CN112885087A - Method, apparatus, device and medium for determining road condition information and program product - Google Patents
Method, apparatus, device and medium for determining road condition information and program product Download PDFInfo
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Abstract
Example embodiments of the present disclosure provide a method, an apparatus, a device, a computer-readable storage medium, and a computer program product for determining traffic information, which may be used in the field of intelligent transportation. The method described herein comprises: receiving images of one or more surrounding objects of a place or area with abnormal road conditions; detecting a target object associated with a road management measure from one or more surrounding objects by analyzing the image; and providing a prompt for a road management action in response to detecting the target object. The embodiment of the disclosure can effectively determine the road condition information, and further improve the navigation experience of the user.
Description
Technical Field
Embodiments of the present disclosure relate generally to the field of intelligent transportation, and more particularly, to a method, apparatus, device, computer-readable storage medium, and computer program product for determining road condition information.
Background
Road management measures are measures for controlling the passage of vehicles and persons over part or all of a traffic route for safety reasons. Road management measures are generally used for limiting traffic behaviors under the conditions of meeting wandering, large-scale sports meetings, road and bridge construction, disaster relief and rescue, execution of important guard tasks and the like. However, since the road management measures are often temporary, it is difficult to be discovered and prompted to the user in time. This may cause a poor navigation experience for users who travel through the road segment on which the road management measure is implemented. Accordingly, it is desirable to provide a scheme for determining the road management measures and prompting the user for the road management measures.
Disclosure of Invention
In a first aspect of the present disclosure, a method of determining road condition information is provided. The method comprises receiving images of one or more surrounding objects of a location or area with abnormal road conditions; detecting a target object associated with a road management measure from one or more surrounding objects by analyzing the image; and providing a prompt for a road management action in response to detecting the target object.
In a second aspect of the present disclosure, an apparatus for determining traffic information is provided. The device includes: a first image receiving module configured to receive images of one or more surrounding objects of a location or area having abnormal road conditions; an image analysis module configured to detect a target object associated with a road management measure from the one or more surrounding objects by analyzing the image; and a first prompt module configured to provide a prompt for the road management action in response to detecting the target object.
In a third aspect of the disclosure, an electronic device is provided that includes one or more processors; and storage means for storing the one or more programs which, when executed by the one or more processors, cause the one or more processors to carry out the method according to the first aspect of the disclosure.
In a fourth aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored which, when executed by a processor, implements a method according to the first aspect of the present disclosure.
In a fifth aspect of the present disclosure, there is provided a computer program product comprising computer program instructions to implement, by a processor, a method according to the first aspect of the present disclosure.
It should be understood that the statements herein reciting aspects are not intended to limit the critical or essential features of the embodiments of the present disclosure, nor are they intended to limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.
Drawings
The above and other features, advantages and aspects of various embodiments of the present disclosure will become more apparent by referring to the following detailed description when taken in conjunction with the accompanying drawings. In the drawings, like or similar reference characters designate like or similar elements, and wherein:
FIG. 1 illustrates a schematic diagram of an example environment in which embodiments of the present disclosure can be implemented;
fig. 2 illustrates a flow chart of a process of determining road condition information according to some embodiments of the present disclosure;
FIG. 3 illustrates a flow chart of a process of receiving an image of a road anomaly location or area, according to some embodiments of the present disclosure;
fig. 4 shows a schematic block diagram of an apparatus for determining traffic information according to some embodiments of the present disclosure; and
FIG. 5 illustrates a block diagram of a computing device capable of implementing various embodiments of the present disclosure.
Detailed Description
Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure are shown in the drawings, it is to be understood that the present disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein, but rather are provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the disclosure are for illustration purposes only and are not intended to limit the scope of the disclosure.
In describing embodiments of the present disclosure, the terms "include" and its derivatives should be interpreted as being inclusive, i.e., "including but not limited to. The term "based on" should be understood as "based at least in part on". The term "one embodiment" or "the embodiment" should be understood as "at least one embodiment". The terms "first," "second," and the like may refer to different or the same object. Other explicit and implicit definitions are also possible below.
The terms "passenger", "passenger end", "vehicle occupant", "user terminal", and the like, as used herein, are interchangeable, and refer to a party that needs or orders a service, either individually or as a tool. Likewise, "driver," "driver-side," and the like, as described herein, are also interchangeable and refer to an individual, tool, or other entity, etc. that provides a service or assists in providing a service. In addition, a "user" as described herein may be a party that needs or subscribes to a service, or a party that provides or assists in providing a service.
As briefly described above, there is a need for a solution that determines a road management measure and prompts the user for the road management measure. In the conventional scheme, the road management measures can be determined by acquiring temporary traffic control information issued by a traffic management department or on a network. However, the traffic control information is often inaccurate or not updated in a timely manner. Therefore, the road condition information cannot be accurately determined, and the navigation experience of the user is reduced.
In order to meet the requirements of timely determining road condition information and improving navigation experience of a user, embodiments of the present disclosure provide a scheme for determining road condition information. According to the solution described herein, an image of one or more surrounding objects in an abnormal location or area of a road condition is first acquired. The images are then analyzed to detect the presence of a target object indicative of a road management measure among surrounding objects. And finally providing a prompt of road management measures if the target object is detected. In this way, the position or the area where the road management measure exists can be effectively determined and prompted, and therefore the navigation experience of the user is improved.
Fig. 1 illustrates a schematic diagram of an example environment 100 in which various embodiments of the present disclosure can be implemented. FIG. 1 may include an image 110 of one or more surrounding objects of an abnormal place or area of road conditions (hereinafter may be referred to simply as image 110), surrounding objects 120-1, 120-2, 120-3, and 120-4 (hereinafter collectively referred to as one or more surrounding objects 120), and a computing device 130. Although the place or area of the abnormal road condition is illustrated as one intersection and 4 surrounding objects exist, this is only exemplary. The abnormal road condition location or area may also be a different traffic scenario associated with the user's trip and there may be a different number of surrounding objects, and the disclosure is not limited thereto.
In the present disclosure, the road management measures are not limited only to the traffic control and road construction scenarios described below. The road management measures may include measures that cause various traffic roads associated with the trip to be prohibited from passing or restricted from passing for any reason. The scenarios utilized to describe the present disclosure are not intended to limit the scope of the present disclosure.
The computing device 130 shown in fig. 1 may be any device having computing capabilities. In some embodiments, the computing device 130 may be a server associated with a web appointment application (or other application associated with a trip, such as a navigation application, a pull application, for example). In this case, the computing device 130 may receive the location information reported by the user, including the location or area of the abnormal road condition, or determine the location information of the yaw location or area of the vehicle associated with the trip, or receive the location information of the abnormal road condition location or area reported by the terminal of the vehicle associated with the trip (or a device that can collect the road condition information, such as a road side camera). The computing device 130 may then issue an image 110 that captures information about the location. By way of non-limiting example, the computing device 130 may be any type of stationary, mobile, or portable computing device, including but not limited to a desktop computer, laptop computer, notebook computer, netbook computer, tablet computer, multimedia computer, mobile phone, and the like.
The vehicle associated with the trip may be any type of vehicle that may carry people and/or things and be moved by a powered system such as an engine, including but not limited to a car, truck, bus, electric vehicle, motorcycle, recreational vehicle, train, and the like. The present disclosure is not limited thereto. In some embodiments, the vehicle may be a vehicle equipped with certain autopilot capabilities, where the autopilot capabilities may include, but are not limited to, assisted driving capabilities, semi-autopilot capabilities, highly autopilot capabilities, or fully autopilot capabilities. It should be understood that embodiments of the present disclosure may be similarly applied to other objects, such as aircraft and the like.
The image 110 may be an image reflecting traffic information of an abnormal location or area. The image 110 may be captured in response to a capture request issued by the computing device 130 described above. In some embodiments, the image 110 may be captured by an image sensor of a vehicle associated with the trip. For example, when the computing device 130 determines location information, information for vehicles that are about to pass through the location may be determined and the images 110 captured by the vehicles that are indicated to be about to pass through the location. The image sensor may be a camera with one or more wide-angle or ultra-wide-angle cameras capable of capturing a scene within 360 degrees of the surrounding environment. The image sensor may also be of a rotatable construction to rotatably detect real-time scenes from multiple directions outside the vehicle.
Alternatively, in some embodiments, the computing device 130 may also capture images via roadside cameras around the location described above or direct users passing by the location to take the image 110. The image 110 may also be acquired by any suitable method, and the disclosure is not limited thereto.
One or more surrounding objects 120 of an abnormal road condition location or area may be included in the image 110. The example surrounding objects in fig. 1 are a tree 120-1, a prohibited right turn flag 120-2, a cone bucket 120-3, and a police car 120-4. The computing device 130 may determine from one or more surrounding objects 120 whether a target object associated with a road management action exists. If it is determined that the target object is present, the computing device 130 may determine that a road management measure is present and issue a prompt message to the user via the user interface. The above process will be described in detail with reference to fig. 2 to 3.
The user interface may be an interface for providing web appointment/navigation/sharing of cars/transporting goods and other applications associated with the itinerary to a user associated with the itinerary. The user interface can display the position of the vehicle in the map, map information, navigation information, different types of prompt information and the like. Depending on the mode, different layouts may also be applied in the user interface. Devices that present the user interface include, but are not limited to, an in-vehicle heads-up display system, a user's terminal device (e.g., smart phone, tablet), or various types of display screens embedded in a vehicle. The user interface may be presented to the user by any suitable display device, and the disclosure is not limited thereto. Note that the above-described prompt is not necessarily a prompt for prompting the user in the vehicle, but may also be an indication for instructing the unmanned vehicle to avoid passing through a road segment associated with a road management measure, and the disclosure is not limited herein.
For clarity, an embodiment of determining road condition information of the present disclosure will be described below with reference to environment 100 of fig. 1. It is to be understood that embodiments of the present disclosure may also include additional acts not shown and/or may omit acts shown. The scope of the present disclosure is not limited in this respect. For ease of understanding, specific data mentioned in the following description are exemplary and are not intended to limit the scope of the present disclosure.
In order to more clearly understand the solutions provided by the embodiments of the present disclosure, embodiments of the present disclosure will be further described with reference to fig. 2. Fig. 2 shows a flowchart of a process 200 of determining road condition information according to an embodiment of the present disclosure. Process 200 may be implemented by computing device 130 of fig. 1. For ease of discussion, process 200 will be described in conjunction with FIG. 1.
At block 210, the computing device 130 receives an image 110 of one or more surrounding objects 120 of an abnormal road condition location or area. For example, the computing device 120 may initiate an image capture request for an anomalous road condition location or area in response to the image capture trigger condition being satisfied. The computing device 120 then receives the captured image 110.
Examples of the image acquisition trigger condition being triggered and the image being acquired will be further described in connection with fig. 3. Fig. 3 illustrates a flow diagram of a process 300 of receiving an image of a road anomaly location or area, according to some embodiments of the present disclosure.
At block 310, the computing device 130 determines whether the number of vehicles yawing away from the predetermined navigation route at the abnormal road condition location or area within the predetermined time period is greater than a threshold number. For example, if the computing device 130 determines that a large number of vehicles are traveling off a predetermined navigation route at a location or area, the computing device 130 determines that road management measures may be present at the location or area.
Taking fig. 1 as an example, in one embodiment, the computing device 130 determines that the number of vehicles that are yawing (e.g., turning left all) from a predetermined navigation route (e.g., straight or turning right) at the illustrated intersection within an hour is 20, and the computing device 130 determines that a road management action may be taken at the intersection. The predetermined time and the threshold number are only exemplary, and different predetermined times and threshold numbers may be set according to the traffic busy degree of different cities and different transit times (morning and evening peaks, etc.), and the disclosure is not limited thereto. By setting the preset time and the threshold number, small-probability yaw events which do not occur due to road management measures can be filtered out, and therefore the calculation cost of the server and the terminal is saved.
At block 320, the computing device 130 sends a request to capture the image 110 if it determines that the number is greater than the threshold number. For example, the computing device 130 may send a request for acquiring an image of the surrounding environment of the abnormal road condition location or area to a terminal of a vehicle near the abnormal road condition location or area or a roadside device in the intelligent transportation system. The acquisition request may include, for example, position information of the acquired image and a time range of the acquired image.
In one embodiment, the abnormal road condition location or area is determined to be the intersection shown in fig. 1 by the computing device 130. In this case, the computing device 130 may determine that a vehicle is about to pass through the intersection in multiple directions within 10 minutes into the future. The computing device 130 can send a request to the vehicle to capture images of the intersection to capture images of surrounding objects at the intersection in multiple directions. The computing device 130 may also send an image capture request to a roadside camera near the intersection, or to a user near the intersection. The computing device 130 may send the image capture request to various suitable terminals, as the disclosure is not limited herein.
Alternatively, in some embodiments, the computing device 130 determines that the location or area of the road condition abnormality is a complex overpass junction, i.e., there are many intersections and road segments that can pass through in a certain area. In this case, the computing device 130 first determines all intersections corresponding to the abnormal road condition location or area. The computing device 130 then sends image capture requests to various suitable terminals as described above to capture images of surrounding objects at all intersections.
At block 330, the computing device 130 receives the image 110 captured in response to the request. For example, the computing device 130 may receive images captured in response to the request from a terminal of a vehicle, a roadside device, or a terminal of a user.
In one embodiment, the computing device 130 may first detect the received image. If the computing device 130 detects the presence or absence of road management measures from the image 110, the receiving of the image may be stopped. The detection process will be explained below.
Alternatively, in some embodiments, the computing device 130 may receive images that are captured within a predetermined time according to the request. Then, it is detected from the image 110 whether or not there is a road management measure in the above traffic abnormality place or area.
In addition to yaw of the trajectory as a trigger for image acquisition, the computing device 130 may issue requests to acquire images based on other triggers. In one example, the computing device 130 sends a request to capture an image if it receives an abnormal road condition message sent at an abnormal road condition location or area. The computing device 130 then receives the images captured in response to the request.
In some embodiments, a user associated with a trip may actively report road management measures via a terminal associated with the trip while passing through a location or area where the road management measures exist. If the computing device 130 receives the abnormal road condition report sent from the abnormal road condition location or area, it sends a request for collecting an image and receives the image. The sending request process of the detailed process refers to the above description, and is not described in detail herein.
Alternatively, in some embodiments, the computing device 130 may receive a report of road conditions anomaly from a terminal of the vehicle. For example, if the terminal of the vehicle detects an object associated with a road management measure in an image captured in real time via a vehicle's tachograph, the terminal of the vehicle reports an abnormal road condition message to the computing device 130 at the abnormal road condition location or area. It will be appreciated that due to cost and space constraints, terminals of vehicles tend to employ lightweight image recognition models (i.e., image detection accuracy is less than a threshold accuracy). The computing device 130 is required to perform the detection and recognition of the image 110 by a more accurate image recognition model (i.e., the accuracy of the image detection is greater than the threshold accuracy). By setting the different image acquisition triggering conditions, the positions or areas where the road management measures exist can be found in different scenes.
The description is continued with reference back to fig. 2. At block 220, the computing device 130 detects a target object associated with the road management action from the one or more surrounding objects 120 by analyzing the image 110. In some embodiments, the target object associated with the road management action may be a first target object associated with a traffic management action, such as a cone, traffic police, police car. Alternatively, in some embodiments, the target object associated with the roadway management action may also be a second target object associated with the roadway construction management action, such as a construction logo, large construction equipment, a cylindrical barrel, a road block ball, a speed bump, a road block post, a road block cone, a pothole, and the like.
In one example, the computing device 130 may detect one or more surrounding objects 120 in the image 110 using a suitable image detection model to determine whether a target object associated with a road management measure is present therein. In some embodiments, the target object associated with the road management measure includes at least one of: the road block comprises a cone barrel, a cylindrical barrel, a road block ball, a traffic police, a police car, a speed bump, a road block column, a road block cone, a tripod, a pothole and car body fragments. Note that the target object associated with the road management measure is not limited to the above-described object described in the present disclosure, and different target objects may be set according to the needs of the scene.
For example, considering fig. 1 as an example, the computing device 130 may determine that a road management measure exists at the intersection if it detects the presence of the cone-bucket 120-3 and the police car 120-4 in one or more surrounding objects 120. The computing device 130 may use Light-head-RCNN as a model for element identification of road management measures. This is merely exemplary, and any other image detection model may also be applied for image analysis and detection, and the disclosure is not limited herein.
At block 330, the computing device 130 provides a prompt for road management measures in response to detecting the target object. In the case where the computing device 130 determines that traffic control exists at an abnormal road condition location or area, a prompt needs to be issued via the terminal associated with the trip in order for the user to avoid the abnormal road condition location or area.
In one example, the computing device 130 first determines at least one road segment associated with the location or area of the anomaly. The computing device 130 then determines at least one candidate route that does not include the at least one road segment if it is determined that the predetermined route associated with the trip includes the at least one road segment. Finally, the computing device 130 provides information related to the at least one candidate route via the terminal associated with the trip.
In some embodiments, the computing device 130 determines at least one candidate route if it determines that the user's trip is about to pass through a road segment involved in an abnormal location or area of road conditions where the traffic management measure is implemented. The transit cost of the at least one candidate route is not greater than a predetermined route including a location or area of abnormal road conditions. That is, the distance passing through the candidate route, the fee required to pass through the toll booth, and the required time are not more than the total cost passing through the predetermined route in the total cost. The computing device 130 may then present information related to the at least one candidate route via the user interface, and may also issue audible prompts for user selection via a terminal associated with the trip.
Alternatively, in some embodiments, the computing device 130 determines that the road segment involved in the traffic management measures described above is a restricted-traffic road segment, for example, a change from an original four-lane traffic to a single-lane traffic. In this case, the computing device 130 will still present the combined cost of the predetermined route and its transit for selection by the user. For example, if a user prefers a route that he is familiar with, the user will not change his choice of route even though his transit costs are high.
Additionally or alternatively, in some embodiments, the computing device 130 may also present, via a terminal associated with the trip, an image including the detected target object described above, the target object having a recognizable level in the presented image above a threshold level. For example, while providing the candidate route, the computing device 130 presents the image 110 to the user if it determines that the level of recognizability of the cone-barrel 120-3 or the police car 120-4 in the image 110 is high (i.e., easily recognized by the user, i.e., above a threshold level). Explaining to the user the reason for providing the candidate route while providing the candidate route may enhance the user's experience of using the application associated with the trip while helping the user save travel costs.
Through the embodiments of the present disclosure, a location or an area where a road management measure is taken can be efficiently and accurately found through data provided by vehicles traveling in a road. In addition, by reasonably determining a candidate route avoiding the place or area and making a prompt to the user, the user can be helped to save travel costs. Further, providing images reflecting the road management measures to the relevant user may improve the navigation experience of the user.
Fig. 4 shows a schematic block diagram of an apparatus 400 for determining traffic information according to some embodiments of the present disclosure. As shown in fig. 4, the apparatus 400 includes a first image receiving module 410 configured to receive images of one or more surrounding objects of an abnormal road condition location or area; an image analysis module 420 configured to detect a target object associated with a road management measure from one or more surrounding objects by analyzing an image; and a first prompt module 430 configured to provide a prompt for a road management measure in response to detecting the target object.
In some embodiments, the first image receiving module 410 may include: a first image acquisition module configured to send a request for acquiring an image if it is determined that the number of vehicles yawing away from a predetermined navigation route at a place or area where a road condition is abnormal within a predetermined time period is greater than a threshold number; and a second image receiving module configured to receive an image captured in response to the request.
In some embodiments, the first image receiving module 410 may include: the second image acquisition module is configured to send an image acquisition request if a road condition abnormal message sent from a road condition abnormal place or area is received; and a third image receiving module configured to receive an image captured in response to the request.
In some embodiments, the first prompting module 430 may include: a road segment determination module configured to determine at least one road segment associated with a location or area of abnormal road conditions; a candidate route determination module configured to determine at least one candidate route that does not include at least one road segment if it is determined that the predetermined route associated with the trip includes at least one road segment; and a candidate route prompt module configured to provide information related to at least one candidate route via a terminal associated with the trip.
In some embodiments, the apparatus 400 may further comprise: a target object display module configured to present an image including a target object, a recognizable level of the target object in the presented image being above a threshold level.
In some embodiments, the target object associated with the road management action includes at least one of: a first target object associated with a traffic management measure, a second target object associated with a road construction management measure.
In some embodiments, the target object associated with the road management measure comprises at least one of: the road block comprises a cone barrel, a cylindrical barrel, a road block ball, a traffic police, a police car, a speed bump, a road block column, a road block cone, a tripod, a pothole and car body fragments.
Fig. 5 illustrates a schematic block diagram of an example device 500 that may be used to implement embodiments of the present disclosure. Device 500 may be used to implement computing device 130 of fig. 1. As shown, device 500 includes a Central Processing Unit (CPU)501 that may perform various appropriate actions and processes in accordance with computer program instructions stored in a Read Only Memory (ROM)502 or loaded from a storage unit 508 into a Random Access Memory (RAM) 503. In the RAM 503, various programs and data required for the operation of the device 500 can also be stored. The CPU 501, ROM 502, and RAM 503 are connected to each other via a bus 504. An input/output (I/O) interface 505 is also connected to bus 504.
A number of components in the device 500 are connected to the I/O interface 505, including: an input unit 506 such as a keyboard, a mouse, or the like; an output unit 507 such as various types of displays, speakers, and the like; a storage unit 508, such as a magnetic disk, optical disk, or the like; and a communication unit 509 such as a network card, modem, wireless communication transceiver, etc. The communication unit 509 allows the device 500 to exchange information/data with other devices through a computer network such as the internet and/or various telecommunication networks.
The processing unit 501 performs the various methods and processes described above, such as the process 200 and the process 300. For example, in some embodiments, processes 200 and 300 may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as storage unit 508. In some embodiments, part or all of the computer program may be loaded and/or installed onto the device 500 via the ROM 502 and/or the communication unit 509. When the computer program is loaded into RAM 503 and executed by CPU 501, one or more steps of processes 200 and 300 described above may be performed. Alternatively, in other embodiments, CPU 501 may be configured to perform processes 200 and 300 in any other suitable manner (e.g., by way of firmware).
The present disclosure may be methods, apparatus, systems, and/or computer program products. The computer program product may include a computer-readable storage medium having computer-readable program instructions embodied thereon for carrying out various aspects of the present disclosure.
The computer readable storage medium may be a tangible device that can hold and store the instructions for use by the instruction execution device. The computer readable storage medium may be, for example, but not limited to, an electronic memory device, a magnetic memory device, an optical memory device, an electromagnetic memory device, a semiconductor memory device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a Static Random Access Memory (SRAM), a portable compact disc read-only memory (CD-ROM), a Digital Versatile Disc (DVD), a memory stick, a floppy disk, a mechanical coding device, such as punch cards or in-groove projection structures having instructions stored thereon, and any suitable combination of the foregoing. Computer-readable storage media as used herein is not to be construed as transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission medium (e.g., optical pulses through a fiber optic cable), or electrical signals transmitted through electrical wires.
The computer-readable program instructions described herein may be downloaded from a computer-readable storage medium to a respective computing/processing device, or to an external computer or external storage device via a network, such as the internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. The network adapter card or network interface in each computing/processing device receives computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in the respective computing/processing device.
The computer program instructions for carrying out operations of the present disclosure may be assembler instructions, Instruction Set Architecture (ISA) instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider). In some embodiments, the electronic circuitry that can execute the computer-readable program instructions implements aspects of the present disclosure by utilizing the state information of the computer-readable program instructions to personalize the electronic circuitry, such as a programmable logic circuit, a Field Programmable Gate Array (FPGA), or a Programmable Logic Array (PLA).
Various aspects of the present disclosure are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer-readable program instructions.
These computer-readable program instructions may be provided to a processing unit of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processing unit of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer-readable program instructions may also be stored in a computer-readable storage medium that can direct a computer, programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer-readable medium storing the instructions comprises an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.
The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer, other programmable apparatus or other devices implement the functions/acts specified in the flowchart and/or block diagram block or blocks.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). 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.
The foregoing description of the embodiments of the present disclosure has been presented for purposes of illustration and description, and is not intended to be exhaustive or limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen in order to best explain the principles of the embodiments, the practical application, or improvements made to the technology in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.
The embodiment of the application discloses:
the ts1. a method for determining traffic information, comprising:
receiving images of one or more surrounding objects of a place or area with abnormal road conditions;
detecting a target object associated with a road management measure from the one or more surrounding objects by analyzing the image; and
in response to detecting the target object, providing a prompt for the road management action.
Ts2. the method of TS1, wherein receiving an image of one or more surrounding objects of an abnormal road condition location or area comprises:
if the number of vehicles which yaw with the preset navigation route at the abnormal road condition place or area in the preset time period is determined to be more than the threshold number, sending a request for acquiring the image; and
receiving the image captured in response to the request.
Ts3. the method of TS1, wherein receiving an image of one or more surrounding objects of an abnormal road condition location or area comprises:
if receiving the abnormal road condition information sent from the abnormal road condition place or area, sending a request for acquiring the image; and
receiving the image captured in response to the request.
Ts4. the method of TS1, wherein providing the prompt for the road management action includes:
determining at least one road segment associated with the abnormal road condition location or area;
determining at least one candidate route that does not include the at least one road segment if it is determined that the predetermined route associated with the trip includes the at least one road segment; and
providing information related to the at least one candidate route via a terminal associated with the trip.
Ts5. the method of TS4, further comprising:
presenting an image including the target object, the target object having a recognizable level in the presented image above a threshold level.
Ts6. the method of TS1, wherein the target object associated with the road management action includes at least one of:
a first target object associated with a traffic management measure,
a second target object associated with the road construction management action.
Ts7. the method according to TS1, wherein the target object associated with a road management measure comprises at least one of:
the road block comprises a cone barrel, a cylindrical barrel, a road block ball, a traffic police, a police car, a speed bump, a road block column, a road block cone, a tripod, a pothole and car body fragments.
TS8, an apparatus for determining traffic information, comprising:
a first image receiving module configured to receive images of one or more surrounding objects of a location or area having abnormal road conditions;
an image analysis module configured to detect a target object associated with a road management measure from the one or more surrounding objects by analyzing the image; and
a first prompt module configured to provide a prompt for the road management action in response to detecting the target object.
Ts9. the device according to TS8, wherein the first image receiving module comprises:
a first image acquisition module configured to send a request for acquiring the image if it is determined that the number of vehicles yawing away from a predetermined navigation route at the abnormal road condition location or area within a predetermined time period is greater than a threshold number; and
a second image receiving module configured to receive the image captured in response to the request.
Ts10. the device according to TS8, wherein the first image receiving module comprises:
the second image acquisition module is configured to send a request for acquiring the image if a road condition abnormal message sent out at the road condition abnormal place or area is received; and
a third image receiving module configured to receive the image captured in response to the request.
Ts11. the device according to TS8, wherein the first prompting module comprises:
a road segment determination module configured to determine at least one road segment associated with the location or area of the road condition anomaly;
a candidate route determination module configured to determine at least one candidate route that does not include the at least one road segment if it is determined that the predetermined route associated with the trip includes the at least one road segment; and
a candidate route prompt module configured to provide information related to the at least one candidate route via a terminal associated with the trip.
Ts12. the apparatus of TS11, further comprising:
a target object display module configured to present an image including the target object, the target object having a recognizable level in the presented image above a threshold level.
The apparatus of TS13. the TS8, wherein the target object associated with the road management action includes at least one of:
a first target object associated with a traffic management measure,
a second target object associated with the road construction management action.
The ts14. apparatus of TS8, wherein the target object associated with a road management measure includes at least one of:
the road block comprises a cone barrel, a cylindrical barrel, a road block ball, a traffic police, a police car, a speed bump, a road block column, a road block cone, a tripod, a pothole and car body fragments.
Ts15. an electronic device, the device comprising:
one or more processors; and
storage means for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to carry out the method of any one of TS1 to 7.
Ts16. a computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method according to any one of TS1 to TS7.
Ts17 a computer program product comprising computer program instructions, characterized in that the computer program instructions are implemented by a processor to implement the method as described in any of TS1 to TS7.
Claims (10)
1. A method for determining traffic information, comprising:
receiving images of one or more surrounding objects of a place or area with abnormal road conditions;
detecting a target object associated with a road management measure from the one or more surrounding objects by analyzing the image; and
in response to detecting the target object, providing a prompt for the road management action.
2. The method of claim 1, wherein receiving images of one or more surrounding objects of the location or area of the anomaly comprises:
if the number of vehicles which yaw with the preset navigation route at the abnormal road condition place or area in the preset time period is determined to be more than the threshold number, sending a request for acquiring the image; and
receiving the image captured in response to the request.
3. The method of claim 1, wherein receiving images of one or more surrounding objects of the location or area of the anomaly comprises:
if receiving the abnormal road condition information sent from the abnormal road condition place or area, sending a request for acquiring the image; and
receiving the image captured in response to the request.
4. The method of claim 1, wherein providing the prompt for the road management action comprises:
determining at least one road segment associated with the abnormal road condition location or area;
determining at least one candidate route that does not include the at least one road segment if it is determined that the predetermined route associated with the trip includes the at least one road segment; and
providing information related to the at least one candidate route via a terminal associated with the trip.
5. The method of claim 4, further comprising:
presenting an image including the target object, the target object having a recognizable level in the presented image above a threshold level.
6. The method of claim 1, wherein the target object associated with the road management action comprises at least one of:
a first target object associated with a traffic management measure,
a second target object associated with the road construction management action.
7. An apparatus for determining traffic information, comprising:
a first image receiving module configured to receive images of one or more surrounding objects of a location or area having abnormal road conditions;
an image analysis module configured to detect a target object associated with a road management measure from the one or more surrounding objects by analyzing the image; and
a first prompt module configured to provide a prompt for the road management action in response to detecting the target object.
8. An electronic device, the device comprising:
one or more processors; and
storage means for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to carry out the method of any one of claims 1 to 6.
9. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1 to 6.
10. A computer program product comprising computer program instructions, characterized in that the computer program instructions are implemented by a processor for the method according to any of claims 1 to 6.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113421432A (en) * | 2021-06-21 | 2021-09-21 | 北京百度网讯科技有限公司 | Traffic restriction information detection method and device, electronic equipment and storage medium |
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