data has been described above with reference to method step S320 in FIG. 3, and details are not described herein again.

Subsequently, in step S430, a navigation plan generated based on the vehicle motion information and road data is acquired. As shown above, the navigation plan may be generated in the vehicle 110, the roadside sensing device 200, and the server 160 as needed. Step S430 may obtain the navigation plan from the vehicle 110, the roadside sensing device 200, or the server 160 according to requirements. As mentioned above, navigation planning is lane-level navigation path planning. Because the road data contains static and dynamic data related to the lane, when planning the navigation path, lane-level avoidance can also be performed according to the situation of the road (obstacles, faulty vehicles, congested lanes, accident lanes, etc.) to achieve Lane-level navigation path planning.

Subsequently, in step S440, according to the obtained navigation plan, the navigation vehicle is instructed to proceed to the destination.

Alternatively, it is considered that the vehicle is usually driving at a high speed, and there is a time delay in data transmission. Therefore, it is likely that the vehicle position sent by the sensing unit may have lagged. To this end, the method S400 further includes a step S450, in which the time difference is obtained by comparing the vehicle time with the vehicle data time sensed by the sensing unit. Then, in step S460, according to the time difference, the vehicle speed, acceleration, and angular velocity included in the vehicle motion information, the vehicle position included in the vehicle motion information is adjusted to obtain the current actual position information of the navigation vehicle.

In addition, optionally, when there is a V2X / 5G communication method between the vehicle and the sensing device 200, considering the high real-time nature of V2X communication, the above-mentioned time difference will be relatively small, generally within 50ms. That is, the cumulative error calculated will be relatively small. In this case, in step S460, the vehicle's real-time position adjustment can be performed from the vehicle speed, acceleration, angular velocity and other data acquired by the vehicle itself, thereby realizing lane-level navigation with higher accuracy.

According to the vehicle navigation scheme of the present invention, the sensing capability of the roadside unit can be fully utilized to provide high-precision road data, thereby providing lane-level navigation path planning.

It should be understood that, in order to simplify the present disclosure and help to understand one or more of the various aspects of the invention, in the above description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together into a single embodiment, diagram, or In its description. However, this disclosed method should not be construed to reflect the intention that the claimed invention requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single embodiment previously disclosed. Thus, the claims following a specific embodiment are hereby explicitly incorporated into this specific embodiment, wherein each claim itself is a separate embodiment of the present invention.

Those skilled in the art should understand that the modules or units or components of the device in the example disclosed herein may be arranged in the device as described in this embodiment, or alternatively may be positioned differently from the device in this example Of one or more devices. The modules in the foregoing examples may be combined into one module or may be further divided into multiple sub-modules.

Those skilled in the art can understand that the modules in the device in the embodiment can be adaptively changed and set in one or more devices different from the embodiment. The modules or units or components in the embodiment may be combined into one module or unit or component, and furthermore, they may be divided into a plurality of sub-modules or sub-units or sub-components. Except for such features and / or processes or units, which are mutually exclusive, all features disclosed in this specification (including the accompanying claims, abstract and drawings) and any methods so disclosed may be employed in any combination or All processes or units of the equipment are combined. Each feature disclosed in this specification (including the accompanying claims, abstract, and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.

In addition, those skilled in the art can understand that although some embodiments described herein include certain features included in other embodiments and not other features, the combination of features of different embodiments is meant to be within the scope of the present invention Within and form different embodiments. For example, in the following claims, any one of the claimed embodiments can be used in any combination.

Furthermore, some of the described embodiments are described herein as methods or combinations of method elements that can be implemented by a processor of a computer system or by other devices that perform the described functions. Thus, a processor having the necessary instructions for implementing the method or method element forms a means for implementing the method or method element. Furthermore, the elements of the device embodiment described here are examples of devices that are used to implement functions performed by the elements for the purpose of implementing the invention.

As used herein, unless otherwise specified, the use of the ordinal numbers "first", "second", "third", etc. to describe ordinary objects merely means different instances involving similar objects, and is not intended to imply such The described objects must have a given order in time, space, order, or in any other way.

Although the invention has been described in terms of a limited number of embodiments, benefiting from the above description, those skilled in the art will appreciate that other embodiments are contemplated within the scope of the invention as described herein. In addition, it should be noted that the language used in this specification is mainly selected for readability and teaching purposes, and not for explaining or limiting the subject matter of the present invention. Accordingly, many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the appended claims. As for the scope of the present invention, the disclosure of the present invention is illustrative and not restrictive, and the scope of the present invention is defined by the appended claims.

Claims (24)

1. A method for assisting vehicle navigation, the method includes steps:

   Acquiring road data within a predetermined range, where the road data includes static and / or dynamic information of objects in the predetermined range;

   Identifying one or more vehicles and vehicle motion information in the objects based on the road data;

   Sending the identified vehicle motion information and the road data to the one or more vehicles so that the one or more vehicles perform vehicle navigation.
2. The assisted vehicle navigation method according to claim 1, wherein the step of obtaining road data within a predetermined range comprises:

   Obtaining pre-stored static information about the predetermined range;

   Obtaining static and / or dynamic information of each object in the predetermined range by using each sensor in the roadside sensing device deployed in the predetermined range;

   Combining the pre-stored static information and information obtained by each sensor to generate the road data.
3. The assisted vehicle navigation method according to claim 2, wherein the step of obtaining road data within a predetermined range comprises:

   Receiving vehicle driving information sent by vehicles within the predetermined range through the predetermined communication method; and

   The road data is generated by combining the pre-stored static information, information obtained by each sensor, and received vehicle driving information.
4. The assisted vehicle navigation method according to claim 2 or 3, wherein the step of obtaining static information on a predetermined range of the road position is stored in advance:

   Determine the geographic location of the roadside sensing device; and

   Static information within a predetermined range of the geographic location is obtained from a server.
5. The assisted vehicle navigation method according to any one of claims 1 to 4, wherein the step of identifying one or more vehicles and vehicle motion information of the objects based on the road data comprises:

   Determining a vehicle object belonging to the vehicle and its motion information based on the motion characteristics of each object; and

   Identification of each vehicle object.
6. The assisted vehicle navigation method according to any one of claims 1 to 5, further comprising the steps:

   Receiving a navigation request sent by a navigation vehicle within the predetermined range through a predetermined communication method;

   Matching the navigation vehicle from the identified one or more vehicles; and

   In response to the navigation request, the vehicle motion information of the matched navigation vehicle and the road data are sent to the navigation vehicle, so that the navigation vehicle performs vehicle navigation.
7. The assisted vehicle navigation method according to any one of claims 1-6, further comprising the steps:

   After determining a vehicle matching the navigation vehicle, calculating a navigation plan for the navigation vehicle based on the vehicle motion information of the matched vehicle and the road data; and

   Send the calculated navigation plan to the navigation vehicle.
8. The assisted vehicle navigation method according to claim 7, wherein the navigation planning is performed using a lane on a road as a basic unit.
9. The assisted vehicle navigation method according to any one of claims 1-8, further comprising the steps:

   Receiving a clock synchronization request from the navigation vehicle and performing clock synchronization.
10. The method for assisting vehicle navigation according to any one of claims 1-9, the communication method between the vehicle and the roadside sensing device comprises one or more of the following:

    V2X, 5G, 4G and 3G communication.
11. The assisted vehicle navigation method according to any one of claims 1-10, wherein each object includes one or more of the following objects: lane lines, guardrails, barriers, vehicles, pedestrians, and throws;

    The static and / or dynamic information includes one or more of the following: position, distance, speed, angular velocity, license plate, type and size, and the like.
12. The assisted vehicle navigation method according to any one of claims 2-11, the sensors in the roadside sensing device forming the road data include one or more of the following:

    Millimeter wave radar, lidar, camera, infrared probe.
13. The assisted vehicle navigation method according to any one of claims 1-12, wherein the method is adapted to be executed in a roadside sensing device deployed in the predetermined range or a server coupled to the roadside sensing device .
14. A method for assisted vehicle navigation performed in a vehicle, said vehicle driving on a road on which a roadside sensing device is deployed, said method comprising the steps:

    Send navigation request;

    Receiving vehicle motion information determined by the roadside sensing device and road data of a road segment associated with the roadside sensing device returned in response to the navigation request;

    Acquiring a navigation plan generated based on the vehicle motion information and the road data; and

    Vehicle navigation is performed based on the navigation plan.
15. The assisted vehicle navigation method according to claim 14, further comprising the steps:

    Send a clock synchronization request to achieve clock synchronization between the vehicle and the roadside sensing device.
16. The assisted vehicle navigation method according to claim 14 or 15, wherein the navigation plan is at any one of the vehicle, the roadside sensing device, and a server coupled to the vehicle and the roadside sensing device. generate.
17. The assisted vehicle navigation method according to any one of claims 14 to 16, wherein the navigation planning is performed using a lane on a road as a basic unit.
18. The assisted vehicle navigation method according to any one of claims 14-17, further comprising the steps:

    Compare the current vehicle time with the vehicle data time corresponding to the received vehicle motion information to get the time difference;

    Adjusting the vehicle position contained in the vehicle motion information to obtain the current actual position information of the vehicle according to the time difference, vehicle speed, acceleration, and angular velocity included in the vehicle motion information; and

    Car navigation is performed based on the current actual position information of the vehicle and according to the navigation plan.
19. The assisted vehicle navigation method according to claim 18, wherein the vehicle position adjustment process is performed using vehicle speed, acceleration, and angular velocity acquired by the vehicle itself.
20. A roadside sensing device, which is deployed at a road location and includes:

    Each sensor is adapted to obtain static and dynamic information of each object within the predetermined range;

    A storage unit adapted to store road data including static and dynamic information of objects within the predetermined range; and

    A computing unit adapted to perform the method according to any one of claims 1-12.
21. A vehicle navigation system includes:

    A plurality of roadside sensing devices according to claim 20, which are deployed at roadside positions; and

    A vehicle travels on the road and executes the vehicle navigation method according to any one of claims 14-18.
22. The vehicle navigation system of claim 21, further comprising:

    The cloud server is adapted to receive the road data of the roadside sensing device, and combine the road data based on the deployment position of each roadside sensing device to generate road data for the entire road.
23. A computing device includes:

    At least one processor; and

    Memory storing program instructions, wherein the program instructions are configured to be executed by the at least one processor, the program instructions including instructions for performing a method according to any one of claims 1-19 .
24. A readable storage medium storing program instructions, when the program instructions are read and executed by a computing device, cause the computing device to execute the method according to any one of claims 1-19.

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