CN115451985B - Traffic event driven lane-level navigation decision-making method and equipment for automatic driving - Google Patents
Traffic event driven lane-level navigation decision-making method and equipment for automatic driving Download PDFInfo
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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
- G01C21/36—Input/output arrangements for on-board computers
- G01C21/3626—Details of the output of route guidance instructions
- G01C21/3658—Lane guidance
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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
- G01C21/3407—Route searching; Route guidance specially adapted for specific applications
- G01C21/3415—Dynamic re-routing, e.g. recalculating the route when the user deviates from calculated route or after detecting real-time traffic data or accidents
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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
- G01C21/3407—Route searching; Route guidance specially adapted for specific applications
- G01C21/343—Calculating itineraries, i.e. routes leading from a starting point to a series of categorical destinations using a global route restraint, round trips, touristic trips
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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
- G01C21/3667—Display of a road map
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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
Abstract
The invention provides an automatic driving-oriented traffic event-driven lane-level navigation decision method and equipment. The method comprises the following steps: detecting traffic events and transmitting detected information to a cloud; planning a path and a pre-crossing lane, and performing lane-level navigation on an affected area of a traffic event; traffic event-driven lane-level navigation decision settings are made for traffic events related to traffic flow or traffic events related to traffic restrictions. The invention plans road level and lane level driving paths in real time according to the road network, the lane network, the traffic sign, the traffic identification information and the real-time traffic event information in the map static data layer based on the map and the traffic event information, and provides sufficient global path information for automatic driving vehicle decision planning.
Description
Technical Field
The embodiment of the invention relates to the technical field of automatic driving navigation, in particular to an automatic driving-oriented traffic event-driven lane-level navigation decision method and equipment.
Background
The navigation engine system in a plurality of map software on the current market is complete, but the matching degree of the product positioning and the self attribute and the requirement of an automatic driving system is low, the self audience is a driver, the purpose is to provide road-level navigation assistance for people, and sufficient information can not be provided for the navigation decision of an automatic driving machine main body. The modern large-scale urban road system is extremely complex, various complex intersections, overpasses, urban surrounding high-speed, underground roads and roundabout are jointly constructed into a three-dimensional traffic network, and the three-dimensional traffic network only has road-level navigation, so that intelligent vehicles can generate the phenomena of getting lost or missing a turning opportunity and missing an exit due to incorrect lane selection but impermissible lane rule semantic definition at the intersections, and the road-level navigation is realized by being far higher than the assistance of a map of a traditional navigation map in the aspects of information richness and information precision. In addition, under a real automatic driving scene, traffic events in the surrounding environment are complex and real-time and changeable, the safety and the high efficiency of driving are considered from the viewpoint of standing on a machine, and the lane-level path planning is certainly changed in real time along with the occurrence of various traffic events. Therefore, developing a traffic event-driven lane-level navigation decision method and device for automatic driving effectively overcomes the defects in the related art, and becomes a technical problem to be solved in the industry.
Disclosure of Invention
Aiming at the problems in the prior art, the embodiment of the invention provides an automatic driving-oriented traffic event-driven lane-level navigation decision method and equipment.
In a first aspect, an embodiment of the present invention provides an automatic driving-oriented traffic event driven lane-level navigation decision method, including: detecting traffic events and transmitting detected information to a cloud; planning a path and a pre-crossing lane, and performing lane-level navigation on an affected area of a traffic event; traffic event-driven lane-level navigation decision settings are made for traffic events related to traffic flow or traffic events related to traffic restrictions.
Based on the content of the embodiment of the method, the traffic event-driven lane-level navigation decision method for automatic driving provided by the embodiment of the invention detects the traffic event and transmits the detected information to the cloud, and the method comprises the following steps: the intelligent road side units, pedestrians and traffic incidents relate to information detected by vehicles, surrounding vehicles, government traffic departments and real-time remote sensing images, and detected information is processed by an automatic driving vehicle sensor, a government traffic department or crowdsourcing user and transmitted to the cloud.
On the basis of the content of the embodiment of the method, the traffic event driven lane-level navigation decision method for automatic driving provided by the embodiment of the invention comprises the following steps: and obtaining road or lane numbers between the ends by adopting a map engine, and obtaining the road numbers and the suggested lane numbers on non-intersection roads.
On the basis of the content of the embodiment of the method, the traffic event driven lane-level navigation decision method for automatic driving comprises the following steps: and finding out the crossing passing through the planned path, and planning a correct lane at the pre-crossing in the path to ensure that the vehicle is kept on the planned path.
On the basis of the content of the embodiment of the method, the method for decision-making of traffic event driven lane-level navigation for automatic driving, provided by the embodiment of the invention, carries out lane-level navigation on the affected area of the traffic event, and comprises the following steps: dynamically setting the topology of a corresponding lane to a forbidden state for the traffic accident occurrence lane which is affected and cannot pass; and adding corresponding lane traffic topology for the lane sections which are temporarily set to allow reverse driving or borrow the road during road construction, realizing real-time lane-level planning, and dynamically realizing lane-level navigation for the affected area on the basis of initial path planning.
On the basis of the foregoing method embodiment, the traffic event-driven lane-level navigation decision method for automatic driving provided in the embodiment of the present invention includes: by means of real-time remote sensing image monitoring, vehicle networking information transmission and real-time traffic flow data identification or predicted congestion road sections, accurate journey time length estimation is calculated by combining the speed of the vehicle and the current position of the vehicle, map priori lane network information is adopted to avoid the congestion road sections, global path planning is conducted again, the passing time length is calculated, finally, the passing time length is compared with the passing time length of the planned path which is congested before, and a path with shorter passing time length is selected preferentially.
On the basis of the foregoing method embodiment, the method for traffic event driven lane-level navigation decision-making for automatic driving in the embodiment of the present invention includes: the method comprises the steps that severe weather and natural disasters are road-level influences in an automatic driving scene, real-time information of an influence area is transmitted to a cloud end, the road communication state influenced by an event is set to be forbidden, and when the influence range comprises a planned path, the road is abandoned to be re-planned; for traffic control, road engineering and traffic accidents, the road traffic condition or the lane traffic condition is influenced, and the road traffic condition is consistent with the natural disaster treatment condition; affecting traffic conditions of a lane includes: for the affected traffic lane which cannot pass, dynamically setting the topology of the corresponding traffic lane to be in a forbidden state; and adding a corresponding lane traffic topology for the temporary lane, and realizing dynamic lane-level navigation for the affected area on the basis of initial path planning.
In a second aspect, an embodiment of the present invention provides an automatic driving-oriented traffic event driven lane-level navigation decision apparatus, including: the first main module is used for detecting traffic events and transmitting detected information to the cloud; the second main module is used for planning a path and a pre-crossing lane and performing lane-level navigation on the affected area of the traffic event; and the third main module is used for carrying out traffic event-driven lane-level navigation decision setting on traffic events related to traffic flow or traffic events related to traffic limitation.
In a third aspect, an embodiment of the present invention provides an electronic device, including:
at least one processor; and
at least one memory communicatively coupled to the processor, wherein:
the memory stores program instructions executable by the processor, the processor invoking the program instructions capable of executing the automated driving oriented traffic event driven lane level navigation decision method provided by any of the various implementations of the first aspect.
In a fourth aspect, embodiments of the present invention provide a non-transitory computer-readable storage medium storing computer instructions that cause a computer to perform the automated driving-oriented traffic event driven lane-level navigation decision method provided by any of the various implementations of the first aspect.
The traffic event driven lane-level navigation decision-making method and the traffic event-level navigation decision-making device for automatic driving are based on the map and the traffic event information, and the road level and lane-level driving paths are planned in real time according to the road network, the lane network, the traffic sign information and the real-time traffic event information in the map static data layer, so that sufficient global path information is provided for decision-making of the automatic driving vehicles.
Drawings
For a clearer description of embodiments of the invention or of solutions according to the prior art, a brief description will be given below of the drawings used in the description of the embodiments or of the prior art, it being obvious that the drawings in the description below are some embodiments of the invention, and that other drawings are obtained from them without the aid of inventive labour for a person skilled in the art.
FIG. 1 is a flow chart of a traffic event driven lane level navigation decision method for automatic driving according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of an automatic driving-oriented traffic event driven lane-level navigation decision-making device according to an embodiment of the present invention;
fig. 3 is a schematic diagram of an entity structure of an electronic device according to an embodiment of the present invention;
FIG. 4 is a technical roadmap provided by an embodiment of the invention;
FIG. 5 is a technical flowchart provided by an embodiment of the present invention;
fig. 6 is a schematic diagram of a traffic event driven lane level navigation mechanism according to an embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention. In addition, technical features of each embodiment or the individual embodiments provided in the present invention are arbitrarily combined with each other to form a technical solution in a row, and such combination is not limited by the sequence of steps and/or the structural composition mode, but must be based on the fact that a person skilled in the art can implement the combination, and when the technical solutions are contradictory or cannot be implemented, it should be considered that the combination of the technical solutions does not exist and is not within the scope of protection claimed in the present invention.
The embodiment of the invention provides an automatic driving-oriented traffic event-driven lane-level navigation decision method, which is shown in fig. 1 and comprises the following steps: detecting traffic events and transmitting detected information to a cloud; planning a path and a pre-crossing lane, and performing lane-level navigation on an affected area of a traffic event; traffic event-driven lane-level navigation decision settings are made for traffic events related to traffic flow or traffic events related to traffic restrictions.
Based on the foregoing disclosure of the foregoing method embodiment, as an optional embodiment, the traffic event-driven lane-level navigation decision method for automatic driving provided in the embodiment of the present invention detects a traffic event and transmits the detected information to a cloud, including: the intelligent road side units, pedestrians and traffic incidents relate to information detected by vehicles, surrounding vehicles, government traffic departments and real-time remote sensing images, and detected information is processed by an automatic driving vehicle sensor, a government traffic department or crowdsourcing user and transmitted to the cloud.
Based on the foregoing content of the foregoing method embodiment, as an optional embodiment, the traffic event driven lane-level navigation decision method for automatic driving according to the embodiment of the present invention, the planning a path includes: and obtaining road or lane numbers between the ends by adopting a map engine, and obtaining the road numbers and the suggested lane numbers on non-intersection roads.
Based on the content of the above method embodiment, as an optional embodiment, the traffic event driven lane-level navigation decision method for automatic driving, provided in the embodiment of the present invention, the planning of the pre-crossing lane includes: and finding out the crossing passing through the planned path, and planning a correct lane at the pre-crossing in the path to ensure that the vehicle is kept on the planned path.
Based on the foregoing disclosure of the method embodiment, as an optional embodiment, the method for determining the lane-level navigation of the traffic event driven lane for automatic driving provided in the embodiment of the present invention, and performing lane-level navigation on the affected area of the traffic event, includes: dynamically setting the topology of a corresponding lane to a forbidden state for the traffic accident occurrence lane which is affected and cannot pass; and adding corresponding lane traffic topology for the lane sections which are temporarily set to allow reverse driving or borrow the road during road construction, realizing real-time lane-level planning, and dynamically realizing lane-level navigation for the affected area on the basis of initial path planning.
Based on the foregoing disclosure of the foregoing method embodiment, as an optional embodiment, the method for driving lane-level navigation decision by using an autopilot-oriented traffic event provided in the embodiment of the present invention, where the setting of lane-level navigation decision by using traffic event driving is performed on traffic events related to traffic flow includes: by means of real-time remote sensing image monitoring, vehicle networking information transmission and real-time traffic flow data identification or predicted congestion road sections, accurate journey time length estimation is calculated by combining the speed of the vehicle and the current position of the vehicle, map priori lane network information is adopted to avoid the congestion road sections, global path planning is conducted again, the passing time length is calculated, finally, the passing time length is compared with the passing time length of the planned path which is congested before, and a path with shorter passing time length is selected preferentially.
Based on the foregoing disclosure of the foregoing method embodiment, as an optional embodiment, the method for driving lane-level navigation decision by using an autopilot-oriented traffic event in the embodiment of the present invention, where the setting of lane-level navigation decision by using traffic event driving is performed on traffic events related to traffic restrictions includes: the method comprises the steps that severe weather and natural disasters are road-level influences in an automatic driving scene, real-time information of an influence area is transmitted to a cloud end, the road communication state influenced by an event is set to be forbidden, and when the influence range comprises a planned path, the road is abandoned to be re-planned; for traffic control, road engineering and traffic accidents, the road traffic condition or the lane traffic condition is influenced, and the road traffic condition is consistent with the natural disaster treatment condition; affecting traffic conditions of a lane includes: for the affected traffic lane which cannot pass, dynamically setting the topology of the corresponding traffic lane to be in a forbidden state; and adding a corresponding lane traffic topology for the temporary lane, and realizing dynamic lane-level navigation for the affected area on the basis of initial path planning.
The traffic event driven lane-level navigation decision-making method for automatic driving provided by the embodiment of the invention is based on the map and the traffic event information, and the road level and lane-level driving path is planned in real time according to the road network, the lane network, the traffic sign information and the real-time traffic event information in the map static data layer, so that sufficient global path information is provided for automatic driving vehicle decision-making planning.
In another embodiment, as shown in fig. 4, the mode of combining the automatic driving car with the map gradually changes to a strong map mode: the map at this time becomes an extremely important platform, and various sensors and cloud data are fused into the map, so that various traffic events can cause static and dynamic map layer updating of the map. Based on novel data of the traffic event information, the map information and the perception scene information, the method combines known rules to realize full-layer efficient linkage, rapidly calculates and outputs lane-level navigation oriented to automatic driving, and forms an intelligent navigation mechanism driven by the traffic event.
As shown in fig. 5, the mechanism includes a map module (including a content locating module, a POI matching module, and a global path planning module), a traffic event detecting module, a traffic event pushing module, a rule driving module, and a pushing navigation module.
The degree positioning module is used for determining the navigation starting point in real time.
The POI matching module is used for determining a navigation end point.
The global path planning module: the method is used for realizing lane-level path planning, and comprises initial path planning, pre-crossing lane selection and traffic event-driven real-time lane navigation.
The traffic event detection module is only used for traffic event detection and information extraction.
The traffic event pushing module is used for transmitting traffic event information to the cloud end in real time.
The rule driving module is used for realizing the matching calculation of the defined traffic rule (derived from the traffic rule) and the planned lane and changing lane-level path planning in real time.
The pushing module is used for pushing the real-time lane-level navigation from the cloud to the vehicle end.
As shown in FIG. 6, the specific steps of the traffic event driven lane level navigation mechanism of the present invention include 1) initial path planning; 2) Constructing and transmitting traffic event scenes; 3) Traffic event driven lane-level path planning: navigation path planning update under multiple influencing factors (the influencing factors are dimensionalized so as to determine road weights); combining influence factors, improving heuristic functions to construct a new navigation strategy; 4) The planned path is synchronized to the vehicle end.
Further, the steps are refined as follows:
initial path planning:
wherein the steps include determining a starting point by means of map realization level positioning; the POI discrete points are input to be adsorbed to the nearest road to determine an end point; constructing and inquiring a road network and a lane network topology; and carrying out global path planning according to a certain strategy. Among the common path planning strategies are: 1) Planning according to the principle that the total mileage duration between the estimated driving to the destination is shortest; 2) Avoiding toll stations as much as possible; 3) Planning according to the intelligent vehicle type: the road planning system is generally divided into a small car, a light car, a medium car, a heavy car and others, and is planned according to road bearing and road geometry; 4) Planning according to the traffic control of the vehicle: when the vehicle type and license plate number vehicle information are acquired, planning is carried out according to local traffic control rules, including planning according to special lane limits of buses and special road section limits of double number traffic of license plate tail numbers. In actual driving, the global path planning strategy is determined adaptively according to user wish by combining map user layer information; and finally, combining map detailed lane network information, determining a road junction in the planned road, selecting a lane meeting the regulations when the pre-crossing enters the road junction, selecting a next lane (because the pre-crossing cannot change the lane), selecting a lane according to the successor and successor combination of the pre-crossing lane, and finally forming a driving list comprising the planned road and partial lanes of the pre-crossing, and in addition, defining forbidden lanes (such as private cars cannot travel on buses) of each road on the non-crossing road and dynamically recommending an optimal lane according to traffic flow and minimum lane changing rules.
2. Traffic event detection and transmission:
the road side unit, pedestrians and incident related vehicles, surrounding vehicles, traffic police authorities and real-time remote sensing images are all used as traffic incident detection units. After the event is detected, traffic event related information is processed and generated through traffic management departments or crowdsourcing users, wherein the traffic event information comprises traffic event types, event positions, lanes where the events are located, event influence areas, event duration time, event priorities and traffic participants related to the events are transmitted to the cloud.
3. Traffic event driven lane level navigation:
traffic rules are one of the kernels of the drive, connecting traffic event elements with navigation. Different traffic events, such as front congestion, traffic accidents, road engineering and traffic control, occur in the running process of the vehicle, the current traffic rule is required to be combined as constraint conditions, and map association is carried out according to the topological association of map elements through the steps of transmission and calculation, so that a series of driving behavior decision knowledge chains are formed.
4. Navigation path transmission:
and sending the real-time navigation path to a vehicle-end platform, and transmitting the real-time navigation path to the vehicle-end by using ProtoBuffer serialization and transmission protocol TCP/Some/IP protocol in combination with the defined navigation road and lane list data structure.
The implementation basis of the embodiments of the present invention is realized by a device with a processor function to perform programmed processing. Therefore, in engineering practice, the technical solutions and the functions of the embodiments of the present invention are packaged into various modules. Based on the actual situation, on the basis of the above embodiments, the embodiments of the present invention provide an automatic driving-oriented traffic event driven lane level navigation decision device, which is used for executing the automatic driving-oriented traffic event driven lane level navigation decision method in the above method embodiments. Referring to fig. 2, the apparatus includes: the first main module is used for detecting traffic events and transmitting detected information to the cloud; the second main module is used for planning a path and a pre-crossing lane and performing lane-level navigation on the affected area of the traffic event; and the third main module is used for carrying out traffic event-driven lane-level navigation decision setting on traffic events related to traffic flow or traffic events related to traffic limitation.
The traffic event driven lane-level navigation decision-making device for automatic driving provided by the embodiment of the invention adopts a plurality of modules in fig. 2, and based on the map and the traffic event information, the road level and lane-level driving path are planned in real time according to the road network, the lane network, the traffic sign information and the real-time traffic event information in the map static data layer, so that sufficient global path information is provided for automatic driving vehicle decision-making planning.
The device in the device embodiment provided by the invention is used for realizing the method in the device embodiment and also used for realizing the method in the other device embodiment provided by the invention, and the difference is only that corresponding functional modules are arranged, the principle of the device is basically the same as that of the device embodiment provided by the invention, as long as a person skilled in the art refers to the specific technical scheme in the other device embodiment on the basis of the device embodiment, the corresponding technical means are obtained by combining technical characteristics, and the technical scheme formed by the technical means, so that the device in the device embodiment is improved to obtain the corresponding device embodiment on the premise of ensuring that the technical scheme has practicability, and the method in the other device embodiment is realized. For example:
based on the content of the above device embodiment, as an optional embodiment, the traffic event driven lane-level navigation decision device for automatic driving according to the embodiment of the present invention further includes: the first sub-module is configured to implement the detection of the traffic event and transmit the detected information to the cloud, and includes: the intelligent road side units, pedestrians and traffic incidents relate to information detected by vehicles, surrounding vehicles, government traffic departments and real-time remote sensing images, and detected information is processed by an automatic driving vehicle sensor, a government traffic department or crowdsourcing user and transmitted to the cloud.
Based on the content of the above device embodiment, as an optional embodiment, the traffic event driven lane-level navigation decision device for automatic driving according to the embodiment of the present invention further includes: the second sub-module is configured to implement the path planning, and includes: and obtaining road or lane numbers between the ends by adopting a map engine, and obtaining the road numbers and the suggested lane numbers on non-intersection roads.
Based on the content of the above device embodiment, as an optional embodiment, the traffic event driven lane-level navigation decision device for automatic driving according to the embodiment of the present invention further includes: the third sub-module is configured to implement the planning of the pre-intersection lane, and includes: and finding out the crossing passing through the planned path, and planning a correct lane at the pre-crossing in the path to ensure that the vehicle is kept on the planned path.
Based on the content of the above device embodiment, as an optional embodiment, the traffic event driven lane-level navigation decision device for automatic driving according to the embodiment of the present invention further includes: a fourth sub-module for implementing the lane-level navigation of the affected area of the traffic event, including: dynamically setting the topology of a corresponding lane to a forbidden state for the traffic accident occurrence lane which is affected and cannot pass; and adding corresponding lane traffic topology for the lane sections which are temporarily set to allow reverse driving or borrow the road during road construction, realizing real-time lane-level planning, and dynamically realizing lane-level navigation for the affected area on the basis of initial path planning.
Based on the content of the above device embodiment, as an optional embodiment, the traffic event driven lane-level navigation decision device for automatic driving according to the embodiment of the present invention further includes: a fifth sub-module, configured to implement the traffic event related to the traffic flow, and perform traffic event-driven lane-level navigation decision setting, including: by means of real-time remote sensing image monitoring, vehicle networking information transmission and real-time traffic flow data identification or predicted congestion road sections, accurate journey time length estimation is calculated by combining the speed of the vehicle and the current position of the vehicle, map priori lane network information is adopted to avoid the congestion road sections, global path planning is conducted again, the passing time length is calculated, finally, the passing time length is compared with the passing time length of the planned path which is congested before, and a path with shorter passing time length is selected preferentially.
Based on the content of the above device embodiment, as an optional embodiment, the traffic event driven lane-level navigation decision device for automatic driving according to the embodiment of the present invention further includes: a sixth sub-module, configured to implement the traffic event related to traffic restriction, and perform traffic event-driven lane-level navigation decision setting, including: the method comprises the steps that severe weather and natural disasters are road-level influences in an automatic driving scene, real-time information of an influence area is transmitted to a cloud end, the road communication state influenced by an event is set to be forbidden, and when the influence range comprises a planned path, the road is abandoned to be re-planned; for traffic control, road engineering and traffic accidents, the road traffic condition or the lane traffic condition is influenced, and the road traffic condition is consistent with the natural disaster treatment condition; affecting traffic conditions of a lane includes: for the affected traffic lane which cannot pass, dynamically setting the topology of the corresponding traffic lane to be in a forbidden state; and adding a corresponding lane traffic topology for the temporary lane, and realizing dynamic lane-level navigation for the affected area on the basis of initial path planning.
The method of the embodiment of the invention is realized by the electronic equipment, so that the related electronic equipment is necessary to be introduced. To this end, an embodiment of the present invention provides an electronic device, as shown in fig. 3, including: at least one processor (processor), a communication interface (Communications Interface), at least one memory (memory) and a communication bus, wherein the at least one processor, the communication interface, and the at least one memory communicate with each other via the communication bus. The at least one processor invokes the logic instructions in the at least one memory to perform all or part of the steps of the methods provided by the various method embodiments described above.
Further, the logic instructions in the at least one memory described above are implemented in the form of software functional units and stored in a computer-readable storage medium when sold or used as a stand-alone product. Based on this understanding, the technical solution of the present invention is essentially or what contributes to the prior art or that part of the technical solution is embodied in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (being a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a usb disk, a removable hard disk, a Read-Only Memory (ROM), a random-access Memory (RAM, random Access Memory), a magnetic or optical disk, or various media storing program codes.
The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements are or are not physically separated, and the elements shown as elements are or are not physical elements, are located in one place, or are also distributed over a plurality of network elements. The purpose of the embodiment is achieved by actually selecting some or all of the modules. Those of ordinary skill in the art will understand and implement the invention without undue burden.
From the above description of embodiments, it will be apparent to those skilled in the art that the embodiments are implemented by means of software plus the necessary general hardware platform, but of course also by means of hardware. Based on this understanding, the above technical solution is essentially or what contributes to the prior art embodied in the form of a software product stored in a computer-readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, comprising several instructions for causing a computer device (being a personal computer, a server, or a network device) to execute the method described in the various embodiments or parts of the embodiments.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of implementations of systems, methods and computer program products according to various embodiments of the present invention. Based on this knowledge, each block in the flowchart or block diagrams is a module, segment, or portion of code, which comprises one or more execution instructions for implementing the specified logical function(s). It should also be noted that in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
It is noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises the element.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments is still modified or some technical features thereof are replaced with others; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (5)
1. An automatic driving-oriented traffic event driven lane-level navigation decision-making method is characterized by comprising the following steps of:
detecting traffic events and transmitting detected information to a cloud; comprising the following steps: the intelligent road side unit, pedestrians and traffic incidents relate to information detected by vehicles, surrounding vehicles, government traffic departments and real-time remote sensing images, and detected information is processed by an automatic driving vehicle sensor, government traffic departments or crowdsourcing users and transmitted to the cloud;
planning a path and a pre-crossing lane, and performing lane-level navigation on an affected area of a traffic event; comprising the following steps: obtaining road or lane numbers between ends by adopting a map engine, and obtaining the road numbers and suggested lane numbers on non-intersection roads; finding out the crossing passing through the planned path, planning a correct lane at the pre-crossing in the path, and ensuring that the vehicle is kept on the planned path;
dynamically setting the topology of a corresponding lane to a forbidden state for the traffic accident occurrence lane which is affected and cannot pass; for the lane sections which are temporarily set to allow reverse driving or borrow the road during road construction, adding corresponding lane traffic topology, realizing real-time lane-level planning, and dynamically realizing lane-level navigation on the affected area on the basis of initial path planning;
traffic event-driven lane-level navigation decision setting is carried out on traffic events related to traffic flow or traffic events related to traffic limitation; comprising the following steps: by means of real-time remote sensing image monitoring, vehicle networking information transmission and real-time traffic flow data identification or predicted congestion road sections, accurate journey time length estimation is calculated by combining the speed of the vehicle and the current position of the vehicle, map priori lane network information is adopted to avoid the congestion road sections, global path planning is conducted again, the passing time length is calculated, finally, the passing time length is compared with the passing time length of the planned path which is congested before, and a path with shorter passing time length is selected preferentially.
2. The automated driving-oriented traffic event driven lane-level navigation decision method of claim 1, wherein the traffic event driven lane-level navigation decision setting for traffic restriction related traffic events comprises:
the method comprises the steps that severe weather and natural disasters are road-level influences in an automatic driving scene, real-time information of an influence area is transmitted to a cloud end, the road communication state influenced by an event is set to be forbidden, and when the influence range comprises a planned path, the road is abandoned to be re-planned; for traffic control, road engineering and traffic accidents, the road traffic condition or the lane traffic condition is influenced, and the road traffic condition is consistent with the natural disaster treatment condition; affecting traffic conditions of a lane includes: for the affected traffic lane which cannot pass, dynamically setting the topology of the corresponding traffic lane to be in a forbidden state; and adding a corresponding lane traffic topology for the temporary lane, and realizing dynamic lane-level navigation for the affected area on the basis of initial path planning.
3. An automated driving-oriented traffic event driven lane-level navigation decision-making device, comprising:
the first main module is used for detecting traffic events and transmitting detected information to the cloud; comprising the following steps: the intelligent road side unit, pedestrians and traffic incidents relate to information detected by vehicles, surrounding vehicles, government traffic departments and real-time remote sensing images, and detected information is processed by an automatic driving vehicle sensor, government traffic departments or crowdsourcing users and transmitted to the cloud;
the second main module is used for planning a path and a pre-crossing lane and performing lane-level navigation on the affected area of the traffic event; comprising the following steps: obtaining road or lane numbers between ends by adopting a map engine, and obtaining the road numbers and suggested lane numbers on non-intersection roads; finding out the crossing passing through the planned path, planning a correct lane at the pre-crossing in the path, and ensuring that the vehicle is kept on the planned path;
dynamically setting the topology of a corresponding lane to a forbidden state for the traffic accident occurrence lane which is affected and cannot pass; for the lane sections which are temporarily set to allow reverse driving or borrow the road during road construction, adding corresponding lane traffic topology, realizing real-time lane-level planning, and dynamically realizing lane-level navigation on the affected area on the basis of initial path planning;
the third main module is used for carrying out traffic event-driven lane-level navigation decision setting on traffic events related to traffic flow or traffic events related to traffic limitation; comprising the following steps: by means of real-time remote sensing image monitoring, vehicle networking information transmission and real-time traffic flow data identification or predicted congestion road sections, accurate journey time length estimation is calculated by combining the speed of the vehicle and the current position of the vehicle, map priori lane network information is adopted to avoid the congestion road sections, global path planning is conducted again, the passing time length is calculated, finally, the passing time length is compared with the passing time length of the planned path which is congested before, and a path with shorter passing time length is selected preferentially.
4. An electronic device, comprising:
at least one processor, at least one memory, and a communication interface; wherein,
the processor, the memory and the communication interface are communicated with each other;
the memory stores program instructions for execution by the processor, the processor invoking the program instructions to perform the method of any of claims 1-2.
5. A non-transitory computer-readable storage medium storing computer instructions that cause the computer to perform the method of any one of claims 1-2.
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