CN110940347B - A method and system for assisting vehicle navigation - Google Patents

Abstract

The present invention discloses a method for assisting vehicle navigation, the method comprising the steps of: acquiring road data within a predetermined range, the road data including static and/or dynamic information of each object within the predetermined range; identifying one or more vehicles and vehicle motion information of each object based on the road data; and sending the vehicle motion information and road data to one or more vehicles so that these vehicles can perform vehicle navigation. The present invention also discloses a corresponding roadside sensing device and a vehicle navigation system.

Description

A method and system for assisting vehicle navigation

Technical Field

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

Background technique

As the automotive industry enters the Internet and intelligent era, sensors and computing units in or around vehicles 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 simpler, smarter and safer.

There are various vehicle navigation solutions. One common vehicle navigation solution is to use the location information of the vehicle or the smart device on the vehicle. That is, first obtain the location information of the vehicle and the map information of the road, superimpose the location of the vehicle on the map information, and after the destination specified by the user, use the vehicle location and map information to determine the navigation planning route. Then, as the vehicle moves, the location of the vehicle on the map is updated, and the vehicle is guided to the destination according to the map features.

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

Another problem with existing navigation methods is that the congestion level on the map may be based on reports from 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 by lane. Therefore, lane-based navigation planning cannot be achieved.

With the development of V2X technology, a collaborative environmental perception system has emerged. This system can use the data of the vehicle and the surrounding environment to navigate the vehicle. However, how to construct environmental data and how to integrate the vehicle itself and the environmental data are the problems faced by the collaborative environmental perception system.

Therefore, a new navigation system is needed that can provide lane-level navigation planning. This 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

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

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

Optionally, in the auxiliary 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; using various sensors deployed in the road test perception equipment to obtain static and/or dynamic information of each object within the predetermined range; combining the pre-stored static information and 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 acquiring road data within a predetermined range also includes: receiving vehicle driving information sent by vehicles within the predetermined range through a predetermined communication method; and combining pre-stored static information, information obtained by various sensors and the received vehicle driving information to generate road data.

Optionally, in the method for assisting vehicle navigation according to the present invention, the step of acquiring static information about a predetermined range includes: determining a geographical location of the roadside perception device; and acquiring static information within a predetermined range of the geographical location 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 among each object based on road data includes: determining the vehicle objects belonging to the vehicle and their motion information based on the motion characteristics of each object; and identifying the identification of each vehicle object.

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

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

Optionally, in the auxiliary vehicle navigation method according to the present invention, each object includes one or more of the following objects: lane lines, guardrails, isolation strips, vehicles, pedestrians and spilled objects; static and/or dynamic information includes one or more of the following: 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 sensor in the roadside perception device includes one or more of the following: millimeter wave radar, laser radar, camera, infrared probe.

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

Optionally, the auxiliary vehicle navigation method according to the present invention also 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 sending the calculated navigation plan to the navigation vehicle.

Optionally, in the method for assisting vehicle navigation according to the present invention, navigation planning is performed with lanes on the road as basic units.

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

Optionally, the method for assisting vehicle navigation according to the present invention is also suitable for being executed in a roadside perception device deployed at a road location or in a server coupled to the roadside perception device.

According to another aspect of the present invention, there is provided an assisted vehicle navigation method executed in a vehicle, wherein the vehicle is traveling on a road on which a roadside sensing device is deployed, the method comprising the steps of: sending a 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; obtaining a navigation plan generated based on the vehicle motion information and the road data; and performing vehicle navigation based on the navigation plan.

According to another aspect of the present invention, there is provided a roadside perception device, which is deployed at a road location, and includes: a sensor group, suitable for obtaining static and dynamic information of each object within a predetermined range; a storage unit, suitable for storing the road data, the road data including static and dynamic information of each object within the predetermined range; and a computing unit, suitable for executing the auxiliary vehicle navigation method according to the present invention.

According to another aspect of the present invention, a vehicle navigation system is provided, comprising: a plurality of the above-mentioned roadside sensing devices, deployed at the side of the road; and a vehicle, traveling on the road and executing the auxiliary vehicle navigation method according to the present invention.

According to another aspect of the present invention, a computing device is provided, which 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 executing the above-mentioned vehicle navigation assistance method.

According to yet another aspect of the present invention, a readable storage medium storing program instructions is provided. When the program instructions are read and executed by a computing device, the computing device executes the above-mentioned method for assisting vehicle navigation.

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

BRIEF DESCRIPTION OF THE DRAWINGS

In order to achieve the above and related purposes, 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 fall within the scope of the claimed subject matter. The above and other purposes, features and advantages of the present disclosure will become more apparent by reading the following detailed description in conjunction with the accompanying drawings. Throughout the present disclosure, the same reference numerals generally refer to the same parts or elements.

FIG1 shows a schematic diagram of a driving assistance system according to an embodiment of the present invention;

FIG2 shows a schematic diagram of a roadside sensing device according to an embodiment of the present invention;

FIG3 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 ways

The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying 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 in order to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

FIG1 shows a schematic diagram of a vehicle navigation system 100 according to an embodiment of the present invention. As shown in FIG1 , the vehicle navigation system 100 includes a vehicle 110 and a roadside sensing device 200. The vehicle 110 travels on a road 140. The road 140 includes a plurality of lanes 150. While the vehicle 110 is traveling on the road 140, it can switch between different lanes 150 according to the road conditions and the driving target. 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 range. According to the coverage range 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, it is not necessary to achieve full coverage of the entire road. Roadside sensing devices 200 can be deployed at the characteristic points (turns, intersections, forks) of each road to obtain characteristic data about the road. The present invention is not limited to the specific number of roadside sensing devices 200 and the coverage range of the road.

When deploying the roadside sensing device 200, firstly, the position of the sensing device 200 to be deployed is 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 of the sensor in the sensing device 200 for sensing. The condition of the road 140 includes the road length, the number of lanes 150, the road curvature and slope, etc. The deployment position of the sensing device 200 can be calculated by any method 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, the clock of the roadside sensing device 200 needs to be synchronized, 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 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-precision absolute position of the sensing device 200. According to one embodiment, a global satellite navigation system (GNSS) can be used to determine the high-precision position.

The roadside sensing device 200 uses its sensors to collect and sense the static conditions (lane lines 120, guardrails, isolation belts, etc.) and dynamic conditions (moving vehicles 110, pedestrians 130 and spilled objects) of the road in its coverage area, and fuses the sensing data of different sensors to form the road data of the section of road. The road data includes the static and dynamic information of all objects within the coverage area of the sensing device 200, especially in the road-related field. The roadside sensing device 200 can then determine the various vehicles in its coverage area and the motion information of each vehicle based on the road data.

A vehicle 110 that enters the coverage area of a 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 travels at a high speed and the time delay of communication is required to be as short as possible, the V2X communication method is adopted in the general implementation 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 section of road from the roadside perception device 200 and use the data to perform vehicle navigation.

The vehicle 110 may receive the vehicle motion information related to the vehicle 110 and the road data of the road section in various ways. In one implementation, the vehicle 110 that enters the coverage area of the roadside perception device 200 may automatically receive the information and data for navigation. In another implementation, the vehicle 110 may issue a navigation request, and the roadside perception device 200 may respond to the request and send the vehicle motion information related to the vehicle 110 and the road data of the road section to the vehicle 110 so that the vehicle 110 can navigate.

The present invention is not limited to the specific method by which the vehicle 110 receives the vehicle motion information and the road data of the section of road. All methods that can receive the vehicle motion information and the road data of the section of road and navigate accordingly are within the protection scope of the present invention.

Optionally, the vehicle navigation system 100 also includes a server 160. Although only one server 160 is shown in FIG1 , 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 perceived road data to the server 160. The server 160 may combine the road data based on the position of each roadside sensing device 100 to form the road data of the entire road. The server 160 may also further process the road data of the road to form the information required for vehicle navigation, such as the traffic conditions of the entire road, the section of the road where an accident occurs, the expected passing time, etc.

Considering the requirements of computing power and time delay, the navigation plan can 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 section of road. The server 160 has the strongest computing power, but the data needs to be sent to the server 160 before calculation. The vehicle 110 may not have strong computing power, but the real-time operation information of the vehicle is directly used locally to calculate the navigation plan, so it has accurate navigation planning 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 select which device to perform navigation planning calculation in according to the specific application situation. No matter where the navigation planning calculation is performed, it is within the protection scope of the present invention.

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

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

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

The roadside perception device 200 needs to communicate with each vehicle 110 that enters 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 perception device 200 also needs to communicate with the server 160. The communication unit 210 provides a communication function for the roadside perception device 200. The communication unit 210 can use various communication methods, including but not limited to Ethernet, V2X, 5G, 4G and 3G mobile communications, as long as these communication methods can complete data communication with as little time delay as possible. In one embodiment, the roadside perception device 200 can use V2X to communicate with the vehicle 110 that enters its coverage area, and the roadside perception device 200 can use, for example, high-speed Internet to communicate with the server 160.

The sensor group 220 includes various sensors, such as radar sensors such as millimeter wave radar 222 and laser radar 224, and image sensors such as camera 226 with fill light function and infrared probe 228. For the same object, various sensors can obtain different properties of the object, for example, radar sensor can measure the speed and acceleration of the object, while image sensor can obtain the shape and relative angle of the object.

The sensor group 220 uses various sensors to collect and perceive the static conditions (lane lines 120, guardrails, isolation belts, etc.) and dynamic conditions (moving vehicles 110, pedestrians 130 and spilled objects) of the roads in the coverage area, and stores the data collected and perceived by each sensor in the storage unit 230.

The computing unit 240 fuses the data sensed by each sensor to form the road data of the road section, and also stores the road data in 234. In addition, the computing unit 240 can also continue to perform data analysis based on the road data to identify one or more vehicles and vehicle movement information. These data and information can be stored in the storage unit 230 so as to be sent to the vehicle 110 or the server 160 via the communication unit 210.

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

FIG3 shows a schematic diagram of a method 300 for assisting vehicle navigation according to an embodiment of the present invention. The method 300 for assisting vehicle navigation is suitable for being executed in the roadside perception device 200 shown in FIG2 or in the server 160. When executed in the server 160, all relevant data generated or received by the roadside perception device 200 need to be sent to the server 160 so as to be processed in the server 160.

As shown in FIG. 3 , the method 300 for assisting vehicle navigation begins at step S310 .

In step S310, road data within a predetermined range of the road position is obtained. As described above with reference to FIG1, the roadside sensing device 200 is usually fixedly deployed near a certain road, and therefore has a corresponding road position. In addition, depending on at least the arrangement height of the sensing device 200 and the effective distance of the sensor in the sensing device 200 for sensing, the roadside sensing device 200 has a predetermined coverage area. Once the roadside sensing device 200 is deployed on the side of a certain road, the predetermined range of the road that the sensing device can cover can be determined based on the specific position, height and effective sensing distance of the sensing device and the road.

The roadside sensing device 200 uses its various sensors to collect and/or sense the static conditions (lane lines 120, guardrails, isolation belts, etc.) and dynamic conditions (moving vehicles 110, pedestrians 130 and spilled objects) of the road in the coverage area to obtain and store various sensor data.

As described above, the roadside perception device 200 includes various sensors, such as radar sensors such as millimeter wave radar 222 and laser radar 224, and image sensors such as camera 226 with fill light function and infrared probe 228. For the same object, various sensors can obtain different properties of the object, for example, radar sensors can measure the speed and acceleration of the object, while image sensors can obtain the shape and relative angle of the object.

In step S310, processing and fusion can be performed based on the various sensor raw data obtained to form unified road data. In one embodiment, step S310 may also include sub-step S312. In step S312, pre-stored static information about a predetermined range of road positions is obtained. After the roadside sensing device is deployed at a certain position on the road, the road range covered by the sensing device is fixed. Static information of the predetermined range can be obtained, such as the road width, number of lanes, turning radius, etc. within the range. There are many ways to obtain static information of the road. In one embodiment, this static information can be pre-stored in the sensing device when the sensing device is deployed. In another embodiment, the location information of the sensing device can be first obtained, and then a request containing the location information is 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 and size recognition, etc. Then, in step S316, based on the road static data obtained in step S312, different sensor data is used as a reference in different situations, and other sensor data is used for calibration to finally form unified road data.

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

According to one embodiment, each vehicle 110 that enters the coverage of the roadside perception device 200 will actively communicate with the perception device 200 through various communication methods (such as V2X). Therefore, as described in step S318, the vehicle 110 will send the vehicle driving information of the vehicle to the perception device 200. The driving information of the vehicle includes the operating information of the vehicle during driving, such as the current time when the operating information is generated, the size, speed, acceleration, angular velocity and position of the vehicle. Method S310 also includes step S319, in which, based on the road data formed in step S316, the vehicle driving information obtained in step S318 is further integrated 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 perception 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, that is, identifying which objects in the road data are vehicle objects. Since vehicle objects have different motion characteristics, such as fast speed, driving in a lane in one direction, and generally not colliding with other objects, etc. A traditional classification detection model or a deep learning-based model can be constructed based on these motion characteristics, and the constructed model can be applied to the road data to determine the motion characteristics such as the vehicle objects and the motion trajectory of the vehicle objects in the road data.

Another aspect of identification is to identify 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, by 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 for 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 section and is used to distinguish it from other vehicle objects. The vehicle identification will be used in subsequent data transmission and will be transmitted to different roadside sensing devices in this road for overall analysis.

Then, in step S330, a data request is received from a navigation vehicle 110 that enters the coverage area of the roadside perception device 200 and desires to perform navigation. Since the road data generated by the roadside perception 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 the roadside perception device 200.

Subsequently, in step S340, after receiving the data request sent by the navigation vehicle 110, it is necessary to match the navigation vehicle 110 that sent the request with all vehicles within the coverage range of the perception device 200 to determine which vehicle within the coverage range sent the data request.

Vehicle matching can be performed through a variety of matching methods or combinations thereof, such as license plate matching, driving speed and type matching, and location information fuzzy 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 then 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 the vehicle matching the navigation vehicle is determined in step S340, in step S350, the vehicle motion information of the matched vehicle determined in step S320 and the road data determined in step S310 are sent to the navigation vehicle 110 so that the navigation vehicle can perform vehicle navigation.

It should be noted that the above steps S330 and S340 are not necessary steps for the present invention. The vehicle 110 may receive the vehicle motion information related to the vehicle 110 and the road data of the section of road in various ways. In one implementation, the vehicle 110 that enters the coverage area of the roadside sensing device 200 may automatically receive this information and data for navigation. In another implementation, the vehicle 110 may issue a navigation request, and the roadside sensing device 200 may send the vehicle motion information related to the vehicle 110 and the road data of the section of road to the vehicle 110 in response to the request, so that the vehicle 110 may navigate. The present invention is not limited to the specific method in which the vehicle 110 receives the vehicle motion information and the road data of the section of road, and all methods that can receive the vehicle motion information and the road data of the section of road and navigate accordingly are within the protection scope of the present invention.

Therefore, in one embodiment, in step S350, vehicle motion information related to one or more vehicles 110 identified in step S320 and road data of the road section may be actively sent to facilitate navigation of these vehicles 110.

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 navigation of the navigation vehicle 110, the method 300 also includes step S360. In step S360, a navigation plan is calculated for the navigation vehicle based on the vehicle motion information and road data of the matched vehicle. Navigation planning can be performed using various methods in the art, and these are all within the scope of protection of the present invention. Optionally, the vehicle motion information and road data can also be sent to the cloud server 160, and the navigation planning calculation is performed on the cloud server 160, and the calculated navigation plan is obtained from the cloud server 160.

According to one embodiment of the present invention, the navigation planning is lane-level navigation path planning (this planning can also be calculated on the vehicle side). Since 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 road conditions (obstacles, faulty vehicles, congested lanes, accident lanes, etc.), thereby realizing lane-level navigation path planning.

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

Since the server 160 includes the road data of the entire road, the server 160 can consider the global optimum of the entire road to determine the planned path of a 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, since navigation requires as strict time consistency as possible, the navigation vehicle usually needs to synchronize time with a device that provides navigation path planning or navigation basic data (i.e., vehicle motion information and road data). To this end, the method 300 also needs to include receiving a time synchronization request from the navigation vehicle and processing it to ensure the time consistency of the navigation vehicle 110, the roadside perception device 200, and the server 160.

FIG4 shows a schematic diagram of an auxiliary vehicle navigation method 400 according to another embodiment of the present invention. The vehicle navigation method 400 is suitable for being executed in a vehicle 110, and the vehicle 110 is traveling on a road where a roadside sensing device 200 is deployed. The method 400 includes step S410. In step S410, a navigation request is sent. The navigation request can be sent to the roadside sensing device 200 or the server 160. The sensing device 200 and the server 160 both 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 road test sensing device returned in response to the navigation request of step S410 are received. The specific manner of calculating the vehicle motion information and the road data has been described in step S320 of the method with reference to FIG. 3 above, and will not be repeated here.

Subsequently, in step S430, a navigation plan generated based on the vehicle motion information and road data is obtained. As shown above, the navigation plan can be generated in the vehicle 110, the roadside perception device 200 and the server 160 as needed. Step S430 can obtain the navigation plan from the vehicle 110, the roadside perception device 200 or the server 160 as needed. As mentioned above, the navigation plan is a lane-level navigation path planning. Since 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 road conditions (obstacles, faulty vehicles, congested lanes, accident lanes, etc.), thereby realizing lane-level navigation path planning.

Then, in step S440, the navigation vehicle is guided to go to the destination according to the obtained navigation plan.

Optionally, considering that vehicles usually travel at high speeds, data transmission may have a time delay. Therefore, it is likely that the vehicle position sent by the perception unit may have lagged behind. To this end, method S400 also includes step S450, in which the time difference is obtained by comparing the vehicle moment and the vehicle data moment perceived by the perception unit. And then in step S460, according to the time difference, the vehicle speed, acceleration and angular velocity 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 navigation vehicle.

In addition, optionally, when there is a V2X/5G communication mode between the vehicle and the perception device 200, considering the high real-time performance of V2X communication, the above time difference will be relatively small, generally within 50ms, that is, the calculated cumulative error will be relatively small. In this case, in step S460, the vehicle speed, acceleration, angular velocity and other data obtained from the vehicle itself can be used to adjust the vehicle's real-time position, thereby achieving higher-precision lane-level navigation.

According to the vehicle navigation solution of the present invention, the perception 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 streamline the present disclosure and aid in understanding one or more of the various inventive aspects, in the above description of exemplary embodiments of the present invention, various features of the present invention are sometimes grouped together into a single embodiment, figure, or description thereof. However, this disclosed method should not be interpreted as reflecting the following intention: that the claimed invention requires more features than those explicitly recited in each claim. More specifically, as reflected in the claims below, inventive aspects lie in less than all the features of the individual embodiments disclosed above. Therefore, the claims that follow the specific embodiment are hereby expressly incorporated into the specific embodiment, with each claim itself serving as a separate embodiment of the present 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 the devices described in the embodiment, or alternatively may be located in one or more devices different from the devices in the examples. The modules in the foregoing examples may be combined into one module or may be divided into multiple submodules.

Those skilled in the art will appreciate that the modules in the devices in the embodiments may be adaptively changed and arranged in one or more devices different from the embodiments. The modules or units or components in the embodiments may be combined into one module or unit or component, and in addition they may be divided into a plurality of submodules or subunits or subcomponents. Except that at least some of such features and/or processes or units are mutually exclusive, all features disclosed in this specification (including the accompanying claims, abstracts and drawings) and all processes or units of any method or device disclosed in this manner may be combined in any combination. Unless otherwise expressly stated, each feature disclosed in this specification (including the accompanying claims, abstracts and drawings) may be replaced by an alternative feature providing the same, equivalent or similar purpose.

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

In addition, some of the 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 functions. Therefore, a processor with necessary instructions for implementing the method or method elements forms a device for implementing the method or method elements. In addition, the elements described herein of the device embodiments are examples of devices for implementing the functions performed by the elements for the purpose of implementing the invention.

As used herein, unless otherwise specified, the use of ordinal numbers "first," "second," "third," etc. to describe common objects merely indicates that different instances of similar objects are involved, and is not intended to imply that the objects so described must have a given order in time, space, order, or in any other manner.

Although the present invention has been described according to a limited number of embodiments, it will be apparent to those skilled in the art, with the benefit of the above description, that other embodiments may be envisioned within the scope of the invention thus described. In addition, it should be noted that the language used in this specification is selected primarily for readability and didactic purposes, rather than for explaining or defining the subject matter of the present invention. Therefore, many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the appended claims. The disclosure of the present invention is illustrative, not restrictive, with respect to the scope of the present invention, which is defined by the appended claims.

Claims (22)

1. A method of assisting vehicle navigation applied to a road side awareness apparatus on a road, 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, the road data respectively processes original sensor data according to different sensors to form sensing data comprising ranging, speed measurement, type and size identification as dynamic information, and based on the acquired road static data, calibrating other sensor data by taking the different sensor data as a reference to form static information;

identifying one or more vehicles and vehicle motion information in the objects based on the road data, including: determining a vehicle object belonging to the vehicle and motion information thereof based on the motion characteristics of the objects; an identification identifying each vehicle object;

transmitting the identified vehicle movement information and the road data to the one or more vehicles for lane-level vehicle navigation by the one or more vehicles;

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

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

acquiring pre-stored static information about the predetermined range;

obtaining static and/or dynamic information of each object in the predetermined range by each sensor deployed in the road side sensing device in the predetermined range;

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

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

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

the road data is generated by combining the prestored static information, the information obtained by the respective sensors, and the received vehicle running information.

4. A method of assisting vehicle navigation according to claim 2 or 3, the step of acquiring static information about a predetermined range of road positions stored in advance comprising:

determining the geographic position of the road side sensing equipment; and

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

5. A method of assisting vehicle navigation according to any one of claims 1-3, further comprising the step of:

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

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

and responding to the navigation request, and transmitting the vehicle motion information of the matched navigation vehicle and the road data to the navigation vehicle so that the navigation vehicle can perform vehicle navigation.

6. A method of assisting vehicle navigation according to any one of claims 1-3, further comprising the step of:

after determining a vehicle that matches a 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.

7. The aided vehicle navigation method of claim 6, wherein the navigation planning is performed in a lane on a road as a basic unit.

8. A method of assisting vehicle navigation according to any one of claims 1-3, further comprising the step of: and receiving a clock synchronization request of the navigation vehicle and performing clock synchronization.

9. A method of assisting vehicle navigation in accordance with claim 3, the means of communication comprising one or more of: V2X, 5G, 4G and 3G communications.

10. A method of assisting vehicle navigation as claimed in any one of claims 1 to 3, the objects comprising one or more of the following: lane lines, guardrails, isolation belts, vehicles, pedestrians and sprinklers; the static and/or dynamic information includes one or more of the following: location, distance, speed, angular velocity, license plate, type, and size.

11. A method of assisting vehicle navigation as claimed in any one of claims 2 to 3, the sensors in the road side sensing apparatus comprising one or more of the following:

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

12. A method of assisting vehicle navigation as claimed in any one of claims 1 to 3, wherein the method is adapted to be performed in a road side sensing device deployed within the predetermined range or a server coupled to the road side sensing device.

13. A method of assisting vehicle navigation performed in a vehicle traveling on a road on which a roadside sensing device is disposed in claim 1, 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 road segments associated with the road side sensing device, which are returned in response to the navigation request;

acquiring a navigation plan generated based on the vehicle motion information and the road data; and performing lane-level vehicle navigation based on the navigation plan.

14. The assisted vehicle navigation method of claim 13, further comprising the step of:

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

15. A method of assisting vehicle navigation as claimed in claim 13 or 14, wherein the navigation plan is generated at any one of the vehicle, the road side awareness apparatus and a server coupled to the vehicle and road side awareness apparatus.

16. The aided vehicle navigation method of claim 13 or 14, wherein the navigation planning is performed in a basic unit of a lane on a road.

17. The assisting vehicle navigation method in accordance with claim 15, wherein the vehicle position adjustment process is performed using a vehicle speed, an acceleration, and an angular speed acquired by the vehicle itself.

18. A roadside awareness device deployed at a roadway location, comprising:

each sensor is suitable for obtaining static and dynamic information of each object in the preset 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 1-3.

19. A vehicle navigation system comprising:

a plurality of roadside awareness devices of claim 18 deployed at roadside locations; and

a vehicle traveling on the road and performing the vehicle navigation method according to any one of claims 13 to 14.

20. The vehicle navigation system of claim 19, further comprising:

and the cloud server is suitable for receiving the road data of the road side sensing devices, and combining the road data based on the deployment positions of the road side sensing devices to generate the road data of the whole road.

21. A computing device, comprising:

at least one processor; and

a memory storing program instructions, wherein the program instructions are configured to be adapted to be executed by the at least one processor, the program instructions comprising instructions for performing the assisted vehicle navigation method of any of claims 1-3, or the assisted vehicle navigation method of claim 13 or 14.

22. A readable storage medium storing program instructions that, when read and executed by a computing device, cause the computing device to perform the assisted vehicle navigation method of any of claims 1-3, or the assisted vehicle navigation method of claim 13 or 14.