WO2024037009A1 - 一种恶劣天气下停车场所推荐方法、系统、电子设备和存储介质 - Google Patents

一种恶劣天气下停车场所推荐方法、系统、电子设备和存储介质 Download PDF

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Publication number
WO2024037009A1
WO2024037009A1 PCT/CN2023/088953 CN2023088953W WO2024037009A1 WO 2024037009 A1 WO2024037009 A1 WO 2024037009A1 CN 2023088953 W CN2023088953 W CN 2023088953W WO 2024037009 A1 WO2024037009 A1 WO 2024037009A1
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WIPO (PCT)
Prior art keywords
weather
vehicle
risk
intelligent
risk avoidance
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PCT/CN2023/088953
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English (en)
French (fr)
Inventor
李晓琴
刘杰
陈彩可
李保国
李�浩
李龙飞
史绍伟
王云坤
张炜玮
武鹏飞
Original Assignee
中国第一汽车股份有限公司
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Application filed by 中国第一汽车股份有限公司 filed Critical 中国第一汽车股份有限公司
Publication of WO2024037009A1 publication Critical patent/WO2024037009A1/zh

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Classifications

    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/14—Traffic control systems for road vehicles indicating individual free spaces in parking areas
    • G08G1/141—Traffic control systems for road vehicles indicating individual free spaces in parking areas with means giving the indication of available parking spaces
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/09—Arrangements for giving variable traffic instructions
    • G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
    • G08G1/0967—Systems involving transmission of highway information, e.g. weather, speed limits
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/09—Arrangements for giving variable traffic instructions
    • G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
    • G08G1/0968—Systems involving transmission of navigation instructions to the vehicle
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
    • Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Definitions

  • the present invention relates to a parking lot recommendation method, system, electronic device and storage medium, and in particular to a parking lot recommendation method, system, electronic device and storage medium in bad weather.
  • the existing navigation software recommends parking places.
  • the recommendation logic is to sort the vehicles according to their distance, and then the software users choose them. Even after selecting the intelligent recommendation mode, the recommendations are usually based on the distance, which cannot be done. Meet the needs of users to find suitable parking lots in special scenarios.
  • the special scenario mentioned refers to the fact that the existing navigation software uses its own parking recommendation tool to make navigation recommendations based only on static information such as geographical location, relative distance, charging conditions, number of parking spaces, and whether it is open to the public, without considering real-time information.
  • static information such as geographical location, relative distance, charging conditions, number of parking spaces, and whether it is open to the public, without considering real-time information.
  • weather conditions on the recommendation results, for example: when faced with special weather scenarios such as heavy rain, hail, strong winds, etc., the existing technology only recommends and sorts vehicles based on their distance, and lacks the function of recommending different parking spots.
  • the purpose of the present invention is to provide a method, system, electronic device and storage medium for recommending parking lots in bad weather.
  • the first technical problem to be solved is to enable users to find suitable parking spots in special scenarios.
  • the second technical problem to be solved is Classify the hazard levels of severe weather, make intelligent decisions and adopt different corresponding strategies according to different hazard levels; the present invention can also use the human-computer interaction function of the intelligent terminal to allow users to choose intelligent strategies independently.
  • the present invention provides the following solutions:
  • a recommended method for parking in bad weather includes:
  • the personnel information specifically includes: the number of people in the vehicle, the age of the people in the vehicle, and the history information of the passengers driving the vehicle.
  • the risk levels will be divided according to the type, impact and severity of the risk, and different risk hedging recommendation services will be provided according to the risk level.
  • intelligent decisions are made based on the results of risk avoidance recommendations, and parking lots suitable for risk avoidance are searched, specifically including: parking lots, hotels, and public transportation stops.
  • the intelligent interaction with the user through the intelligent terminal is specifically: informing the user of the reasons and methods of risk avoidance recommendations through voice broadcast, screen display of weather or navigation routes, and executing intelligent decision-making results through the results of intelligent interaction. , or re-make risk avoidance recommendations and intelligent decisions based on user instructions.
  • severe weather include: wind, cloud, fog, rain, flash, snow, frost, thunder, hail, and haze;
  • the weather hazard level is divided into 5 levels, with Level 1 being the mildest weather condition and Level 5 being the worst weather condition.
  • the query for the current weather conditions is specifically as follows: when the vehicle is started, the navigation module accesses the weather data interface every half hour.
  • a parking lot recommendation system in bad weather including:
  • Vehicle information and weather conditions query module used to obtain vehicle location information, route information and personnel information, and query current weather conditions
  • the vehicle travel risk assessment module is used to conduct risk assessment on vehicle travel and determine whether there is a need for hedging;
  • the risk avoidance recommendation push module is used to make risk avoidance recommendations based on the risk level of weather conditions and the actual situation of the vehicle;
  • the intelligent decision-making module for safe havens is used to make intelligent decisions based on the results of risk avoidance recommendations and find parking lots suitable for safe havens;
  • the intelligent terminal interaction module is used to intelligently interact with users through intelligent terminals, execute intelligent decision-making results, or re-make risk avoidance recommendations and intelligent decisions based on user instructions.
  • An electronic device characterized in that it includes: a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory complete communication with each other through the communication bus; a computer program is stored in the memory.
  • the computer program when executed by the processor, causes the processor to perform the steps of a recommended method for parking lots in bad weather.
  • a computer-readable storage medium stores a computer program that can be executed by an electronic device.
  • the computer program When the computer program is run on the electronic device, the electronic device performs the steps of the recommended method for parking lots in bad weather.
  • the present invention has the following advantages:
  • the existing navigation software only relies on the distance when recommending parking spots, without considering other factors, especially bad weather factors as an important basis for decision-making.
  • the present invention uses bad weather factors as an important basis for intelligent decision-making.
  • the present invention estimates weather conditions, vehicle locations, vehicle navigation destinations, driving routes and other information, fully considers the risk avoidance purposes of vehicles and people, and proactively recommends destinations or safe parking lots on the way. , even if the distance is far or the price is higher, or it requires Recommendations will also be made when changing to public transportation, because in special scenarios users will be more willing to follow the instructions to make emergency stops, thereby helping car owners reduce the risk of natural disaster losses and increase satisfaction with the intelligent navigation recommendation function.
  • the invention presets severe weather types and standards, and classifies the weather types into: wind, cloud, fog, rain, flash, snow, frost, thunder, hail, haze, etc., and classifies the severity of the weather into levels 1-5. , 1 is the mildest, and 5 is the worst. According to different weather types and severity, different levels of danger warnings are provided, and different intelligent recommendation strategies are adopted to target different special groups (such as the elderly or children). Targeted intelligent recommendation results meet the personalized needs of different groups of people and different scenarios.
  • Figure 1 is a flow chart of the method recommended for parking lots in bad weather according to the present invention.
  • Figure 2 is an architectural diagram of the system recommended for parking lots in bad weather according to the present invention.
  • Figure 3 is a flow chart of the recommendation method of the embodiment.
  • Figure 4 is a flow chart of the severe weather risk assessment method.
  • Figure 5 is a flow chart of intelligent decision-making for risk avoidance recommendations.
  • Figure 6 is an architecture diagram of a recommended system for a parking lot under severe weather in a specific embodiment.
  • Figure 7 is a system architecture diagram of the electronic device.
  • Step S1 obtain the vehicle's location information, route information and personnel information, and query the current weather conditions; for example, query the current weather conditions, specifically: when the vehicle is started, the navigation module interfaces with the weather data every half hour make a visit;
  • Step S2 Conduct risk assessment on vehicle travel to determine whether there is a need for risk avoidance
  • Step S3 Make risk avoidance recommendations based on the risk level of the weather conditions and the actual situation of the vehicle; for example, the types of severe weather include: wind, cloud, fog, rain, flash, snow, frost, thunder, hail, and haze;
  • the risk level of weather conditions is divided into 5 levels, with level 1 being the mildest weather conditions and level 5 being the worst weather conditions.
  • the actual situation of the vehicle can be: the vehicle's fuel volume, number of passengers, vehicle condition information, vehicle battery power, etc. Those skilled in the art can determine the actual situation of the vehicle based on common sense in life and driving.
  • Step S4 Make intelligent decisions based on the results of the risk avoidance recommendation and find a parking lot suitable for risk avoidance;
  • Step S5 Intelligent interaction with the user through the intelligent terminal, execution of intelligent decision-making results, or re-implementing risk avoidance recommendations and intelligent decision-making according to user instructions.
  • the smart terminal intelligently interacts with the user.
  • the user here may be a driver or a non-driver passenger.
  • Those skilled in the art can understand the term "user” here based on common sense in life and driving. specific meaning.
  • the personnel information specifically includes: the number of people in the vehicle, the ages of the people in the vehicle, and the historical information of the passengers driving the vehicle.
  • the personnel information is obtained to determine the vehicle's travel intention as an input for risk avoidance recommendations.
  • the risk avoidance recommendation service will be provided in the form of risk levels based on the type, impact and severity of the risk. Intelligent decisions will be made based on the results of the risk avoidance recommendation, and parking lots suitable for risk avoidance will be queried. , specifically including: parking lots, hotels, public transportation stops, etc.
  • Illustrative Use algorithms to evaluate the severity of weather, analyze potential dangers to vehicles, and predict the duration of potential dangers.
  • the risk assessment of weather on vehicle stopping and driving includes not only the index, but also the judgment of duration, with the purpose of providing input for risk avoidance recommendations.
  • the user can be advised to set off after the heavy rain, or a driving route that is less likely to cause water accumulation problems; if the expected duration of the heavy rain is 10 hours, the user can be advised to park the car in a safe place. of parking lots and use safe public transportation.
  • the algorithm is used to evaluate the severity of the weather and analyze the impact on the vehicle and driving. Potential hazard, the expected duration of the potential hazard.
  • the navigation tool combines the estimated weather conditions and vehicle location, vehicle navigation destination and driving route information to actively recommend destinations or safe parking lots on the way for the purpose of avoiding risks for vehicles and people, even if the distance is far or the price is high. High, or need to transfer to public transportation. Users will also have a higher willingness to follow the instructions for emergency parking, thereby helping car owners reduce the risk of natural disaster losses and increase satisfaction with the intelligent navigation recommendation function.
  • the user is informed of the reasons and methods of risk avoidance recommendations through voice broadcasts, screen display of weather or navigation routes, and intelligent decision-making results are executed through the results of intelligent interaction, or risk avoidance recommendations and intelligent decisions are re-executed according to user instructions. .
  • the navigation calculation is resubmitted through the navigation module.
  • the navigation destination may be changed to a safe parking lot along the way or at the destination, or it may be changed to a parking lot along the way + public transportation.
  • the plan may also be changed to hotels along the way, or the user may even be advised to cancel the trip.
  • the vehicle-mounted system informs users of the reasons and methods for risk avoidance recommendations through voice broadcasts and screen display of weather or navigation routes, and solicits the user's choice as a recalculation method.
  • Re-update navigation information according to user instructions. For example, after the user selects a recommended parking lot and driving route along the way, the subsequent itinerary is planned for the user.
  • the method steps are expressed as a series of action combinations for the purpose of simple description.
  • the embodiments of the present invention are not limited by the described action sequence because According to embodiments of the present invention, certain steps may be performed in other orders or simultaneously.
  • those skilled in the art should also know that the embodiments described in the specification are preferred embodiments, and the actions involved are not necessarily necessary for the embodiments of the present invention.
  • Figure 2 shows the architecture diagram of the recommended system for parking lots in bad weather.
  • the recommended system specifically includes:
  • Vehicle information and weather conditions query module used to obtain vehicle location information, route information and personnel information, and query current weather conditions
  • the vehicle travel risk assessment module is used to conduct risk assessment on vehicle travel and determine whether there is a need for hedging;
  • the risk avoidance recommendation push module is used to make risk avoidance recommendations based on the risk level of weather conditions and the actual situation of the vehicle;
  • the intelligent decision-making module for safe havens is used to make intelligent decisions based on the results of risk avoidance recommendations and find parking lots suitable for safe havens;
  • the intelligent terminal interaction module is used to intelligently interact with users through intelligent terminals, execute intelligent decision-making results, or re-make risk avoidance recommendations and intelligent decisions based on user instructions.
  • the device embodiments described above are only illustrative.
  • the units described as separate components may or may not be physically separated.
  • the components shown as units may or may not be physical units, that is, they may be located at One location, or it can be distributed across multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of this embodiment. Persons of ordinary skill in the art can understand and implement the method without any creative effort.
  • this embodiment shows a specific application scenario of the present invention.
  • the method steps specifically include:
  • Step S31 Actively query the current location and driving destination of the vehicle
  • Step S32 Actively query and predict the expected and subsequent weather conditions at the time and location of the vehicle along the route;
  • Step S33 Determine whether there is a need for hedging. If it is judged that there is no need for hedging, continue to actively query the vehicle's current location, driving destination, expected time and location along the way, and subsequent weather conditions;
  • Step S34 Determine the type, impact, and severity of the danger and provide it to the risk avoidance recommendation module in a standardized manner;
  • Step S35 Obtain the status of the passengers in the car, extract the historical driving information of the passengers and the vehicle, and determine the trip intention;
  • Step S36 Actively query information on safe escape facilities such as parking lots, hotels, and public transportation, and road information on routes;
  • Step S37 Re-calculate the navigation through the navigation module, based on the queried information on safe escape facilities such as parking lots, hotels, public transportation, etc. and the road information of the route;
  • Step S38 Inform the user of the risk avoidance recommendation through intelligent interaction and ask for the user's consent. If the user agrees, re-update the navigation information according to the user's instructions. If the user does not agree, return to step S37 and continue through the navigation module. Navigate computing and continue to interact with users through intelligent interactions;
  • Step S39 Execute the query results of the navigation information.
  • the present invention can analyze the driving or parking situations that the vehicle may face in bad weather from multiple dimensions. Carry out a comprehensive assessment, and based on the severity of the weather and the different conditions of the drivers and passengers, recommend parking lots, hotels, public transportation and other parking places with risk avoidance capabilities that are different from the existing technology.
  • the recommendation logic of the existing technology is based on the vehicle The distance is sorted, and then the software user makes a selection. Even after selecting the intelligent recommendation mode, recommendations are usually based on distance. However, the recommendation logic of the present invention is to consider vehicle safety under severe weather conditions. The personal safety of the car owner and the distance of the parking lot are not the primary considerations.
  • Step S41 Regularly obtain weather data information about the vehicle's current location, driving destination and locations along the way.
  • the weather data information includes real-time weather data information and future weather data information.
  • Step S42 Determine whether the severe weather level is higher than the system's preset severe weather standard
  • the severe weather level is not higher than the severe weather standard preset by the system, then return to step S41 and continue to regularly obtain weather data information about the vehicle's current location, driving destination and locations along the way.
  • Step S43 If the severe weather level is higher than the severe weather standard preset by the system, then use the algorithm to evaluate the severity of the weather, analyze the potential danger to vehicles and driving, and predict the duration of the potential danger.
  • the weather query should consider the estimated time of arrival at the location and the weather conditions 2-4 hours after that time.
  • the types and standards of severe weather should be clearly divided so that the system has a clear and sufficient basis for executing instructions.
  • the weather information value is higher than the system's pre-stored
  • the type and standard of severe weather are determined, it is considered that the preset "severe weather" standards are met, and the system needs to execute corresponding instructions.
  • weather types are divided into: wind, cloud, fog, rain, flash, snow, frost, thunder, hail, haze, etc.
  • the severity of the weather is graded from 1 to 5, with 1 being the mildest and 5 being the worst.
  • the system pre-stores standards that affect driving safety or vehicle safety:
  • the standard for vehicle safety of fog is 5, and the standard for driving safety is 3. Therefore, when the fog index at the destination is 4, the danger warning standard is not reached, but when the fog index along the way is 4, the danger warning standard is reached.
  • Hail's standard for vehicle safety is 1, and its standard for driving safety is 1. Therefore, when the hail index of the weather conditions at the destination or along the way and subsequent weather is 1, it reaches the danger warning standard.
  • the flow chart of intelligent decision-making for risk avoidance recommendations includes:
  • Step S51 Calculate the risk index of driving and parking on the current route: including vehicle driving risk and vehicle parking risk, including the current and subsequent time of the trip;
  • the risk index is a comprehensively calculated value, and the calculation formula is specifically:
  • Driving safety index Severity of weather at the time of the driving journey * Safety relevance of severe weather to vehicle driving * Length of the driving journey + Severity of weather at subsequent times of the driving journey * Safety relevance of severe weather to vehicle driving * Length of driving journey ;
  • Parking safety index Severity of weather at the parking location * Safety relevance of severe weather to vehicle parking * Length of time at the parking location + Severity of weather at subsequent times at the parking location * Safety relevance of severe weather to parking location * Length of parking time;
  • Personnel safety index Severity of the weather at the time of the driving journey * Safety relevance of the severe weather to the safety of the people driving the vehicle * Length of the driving journey + Severity of the weather at the parking location * Safety relevance of the severe weather to the safety of the people at the parking location + Other modes of transportation Severity of weather at the time * Safety relevance of severe weather to people on other modes of transportation * Length of time on other modes of transportation
  • Step S52 Based on the in-car camera or voice multi-mode input, determine the number and type of passengers in the car as a restriction condition for decision-making calculation: if it is determined that there are elderly people with mobility difficulties in the car, the public transportation recommendations in the back can be blocked; if the car Having a baby on board can avoid making longer detours or waiting for recommendations.
  • Step S53 Based on the judgment of historical driving behavior intention, the estimated trip is round trip or one way, which is used as a restriction condition for decision calculation;
  • the navigation is round-trip or one-way. If there is a round-trip, public transportation options for the second half of the journey can be recommended, and you can still drive on the return trip. If it is a one-way trip, leaving the vehicle and taking public transportation cannot be recommended.
  • Select the optimal solution Compare the risk index after calculation with the risk index calculated last time, that is: combine the risk index before and after calculation to determine whether it is the optimal solution, that is: obtain one or several groups of optimal solutions, and select among them the optimal solution;
  • Step S55 Comprehensive all recommended information, recommend the user's new driving and parking plan.
  • Illustrative When recommending users, give priority to recommending solutions that have the greatest impact on the risk index. For example, when the impact of hail on vehicle suspension is greater than that of flooded roads, parking lots that users can use to avoid danger will be recommended first, and then reasonable routes will be recommended to avoid flooded roads.
  • Step S56 According to the user's selection, reset the navigation target, or initiate other commercial services: such as reserving charging piles or reserving hotels and restaurants for the user.
  • a third-party weather server is used to provide a data interface for weather query to the weather module, provide weather data to the weather module through data interaction, and convert the weather data into
  • the third-party navigation server is used to provide third-party navigation data interfaces to mobile terminals, car terminals and other terminal devices, provide navigation data to the navigation module through data interaction, and send the navigation data to the navigation module of the intelligent vehicle controller in the car cockpit;
  • the information receiving module of risk-avoidance-related facilities receives third-party hotel/parking lot/road information through various existing data platforms, interfaces or data supply servers on the market;
  • the account and driving behavior server is used to provide account and driving behavior information related to vehicles and car owners to terminal devices such as mobile terminals and car terminals;
  • the in-car face recognition/voiceprint module is used to identify people in the car through face recognition or voiceprint recognition, and provides relevant data information to the account and driving behavior modules.
  • the risk avoidance recommendation notification and instruction receiving module is used for human-computer interaction with the people in the vehicle. Through intelligent interaction, the user is notified of the risk avoidance recommendation, the user's consent is sought, and the result of the user's agreement or disagreement is sent to the risk avoidance agent. Recommend computing and execution modules for intelligent decision-making.
  • the destination and risk assessment module along the way actively queries the third-party navigation module for the vehicle's current location, driving destination, driving route and driving time information through the navigation module; it queries the weather module for the vehicle's address along the way and the corresponding time period based on the time and address information. and weather conditions in subsequent periods.
  • the destination and route risk assessment module In addition to connecting with the navigation module and weather module, the destination and route risk assessment module also actively queries and predicts the expected and subsequent weather conditions at the time and location of the vehicle along the way, and evaluates whether the weather factors at the current location, along the way, and at the destination point will affect the vehicle. Damage is caused to the vehicle itself, driving safety, and personnel safety.
  • Each of the above modules is interconnected with the risk avoidance recommendation calculation and execution module for data interaction to provide data for intelligent decision-making;
  • the status of the passengers in the car such as the number and age
  • the historical driving information of the passengers and the vehicle is extracted to determine the trip intention, such as inputting one-way or round-trip, to help make risk avoidance recommendations.
  • risk avoidance recommendation Based on the conclusion of the risk avoidance recommendation, proactively inquire about information on risk avoidance facilities such as parking lots, hotels, and public transportation, as well as information on navigation routes and roads;
  • the navigation destination may be changed to a safe parking lot along the way or at the destination, or it may be changed to a parking lot + public transportation solution along the way, or it may be changed to a hotel along the way, or the user may even be advised to cancel the trip;
  • Re-update navigation information according to user instructions. For example, after the user selects a recommended parking lot and driving route along the way, the subsequent itinerary is planned for the user.
  • the present invention also provides electronic equipment and storage media corresponding to the recommended methods and systems for parking lots in bad weather:
  • An electronic device including: a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory complete communication with each other through the communication bus; a computer program is stored in the memory.
  • the processor When executed by the processor, the processor is caused to execute the steps of the parking recommendation method in bad weather.
  • a computer-readable storage medium stores a computer program that can be executed by an electronic device.
  • the computer program When the computer program is run on the electronic device, the electronic device performs the steps of a parking recommendation method in bad weather.
  • the communication bus mentioned in the above-mentioned electronic equipment can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc.
  • PCI Peripheral Component Interconnect
  • EISA Extended Industry Standard Architecture
  • the communication bus can be divided into address bus, data bus, control bus, etc. For ease of presentation, only one thick line is used in the figure, but it does not mean that there is only one bus or one type of bus.
  • Electronic devices include a hardware layer, an operating system layer running on the hardware layer, and an application layer running on the operating system.
  • This hardware layer includes hardware such as central processing unit (CPU, Central Processing Unit), memory management unit (MMU, Memory Management Unit), and memory.
  • the operating system can be any one or more computer operating systems that realize control of electronic devices through processes, such as Linux operating system, Unix operating system, Android operating system, iOS operating system or windows operating system, etc.
  • the electronic device may be a handheld device such as a smartphone or a tablet computer, or may be an electronic device such as a desktop computer or a portable computer, which is not particularly limited in the embodiment of the present invention.
  • the execution subject of electronic device control in the embodiment of the present invention may be an electronic device, or a functional module in the electronic device that can call a program and execute the program.
  • the electronic device can obtain the firmware corresponding to the storage medium.
  • the firmware corresponding to the storage medium is provided by the supplier.
  • the firmware corresponding to different storage media can be the same or different, and is not limited here.
  • After the electronic device obtains the firmware corresponding to the storage medium it can write the firmware corresponding to the storage medium into the storage medium, specifically to the storage medium. Burn the corresponding firmware into the storage medium.
  • the process of burning the firmware into the storage medium can be implemented using existing technology, and will not be described again in the embodiment of the present invention.
  • the electronic device can also obtain the reset command corresponding to the storage medium.
  • the reset command corresponding to the storage medium is provided by the supplier.
  • the reset commands corresponding to different storage media can be the same or different, and are not limited here.
  • the storage medium of the electronic device is a storage medium in which the corresponding firmware is written.
  • the electronic device can respond to the reset command corresponding to the storage medium in the storage medium in which the corresponding firmware is written, so that the electronic device responds to the reset command corresponding to the storage medium.
  • Reset command to reset the storage medium in which the corresponding firmware is written.
  • the process of resetting the storage medium according to the reset command can be implemented with existing technology, and will not be described again in the embodiment of the present invention.
  • the present invention can be implemented by means of software plus a necessary general hardware platform. Based on this understanding, The technical solution of the present invention essentially or the part that contributes to the existing technology can be embodied in the form of a software product.
  • the computer software product can be stored in a storage medium, such as ROM/RAM, magnetic disk, optical disk, etc., including Several instructions are used to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in various embodiments or certain parts of the embodiments of the present invention.
  • the present invention may be used in a variety of general or special purpose computing system environments or configurations, such as: personal computers, server computers, handheld or portable devices, tablet devices, multi-processor systems, microprocessor-based systems, set-top boxes, Programmed consumer electronics devices, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, etc.
  • the invention may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer.
  • program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types.
  • the present invention may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communications network.
  • program modules may be located in both local and remote computer storage media including storage devices.
  • each block in the flowchart or block diagrams may represent a module, segment, or portion of code that contains one or more components for implementing the specified logical function(s). Executable instructions. 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.
  • each block of the block diagram and/or flowchart illustration, and combinations of blocks in the block diagram and/or flowchart illustration can be implemented by special purpose hardware-based systems that perform the specified functions or acts. , or can be implemented using a combination of specialized hardware and computer instructions.
  • each functional module in various embodiments of the present invention can be integrated together to form an independent part, each module can exist alone, or two or more modules can be integrated to form an independent part.
  • the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium.
  • the technical solution of the present invention essentially or the part that contributes to the existing technology or the part of the technical solution can be embodied in the form of a software product.
  • the computer software product is stored in a storage medium, including Several instructions are used to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention.
  • the aforementioned storage media include: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic disk or optical disk and other media that can store program code.
  • ROM read-only memory
  • RAM random access memory
  • magnetic disk or optical disk and other media that can store program code.
  • relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and not necessarily Requiring or implying any such actual relationship or sequence between these entities or operations.
  • the terms “comprises,””comprises,” or any other variation thereof are intended to cover a non-exclusive inclusion such that a process, method, article, or apparatus that includes a list of elements includes not only those elements, but also those not expressly listed other elements, or elements inherent to the process, method, article or equipment.
  • an element defined by the statement “comprises a" does not exclude the presence of additional identical elements in a process, method, article, or apparatus that includes the stated element.
  • modules in the devices in the embodiment can be adaptively changed and arranged in one or more devices different from that in the embodiment.
  • the modules or units or components in the embodiments may be combined into one module or unit or component, and furthermore they may be divided into a plurality of sub-modules or sub-units or sub-components. All features disclosed in this specification (including accompanying claims, abstract and drawings) and any method so disclosed may be employed in any combination, except that at least some of such features and/or processes or units are mutually exclusive. All processes or units of the equipment are combined.
  • Each feature disclosed in this specification may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.
  • Various component embodiments of the present invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof.
  • a microprocessor or a digital signal processor (DSP) may be used in practice to implement some or all functions of some or all components in a device for distributing messages according to embodiments of the present invention.
  • Book The invention may also be implemented as an apparatus or apparatus program (eg, computer program and computer program product) for performing part or all of the methods described herein.
  • Such a program implementing the present invention may be stored on a computer-readable medium, or may be in the form of one or more signals. Such signals may be downloaded from an Internet website, or provided on a carrier signal, or in any other form.

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Abstract

本发明公开了一种恶劣天气下停车场所推荐方法、系统、电子设备和存储介质，方法步骤具体包括：获取车辆的位置信息、路线信息和人员信息，并查询当前的天气情况，判断是否有避险需求；根据天气情况危险等级并结合车辆的实际情况，进行避险推荐和智能决策，寻找适于避险的停车场所；与用户进行智能交互，执行智能决策的结果，系统、电子设备和存储介质与方法相对应。本发明会充分考虑车辆和人员的避险目的，在主动推荐目的地或途中的安全停车场时，即使距离较远甚至收费价格较高，或者需要换乘公共交通工具，也会进行推荐，因为在特殊场景下用户会有较高的意愿按照指引去紧急停车，能够降低自然灾害的风险。

Description

一种恶劣天气下停车场所推荐方法、系统、电子设备和存储介质 技术领域
本发明涉及一种停车场所推荐方法、系统、电子设备和存储介质，尤其涉及一种恶劣天气下停车场所推荐方法、系统、电子设备和存储介质。
背景技术
现有技术的导航软件推荐停车场所，其推荐逻辑是根据车辆距离远近进行排序，再由软件使用者去选择，即使在选择了智能推荐模式后，通常也是按照距离的远近来看推荐的，无法满足用户在特殊场景下找到合适停车场的需求。
所述的特殊场景，指的是现有技术的导航软件根据自带的停车推荐工具，仅根据地理位置、相对距离、收费情况、车位数量、是否对外开放等静态信息进行导航推荐，没有考虑实时的天气情况对推荐结果带来的影响，例如：当面临暴雨、冰雹、大风等特殊场景的天气时，现有技术也只根据车辆距离远近进行推荐和排序，缺少推荐不同停车场所的功能。
发明内容
本发明的目的在于提供一种恶劣天气下停车场所推荐方法、系统、电子设备和存储介质，首先要解决的技术问题能够让用户在特殊场景下找到合适的停车场所，其次要解决的技术问题是将恶劣天气进行危险等级分级，根据不同的危险等级，进行智能决策，采取不同的对应策略；本发明还能利用智能终端的人机交互功能，让用户自主选择智能策略。
本发明提供了下述方案：
一种恶劣天气下停车场所推荐方法，具体包括：
获取车辆的位置信息、路线信息和人员信息，并查询当前的天气情况；
对车辆出行进行风险评估，判断是否有避险需求；
根据天气情况危险等级并结合车辆的实际情况，进行避险推荐；
根据避险推荐的结果进行智能决策，寻找适于避险的停车场所；
通过智能终端与用户进行智能交互，执行智能决策结果，或根据用户指令，重新进行避险推荐和智能决策。
进一步的，所述人员信息具体包括：车内人员数量、车内人员年龄、乘客驾驶车辆的历史信息。
进一步的，判断存在避险需求，则根据危险的类型、影响程度以及严重程度划分危险等级，按照危险等级提供对应不同的避险推荐服务。
进一步的，根据避险推荐的结果进行智能决策，查询适于避险的停车场所，具体包括：停车场、酒店、公共交通停靠站。
进一步的，所述通过智能终端与用户进行智能交互，具体为：通过语音播报，屏幕显示天气或导航线路的方式，告知用户避险推荐的原因和方法，通过智能交互的结果，执行智能决策结果，或根据用户指令，重新进行避险推荐和智能决策。
进一步的，所述恶劣天气的类型包括：风、云、雾、雨、闪、雪、霜、雷、雹、霾；
所述天气情况危险等级分为5级，1级为最轻微的天气情况，5级为最恶劣的天气情况。
进一步的，所述查询当前的天气情况，具体为：在车辆启动时，导航模块每隔半小时对天气数据接口进行访问。
一种恶劣天气下停车场所推荐系统，具体包括：
车辆信息及天气情况查询模块，用于获取车辆的位置信息、路线信息和人员信息，并查询当前的天气情况；
车辆出行风险评估模块，用于对车辆出行进行风险评估，判断是否有避险需求；
避险推荐推送模块，用于根据天气情况危险等级并结合车辆的实际情况，进行避险推荐；
避险场所智能决策模块，用于根据避险推荐的结果进行智能决策，寻找适于避险的停车场所；
智能终端交互模块，用于通过智能终端与用户进行智能交互，执行智能决策结果，或根据用户指令，重新进行避险推荐和智能决策。
一种电子设备，其特征在于，包括：处理器、通信接口、存储器和通信总线，其中，处理器，通信接口，存储器通过通信总线完成相互间的通信；所述存储器中存储有计算机程序，当所述计算机程序被所述处理器执行时，使得所述处理器执行恶劣天气下停车场所推荐方法的步骤。
一种计算机可读存储介质，其存储有可由电子设备执行的计算机程序，当所述计算机程序在所述电子设备上运行时，使得所述电子设备执行恶劣天气下停车场所推荐方法的步骤。
本发明与现有技术相比具有以下的优点：
现有技术的导航软件，在推荐停车场所时只依据距离远近，未考虑其他因素，尤其是未将恶劣天气因素作为重要的决策依据进行考量，本发明将恶劣天气因素作为重要的智能决策依据进行考量，在通过导航选择停车场所时，充分考虑恶劣天气因素带来的危险，不再只根据地理位置、相对距离、收费情况、车位数量等常规决策依据进行智能决策，充分考虑了实时天气情况对停车场所的推荐结果带来的影响。
本发明应用于导航软件、导航工具时，预估天气情况、车辆位置、车辆导航目的地和行驶路线等信息，充分考虑车辆和人员避险目的，在主动推荐目的地或途中的安全停车场时，即使距离较远甚至收费价格较高，或者需要 换乘公共交通工具，也会进行推荐，因为在特殊场景下用户会有较高的意愿按照指引去紧急停车，从而帮助车主降低承担自然灾害损失的风险，增加对导航智能推荐功能的满意度。
本发明预设了恶劣天气类型和标准，将天气的类型分为：风、云、雾、雨、闪、雪、霜、雷、雹、霾等，将天气的恶劣程度分为1-5级，1为最轻微，5为最恶劣，根据不同的天气类型和恶劣程度，进行不同程度的危险预警提示，并采用不同的智能推荐策略，针对不同的特殊人群(比如老人或小孩)也会推送有针对性的智能推荐结果，满足了不同人群、不同场景的个性化需求。
附图说明
为了更清楚地说明本发明具体实施方式或现有技术中的技术方案，下面将对具体实施方式或现有技术描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图是本发明的一些实施方式，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1是本发明恶劣天气下停车场所推荐方法的流程图。
图2是本发明恶劣天气下停车场所推荐系统的架构图。
图3是实施例的推荐方法流程图。
图4是恶劣天气风险评估方法的流程图。
图5是避险推荐智能决策的流程图。
图6是一个具体实施例中恶劣天气下停车场所推荐系统的架构图。
图7是电子设备的系统架构图。
具体实施方式
下面将结合附图对本发明的技术方案进行清楚、完整地描述，显然，所描述的实施例是本发明一部分实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的范围。
如图1所示的恶劣天气下停车场所推荐方法，具体包括：
步骤S1，获取车辆的位置信息、路线信息和人员信息，并查询当前的天气情况；示例性的，查询当前的天气情况，具体为：在车辆启动时，导航模块每隔半小时对天气数据接口进行访问；
步骤S2，对车辆出行进行风险评估，判断是否有避险需求；
步骤S3，根据天气情况危险等级并结合车辆的实际情况，进行避险推荐；示例性的，恶劣天气的类型包括：风、云、雾、雨、闪、雪、霜、雷、雹、霾；天气情况危险等级分为5级，1级为最轻微的天气情况，5级为最恶劣的天气情况。具体的，车辆的实际情况可以是：车辆的油量、乘员数量、车况信息、车载电池的电量等实际情况，本领域技术人员根据生活常识和驾驶常识，即可判断出车辆的实际情况。
步骤S4，根据避险推荐的结果进行智能决策，寻找适于避险的停车场所；
步骤S5，通过智能终端与用户进行智能交互，执行智能决策结果，或根据用户指令，重新进行避险推荐和智能决策。示例性的，在本实施例中智能终端与用户进行智能交互，这里的用户可以是司机，也可以是非司机的乘员，本领域技术人员根据生活常识和驾驶常识即可理解此处“用户”的具体含义。
优选的，所述人员信息具体包括：车内人员数量、车内人员年龄、乘客驾驶车辆的历史信息，获取所述人员信息，判断车辆的行程意图，作为避险推荐的输入量。
优选的，判断存在避险需求，则根据危险的类型、影响程度以及严重程度，以危险等级的方式提供避险推荐服务，根据避险推荐的结果进行智能决策，查询适于避险的停车场所，具体包括：停车场、酒店、公共交通停靠站，等等。
示例性的：结合算法评估天气的恶劣程度，分析对车辆的潜在危险，潜在危险发生的持续时间预期。天气对车辆停驶和车辆驾驶的危险评估不仅包含指数，还要考虑持续时间的判断，目的是对避险推荐提供输入。
例如：如果暴雨的预计持续时间是1小时，可以建议用户暴雨后再出发，或推荐不易发生积水问题的行驶路线；如果暴雨的预计持续时间是10小时，可以建议用户将车停驶在安全的停车场，采用安全的公共交通出行。
定期获取车辆当前位置、行驶目的地和沿途的位置的实时和未来时间的天气数据信息，当天气信息数值高于系统预存的恶劣天气标准时，结合算法评估天气的恶劣程度，分析对车辆和驾驶的潜在危险，潜在危险发生的持续时间预期。
例如：大雨天气时，有地下停车场积水甚至被淹的风险，此时应当优先推荐地面或高于地面的停车场；
例如：冰雹天气时，有车辆被砸坑的风险，此时应当优先推荐室内停车场。
例如：大风天气时，有车辆被掉落的树枝砸中的风险，此时应推荐室内停车场，并且引导路线应避开较多树木下方的道路。
导航工具结合预估天气情况和车辆位置，车辆导航目的地和行驶路线等信息，出于车辆和人员避险目的，主动推荐目的地或途中的安全停车场时，即使距离较远甚至收费价格较高，或者需要换乘公共交通工具。用户也会有较高的意愿按照指引去紧急停车，从而帮助车主降低承担自然灾害损失的风险，增加对导航智能推荐功能的满意度。
优选的，通过语音播报，屏幕显示天气或导航线路的方式，告知用户避险推荐的原因和方法，通过智能交互的结果，执行智能决策结果，或根据用户指令，重新进行避险推荐和智能决策。
示例性的：根据智能终端与用户之间进行智能交互的结果，通过导航模块重新提交导航计算，导航目的地可能变更为沿途或目的地的安全停车场，也可能变更为沿途停车场+公共交通方案，也可能变更为沿途酒店，甚至建议用户取消行程。
车载系统通过语音播报，屏幕显示天气或导航线路的方式，告知用户避险推荐的原因和方法，征求用户的选择作为重新计算方法。
根据用户指令，重新更新导航信息。例如，用户选择了推荐的某一个沿途停车场和行车路线后，为用户规划后续的行程。
对于上述实施例公开的方法步骤，出于简单描述的目的将方法步骤表述为一系列的动作组合，但是本领域技术人员应该知悉，本发明实施例并不受所描述的动作顺序的限制，因为依据本发明实施例，某些步骤可以采用其他顺序或者同时进行。其次，本领域技术人员也应该知悉，说明书中所描述的实施例均属于优选实施例，所涉及的动作并不一定是本发明实施例所必须的。
如图2所示的恶劣天气下停车场所推荐系统的架构图，推荐系统具体包括：
车辆信息及天气情况查询模块，用于获取车辆的位置信息、路线信息和人员信息，并查询当前的天气情况；
车辆出行风险评估模块，用于对车辆出行进行风险评估，判断是否有避险需求；
避险推荐推送模块，用于根据天气情况危险等级并结合车辆的实际情况，进行避险推荐；
避险场所智能决策模块，用于根据避险推荐的结果进行智能决策，寻找适于避险的停车场所；
智能终端交互模块，用于通过智能终端与用户进行智能交互，执行智能决策结果，或根据用户指令，重新进行避险推荐和智能决策。
值得注意的是，虽然在本系统中只披露了车辆信息及天气情况查询模块、车辆出行风险评估模块、避险推荐推送模块、避险场所智能决策模块、智能终端交互模块，但并不意味着本系统的组成仅仅局限于上述基本功能模块，相反，本发明所要表达的意思是：在上述基本功能模块的基础之上本领域技术人员可以结合现有技术任意添加一个或多个功能模块，形成无穷多个实施例或技术方案，也就是说本系统是开放式而非封闭式的，不能因为本实施例仅仅披露了个别基本功能模块，就认为本发明权利要求的保护范围局限于所公开的基本功能模块。同时，为了描述的方便，描述以上装置时以功能分为各种单元、模块分别描述。当然在实施本发明时可以把各单元、模块的功能在同一个或多个软件和/或硬件中实现。
以上所描述的装置实施方式仅仅是示意性的，其中所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部模块来实现本实施方式方案的目的。本领域普通技术人员在不付出创造性劳动的情况下，即可以理解并实施。
如图3所示的具体实施例，本实施例展现了本发明的一个具体应用场景，方法步骤具体包括：
步骤S31：主动查询车辆当前位置和行驶目的地；
步骤S32：主动查询和预判车辆沿途时间和位置的预期和后续天气情况；
步骤S33：判断是否有避险需求，如果判断无避险需求，则继续主动查询车辆当前位置、行驶目的地、沿途时间和位置的预期以及后续天气情况；
步骤S34：判断危险的类型、影响、严重程度，以标准化方式提供给避险推荐模块；
步骤S35：获取车内的乘客情况，并提取乘客和车辆的历史驾驶信息，判断行程意图；
步骤S36：主动查询停车场、酒店、公共交通等可避险设施的信息和路线的道路信息情况；
步骤S37：通过导航模块重新进行导航计算，根据查询到的停车场、酒店、公共交通等可避险设施的信息和路线的道路信息情况；
步骤S38：通过智能交互的方式，将避险推荐告知用户，征求用户同意，如果用户同意，则根据用户指令，重新更新导航信息，如果用户不同意，则返回步骤S37，继续通过导航模块重新进行导航计算，并通过智能交互方式继续与用户进行交互；
步骤S39：执行导航信息的查询结果。
通过本实施例可以看出，本发明根据车辆的具体情况、行驶路线、目的地、沿途时间、车内人员，并结合天气情况，从多个维度对车辆可能面临处于恶劣天气下行驶或停车情况进行综合评估，根据天气的恶劣程度、司乘人员的不同情况，推荐有别于现有技术的停车场、酒店、公共交通等具备避险能力的停车场所，现有技术的推荐逻辑是根据车辆距离远近进行排序，再由软件使用者去选择，即使在选择了智能推荐模式后，通常也是按照距离的远近来看推荐的，但本发明的推荐逻辑是优选考虑在恶劣天气条件下的车辆安全和车主的人身安全，停车场所的距离远近并不是首要考虑因素。
如图4所示的恶劣天气风险评价流程：
步骤S41：定期获取车辆当前位置、行驶目的地和沿途位置的天气数据信息，上述天气数据信息中包括实时天气数据信息和未来天气数据信息。
示例性的：由于对于频繁的对第三方天气的数据访问会受到限制，所以对天气的访问可以设置在车辆启动，导航开始以及此后每隔半个小时进行数据的更新。
步骤S42：判断天气恶劣等级是否高于系统预设的恶劣天气标准
如果天气恶劣等级未高于系统预设的恶劣天气标准，那么返回步骤S41，继续定期获取车辆当前位置、行驶目的地和沿途位置的天气数据信息。
步骤S43：如果天气恶劣等级高于系统预设的恶劣天气标准，那么结合算法评估天气的恶劣程度，分析对车辆和驾驶的潜在危险，预测潜在危险发生的持续时间。
由于考虑到长途开车乘客会进行休息的情况，天气查询应当考虑预计到达地点时间，以及该时间之后2-4个小时的天气情况。
作为进一步的改进，在确定什么是“恶劣天气”时，应当对恶劣天气的类型和标准进行较为清晰的划分，以便系统在执行指令时有明确而充分的依据，当天气信息数值高于系统预存的恶劣天气的类型和标准时，认为符合了预设的“恶劣天气”的标准，需要系统执行相应的指令。
例如：天气的类型分为：风、云、雾、雨、闪、雪、霜、雷、雹、霾等。天气的恶劣程度分为1-5级，1为最轻微，5为最恶劣。
系统预存对驾驶安全或车辆安全造成影响的标准：
如：雾对车辆安全的标准为5，对驾驶安全的标准为3。故当目的地的雾指数为4时，未达到危险预警标准，但是当沿途的雾指数为4时，达到危险预警标准。
再如：雹对车辆安全的标准为1，对驾驶安全的标准为1。故当目的地或沿途天气情况及后续天气的雹指数为1时，均达到危险预警标准。
如图5所示的避险推荐智能决策的流程图，方法步骤具体包括：
避险推荐计算决策流程：
步骤S51：计算当前路线的行驶以及停车的危险指数：包括车辆驾驶危险，车辆停车危险，包括行程当时和后续时间；
危险指数是一个综合计算的数值，计算公式具体为：
危险指数＝驾驶安全指数+停车安全指数+人员安全指数；
驾驶安全指数＝驾驶路程当时天气恶劣程度*恶劣天气对车辆行驶的安全相关性*驾驶行程的时间长度+驾驶路程后续时间天气恶劣程度*恶劣天气对车辆行驶的安全相关性*驾驶行程的时间长度；
停车安全指数＝停车地点当时天气恶劣程度*恶劣天气对车辆停车的安全相关性*停车地点的时间长度+停车地点后续时间天气恶劣程度*恶劣天气对停车地点的安全相关性*停车的时间长度；
人员安全指数＝驾驶路程当时天气恶劣程度*恶劣天气对车辆行驶中人员的安全相关性*驾驶路程的时间长度+停车地点天气恶劣程度*恶劣天气对停车地点人员安全的安全相关性+其他交通方式当时天气恶劣程度*恶劣天气对其他交通方式人员的安全相关性*其他交通方式的时间长度
步骤S52：根据车内摄像头或语音多模输入，判断车内乘客的人数和类型，作为决策计算的限制条件：如果车内判断有行动不便的老人，可以屏蔽掉后面的公共交通推荐；如果车内有婴儿，可以避免做出行程较长的绕路方案或等待推荐。
步骤S53：根据历史驾驶行为意图判断，预估行程属于往返和单程，作用决策计算用的限制条件；
根据目的地地点的远近，类型和路程时长(例如超过6小时)，推断导航是往返还是单程，如果往返可以推荐后半程公共交通方案，返程仍然可以驾车。如果是单程，则不能推荐离开车辆采用公共交通的方式。
选择最优方案：比对计算后的危险指数和上一次计算的危险指数，即：结合计算前后的危险指数，判断是否为最优方案，即：获得一组或几组最优方案，选择其中的最优方案；
步骤S55：综合所有推荐信息，推荐用户新的驾驶和停车方案。示例性的：在推荐用户时，优先推荐对危险指数影响最大的方案。例如，冰雹对车辆停驶的影响大于积水路线时，优先推荐用户可用于避险的停车场，再行推荐合理路线避开积水路段。
步骤S56：根据用户的选择，重新设定导航目标，或发起其他商业服务：例如为用户预约充电桩或者预定酒店和餐厅等。
如图6所示，在汽车座舱中通过智能车机控制器进行恶劣天气下停车场所推荐系统的整体架构：
第三方天气服务器，用于向天气模块提供天气查询的数据接口，通过数据交互向天气模块提供天气数据，将天气数据
第三方导航服务器，用于向移动端、车端等终端设备提供第三方导航数据接口，通过数据交互向导航模块提供导航数据，将导航数据发送给汽车座舱内智能车机控制器的导航模块；
避险相关设施的信息接收模块，通过市面上各种现有的数据平台、接口或数据供应服务器，接收第三方酒店/停车场/道路信息；
账号和驾驶行为服务器，用于向移动端、车端等终端设备提供与车辆和车主相关的账号与驾驶行为信息；
车内人脸识别/声纹模块，用于通过人脸识别或声纹识别对车内人员进行辨识，并将相关数据信息提供给账号和驾驶行为模块。
避险推荐通知和指令接收模块，用于与车内人员进行人机交互，通过智能交互的方式，将避险推荐告知用户，征求用户同意，并将用户同意或不同意的结果发送给避险推荐计算和执行模块进行智能决策。
目的地和沿途风险评价模块，通过导航模块主动查询第三方导航模块的车辆当前位置、行驶目的地、行驶路线和行驶时间的信息；根据时间和地址信息向天气模块查询车辆沿途地址和相应时间段和后续时间段的天气情况。
除与导航模块和天气模块进行连接以外，目的地和沿途风险评价模块还主动查询和预判车辆沿途时间和位置的预期和后续天气情况，评估当前地点、沿途和目的地点的天气因素是否会对车辆自身、驾驶安全、人员安全造成损害。
在评估有避险需求的情况下，危险的类型、影响、严重程度以标准化方式提供避险推荐模块。本实施例的工作原理是：
上述各个模块均与避险推荐计算和执行模块相互连接，进行数据交互，为智能决策提供数据；
通过车内设备获取车内乘客人员情况，如人数和年龄，并提取乘客和车辆的历史驾驶信息，判断行程意图，例如输入单程还是往返，帮助做出避险推荐。示例性的：通过车内人脸识别/声纹识别模块获取车内乘客人员情况；
根据避险推荐的结论，主动查询停车场、酒店、公共交通等可避险设施的信息和导航路线的道路等信息；
通过导航模块重新提交导航计算。导航目的地可能变更为沿途或目的地的安全停车场，也可能变更为沿途停车场+公共交通方案，也可能变更为沿途酒店，甚至建议用户取消行程；
通过语音播报，屏幕显示天气或导航线路的方式，告知用户避险推荐的原因和方法，征求用户的选择作为重新计算方法；
根据用户指令，重新更新导航信息。例如，用户选择了推荐的某一个沿途停车场和行车路线后，为用户规划后续的行程。
如图7所示，本发明还提供与恶劣天气下停车场所推荐方法、系统相对应的电子设备和存储介质：
一种电子设备，包括：处理器、通信接口、存储器和通信总线，其中，处理器，通信接口，存储器通过通信总线完成相互间的通信；所述存储器中存储有计算机程序，当所述计算机程序被所述处理器执行时，使得所述处理器执行恶劣天气下停车推荐方法的步骤。
一种计算机可读存储介质，其存储有可由电子设备执行的计算机程序，当所述计算机程序在所述电子设备上运行时，使得所述电子设备执行恶劣天气下停车推荐方法的步骤。
上述电子设备提到的通信总线可以是外设部件互连标准(Peripheral Component Interconnect，PCI)总线或扩展工业标准结构(Extended Industry Standard Architecture，EISA)总线等。该通信总线可以分为地址总线、数据总线、控制总线等。为便于表示，图中仅用一条粗线表示，但并不表示仅有一根总线或一种类型的总线。
电子设备包括硬件层，运行在硬件层之上的操作系统层，以及运行在操作系统上的应用层。该硬件层包括中央处理器(CPU，Central Processing Unit)、内存管理单元(MMU，Memory Management Unit)和内存等硬件。该操作系统可以是任意一种或多种通过进程(Process)实现电子设备控制的计算机操作系统，例如，Linux操作系统、Unix操作系统、Android操作系统、iOS操作系统或windows操作系统等。并且在本发明实施例中该电子设备可以是智能手机、平板电脑等手持设备，也可以是桌面计算机、便携式计算机等电子设备，本发明实施例中并未特别限定。
本发明实施例中的电子设备控制的执行主体可以是电子设备，或者是电子设备中能够调用程序并执行程序的功能模块。电子设备可以获取到存储介质对应的固件，存储介质对应的固件由供应商提供，不同存储介质对应的固件可以相同可以不同，在此不做限定。电子设备获取到存储介质对应的固件后，可以将该存储介质对应的固件写入存储介质中，具体地是往该存储介质 中烧入该存储介质对应固件。将固件烧入存储介质的过程可以采用现有技术实现，在本发明实施例中不做赘述。
电子设备还可以获取到存储介质对应的重置命令，存储介质对应的重置命令由供应商提供，不同存储介质对应的重置命令可以相同可以不同，在此不做限定。
此时电子设备的存储介质为写入了对应的固件的存储介质，电子设备可以在写入了对应的固件的存储介质中响应该存储介质对应的重置命令，从而电子设备根据存储介质对应的重置命令，对该写入对应的固件的存储介质进行重置。根据重置命令对存储介质进行重置的过程可以现有技术实现，在本发明实施例中不做赘述。
本技术领域技术人员可以理解，除非另外定义，这里使用的所有术语(包括技术术语和科学术语)，具有与本发明所属领域中的普通技术人员的一般理解相同的意义。还应该理解的是，诸如通用字典中定义的那些术语，应该被理解为具有与现有技术的上下文中的意义一致的意义，并且除非被特定定义，否则不会用理想化或过于正式的含义来解释。
需要说明的是，本说明书与权利要求中使用了某些词汇来指称特定元件。本领域技术人员应可以理解，车辆制造商可能会用不同名词来称呼同一个元件。本说明书与权利要求并不以名词的差异来作为区分元件的方式，而是以元件在功能上的差异作为区分的准则。如通篇说明书及权利要求当中所提及的“包含”或“包括”为一开放式用语，故其应被理解成“包括但不限定于”。后续将对实施本发明的较佳实施方式进行描述说明，但是所述说明是以说明书的一般原则为目的，并非用于限定本发明的范围。本发明的保护范围当根据其所附的权利要求所界定者为准。
通过以上的实施方式的描述可知，本领域的技术人员可以清楚地了解到本发明可借助软件加必需的通用硬件平台的方式来实现。基于这样的理解， 本发明的技术方案本质上或者说对现有技术做出贡献的部分可以以软件产品的形式体现出来，该计算机软件产品可以存储在存储介质中，如ROM/RAM、磁碟、光盘等，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)执行本发明各个实施方式或者实施方式的某些部分所述的方法。
本发明可用于众多通用或专用的计算系统环境或配置中，例如：个人计算机、服务器计算机、手持设备或便携式设备、平板型设备、多处理器系统、基于微处理器的系统、置顶盒、可编程的消费电子设备、网络PC、小型计算机、大型计算机、包括以上任何系统或设备的分布式计算环境等等。
本发明可以在由计算机执行的计算机可执行指令的一般上下文中描述，例如程序模块。一般地，程序模块包括执行特定任务或实现特定抽象数据类型的例程、程序、对象、组件、数据结构等等。也可以在分布式计算环境中实践本发明，在这些分布式计算环境中，由通过通信网络而被连接的远程处理设备来执行任务。在分布式计算环境中，程序模块可以位于包括存储设备在内的本地和远程计算机存储介质中。
在本说明书的描述中，参考术语“一个实施例”、“示例”、“具体示例”等的描述意指结合该实施例或示例描述的具体特征、结构、材料或者特点包含于本发明的至少一个实施例或示例中。在本说明书中，对上述术语的示意性表述不一定指的是相同的实施例或示例。而且，描述的具体特征、结构、材料或者特点可以在任何的一个或多个实施例或示例中以合适的方式结合。
另外，本发明各个实施例之间的技术方案可以相互结合，但是必须是以本领域普通技术人员能够实现为基础，当技术方案的结合出现相互矛盾或无法实现时应当认为这种技术方案的结合不存在，也不在本发明要求的保护范围之内。
在本发明所提供的几个实施例中，应该理解到，所揭示的装置和方法，也可以通过其它的方式实现。以上所描述的装置实施例仅仅是示意性的，例如，附图中的流程图和框图显示了根据本发明的多个实施例的装置、方法和计算机程序产品的可能实现的体系架构、功能和操作。在这点上，流程图或框图中的每个方框可以代表一个模块、程序段或代码的一部分，所述模块、程序段或代码的一部分包含一个或多个用于实现规定的逻辑功能的可执行指令。也应当注意，在有些作为替换的实现方式中，方框中所标注的功能也可以以不同于附图中所标注的顺序发生。例如，两个连续的方框实际上可以基本并行地执行，它们有时也可以按相反的顺序执行，由所涉及的功能而定。也要注意的是，框图和/或流程图中的每个方框、以及框图和/或流程图中的方框的组合，可以用执行规定的功能或动作的专用的基于硬件的系统来实现，或者可以用专用硬件与计算机指令的组合来实现。
另外，在本发明各个实施例中的各功能模块可以集成在一起形成一个独立的部分，也可以是各个模块单独存在，也可以两个或两个以上模块集成形成一个独立的部分。
所述功能如果以软件功能模块的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取存储介质中。基于这样的理解，本发明的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)执行本发明各个实施例所述方法的全部或部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(ROM，Read-Only Memory)、随机存取存储器(RAM，Random Access Memory)、磁碟或者光盘等各种可以存储程序代码的介质。需要说明的是，在本文中，诸如第一和第二等之类的关系术语仅仅用来将一个实体或者操作与另一个实体或操作区分开来，而不一定 要求或者暗示这些实体或操作之间存在任何这种实际的关系或者顺序。而且，术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系列要素的过程、方法、物品或者设备不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、物品或者设备所固有的要素。在没有更多限制的情况下，由语句“包括一个……”限定的要素，并不排除在包括所述要素的过程、方法、物品或者设备中还存在另外的相同要素。
本领域那些技术人员可以理解，可以对实施例中的设备中的模块进行自适应性地改变并且把它们设置在与该实施例不同的一个或多个设备中。可以把实施例中的模块或单元或组件组合成一个模块或单元或组件，以及此外可以把它们分成多个子模块或子单元或子组件。除了这样的特征和/或过程或者单元中的至少一些是相互排斥之外，可以采用任何组合对本说明书(包括伴随的权利要求、摘要和附图)中公开的所有特征以及如此公开的任何方法或者设备的所有过程或单元进行组合。除非另外明确陈述，本说明书(包括伴随的权利要求、摘要和附图)中公开的每个特征可以由提供相同、等同或相似目的的替代特征来代替。
此外，本领域的技术人员能够理解，尽管在此所述的一些实施例包括其它实施例中所包括的某些特征而不是其它特征，但是不同实施例的特征的组合意味着处于本发明的范围之内并且形成不同的实施例。例如，在下面的权利要求书中，所要求保护的实施例的任意之一都可以以任意的组合方式来使用。
本发明的各个部件实施例可以以硬件实现，或者以在一个或者多个处理器上运行的软件模块实现，或者以它们的组合实现。本领域的技术人员应当理解，可以在实践中使用微处理器或者数字信号处理器(DSP)来实现根据本发明实施例的分发消息的设备中的一些或者全部部件的一些或者全部功能。本 发明还可以实现为用于执行这里所描述的方法的一部分或者全部的设备或者装置程序(例如，计算机程序和计算机程序产品)。这样的实现本发明的程序可以存储在计算机可读介质上，或者可以具有一个或者多个信号的形式。这样的信号可以从因特网网站上下载得到，或者在载体信号上提供，或者以任何其他形式提供。
最后应说明的是：以上各实施例仅用以说明本发明的技术方案，而非对其限制；尽管参照前述各实施例对本发明进行了详细的说明，本领域的普通技术人员应当理解：其依然可以对前述各实施例所记载的技术方案进行修改，或者对其中部分或者全部技术特征进行等同替换；而这些修改或者替换，并不使相应技术方案的本质脱离本发明各实施例技术方案的范围。

Claims (10)

  1. 一种恶劣天气下停车场所推荐方法，其特征在于，具体包括：
    获取车辆的位置信息、路线信息和人员信息，并查询当前的天气情况；
    对车辆出行进行风险评估，判断是否有避险需求；
    根据天气情况危险等级并结合车辆的实际情况，进行避险推荐；
    根据避险推荐的结果进行智能决策，寻找适于避险的停车场所；
    通过智能终端与用户进行智能交互，执行智能决策结果，或根据用户指令，重新进行避险推荐和智能决策。
  2. 根据权利要求1所述的恶劣天气下停车场所推荐方法，其特征在于，所述人员信息具体包括：车内人员数量、车内人员年龄、乘客驾驶车辆的历史信息。
  3. 根据权利要求1所述的恶劣天气下停车场所推荐方法，其特征在于，判断存在避险需求，则根据危险的类型、影响程度以及严重程度划分危险等级，按照危险等级提供对应不同的避险推荐服务。
  4. 根据权利要求1所述的恶劣天气下停车场所推荐方法，其特征在于，根据避险推荐的结果进行智能决策，查询适于避险的停车场所，具体包括：停车场、酒店、公共交通停靠站。
  5. 根据权利要求1所述的恶劣天气下停车场所推荐方法，其特征在于，所述通过智能终端与用户进行智能交互，具体为：通过语音播报，屏幕显示天气或导航线路的方式，告知用户避险推荐的原因和方法，通过智能交互的结果，执行智能决策结果，或根据用户指令，重新进行避险推荐和智能决策。
  6. 根据权利要求1所述的恶劣天气下停车场所推荐方法，其特征在于，
    所述恶劣天气的类型包括：风、云、雾、雨、闪、雪、霜、雷、雹、霾；
    所述天气情况危险等级分为5级，1级为最轻微的天气情况，5级为最恶劣的天气情况。
  7. 根据权利要求1所述的恶劣天气下停车场所推荐方法，其特征在于，所述查询当前的天气情况，具体为：在车辆启动时，导航模块每隔半小时对天气数据接口进行访问。
  8. 一种恶劣天气下停车场所推荐系统，其特征在于，具体包括：
    车辆信息及天气情况查询模块，用于获取车辆的位置信息、路线信息和人员信息，并查询当前的天气情况；
    车辆出行风险评估模块，用于对车辆出行进行风险评估，判断是否有避险需求；
    避险推荐推送模块，用于根据天气情况危险等级并结合车辆的实际情况，进行避险推荐；
    避险场所智能决策模块，用于根据避险推荐的结果进行智能决策，寻找适于避险的停车场所；
    智能终端交互模块，用于通过智能终端与用户进行智能交互，执行智能决策结果，或根据用户指令，重新进行避险推荐和智能决策。
  9. 一种电子设备，其特征在于，包括：处理器、通信接口、存储器和通信总线，其中，处理器，通信接口，存储器通过通信总线完成相互间的通信；所述存储器中存储有计算机程序，当所述计算机程序被所述处理器执行时，使得所述处理器执行权利要求1至7中任一项所述方法的步骤。
  10. 一种计算机可读存储介质，其特征在于，其存储有可由电子设备执行的计算机程序，当所述计算机程序在所述电子设备上运行时，使得所述电子设备执行权利要求1至7中任一项所述方法的步骤。
PCT/CN2023/088953 2022-08-18 2023-04-18 一种恶劣天气下停车场所推荐方法、系统、电子设备和存储介质 WO2024037009A1 (zh)

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