CN110595495A - Method for automatically updating a vehicle route plan - Google Patents
Method for automatically updating a vehicle route plan Download PDFInfo
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- CN110595495A CN110595495A CN201810605676.1A CN201810605676A CN110595495A CN 110595495 A CN110595495 A CN 110595495A CN 201810605676 A CN201810605676 A CN 201810605676A CN 110595495 A CN110595495 A CN 110595495A
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- 238000000034 method Methods 0.000 title claims abstract description 38
- 238000012545 processing Methods 0.000 claims abstract description 20
- 238000004891 communication Methods 0.000 claims abstract description 19
- 230000004044 response Effects 0.000 claims abstract description 10
- 230000008569 process Effects 0.000 claims description 4
- 238000005516 engineering process Methods 0.000 description 7
- 238000010586 diagram Methods 0.000 description 6
- 238000004458 analytical method Methods 0.000 description 3
- 206010039203 Road traffic accident Diseases 0.000 description 1
- 230000004075 alteration Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 230000006866 deterioration Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000003292 diminished effect Effects 0.000 description 1
- 230000002349 favourable effect Effects 0.000 description 1
- 230000004807 localization Effects 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
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- 238000012360 testing method Methods 0.000 description 1
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Classifications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/3453—Special cost functions, i.e. other than distance or default speed limit of road segments
- G01C21/3492—Special cost functions, i.e. other than distance or default speed limit of road segments employing speed data or traffic data, e.g. real-time or historical
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/36—Input/output arrangements for on-board computers
- G01C21/3691—Retrieval, searching and output of information related to real-time traffic, weather, or environmental conditions
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/0968—Systems involving transmission of navigation instructions to the vehicle
Abstract
The invention provides a method and a system for automatically updating automobile route planning by utilizing an unmanned aerial vehicle. The system comprises an automobile and a drone, wherein the automobile may further comprise a processing unit configured to generate flight parameters related to performing a flight mission in response to a decision to perform the flight mission by a drone associated with the automobile; and a communication unit configured to: sending the flight parameters to the drone; and receiving the collected ground information from the drone; the processing unit is further configured to: processing the received ground information to obtain ground road condition information of a road related to the current automobile route planning; and updating the route plan based on the acquired ground road condition information.
Description
Technical Field
The present invention relates to vehicle-mounted drones, and more particularly, to a method and system for automatically updating automobile route planning using a vehicle-mounted drone.
Background
Today, as navigation technology develops and matures, people have become accustomed to using navigation systems to plan routes and provide real-time directions while driving automobiles. Such navigation systems (such as Google Map, Here, TomTom, grand maps, etc.) typically work based on digital maps and localization techniques. In addition, for the automatic driving automobile still in the development and test stage, the digital map is required to be completely relied on for positioning and navigation. The car route navigation is based on set route start and destination and the route calculation may provide different routes for selection based on different route planning preferences, e.g. shortest distance first, shortest time first or least congestion may be selected, etc. For autonomous vehicles, the suitability of the route for autonomous driving may also be considered, e.g., a route with the shortest distance may contain a route unsuitable for autonomous driving.
On the other hand, route planning may also be based on dynamic mobility information, such as real-time traffic conditions, local hazard warnings, etc. Upon receiving this information, the navigation system may re-plan the route. For autonomous vehicles, it is more necessary to take this information into account and re-route the vehicle during driving. However, these real-time traffic conditions are not truly "real-time".
For example, a congestion situation may be encountered when a car is traveling en route along a route planned by a navigation system. The situation of some congestion is already known by the navigation system and is displayed on the interface of the navigation system in the car 102, for example, yellow, orange, red to represent light congestion, general congestion, severe congestion, and the like, respectively. Such congestion situations known to the navigation system may have been considered when planning the route, or the navigation system may suggest route planning updates based on the newly known congestion situations. However, the real-time congestion condition is not known by the navigation system in time, because the navigation system usually depends on the information of the urban public road condition system or the information reported by the user, and the feedback of the information needs a certain time. Thus, it is often the case that road segments on the navigation system that appear clear are actually slow to pass, and the cause and severity of congestion is unknown to the driver or autonomous vehicle. By the time the navigation system knows the newly occurring congestion, it may be late, for example, a car has been traveling on a closed road (highway, elevated road, one-way road, etc.) and cannot adjust the route in time to select the most appropriate route.
Disclosure of Invention
This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter.
In view of the above problems, the present invention proposes a method performed by a drone for automatically updating a vehicle route plan, the method comprising: in response to a decision to perform a flight mission, takeoff from the associated automobile; collecting ground information of roads related to the current automobile route planning in the process of executing the flight mission; and sending the collected ground information to the automobile.
According to yet another embodiment of the present invention, there is provided a method performed by a vehicle for automatically updating a route plan of the vehicle, the method including: in response to a decision by a drone associated with the automobile to perform a flight mission, generating flight parameters related to performing the flight mission; sending the flight parameters to the drone; receiving the collected ground information from the drone; processing the received ground information to obtain ground road condition information of a road related to the current automobile route planning; and updating the route plan based on the acquired ground road condition information.
According to still another embodiment of the present invention, there is provided an automobile including: a processing unit configured to generate flight parameters related to performing a flight mission in response to a decision to perform the flight mission by a drone associated with the automobile; and a communication unit configured to: sending the flight parameters to the drone; and receiving the collected ground information from the drone; the processing unit is further configured to: processing the received ground information to obtain ground road condition information of a road related to the current automobile route planning; and updating the route plan based on the acquired ground road condition information.
These and other features and advantages will become apparent upon reading the following detailed description and upon reference to the accompanying drawings. It is to be understood that both the foregoing general description and the following detailed description are explanatory only and are not restrictive of aspects as claimed.
Drawings
So that the manner in which the above recited features of the present invention can be understood in detail, a more particular description of the invention, briefly summarized above, may be had by reference to embodiments, some of which are illustrated in the appended drawings. It is to be noted, however, that the appended drawings illustrate only some typical aspects of this invention and are therefore not to be considered limiting of its scope, for the description may admit to other equally effective aspects.
Fig. 1 is a schematic diagram of a system for automatically updating automobile route planning using an onboard drone according to one embodiment of the present invention.
Fig. 2 is a flow diagram of a method performed by an automobile to automatically update automobile route planning with an onboard drone, according to one embodiment of the present invention.
Fig. 3 is a flow diagram of a method performed by a drone for automatically updating automobile route planning with an onboard drone, according to one embodiment of the invention.
Detailed Description
The present invention will be described in detail below with reference to the attached drawings, and the features of the present invention will be further apparent from the following detailed description.
According to one embodiment of the invention, a system and method for automatically updating automobile route planning using an onboard drone is provided. Fig. 1 is a schematic diagram of a system for automatically updating automobile route planning using an onboard drone according to one embodiment of the present invention. As one non-limiting example, the route planning update system 100 of the present invention may include an automobile 102 and an onboard drone 104.
In the event that the automobile 102 is in congestion but the congestion cause and congestion level are not known, according to one embodiment of the invention, personnel (e.g., drivers or passengers) on the automobile 102 may determine that it is necessary for the drone to take off to explore the road congestion ahead. As another example, the automobile 102 may also automatically make a decision that takeoff of the drone is required based on preset conditions. The preset conditions may include, but are not limited to: the car has been stationary or traveling slowly for a certain time, for example 10 minutes, and at this time the navigation system still has no way of knowing the road conditions ahead by existing means.
In response to a manual or automatic decision to perform a flight mission, the automobile 102 may instruct the on-board drone 104 to take off, fly over the target area by the drone 104, and gather relevant ground information in real-time. Based on the collected information, the automobile 102 may analyze the congestion condition of the road segment ahead and provide the congestion condition to the navigation system of the automobile 102, and the navigation system may update the planned route according to the real-time congestion condition.
The drone 104 may further include a communication module 106 for communicating with the automobile 102. The communication module 106 may support various communication technologies including, but not limited to: 4G LTE, Wi-Fi (2.4GHz, 5.8GHz), or with proprietary communication technologies developed by the drone vendor itself (such as LightBridge in major), and so on.
To collect relevant information needed to update the map, the drone 104 may further include one or more sensors 108. In order to extend the range of the drone as much as possible, the drone may be loaded with only the sensors needed to analyze the ground congestion conditions, so as to reduce the weight of the drone as much as possible. As non-limiting examples, the sensors may include one or more of the following sensors: inertial measurement units, cameras, infrared rangefinders, GPS receivers, ultrasonic radars, and the like. Of course, as the technology evolves, the drone may incorporate any required sensors or other components to provide more relevant information as the drone is able to carry more loads while meeting endurance requirements, as will be appreciated by those skilled in the art.
The automobile 102 may further include a drone takeoff and landing platform. In the non-operational state, the drone 104 may be parked on the drone landing platform of the automobile 102. As one example, a drone take-off and landing platform may be mounted on the roof of an automobile. As another example, when the automobile 102 is a truck (e.g., a mini-pick up truck), the drone landing platform may also be installed in the cargo area of the truck. As yet another example, when the automobile 102 is a two or three compartment car, the drone takeoff and landing platform may also be installed in a trunk that may be automatically opened under the control of the automobile 102 as the drone takes off and lands.
The automobile 102 may further include a communication unit 110 and a processing unit 112. According to one embodiment of the invention, the communication unit 110 of the car is used for communication with the drone 104. The communication unit 110 of the automobile 102 may support the same or more communication technologies than the communication module 106 of the drone 104 and communicate between the two using the same communication technologies as the communication unit of the drone 104.
The processing unit 112 of the automobile 102 may be configured to control the drone to perform flight missions to collect sensor data needed to analyze road surface conditions. In one embodiment, the processing unit 112 may be a central processing unit of an onboard control system of the automobile 102. Alternatively, the processing unit 112 may also be implemented as a stand-alone component. As yet another example, some or all of the functionality of the processing unit 112 may be performed by a server in the cloud that is communicatively coupled with the automobile 102 via a communication network.
As mentioned above, in the event that it is desired to utilize an onboard drone to explore congested road conditions that are not already known by the navigation system, the processing unit 112 of the automobile 102 may generate instructions for the drone 104 to perform a flight mission. The process of updating the route plan with the on-board drone of the present invention is described in further detail below in conjunction with figures 2 and 3.
Fig. 2 is a flow diagram of a method 200 performed by an automobile to automatically update automobile route planning with an onboard drone, according to one embodiment of the invention. The method 300 begins at step 302, and at step 202, in response to a determination by a drone 104 associated with an automobile 102 to perform a mission, the automobile 102 generates flight parameters related to performing the mission. As described above, the decision to perform the mission may be made manually by a person (e.g., a driver or passenger) aboard the automobile 102 or may be made automatically by the automobile 102 based on preset conditions.
More specifically, according to one embodiment of the present invention, flight parameters include, but are not limited to: flight path, flight distance, flight altitude, flight speed, or any other suitable parameter relating to the performance of a flight mission by the drone.
As one example, the flight route may be based on a route planned by the navigation system currently being traveled by the automobile 102. For example, the flight path may take the current position of the automobile 102 as a starting point and fly forward along the currently driving planned route.
The flight distance may be a preset value, such as 2km, or any suitable value within the maximum range of the drone 104. In addition, the cruising ability of the drone varies with the use of the drone, for example, deterioration in battery performance leads to diminished cruising ability. When the preset value is greater than the current cruising ability of the unmanned aerial vehicle, a flight distance value smaller than the preset value can be set for the unmanned aerial vehicle, for example, set to 80% of the current cruising distance. When the settable flight distance is less than a minimum distance threshold (e.g., less than 500m), the automobile 102 may make a decision not to perform a flight mission.
Fly height is another parameter that can be set. The setting of the fly height is influenced by the terrain, for example by the presence of trees, street lights, buildings, or other possible obstacles. Therefore, the flying height can be set at least enough to avoid being affected by the obstacle. On the other hand, a suitable flying height facilitates the acquisition of ground information. When the flight height is too low, the collected pictures lack general knowledge of the ground. However, if the flying height is too high, the details may be lost due to the performance of the sensor, and the situation on the ground cannot be accurately identified. Further, the flying height may also be set in combination with the flying distance. It can be understood that when the flight height is higher, because have good field of vision, therefore unmanned aerial vehicle need not to fly to the vertical sky in target area and can judge the ground condition. For example, if it is necessary to determine the road condition 2km ahead of the location of the automobile 102, the unmanned aerial vehicle does not need to fly horizontally for 2km along the planned route (for example, it is sufficient to determine the ground condition only by flying horizontally for 1.5 km) in accordance with the appropriate flying height. In addition, the flight distance and the flight height also depend on the route shape of the planned route. For example, when the planned route of 2km ahead includes a turn, the flight distance may not necessarily be able to be shortened by the increase in flying height.
In another example, the flight route may include roads that intersect the road ahead, in addition to flying along the planned route currently being traveled. Similarly to the currently planned route, in the case where congestion is not known to occur, it is also unknown to the navigation system whether or not these surrounding roads are affected by congestion. Therefore, the flight route comprising the roads can determine the congestion condition of the planned route and know the congestion condition of the surrounding roads, thereby providing a reference for updating the route planning. The detection of the current road and the surrounding road can be finished in one flight, so that the efficiency of the unmanned aerial vehicle for executing flight tasks can be improved. Of course, those skilled in the art will appreciate how long the flight is on the surrounding road can be flexibly set. For example, only tens of meters can fly on these intersecting roads, or only stop at a fork and turn through the lens of the drone for simple viewing.
Airspeed is another parameter that can be set. In addition to its impact on the drain on the battery of the drone, the flying speed primarily affects the clarity of the sensor (e.g., camera) data. Therefore, an appropriate flying speed can be set based on at least the performance of the sensor (such as the shutter speed of the camera) to avoid the blurring of the photographed picture caused by too fast flying, and also avoid excessive power consumption and long task execution time caused by too slow flying. In addition, it can be understood that the flying height also affects the flying speed, and the higher the flying height is, the slower the moving speed of the ground object in the visual field of the sensor of the unmanned aerial vehicle is, and the motion blur can be effectively avoided. Thus, the setting of the flying height and the flying speed can be matched with each other.
Generally speaking, under the condition that the sensor data collected by the unmanned aerial vehicle 104 can satisfy the requirement of the automobile 102 for analyzing the road condition ahead, the mode most favorable for saving the battery power consumption of the unmanned aerial vehicle can be adopted to set the flight parameters and the sensor parameters of the unmanned aerial vehicle.
After the flight parameters of the drone are generated, the flight parameters may be sent to the drone 104 via the communication unit 110 of the automobile 102 at step 204.
Fig. 3 is a flow diagram of a method 300 performed by a drone for automatically updating automobile route planning with an onboard drone, according to one embodiment of the invention. The method 300 begins at step 302, and at step 202, in response to a decision to perform a flight mission, a drone 104 may be launched from a drone takeoff and landing platform of an associated automobile 102. The decision to perform the flight mission is sent to drone 104 along with the flight parameters determined by car 102. The drone 104 then takes off from the drone landing platform of the automobile 102 and performs the flight mission along the determined flight path at the determined altitude and speed of flight based on the various items of information contained in the received instructions related to performing the flight mission.
Next, during the execution of the flight mission, drone 104 may collect ground information for roads relevant to the current vehicle path plan, step 304. In one embodiment, the ground information collected by the drone 104 includes, but is not limited to, images of roads, audio, and video. Thereafter, at step 306, the drone 104 may send the collected ground information to the automobile 102 via the communication module 106. After completing the flight mission, drone 104 may return to the drone takeoff and landing platform of automobile 102.
Returning to fig. 2, at step 206, the automobile 102 may receive its collected ground information from the drone 104 via the communication unit 110. Subsequently, at step 208, the automobile 102 may process the received ground information to obtain ground traffic information for the road associated with the current automobile path plan. The ground traffic information includes but is not limited to: reasons for road congestion; length of road congestion; and traffic speed on congested roads. Various image and video recognition techniques known in the art may be employed for processing the sensor data collected by the drone. For example, events such as traffic accidents and road administration construction in roads can be identified through an image recognition technology as the reasons for road congestion; calculating the road congestion length according to parameters such as the position and the height of the unmanned aerial vehicle; the traffic speed on the road and the like can be detected by a video analysis technique.
At step 210, the route plan is updated based on the acquired ground road condition information. According to one embodiment of the invention, information obtained through analysis, such as the cause of the road congestion, the length of the road congestion, and the traffic flow speed on congested roads, may be submitted to a navigation system on the automobile 102, which, based on this real-time information, may re-plan a route based on user preferences. Optionally, the analyzed real-time information may also be reported to a remote server or other nearby vehicles.
Optionally, the method 200 may further include adjusting flight parameters according to the acquired ground road condition information. According to one example, information collected by the drone 104 may be transmitted back to the car 102 in real-time. The automobile 102 may be analyzed on the fly based on this information. Based on the derived analysis conclusions, the car 102 may adjust the flight parameters of the drone 104. For example, the drone 104 is initially set to fly 2km ahead and return, but when the vehicle 102 analyzes the data returned by the drone 104 and finds that the congestion length is 1km, the vehicle 102 may adjust the flight parameters of the drone 104 and instruct it to return immediately, thereby saving power consumption of the drone. Additionally, the automobile 102 may still be traveling slowly during the flight of the drone 104. Thus, the position at which drone 104 lands after returning changes with the real-time position of car 102, which is also constantly being adjusted by car 102 sending instructions to drone 104.
The foregoing describes non-limiting embodiments of the present method and system for updating route plans with an onboard drone. By the method and the system, the latest road condition information can be known in time, so that the navigation system can update the route planning in time.
What has been described above includes examples of aspects of the claimed subject matter. It is, of course, not possible to describe every conceivable combination of components or methodologies for purposes of describing the claimed subject matter, but one of ordinary skill in the art may recognize that many further combinations and permutations of the claimed subject matter are possible. Accordingly, the disclosed subject matter is intended to embrace all such alterations, modifications and variations that fall within the spirit and scope of the appended claims.
Claims (15)
1. A method performed by a drone for automatically updating a vehicle route plan, the method comprising:
in response to a decision to perform a flight mission, takeoff from the associated automobile;
collecting ground information of roads related to the current automobile route planning in the process of executing the flight mission; and
and sending the collected ground information to the automobile.
2. The method of claim 1, wherein the decision to perform the flight mission is made manually by a person on the vehicle or automatically by the vehicle based on the driving conditions of the vehicle.
3. The method of claim 1, wherein the collected surface information comprises at least one of:
images of roads, audio, and video.
4. The method of claim 1, wherein the roads associated with the current route plan include at least one of:
the automobile plans a road to be traveled according to the current automobile route; and
and the road is intersected with the road which is planned to be driven by the automobile according to the current automobile route.
5. A method performed by a vehicle for automatically updating a vehicle route plan, the method comprising:
in response to a decision by a drone associated with the automobile to perform a flight mission, generating flight parameters related to performing the flight mission;
sending the flight parameters to the drone;
receiving the collected ground information from the drone;
processing the received ground information to obtain ground road condition information of a road related to the current automobile route planning; and
and updating the route plan based on the acquired ground road condition information.
6. The method of claim 5, wherein the flight parameter comprises at least one of:
a flight path;
a flying height;
a flight distance; and
the flying speed.
7. The method of claim 6, wherein the flight route is determined based on the current automotive planned route.
8. The method of claim 5, wherein the ground traffic information comprises at least one of:
reasons for road congestion;
length of road congestion; and
traffic speed on congested roads.
9. The method of claim 5, wherein the method further comprises:
and adjusting the flight parameters according to the acquired ground road condition information.
10. An automobile, characterized in that the automobile comprises:
a processing unit configured to generate flight parameters related to performing a flight mission in response to a decision to perform the flight mission by a drone associated with the automobile; and
a communication unit configured to:
sending the flight parameters to the drone; and
receiving the collected ground information from the drone;
the processing unit is further configured to:
processing the received ground information to obtain ground road condition information of a road related to the current automobile route planning; and
and updating the route plan based on the acquired ground road condition information.
11. The vehicle of claim 10, wherein the decision to perform the mission is made automatically by the vehicle based on the driving conditions of the vehicle.
12. The vehicle of claim 10, wherein the ground traffic information comprises at least one of:
reasons for road congestion;
length of road congestion; and
traffic speed on congested roads.
13. The automobile of claim 10, wherein the roads associated with the current route plan include at least one of:
the automobile plans a road to be traveled according to the current automobile route; and
and the road is intersected with the road which is planned to be driven by the automobile according to the current automobile route.
14. The automobile of claim 10, wherein the flight parameters include at least one of:
a flight path;
a flying height;
a flight distance; and
the flying speed.
15. The vehicle of claim 10, wherein the processing unit of the vehicle is further configured to adjust the flight parameters based on the obtained ground road condition information.
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| CN201810605676.1A CN110595495A (en) | 2018-06-13 | 2018-06-13 | Method for automatically updating a vehicle route plan |
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| CN201810605676.1A CN110595495A (en) | 2018-06-13 | 2018-06-13 | Method for automatically updating a vehicle route plan |
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| WO2022252429A1 (en) * | 2021-06-02 | 2022-12-08 | 北京三快在线科技有限公司 | Unmanned device control method and apparatus, storage medium, and electronic device |
| CN115311848A (en) * | 2022-07-04 | 2022-11-08 | 中国第一汽车股份有限公司 | Vehicle information processing method, system, device, storage medium and vehicle |
| CN115240450A (en) * | 2022-07-13 | 2022-10-25 | 购旺工业(赣州)有限公司 | Intelligent traffic data acquisition equipment and method |
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