CN110940347A

CN110940347A - Auxiliary vehicle navigation method and system

Info

Publication number: CN110940347A
Application number: CN201811109401.5A
Authority: CN
Inventors: 蔡岭; 吴栋磊
Original assignee: Alibaba Group Holding Ltd
Current assignee: Banma Zhixing Network Hongkong Co Ltd
Priority date: 2018-09-21
Filing date: 2018-09-21
Publication date: 2020-03-31
Anticipated expiration: 2038-09-21
Also published as: CN110940347B; WO2020057407A1; TW202024569A

Abstract

The invention discloses an auxiliary vehicle navigation method, which comprises the following steps: acquiring road data in a preset range, wherein the road data comprises static and/or dynamic information of each object in the preset range; identifying one or more vehicles and vehicle motion information in each object based on the road data; and transmitting the vehicle motion information and the road data to one or more vehicles so that the vehicles perform vehicle navigation. The invention also discloses corresponding roadside sensing equipment and a vehicle navigation system.

Description

Auxiliary vehicle navigation method and system

Technical Field

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

Background

As the automotive industry moves into the internet and intelligent era, sensors and arithmetic units in or around the vehicle can provide increasingly greater driving-related data and computing power. These data and capabilities can assist in driving the vehicle more efficiently than previously, making vehicle driving simpler, more intelligent, and safer.

Various vehicle navigation solutions already exist. One common vehicle navigation solution is to utilize location information of the vehicle or smart devices on the vehicle. That is, first, position information of a vehicle and map information of a road are obtained, the position of the vehicle is superimposed on the map information, and after a destination designated by a user, a navigation plan route is determined using the position of the vehicle and the map information. The vehicle's location on the map is then updated as the vehicle travels, and the vehicle is directed to the destination based on the map features.

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

Another problem with existing navigation methods is that information such as congestion levels on the map may be reported by vehicles on the road over a period of time. The congestion on the map cannot be confirmed on a lane-by-lane basis due to the problem of the local positioning accuracy of the vehicle. And thus lane-based navigation planning is not possible.

With the development of the technology of the internet of vehicles V2X, a collaborative environment awareness system appears. The system can use the data of the vehicle and the surrounding environment together to navigate the vehicle. However, how to construct the environmental data and how to fuse the vehicle itself and the environmental data are problems faced by the collaborative environmental awareness system.

For this reason, a new navigation system is needed that can provide a lane-level navigation plan. The navigation scheme does not depend on a high-precision GNSS, can carry out real-time navigation, and can be adjusted at any time according to real-time road conditions.

Disclosure of Invention

To this end, the present invention provides a new vehicle navigation solution in an attempt to solve or at least alleviate at least one of the problems identified above.

According to one aspect of the present invention, there is provided a method of assisting navigation of a vehicle, the method comprising the steps of: acquiring road data in a preset range, wherein the road data comprises static and/or dynamic information of each object in the preset range; identifying one or more vehicles and vehicle motion information in each object based on the road data; and sending the vehicle motion information and the road data to the one or more vehicles so that the one or more vehicles can perform vehicle navigation.

Alternatively, in the aided vehicle navigation method according to the present invention, the step of acquiring road data within a predetermined range includes: acquiring static information which is stored in advance and is about the preset range of the track; obtaining static and/or dynamic information of each object in a preset range by using each sensor deployed in the drive test sensing equipment; the road data is generated by combining static information stored in advance and information obtained by the respective sensors.

Optionally, in the method for assisting vehicle navigation according to the present invention, the step of acquiring road data within a predetermined range further includes: receiving vehicle running information sent by a vehicle in a preset range in a preset communication mode; and combining the pre-stored static information, the information obtained by the respective sensors, and the received vehicle travel information to generate road data.

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

Alternatively, in the aided vehicle navigation method according to the present invention, the identifying one or more vehicles and vehicle motion information in the objects based on the road data comprises: determining vehicle objects belonging to the vehicle and motion information thereof based on the motion characteristics of the objects; and identifying the identity of each vehicle object.

Optionally, the method for assisting vehicle navigation according to the present invention further comprises the steps of: receiving a navigation request sent by a navigation vehicle in a preset range in a preset communication mode; matching the navigation vehicle from the identified one or more vehicles; and responding to the navigation request, and sending the vehicle motion information and the road data of the matched navigation vehicle to the navigation vehicle so as to carry out vehicle navigation.

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

Alternatively, in the method for assisting vehicle navigation according to the present invention, each object includes one or more of the following objects: lane lines, guardrails, isolation strips, vehicles, pedestrians, and sprinkles; the static and/or dynamic information includes one or more of the following: location, distance, velocity, angular velocity, license plate, type and size, etc.

Optionally, in the method for assisting vehicle navigation according to the present invention, the sensor in the roadside sensing device includes one or more of the following: millimeter wave radar, laser radar, camera, infrared probe.

Alternatively, in the auxiliary vehicle navigation method according to the present invention, the vehicle travel information includes one or more of the following: current time, size, velocity, acceleration, angular velocity, and position.

Optionally, the method for assisting vehicle navigation according to the present invention further comprises the steps of: after determining the 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 sending the calculated navigation plan to the navigation vehicle.

Alternatively, in the auxiliary vehicle navigation method according to the present invention, the navigation planning is performed in a basic unit of a lane on a road.

Optionally, the method for assisting vehicle navigation according to the present invention further comprises the steps of: and receiving a clock synchronization request of the navigation vehicle and performing clock synchronization.

Optionally, the method of assisting navigation of a vehicle according to the invention is further adapted to be performed in a roadside awareness apparatus deployed at a road location or in a server coupled to the roadside awareness apparatus.

According to another aspect of the present invention, there is provided a method of assisting vehicle navigation performed in a vehicle that travels on a road on which a roadside sensing device is disposed, the method including the steps of: sending a navigation request; receiving vehicle motion information determined by the road side sensing device and road data of a road section associated with the road side sensing device, which are returned in response to the navigation request; obtaining a navigation plan generated based on the vehicle motion information and the road data; and navigating the vehicle based on the navigation plan.

According to still another aspect of the present invention, there is provided a roadside sensing apparatus disposed at a road location, the apparatus including: the sensor group is suitable for obtaining static and dynamic information of each object in a preset range; a storage unit adapted to store the road data, the road data including static and dynamic information of each object within a predetermined range; and a computing unit adapted to perform the method of assisting navigation of a vehicle according to the invention.

According to still another aspect of the present invention, there is provided a vehicle navigation system including: the roadside sensing devices are deployed at the side positions of the road; and a vehicle that travels on a road and performs the auxiliary vehicle navigation method according to the present invention.

According to still another aspect of the present invention, there is also provided a computing device. 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, there is also provided a readable storage medium storing program instructions that, when read and executed by a computing device, cause the computing device to execute the above-described assisted vehicle navigation method.

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

Drawings

To the accomplishment of the foregoing and related ends, certain illustrative aspects are described herein in connection with the following description and the annexed drawings, which are indicative of various ways in which the principles disclosed herein may be practiced, and all aspects and equivalents thereof 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 from the following detailed description read in conjunction with the accompanying drawings. Throughout this disclosure, like reference numerals generally refer to like parts or elements.

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

FIG. 2 shows a schematic diagram of a roadside sensing device according to one embodiment of the invention;

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

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

Detailed Description

Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

FIG. 1 shows a schematic diagram of a vehicle navigation system 100 according to one 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. Vehicle 110 is traveling on road 140. Roadway 140 includes a plurality of lanes 150. During the driving process of the vehicle 110 on the road 140, different lanes 150 may be switched according to the road condition and the driving target. The roadside sensing device 200 is disposed at the periphery of the road, and collects various information within a predetermined range around the roadside sensing device 200, particularly road data related to the road, using various sensors it has.

The roadside sensing device 200 has a predetermined coverage. According to the coverage range and the road condition of each roadside sensing device 200, a sufficient number of roadside sensing devices 200 can be deployed on two sides of the road, and the whole road can be fully covered. Of course, according to an embodiment, instead of fully covering the entire road, the roadside sensing devices 200 may be deployed at the feature points (corners, intersections, and diversions) of each road to obtain the feature data of the road. The present invention is not limited by the specific number of roadside sensing devices 200 and the coverage of the road.

When the roadside sensing devices 200 are deployed, the positions of the sensing devices 200 to be deployed are 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 on at least the arrangement height of the sensing device 200, the effective distance sensed by the sensors in the sensing device 200, and the like. And the condition of road 140 includes road length, number of lanes 150, road curvature and grade, etc. The deployment location of the perceiving device 200 may be calculated in any manner known in the art.

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

Subsequently, the position of each deployed roadside sensing device 200 is determined. Since the perception device 200 is to provide a highly accurate vehicle navigation function for the vehicle 110 traveling at high speed on the road 140, the position of the perception device 200 must be highly accurate. There are a number of ways to calculate the high accuracy absolute position of the perceiving device 200. According to one embodiment, a Global Navigation Satellite System (GNSS) may be utilized to determine a high accuracy position.

The roadside sensing device 200 collects and senses the static conditions (lane lines 120, guardrails, isolation belts and the like) and the dynamic conditions (running vehicles 110, pedestrians 130 and sprinklers) of the roads in the coverage area thereof by using the sensors thereof, and fuses the sensing data of the different sensors to form the road data of the section of the road. The road data comprises static and dynamic information of all objects within the coverage area of the perceiving device 200, in particular within the road-related field. 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.

A vehicle 110 entering the coverage area of one roadside sensing device 200 may communicate with the roadside sensing device 200. A typical communication method is the V2X communication method. Of course, the mobile internet provided by the mobile communication service provider may communicate with the roadside sensing devices 200 using mobile communication means such as 5G, 4G and 3G. In consideration of the fact that the vehicle runs at a high speed and the requirement for the time delay of communication is as short as possible, the V2X communication method is adopted in the general embodiment of the present invention. However, any communication means that can meet the time delay requirements required by the present invention is within the scope of the present invention.

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

The vehicle 110 may receive vehicle motion information associated with the vehicle 110 and road data for the segment of road in various ways. In one implementation, vehicles 110 entering the coverage area of roadside sensing devices 200 may be automatically receiving such 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 section of road to the vehicle 110 in response to the request so as to navigate by the vehicle 110.

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 segment, and all manners in which the vehicle motion information and the road data of the road segment can be received and navigated according to are within the scope of the present invention.

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 consisting of a plurality of servers. Each roadside sensing device 100 transmits the sensed road data to the server 160. The server 160 may combine the road data based on the location of each roadside sensing device 100 to form road data for the entire road. The server 160 may also perform further processing on the road data of the road to form information required for vehicle navigation, such as traffic conditions of the entire road, an emergency section, an expected transit time, and the like.

The calculation of the navigation plan at the vehicle 110, the roadside sensing device 200, or the server 160 may be selected as needed in consideration of the requirements of the computation power and the time delay. The navigation plan may be calculated on the basis of vehicle motion information of the navigation vehicle and road data of a certain road. The server 160 is most computationally powerful, but requires data to be sent to the server 160 for computation. The vehicle 110 may be computationally inefficient, but locally utilizes the real-time operating information of the vehicle directly to calculate the navigation plan, and thus has accurate navigation plan results. And the navigation plan is calculated on the roadside sensing device 200, which does not need to perform network transmission of a large amount of data and has the best time delay.

The invention may select which device to perform the navigation planning calculations in depending on the particular situation in which it is used. Wherever navigation planning calculations are performed, these are within the scope of the present invention.

The road data and the vehicle motion information of the formed whole road may be sent to each roadside sensing device 200, or the road-related data and the vehicle motion information of a section of road corresponding to several roadside sensing devices 200 adjacent to a certain roadside sensing device 200 may be sent to the roadside sensing device 200. In this way, the vehicle 110 may obtain a greater range of road data from the roadside sensing device 200. Of course, the vehicle 110 may obtain the road data and the 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 within an area and the roadside sensing devices 200 transmit road data to the server 160, navigation instructions for road traffic within the area may be formed at the server 160. Vehicle 110 may receive the navigation instructions from server 160 and navigate accordingly.

FIG. 2 shows a schematic diagram of a roadside sensing device 200 according to one embodiment of the 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 is to communicate with each vehicle 110 entering its coverage area to provide a vehicle navigation service to the vehicle 110 and to receive vehicle travel information of the vehicle from the vehicle 110. At the same time, the roadside sensing devices 200 also need 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 employ various communication methods including, but not limited to, ethernet, V2X, 5G, 4G, and 3G mobile communication, etc., as long as they can complete data communication with as little time delay as possible. In one embodiment, roadside sensing device 200 may communicate with vehicle 110 entering its coverage area using V2X, while roadside sensing device 200 may communicate with server 160 using, for example, a high speed internet.

The sensor group 220 includes various sensors, for example, radar sensors such as a millimeter wave radar 222 and a laser radar 224, and image sensors such as a camera 226 and an infrared probe 228 having a light supplement function. For the same object, various sensors can obtain different properties of the object, for example, radar sensors can make object velocity and acceleration measurements, while image sensors can obtain object shape, relative angle, etc.

The sensor group 220 collects and senses static conditions (lane lines 120, guardrails, isolation strips, etc.) and dynamic conditions (running vehicles 110, pedestrians 130, and sprinklers) of roads in the coverage area using the respective sensors, and stores data collected and sensed by the respective sensors in the storage unit 230.

The computing unit 240 fuses the data sensed by the sensors to form road data for the road segment and also stores the road data in 234. In addition, the calculation unit 240 may further perform data analysis based on the road data to identify one or more vehicles and vehicle motion information therein. Such data and information may be stored in storage unit 230 for transmission to vehicle 110 or server 160 via communication unit 210.

In addition, various calculation models, such as a collision detection model, a license plate recognition model, a navigation planning model, and the like, may be stored in the storage unit 230. These computational models may be used by the computational 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 of assisting vehicle navigation, according to an embodiment of the invention. The aided vehicle navigation method 300 is suitable for being executed in the roadside sensing device 200 shown in fig. 2 or in the server 160. When executed in the server 160, the relevant data generated or received by the roadside sensing device 200 needs to be transmitted to the server 160 so as to perform relevant processing in the server 160.

As shown in fig. 3, the assisted vehicle navigation method 300 begins 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 generally fixedly disposed near a certain road, and thus has a corresponding road position. In addition, the roadside sensing device 200 has a predetermined coverage area depending on at least 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 at a side of a certain road, a predetermined range of the road that can be covered by the sensing device can be determined according to the specific positions, heights and effective sensing distances of the sensing device and the road.

The roadside sensing device 200 collects and/or senses the static conditions (lane lines 120, guardrails, isolation strips, etc.) and dynamic conditions (running vehicles 110, pedestrians 130, and sprinklers) of the road in the coverage area by using the various sensors thereof to obtain and store various sensor data.

As described above, the roadside sensing device 200 includes various sensors, for example, radar sensors such as the millimeter wave radar 222 and the laser radar 224, and image sensors such as the camera 226 and the infrared probe 228 having a light supplement function, and the like. For the same object, various sensors can obtain different properties of the object, for example, a radar sensor can perform object velocity and acceleration measurements, and an image sensor can obtain the shape and relative angle of the object.

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 substep S312. In step S312, static information on a predetermined range of road positions, which is stored in advance, is acquired. After the roadside sensing device is deployed at a certain position of a road, the range of the road covered by the sensing device is fixed. Static information of the predetermined range, such as road width, number of lanes, turning radius, etc., within the range may be obtained. There are a number of ways to obtain static information of a road. In one embodiment, this static information may be pre-stored in the perceiving device at the time of deployment of the perceiving device. In another embodiment, the location information of the perceiving device may be obtained first, and then a request containing the location information may be sent to the server 160, so that the server 160 returns the static information of the relevant road range according to the request.

Subsequently, in step S314, the raw sensor data is processed according to different sensors to form sensing data such as distance measurement, speed measurement, type identification, size identification, and the like. Next, in step S316, based on the road static data obtained in step S312, calibration is performed using different sensor data as a reference and other sensor data, and finally uniform road data is formed.

Steps S312-S136 describe one way to obtain road data. The invention is not limited to the particular manner in which the data of the various sensors is fused to form the roadway data. This approach is within the scope of the present invention as long as the road data contains static and dynamic information for various objects within a predetermined range of the road location.

According to one embodiment, each vehicle 110 entering the coverage area of the roadside sensing device 200 actively communicates with the sensing device 200 through various communication means (e.g., V2X). Therefore, as described in step S318, the vehicle 110 transmits the vehicle travel information of the vehicle to the perception device 200. The travel information of the vehicle includes the travel information that the vehicle has during travel, including, for example, the current time at which the travel information is generated, the size, speed, acceleration, angular velocity, and position of the vehicle. The method S310 further includes a step S319 in which the vehicle travel information obtained in the step S318 is further fused on the basis of the road data formed in the step S316 to form new road data.

Next, in step S320, one or more vehicles within the sensing unit coverage and motion information of the vehicles are identified based on the road data obtained at step S310. The identification in step S320 includes two aspects of identification. One aspect of the identification is vehicle identification, i.e. identifying which objects in the road data are vehicle objects. Since the vehicle objects have different motion characteristics, such as a relatively high speed, traveling in a lane in one direction, generally not sending collisions with other objects, and the like. A conventional classification detection model or a deep learning-based model may be constructed based on these motion characteristics, and the constructed model is applied to road data, thereby determining motion characteristics such as a vehicle object and a motion trajectory of the vehicle object in the road data.

Another aspect of the identification is identifying a vehicle identification. For the recognized vehicle object, its vehicle identification is further determined. One way to determine the identity of the vehicle is to determine the unique license plate of the vehicle, for example by means of image recognition or the like. When the license plate of the vehicle cannot be identified, another way to determine the vehicle identifier may be to generate a unique mark of the vehicle by combining the size, type, position information, driving speed, and the like of the vehicle object. The vehicle identification is the unique identification of the vehicle object within the road section and is used to distinguish it from other vehicle objects. The vehicle identification is used in subsequent data transmission and is transmitted in different road side sensing devices in the road so as to facilitate overall analysis.

Subsequently, in step S330, a data request sent by a navigation vehicle 110 desiring to navigate entering the coverage area of the roadside sensing device 200 is received. Since 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 the road data, so that the navigation vehicle 110 needs to send a request to the roadside sensing device 200.

Subsequently, in step S340, after receiving the data request issued by the navigation vehicle 110, the requested navigation vehicle 110 needs to be matched with all vehicles within the coverage area of the perception device 200, so as to determine which vehicle within the coverage area issued the data request.

Vehicle matching can be performed through various matching modes or combination of license plate matching, driving speed and type matching, position information fuzzy matching and the like. According to one embodiment, the vehicle 110 may bind the license plate information through V2X or application verification, and the license plate information may further be matched to the vehicle data of the corresponding license plate in the roadside sensing device and the server, thereby implementing license plate matching.

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

It should be noted that the above steps S330 and S340 are not essential steps of the present invention. The vehicle 110 may receive vehicle motion information associated with the vehicle 110 and road data for the segment of road in various ways. In one implementation, vehicles 110 entering the coverage area of roadside sensing devices 200 may be automatically receiving such 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 section of road to the vehicle 110 in response to the request so as to navigate by the vehicle 110. 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 segment, and all manners in which the vehicle motion information and the road data of the road segment can be received and navigated according to are within the scope of the present invention.

Thus, in one embodiment, in step S350, the vehicle motion information associated with the one or more vehicles 110 identified in step S320 and the road data of the road segment may be actively transmitted for the vehicles 110 to navigate.

In addition, optionally, after the vehicle motion information and the road data are transmitted to the navigation vehicle 110 in step S350, in order to facilitate the navigation of the navigation vehicle 110, step S360 is further included in the method 300. 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. Navigation planning may be performed in a variety of ways known in the art and are within the scope of the present invention. Alternatively, the vehicle motion information and the road data may be transmitted to the cloud server 160, and the navigation plan calculation is performed at the cloud server 160, and the calculated navigation plan is obtained from the cloud server 160.

According to one embodiment of the invention, the navigation plan is a lane-level navigation path plan (this plan may also be calculated at the vehicle end). Because the road data contains static and dynamic data related to the lane, when the navigation path is planned, lane-level avoidance can be performed according to the road conditions (obstacles, fault vehicles, congested lanes, accident lanes and the like), so that the lane-level navigation path planning is realized.

In addition, when the navigation path is planned, the global optimal scheme of the whole road section can be searched on the basis of the whole vehicle data. And after global optimization, determining the planned path of the navigation vehicle.

Since the server 160 contains the road data of the entire road, the planned path of a certain navigation vehicle can be determined at the server 160 taking into account the global optimum of the entire road.

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

Further, optionally, as strict a time consistency as possible is required due to navigation. For this reason, the navigation vehicle generally needs to be time-synchronized with a device that provides navigation path planning or navigation basic data (i.e., motion information and road data of the vehicle). For this reason, the method 300 further includes receiving a time synchronization request of the navigation vehicle and performing processing 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 of assisting vehicle navigation according to another embodiment of the invention. The vehicle navigation method 400 is adapted to be executed in a vehicle 110, and the vehicle 110 runs on a road on which the roadside sensing device 200 is disposed. The method 400 includes step S410. In step S410, a navigation request is sent. The navigation request may be sent to the roadside sensing device 200 or the server 160. Both the perceiving device 200 and the server 160 have stored therein vehicle movement information of individual vehicles within the coverage area of the perceiving device and road data of associated road segments, so that navigation requests can be processed.

Subsequently, in step S420, the vehicle movement information determined by the roadside sensing device and the road data of the road segment associated with the drive test sensing device, which are returned in response to the navigation request of step S410, are received. The specific manner in which the vehicle motion information and the road data are calculated has been described above with reference to step S320 of the method of fig. 3, and will not be described herein in detail.

Subsequently, in step S430, a navigation plan generated based on the vehicle motion information and the road data is acquired. As indicated above, the navigation plan may be generated in vehicle 110, roadside sensing devices 200, and 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 the requirement. As described above, the navigation plan is a navigation path plan at a lane level. Because the road data contains static and dynamic data related to the lane, when the navigation path is planned, lane-level avoidance can be performed according to the road conditions (obstacles, fault vehicles, congested lanes, accident lanes and the like), so that the lane-level navigation path planning is realized.

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

Alternatively, the data transmission may be delayed in time, considering that the vehicle is usually traveling at a high speed. It is therefore likely that the position of the vehicle transmitted by the sensing unit may have lagged. To this end, the method S400 further includes a step S450, wherein the time difference is obtained by comparing the vehicle time with the vehicle data time sensed by the sensing unit. And then in step S460, the vehicle position included in the vehicle motion information is adjusted to obtain the current actual position information of the navigation vehicle based on the time difference, the vehicle speed, the acceleration, and the angular velocity included in the vehicle motion information.

Alternatively, in the case of V2X/5G communication between the vehicle and the sensing device 200, considering the high real-time performance of V2X communication, the time difference is relatively small, generally within 50ms, that is, the calculated accumulated error is relatively small. In this case, in step S460, the vehicle position can be adjusted in real time from the data such as the vehicle speed, acceleration, and angular velocity acquired from the vehicle itself, and lane-level navigation with higher accuracy is realized.

According to the vehicle navigation scheme provided by the invention, the perception capability of the road side unit can be fully utilized, and high-precision road data can be provided, so that the lane-level navigation path planning can be provided.

It should be appreciated that in the foregoing description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be interpreted as reflecting an intention that: that the invention as claimed 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 foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.

Those skilled in the art will appreciate that the modules or units or components of the devices in the examples disclosed herein may be arranged in a device as described in this embodiment or alternatively may be located in one or more devices different from the devices in this example. 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 will appreciate that the modules in the device in an embodiment may be adaptively changed and disposed in one or more devices different from the embodiment. The modules or units or components of the embodiments 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. All of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or elements of any method or apparatus so disclosed, may be combined in any combination, except combinations where at least some of such features and/or processes or elements are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.

Furthermore, those skilled in the art will appreciate that while some embodiments described herein include some features included in other embodiments, rather than other features, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the following claims, any of the claimed embodiments may be used in any combination.

Furthermore, some of the described embodiments are described herein as a method or combination of method elements that can be performed by a processor of a computer system or by other means of performing the described functions. A processor having the necessary instructions for carrying out the method or method elements thus forms a means for carrying out the method or method elements. Further, the elements of the apparatus embodiments described herein are examples of the following apparatus: the apparatus is used to implement the functions performed by the elements for the purpose of carrying out the invention.

As used herein, unless otherwise specified the use of the ordinal adjectives "first", "second", "third", etc., to describe a common object, merely indicate that different instances of like objects are being referred to, and are not intended to imply that the objects so described must be in a given sequence, either temporally, spatially, in ranking, or in any other manner.

While the invention has been described with respect to a limited number of embodiments, those skilled in the art, having benefit of this description, will appreciate that other embodiments can be devised which do not depart from the scope of the invention as described herein. Furthermore, it should be noted that the language used in the specification has been principally selected for readability and instructional purposes, and may not have been selected to delineate or circumscribe the inventive subject matter. Accordingly, many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the appended claims. The present invention has been disclosed in an illustrative rather than a restrictive sense, and the scope of the present invention is defined by the appended claims.

Claims

1. A method of assisting navigation of a vehicle, the method comprising the steps of:

acquiring road data in a preset range, wherein the road data comprises static and/or dynamic information of each object in the preset range;

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

and sending the identified vehicle motion information and the road data to the one or more vehicles so as to facilitate vehicle navigation of the one or more vehicles.

2. The aided vehicle navigation method of claim 1, the step of acquiring road data within a predetermined range comprising:

acquiring static information which is stored in advance and is about the preset range;

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

combining the pre-stored static information and information obtained by the respective sensors to generate the road data.

3. The aided vehicle navigation method of claim 2, the step of acquiring road data within a predetermined range comprising:

receiving vehicle running information sent by the vehicles in the preset range in the preset communication mode; and

the pre-stored static information, the information obtained by the respective sensors, and the received vehicle travel information are combined to generate the road data.

4. The aided vehicle navigation method of claim 2 or 3, the step of acquiring pre-stored static information about the predetermined range of road positions comprising:

determining a geographical location of the drive test awareness device; and

static information within a predetermined range of the geographic location is obtained from a server.

5. The method of assisting vehicle navigation according to any one of claims 1-4, the identifying one or more vehicles and vehicle motion information in the objects based on the road data step comprising:

determining vehicle objects belonging to the vehicle and motion information thereof based on the motion characteristics of the objects; and

an identification of each vehicle object is identified.

6. The method of assisting vehicle navigation according to any one of claims 1-5, further comprising the steps of:

receiving a navigation request sent by a navigation vehicle in the preset range in a preset communication mode;

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

and responding to the navigation request, and sending the vehicle motion information of the matched navigation vehicle and the road data to the navigation vehicle so as to facilitate the navigation vehicle to carry out vehicle navigation.

7. The method of assisting vehicle navigation according to any one of claims 1-6, further comprising the steps of:

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

and sending the calculated navigation plan to the navigation vehicle.

8. The aided vehicle navigation method of claim 7, wherein the navigation planning is performed in basic units of lanes on a road.

9. The method of assisting vehicle navigation according to any one of claims 1-8, further comprising the steps of:

and receiving a clock synchronization request of the navigation vehicle, and performing clock synchronization.

10. The method of assisting vehicle navigation according to any one of claims 1-9, wherein the communication means includes one or more of:

V2X, 5G, 4G and 3G communications.

11. The method of assisting vehicle navigation according to any one of claims 1-10, the objects comprising one or more of the following: lane lines, guardrails, isolation strips, vehicles, pedestrians, and sprinkles;

the static and/or dynamic information includes one or more of the following: location, distance, velocity, angular velocity, license plate, type and size, etc.

12. The method of assisting vehicle navigation according to any one of claims 2-11, the sensor in the roadside sensing device comprising one or more of:

millimeter wave radar, laser radar, camera, infrared probe.

13. The method of assisting vehicle navigation according to any one of claims 1-12, wherein the method is adapted to be performed in a roadside awareness apparatus deployed within the predetermined range or a server coupled to the roadside awareness apparatus.

14. A method of assisting vehicle navigation performed in a vehicle traveling on a road on which a roadside sensing device is disposed, the method comprising the steps of:

sending a navigation request;

receiving vehicle motion information determined by the road side sensing device and road data of a road section associated with the drive test sensing device, which are returned in response to the navigation request;

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

and navigating the vehicle based on the navigation plan.

15. The method of assisting vehicle navigation according to claim 14, further comprising the step of:

and sending a clock synchronization request to realize clock synchronization of the vehicle and the roadside sensing equipment.

16. The aided vehicle navigation method of claim 14 or 15, wherein the navigation plan is generated at any one of the vehicle, the roadside sensing device and a server coupled to the vehicle and roadside sensing device.

17. The aided vehicle navigation method of any one of claims 14-16, wherein the navigation planning is performed on a basic unit of a lane on a road.

18. The method of assisting vehicle navigation according to any one of claims 14-17, further comprising the steps of:

comparing the current vehicle time with the vehicle data time corresponding to the received vehicle motion information to obtain a time difference;

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

and based on the current actual position information of the vehicle, carrying out vehicle navigation according to the navigation plan.

19. The aided vehicle navigation method of claim 18, wherein the vehicle position adjustment process is performed using a vehicle speed, an acceleration, and an angular velocity that are acquired by the vehicle itself.

20. A roadside sensing device deployed at a road location, comprising:

each sensor adapted to obtain static and dynamic information for each object within the predetermined range;

a storage unit adapted to store the road data including static and dynamic information of each object within the predetermined range; and

a computing unit adapted to perform the method of any of claims 1-12.

21. A vehicle navigation system comprising:

a plurality of roadside sensing devices as recited in claim 20 deployed at a lateral location on a road; and

a vehicle that travels on the road and that performs the vehicle navigation method of any one of claims 14-18.

22. The vehicle navigation system of claim 21, further comprising:

and the cloud server is suitable for receiving the road data of the road side sensing equipment and combining the road data based on the deployment position of each road side sensing equipment to generate the road data of the whole road.

23. A computing device, comprising:

at least one processor; and

a memory storing program instructions configured for execution by the at least one processor, the program instructions comprising instructions for performing the method of any of claims 1-19.

24. A readable storage medium storing program instructions that, when read and executed by a computing device, cause the computing device to perform the method of any of claims 1-19.