CN110949409A - Vehicle-based driving processing method, device and system - Google Patents
Vehicle-based driving processing method, device and system Download PDFInfo
- Publication number
- CN110949409A CN110949409A CN201911301140.1A CN201911301140A CN110949409A CN 110949409 A CN110949409 A CN 110949409A CN 201911301140 A CN201911301140 A CN 201911301140A CN 110949409 A CN110949409 A CN 110949409A
- Authority
- CN
- China
- Prior art keywords
- vehicle
- information
- dangerous
- driver
- driving
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
- B60W50/08—Interaction between the driver and the control system
- B60W50/14—Means for informing the driver, warning the driver or prompting a driver intervention
Landscapes
- Engineering & Computer Science (AREA)
- Automation & Control Theory (AREA)
- Human Computer Interaction (AREA)
- Transportation (AREA)
- Mechanical Engineering (AREA)
- Traffic Control Systems (AREA)
Abstract
The invention provides a vehicle-based driving processing method, a device and a system, wherein the method comprises the following steps: acquiring a running path of a vehicle and/or peripheral information of the vehicle in a running process; determining whether the vehicle is in a dangerous state or not according to the driving path and/or the peripheral information of the vehicle in the driving process; and generating a reminding message when the vehicle is determined to be in the dangerous state. The vehicle related data visualization, consistency and accuracy are realized, and the vehicle driving reminding is realized efficiently and comprehensively. The occupied data storage space is small, and the processing speed is high.
Description
Technical Field
The invention relates to the technical field of vehicle networking, in particular to a vehicle-based driving processing method, device and system.
Background
With the rapid development of the internet, the internet of vehicles is widely applied in the field of vehicles, and can be an interactive network formed by information such as vehicle positions, speeds and routes, the vehicles can complete the collection of self environment and state information through devices such as a GPS, an FRID, a sensor and a camera image processing device, and various information corresponding to all vehicles is transmitted to a large-scale database through the internet technology to realize the processing of a large amount of vehicle information, so that the prediction of the vehicle running state can be output.
In the prior art, a conventional data prediction method may be adopted, for example, abnormal data is found based on the input of relational data, a statistical algorithm is adopted, or a rule is artificially learned, and then, through manual verification, the successfully verified data is added to the rule as a new sample to strengthen the model for prediction. In the prior art, a big data prediction method can be adopted, and a batch processing or real-time stream processing framework stores processed data in a distributed manner based on structured or unstructured big data input; adopting a large-scale machine cluster; running distributed codes through rules made by statistics or human experience or machine learning, and finding abnormal data from distributed storage data; and manual verification is needed only in necessary scenes, automatic verification is realized in most cases, and data which are successfully verified are used as new samples and added into the rules to strengthen the model for prediction.
However, in any of the above prediction methods, the correlation between data is poor, the accuracy of data reading and use is not high, and in addition, the huge data amount not only results in long storage time, but also increases the cost.
Disclosure of Invention
The invention provides a vehicle-based driving processing method, device and system, which are used for realizing visualization, continuity and accuracy of vehicle-related data and efficiently and comprehensively realizing vehicle driving reminding. The occupied data storage space is small, and the processing speed is high.
In a first aspect, an embodiment of the present invention provides a vehicle-based driving processing method, including:
acquiring a running path of a vehicle and/or peripheral information of the vehicle in a running process;
determining whether the vehicle is in a dangerous state or not according to the driving path and/or the peripheral information of the vehicle in the driving process;
and generating a reminding message when the vehicle is determined to be in the dangerous state.
In one possible design, the determining whether the vehicle is in a dangerous state according to the traveling path and/or the surrounding information of the vehicle during traveling includes:
acquiring whether the area of the driving path way comprises a dangerous area or not according to the driving path;
and determining that the vehicle is in a dangerous state when the vehicle is determined to run into the dangerous area or the vehicle runs into the dangerous area within a preset time period.
In one possible design, the surrounding information of the vehicle includes: information of other vehicles present within a preset range centered on the vehicle; determining whether the vehicle is in a dangerous state according to the driving path and/or the surrounding information of the vehicle in the driving process, including:
identifying whether dangerous vehicles exist in the other vehicles according to the information of the other vehicles;
determining that the vehicle is in a dangerous state when the dangerous vehicle is determined.
In one possible design, the information of the other vehicles at least includes one or a combination of the following:
license plate number, model number of vehicle, vehicle color, vehicle travel track, and facial features of the driver in the vehicle.
In one possible design, when the information of the other vehicles includes facial features of a driver in the vehicle, the identifying whether there is a dangerous vehicle in the other vehicles according to the information of the other vehicles includes:
determining whether the driver is a dangerous driver or not according to the facial features of the driver in the vehicle;
and when the driver is determined to be a dangerous driver, identifying that the vehicle driven by the driver is a dangerous vehicle.
In one possible design, the determining whether the vehicle is in a dangerous state according to the traveling path and/or the surrounding information of the vehicle during traveling includes:
determining whether the vehicle is in a preset scene or not according to the peripheral information of the vehicle in the driving process;
determining that the vehicle is in a dangerous state when the vehicle is determined to be in a preset scene;
the peripheral information of the vehicle comprises one or a combination of the following information: weather information and information of the road section where the weather information is located.
In one possible design, further comprising:
when the vehicle driving path or the vehicle reaches an infrastructure area, acquiring information of the infrastructure area and prompting the information to a driver of the vehicle;
alternatively, the first and second electrodes may be,
if the vehicle driving route or the vehicle driving route reaches the infrastructure area, acquiring the time of the vehicle driving to the infrastructure area; and generating a reminding message to remind a driver of the vehicle when the time is determined to be within a preset time period.
In one possible design, further comprising:
when the cell area to which the destination address of the vehicle driving path belongs is determined, acquiring related information inside and/or around the cell area;
and determining the parking position of the vehicle according to the related information inside and/or around the cell area.
In one possible design, further comprising:
acquiring health parameters of all components of the vehicle, and determining the state of the vehicle according to the health parameters;
and generating a reminding message when the state of the vehicle is determined to be the unhealthy state.
In a second aspect, an embodiment of the present invention provides a processing apparatus based on vehicle driving, including:
the system comprises an acquisition module, a processing module and a control module, wherein the acquisition module is used for acquiring a driving path of a vehicle and/or peripheral information of the vehicle in the driving process;
the determining module is used for determining whether the vehicle is in a dangerous state or not according to the running path and/or the peripheral information of the vehicle in the running process;
and the reminding module is used for generating a reminding message when the vehicle is determined to be in the dangerous state.
In one possible design, the determining module is specifically configured to:
acquiring whether the area of the driving path way comprises a dangerous area or not according to the driving path;
and determining that the vehicle is in a dangerous state when the vehicle is determined to run into the dangerous area or the vehicle runs into the dangerous area within a preset time period.
In one possible design, the surrounding information of the vehicle includes: information of other vehicles present within a preset range centered on the vehicle; the determining module is specifically configured to:
identifying whether dangerous vehicles exist in the other vehicles according to the information of the other vehicles;
determining that the vehicle is in a dangerous state when the dangerous vehicle is determined.
In one possible design, the information of the other vehicles at least includes one or a combination of the following:
license plate number, vehicle model, vehicle color, vehicle travel track, and facial features of the driver in the vehicle.
In one possible design, when the information of the other vehicles includes facial features of a driver in the vehicle, the identifying whether there is a dangerous vehicle in the other vehicles according to the information of the other vehicles includes:
determining whether the driver is a dangerous driver or not according to the facial features of the driver in the vehicle;
and when the driver is determined to be a dangerous driver, identifying that the vehicle driven by the driver is a dangerous vehicle.
In one possible design, the determining module is specifically configured to:
determining whether the vehicle is in a preset scene or not according to the peripheral information of the vehicle in the driving process;
determining that the vehicle is in a dangerous state when the vehicle is determined to be in a preset scene;
the peripheral information of the vehicle comprises one or a combination of the following information: weather information and information of the road section where the weather information is located.
In one possible design, further comprising:
when the vehicle driving path is determined to pass through or reach an infrastructure area, acquiring information of the infrastructure area and prompting the information to a driver of the vehicle;
alternatively, the first and second electrodes may be,
if the vehicle driving route or the vehicle driving route reaches the infrastructure area, acquiring the time of the vehicle driving to the infrastructure area; and generating a reminding message to remind a driver of the vehicle when the time is determined to be within a preset time period.
In one possible design, further comprising:
when the cell area to which the destination address of the vehicle driving path belongs is determined, acquiring related information inside and/or around the cell area;
and determining the parking position of the vehicle according to the related information inside and/or around the cell area.
In one possible design, further comprising:
acquiring health parameters of all parts of the vehicle, and determining the state of the vehicle according to the health parameters;
and generating a reminding message when the state of the vehicle is determined to be the unhealthy state.
In a third aspect, an embodiment of the present invention provides a vehicle-based travel processing system including: the device comprises a memory and a processor, wherein the memory stores executable instructions of the processor; wherein the processor is configured to perform the vehicle-based travel processing method of any one of the first aspect via execution of the executable instructions.
In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium on which a computer program is stored, the program, when executed by a processor, implementing the vehicle-based travel processing method according to any one of the first aspect.
The invention provides a vehicle-based driving processing method, a device and a system, wherein the method comprises the following steps: acquiring a running path of a vehicle and/or peripheral information of the vehicle in a running process; determining whether the vehicle is in a dangerous state or not according to the driving path and/or the peripheral information of the vehicle in the driving process; and generating a reminding message when the vehicle is determined to be in the dangerous state. The vehicle related data visualization, consistency and accuracy are realized, and the vehicle driving reminding is realized efficiently and comprehensively. The occupied data storage space is small, and the processing speed is high.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a schematic diagram of an exemplary application scenario of the present invention;
FIG. 2 is a schematic diagram of a storage structure of a vehicle-based driving process according to the present invention;
fig. 3 is a flowchart of a vehicle-based driving processing method according to an embodiment of the present invention;
fig. 4 is a flowchart of a vehicle-based driving processing method according to a second embodiment of the present invention;
fig. 5 is a flowchart of a vehicle-based driving processing method according to a third embodiment of the present invention;
fig. 6 is a schematic structural diagram of a vehicle-based travel processing apparatus according to a fourth embodiment of the present invention;
fig. 7 is a schematic structural diagram of a vehicle-based travel processing system according to a fifth embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terms "first," "second," "third," "fourth," and the like in the description and in the claims, as well as in the drawings, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are, for example, capable of operation in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
The following describes the technical solutions of the present invention and how to solve the above technical problems with specific embodiments. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments. Embodiments of the present invention will be described below with reference to the accompanying drawings.
Fig. 1 is a schematic view of a typical application scenario of the present invention, as shown in fig. 1, a vehicle 11 may be influenced by various factors such as a state of the vehicle itself, a road state, weather, other vehicles, other vehicle drivers, and the like during a driving path and/or a driving process, and affect safe driving of the vehicle driver, and as road traffic vehicles become more, a road driving situation is complicated, and in order to ensure comfort and even safety during the driving process of the vehicle, a prompt message needs to be provided for the vehicle driver at any time, so as to improve experience of the vehicle user.
Referring to fig. 2, fig. 2 is a schematic diagram of a schematic diagram storage structure of a vehicle-based driving process according to the present invention, as shown in fig. 2, a large amount of data related to vehicle driving is stored in a storage manner such as a diagram through internet information, a large amount of data can be gathered to form a knowledge base, and the association between the data can be visually and simply displayed, so that not only can the high speed of data acquisition be realized, but also the complex and diverse association between the data can be displayed to quickly acquire the data with the association, and highly refined feature identifiers (such as portrait tags) of the data can be stored to realize wider data acquisition. Specifically, the method comprises the steps of acquiring a running path of a vehicle and/or peripheral information of the vehicle in the running process; determining whether the vehicle is in a dangerous state or not according to the running path and/or the peripheral information of the vehicle in the running process; and generating a reminding message when the vehicle is determined to be in the dangerous state. The vehicle related data visualization, consistency and accuracy are realized, and the vehicle driving reminding is realized efficiently and comprehensively. The occupied data storage space is small, and the processing speed is high. The following description will be made in detail with a vehicle processing system as an execution subject, wherein the vehicle processing system includes a vehicle sensor, a camera image processing device, and the like, as well as a GPS, a wireless communication network, and the like.
Fig. 3 is a flowchart of a vehicle-based driving processing method according to a first embodiment of the present invention, and as shown in fig. 3, the method in this embodiment may include:
s201, acquiring the running path of the vehicle and/or the peripheral information of the vehicle in the running process.
In an alternative embodiment, the peripheral information of the vehicle includes information of other vehicles present within a preset range centered on the vehicle. In an alternative embodiment, the surrounding information of the vehicle includes weather information, information of a road section where the vehicle is located, and a combination thereof.
In this embodiment, the vehicle processing system may obtain the peripheral information of the vehicle, such as information of other vehicles, weather information, information of a road segment where the vehicle is located, and the like, during the driving route and/or the driving process of the vehicle, and further obtain the reminding message when the vehicle is determined to be in a dangerous state, so as to remind a driver of the vehicle of a dangerous situation that may occur during the driving route or the driving process, thereby ensuring the driving safety of the vehicle.
S202, determining whether the vehicle is in a dangerous state or not according to the running path and/or the peripheral information of the vehicle in the running process.
Specifically, the vehicle processing system may obtain whether a dangerous area is included in an area of the travel path route according to the travel path; and determining that the vehicle is in a dangerous state when the vehicle is determined to run into the dangerous area or the vehicle runs into the dangerous area within a preset time period. The dangerous area refers to an accident frequent area or an area where dangerous vehicles frequently appear. In an alternative embodiment, the dangerous area is matched with the map data through the graphic pattern storage data, and the coordinate range of the accident frequent area is identified. And when the vehicle is determined to enter the dangerous area in the running path and/or the running process, or the vehicle is determined to enter the dangerous area in a preset time period, determining that the vehicle is in a dangerous state, and generating a reminding message.
If the dangerous vehicle exists in the preset range taking the vehicle as the center in the running process of the vehicle; and if the dangerous vehicle is identified to appear in the preset range, generating alarm information. In this embodiment, the preset range is not limited, for example, a circular area with the vehicle as a center and a radius of 100 meters is used as the preset range.
Preferably, the information of other vehicles appearing within the preset range is acquired, and whether dangerous vehicles exist in the other vehicles is determined according to the information of the other vehicles. The information of the other vehicles includes at least: a license plate number; or license plate number and vehicle color; a vehicle travel track; license plate number and vehicle driving track. The dangerous vehicles can include vehicles which are frequently paid by traffic, dangerous driving and the like, and can be judged by the image identifiers such as colors, vehicle types or license plate numbers of the vehicles, preferably by adopting the image identifiers of the license plate numbers; porcelain-hit vehicles may also be included.
In an alternative embodiment, the dangerous vehicle can be identified as a dangerous vehicle by using various vehicle images stored with graphic big data. Dangerous vehicles are identified, for example, from photographs taken of cases revealed by traffic authorities or passersby revealed on the network, recording characteristics of vehicles that are often driven at risk, such as vehicle type, current color, historical color (repainting can record historical color), license plate number, and frequently occurring areas and predetermined time periods (e.g., late-night vehicles). For example, the vehicle camera is matched to capture continuous images, match the operation of the vehicle, correlate road conditions and judge the vehicle which has collided with the porcelain. If the vehicle has a case bottom, or the vehicle driver is suspected to have a porcelain collision ganging through an interpersonal relationship network, or the vehicle driver is in a frequent porcelain collision event area, the vehicle is judged to be a dangerous vehicle. And for example, matching with a vehicle camera, judging that the vehicle is a dangerous vehicle by acquiring the vehicle model, for example, determining that the vehicle is a heavy truck or the like.
In an alternative embodiment, whether a dangerous area is included in the area of the driving path route is obtained according to the driving path, and the driver can be determined to be a dangerous driver according to the facial features of the driver of the other vehicle, so that the dangerous vehicle is identified, and the vehicle is determined to be in a dangerous state in the other vehicle.
Acquiring head images of drivers in other vehicles around the vehicle to acquire head image information of the drivers; determining whether the driver is a dangerous driver or not according to the head portrait information of the driver; and when the driver is determined to be a dangerous driver, generating alarm information. The specific matching vehicle camera captures the face appearance or whole body image of other vehicle drivers, and relevant portrait information is searched in the graphic database, so that other vehicle drivers with labels of traffic offenders or other vehicle drivers with labels touching the bottom of a porcelain case can be obtained, and the drivers are determined to be dangerous drivers, and alarm information is generated.
Preferably, the method further comprises the following steps: acquiring current surrounding scene information of a vehicle; and when the driver is determined to be a dangerous driver and the current surrounding scene information is a preset scene, generating alarm information. Determining whether the vehicle is in a preset scene or not according to the peripheral information of the vehicle in the driving process; and when the vehicle is determined to be in the preset scene, determining that the vehicle is in a dangerous state. The peripheral information of the vehicle comprises one or a combination of the following information: weather information and information of the road section where the weather information is located. The vehicle processing system may determine whether the vehicle is in a preset scene according to the surrounding information of the vehicle during driving, and determine that the vehicle is in a dangerous state when determining that the vehicle is in the preset scene (for example, a preset scene related to weather or a preset scene related to a road section where the vehicle is located during driving).
And S203, generating a reminding message when the vehicle is determined to be in the dangerous state.
In this embodiment, the vehicle processing system determines whether the vehicle is in a dangerous state by acquiring the information around the vehicle in the driving path and/or the driving process of the vehicle, and generates the reminding message when determining that the vehicle is in the dangerous state, so as to provide an accurate and reliable reminding message for a driver of the vehicle, thereby ensuring the driving safety of the vehicle.
In an alternative embodiment, the vehicle processing system may also determine the vehicle travel path or arrival at an infrastructure area (e.g., high speed vehicle service area, etc.), or determine that the current driving time is within a preset time period, and generate a reminder message to remind the driver of the vehicle. In an alternative implementation, the vehicle processing system may determine the parking location of the vehicle based on the destination address home cell area of the vehicle travel path. In another alternative embodiment, the vehicle processing system may determine that the status of the vehicle is unhealthy based on health parameters of various components of the vehicle and generate the alert message.
In the embodiment, the vehicle processing system can comprehensively and continuously acquire the vehicle running path and/or the peripheral information in the running process in the schema database, and realize quick and accurate associated data reading, so that whether the vehicle is in a dangerous state or not is determined, the reminding message is generated, the safety of vehicle running can be ensured, and the experience of a vehicle user can be improved.
With reference to the foregoing embodiment, fig. 4 is a flowchart of a vehicle-based driving processing method according to a second embodiment of the present invention, and as shown in fig. 4, this embodiment mainly relates to a specific process of determining whether a vehicle is in a dangerous state according to a driving route and/or peripheral information of the vehicle during driving, and may include:
s301, identifying whether dangerous vehicles exist in other vehicles according to the information of the other vehicles.
Specifically, determining whether the vehicle is in a dangerous state according to the running path and/or the surrounding information of the vehicle in the running process comprises identifying whether dangerous vehicles exist in other vehicles according to the information of other vehicles, and determining that the vehicle is in the dangerous state when the dangerous vehicles are determined. The information of the periphery of the vehicle includes information of other vehicles appearing in a preset range with the vehicle as a center, and in an optional embodiment, the information of other vehicles at least includes one or a combination of the following: license plate number, vehicle model, vehicle color, vehicle travel track, and facial features of the driver in the vehicle. In another optional embodiment, when the information of the other vehicle includes facial features of a driver in the vehicle, it may be further determined whether the driver is a dangerous driver according to the facial features of the driver in the vehicle, and when the driver is determined to be a dangerous driver, it is identified that the vehicle driven by the driver is a dangerous vehicle, and it is further determined that the vehicle is in a dangerous state.
For example, the dangerous vehicles may include vehicles which are frequently paid for traffic, dangerous driving, etc., and may be determined by image identifiers such as colors, vehicle types, license plate numbers, etc. of the vehicles, preferably by using the image identifiers of the license plate numbers; porcelain-hit vehicles may also be included. In an alternative embodiment, the dangerous vehicle can be identified as a dangerous vehicle by using various vehicle images stored with graphic big data. For example, according to the case disclosed by the traffic law or the photos taken by passers-by disclosed on the network, the characteristics of the vehicles which are frequently driven at risk, such as the type of the vehicle, the current color, the historical color (the historical color can be recorded by repainting), the license plate number, and the frequently-occurring region and the preset time period (such as a midnight violent vehicle) are recorded. A dangerous vehicle is identified. For example, the vehicle camera is matched to capture continuous images, match the operation of the vehicle, correlate road conditions and judge the vehicle which has collided with the porcelain. If the vehicle has a case bottom, or the vehicle driver is suspected to have a porcelain collision ganging through an interpersonal relationship network, or the vehicle driver is in a frequent porcelain collision event area, the vehicle is judged to be a dangerous vehicle. For another example, the vehicle processing system captures facial features of other vehicle drivers or whole body images by using the vehicle camera, and searches relevant portrait information in the graphic database, so as to possibly obtain other vehicle drivers with labels of traffic offenders or obtain other vehicle drivers with labels of hit-to-ground-of-china cases, and further determine that the drivers are dangerous drivers, so as to generate alarm information.
In the embodiment, the vehicle processing system can comprehensively and continuously acquire the vehicle running path and/or the peripheral information in the running process in the schema database, and realize quick and accurate associated data reading, so that whether the vehicle is in a dangerous state or not is determined, the reminding message is generated, the safety of vehicle running can be ensured, and the experience of a vehicle user can be improved.
S302, when the dangerous vehicle is determined, the vehicle is determined to be in a dangerous state.
In this embodiment, the vehicle processing system generates the reminding message when determining that the vehicle is in the dangerous state, so as to provide an accurate and reliable reminding message for a driver of the vehicle, thereby ensuring the safety of vehicle driving.
With reference to the first embodiment, fig. 5 is a flowchart of a vehicle-based driving processing method according to a third embodiment of the present invention, as shown in fig. 5, this embodiment mainly relates to a specific process for determining that a vehicle is in a dangerous state according to a driving route and/or peripheral information of the vehicle during driving, and may include:
s401, determining whether the vehicle is in a preset scene or not according to the peripheral information of the vehicle in the driving process.
The specific vehicle surrounding information may include one or a combination of weather information and information on a road section where the vehicle is located.
In this embodiment, whether the vehicle is in a preset scene is determined according to the surrounding information of the vehicle during driving, so as to determine whether the vehicle is in a dangerous state. For example, according to weather information: if it is determined that the vehicle is in the preset scene, it may be determined that the vehicle is in the preset scene to determine that the vehicle is in a dangerous state. For another example, according to the located link information: when the current vehicle is in a road section such as road construction, the vehicle can be determined to be in a preset scene, and then the vehicle can be determined to be in a dangerous state. For another example, according to whether the weather information and the located road information are the information of a snowstorm and frozen road, the vehicle can be determined to be in a preset scene, and then the vehicle can be determined to be in a dangerous state. For another example, according to the located road section information, when the current vehicle is in the high speed road section information, it may be determined that the vehicle is in the preset scene, and then it may be determined that the vehicle is in a dangerous state.
The preset scene is not specifically limited in this embodiment. The weather information may include severe weather such as heavy snow, freezing, low temperature, strong wind (sand blowing), high temperature, heavy rainfall, continuous rainfall, and the like. The located section information may include a sharply curved section, a steep slope section, a continuous downhill section with poor line of sight distance, a road test critical section, and the like.
S402, determining that the vehicle is in a dangerous state when the vehicle is determined to be in a preset scene.
In combination with the above example, when it is determined that the vehicle is in the preset scene, it is determined that the vehicle is in a dangerous state.
The schema storage database can also store infrastructure area information, cell information and vehicle health factor information, and all have corresponding portrait identification, and can intuitively and continuously display the relevance among data.
In an optional embodiment, the method further comprises the steps of obtaining information of the infrastructure area and prompting a driver of the vehicle when determining the driving path of the vehicle or reaching the infrastructure area; or if the vehicle driving route or the vehicle reaches the infrastructure area is determined, acquiring the time of the vehicle driving to the infrastructure area; and generating a reminding message to remind a driver of the vehicle within a preset time period at the determined time.
The information of the specific infrastructure area may include service information, price information, environmental information, and surrounding parking data information, etc. The preset time period may include a peak time period, a busy time period, and the like. The present embodiment is not particularly limited.
In this embodiment, by aggregating the information of infrastructure areas from different sources through the schema database, the vehicle processing system can obtain information such as service, price, environment and the like from different angles for a gas station, a vehicle repair point, a vehicle wash point, a parking lot and the like to determine the driving route of the vehicle or reach the infrastructure area, thereby obtaining the information of the infrastructure area and prompting the driver of the vehicle. For example, when the vehicle arrives at a gas station in a vehicle service area, the driver of the vehicle is prompted by acquiring comparative price information such as gasoline and the like and acquiring information such as the lowest oil price, so that a charging trap is avoided. For example, when the vehicle driving route or the vehicle reaches the infrastructure area is determined, the time of the vehicle driving to the infrastructure area, such as the information of the environment of the high-speed service area, is acquired, the time of the vehicle driving to the service area environment is acquired, whether the event is within a preset time period, such as a busy time period of spring back to the country, is determined, and a reminding message is generated to remind the driver of the vehicle, so that the crowded time is avoided.
In an optional embodiment, when determining that the destination address of the vehicle driving path belongs to a cell area, acquiring relevant information inside and/or around the cell area;
and determining the parking position of the vehicle according to the related information inside and/or around the cell area.
In this embodiment, data from different sources are collected through the schema database, and the vehicle processing system can indirectly analyze the entrance rate of the residential area, the owner classification, whether parking is convenient or not from multiple dimensions through comments such as network resources, cost and the like according to the daily life rates of different vehicles and the classification of the vehicles. For example, when the vehicle processing system determines that the destination address of the vehicle driving path belongs to a cell area, the related information inside and/or around the cell area, such as an area where parking is suddenly full near the home cell, an area where parking spaces are always present near the home cell, an area where audi parking is most near the home cell, an area where commercial persons park in the vicinity of the home cell, and the like, is acquired to determine the parking position of the vehicle, which greatly facilitates the parking of the vehicle driver, and the like.
In an optional embodiment, further comprising: acquiring health parameters of all parts of the vehicle, and determining the state of the vehicle according to the health parameters;
and when the state of the vehicle is in the unhealthy state, generating a reminding message.
In this embodiment, data from different sources are collected through the schema database, and the vehicle processing system can combine the influence of factors such as nature, human, weather and the like on the health condition of the parts according to the technical indexes issued by the authorities, general part indexes downloaded from encyclopedia, community comments and the like for different vehicle types. And the health of the different parts is weighted on the health of the vehicle. The health parameters of all components of the vehicle are acquired, the state of the vehicle is determined according to the health parameters and the education material data serving as the vehicle driver, if the state of the vehicle is in an unhealthy state, a reminding message can be generated, the current health state of the vehicle is displayed for the vehicle driver, or the state of the vehicle is determined to be in an unhealthy state according to daily improper use of the vehicle driver, a reminding message is generated, and warning is given.
In the embodiment, the vehicle processing system can comprehensively and continuously acquire the vehicle running path and/or the peripheral information in the running process in the schema database, and realize quick and accurate associated data reading, so that whether the vehicle is in a dangerous state or not is determined, a reminding message is generated, the safety of vehicle running can be ensured, and the experience of a vehicle user can be improved.
Fig. 6 is a schematic structural diagram of a vehicle-based travel processing device according to a fourth embodiment of the present invention, and as shown in fig. 6, the vehicle-based travel processing device according to the present embodiment may include:
an obtaining module 51, configured to obtain a driving path of a vehicle and/or information about the periphery of the vehicle during driving;
the determining module 52 is used for determining whether the vehicle is in a dangerous state according to the running path and/or the surrounding information of the vehicle in the running process;
and the reminding module 53 is used for generating a reminding message when the vehicle is determined to be in the dangerous state.
In an alternative embodiment, the determining module 52 is specifically configured to:
acquiring whether the area of the driving path comprises a dangerous area or not according to the driving path;
and determining that the vehicle is in a dangerous state when the vehicle is determined to run into the dangerous area or the vehicle runs into the dangerous area within a preset time period.
In an alternative embodiment, the surrounding information of the vehicle includes: information of other vehicles present within a preset range centered on the vehicle; the determining module is specifically configured to:
identifying whether dangerous vehicles exist in other vehicles according to the information of the other vehicles;
when a dangerous vehicle is determined, it is determined that the vehicle is in a dangerous state.
In an alternative embodiment, the information of other vehicles at least includes one or a combination of the following:
license plate number, vehicle model, vehicle color, vehicle travel track, and facial features of the driver in the vehicle.
In an alternative embodiment, when the information of the other vehicles includes facial features of a driver in the vehicle, identifying whether there is a dangerous vehicle in the other vehicles according to the information of the other vehicles includes:
determining whether the driver is a dangerous driver or not according to the facial features of the driver in the vehicle;
when the driver is determined to be a dangerous driver, the vehicle driven by the driver is recognized as a dangerous vehicle.
In an alternative embodiment, the determining module 52 is specifically configured to:
determining whether the vehicle is in a preset scene or not according to the peripheral information of the vehicle in the driving process;
when the vehicle is determined to be in the preset scene, determining that the vehicle is in a dangerous state;
the peripheral information of the vehicle comprises one or a combination of the following information: weather information and information of the road section where the weather information is located.
In an optional embodiment, further comprising:
when the vehicle driving route is determined to pass through or reach the infrastructure area, acquiring information of the infrastructure area and prompting the information to a driver of the vehicle;
alternatively, the first and second electrodes may be,
if the vehicle driving route or the vehicle driving route reaches the infrastructure area, acquiring the time of the vehicle driving to the infrastructure area; and generating a reminding message to remind a driver of the vehicle within a preset time period at the determined time.
In an optional embodiment, further comprising:
when the cell area to which the destination address of the vehicle driving path belongs is determined, acquiring relevant information inside and/or around the cell area;
and determining the parking position of the vehicle according to the related information inside and/or around the cell area.
In an optional embodiment, further comprising:
acquiring health parameters of all parts of the vehicle, and determining the state of the vehicle according to the health parameters;
and generating a reminding message when the state of the vehicle is determined to be the unhealthy state.
The vehicle-based driving processing apparatus of this embodiment may execute the technical solution in the method shown in fig. 3, and the specific implementation process and technical principle thereof refer to the related description in the method shown in fig. 3, and are not described herein again.
Fig. 7 is a schematic structural diagram of a vehicle-based driving processing system according to a fifth embodiment of the present invention, and as shown in fig. 7, a vehicle-based driving processing system 60 according to this embodiment may include: a processor 61 and a memory 62.
A memory 62 for storing a computer program (such as an application program, a function module, and the like that implement the above-described vehicle-based travel processing method), a computer instruction, and the like;
the computer programs, computer instructions, etc. described above may be stored in one or more memories 62 in partitions. And the above-mentioned computer program, computer instructions, data, etc. can be called by the processor 61.
A processor 61 for executing the computer program stored in the memory 62 to implement the steps of the method according to the above embodiments.
Reference may be made in particular to the description relating to the preceding method embodiment.
The processor 61 and the memory 62 may be separate structures or may be an integrated structure integrated together. When the processor 61 and the memory 62 are separate structures, the memory 62 and the processor 61 may be coupled by a bus 63.
The server in this embodiment may execute the technical solution in the method shown in fig. 3, and for the specific implementation process and the technical principle, reference is made to the relevant description in the method shown in fig. 3, which is not described herein again.
In addition, embodiments of the present application further provide a computer-readable storage medium, in which computer-executable instructions are stored, and when at least one processor of the user equipment executes the computer-executable instructions, the user equipment performs the above-mentioned various possible methods.
Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a general purpose or special purpose computer. An exemplary storage medium is coupled to the processor such the processor can read information from, and write information to, the storage medium. Of course, the storage medium may also be integral to the processor. The processor and the storage medium may reside in an ASIC. Additionally, the ASIC may reside in user equipment. Of course, the processor and the storage medium may reside as discrete components in a communication device.
Those of ordinary skill in the art will understand that: all or a portion of the steps of implementing the above-described method embodiments may be performed by hardware associated with program instructions. The program may be stored in a computer-readable storage medium. When executed, the program performs steps comprising the method embodiments described above; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (12)
1. A vehicle-based travel processing method, comprising:
acquiring a running path of a vehicle and/or peripheral information of the vehicle in a running process;
determining whether the vehicle is in a dangerous state or not according to the driving path and/or the peripheral information of the vehicle in the driving process;
and generating a reminding message when the vehicle is determined to be in the dangerous state.
2. The method according to claim 1, wherein the determining whether the vehicle is in a dangerous state according to the traveling path and/or the surrounding information of the vehicle during traveling includes:
acquiring whether the area of the driving path way comprises a dangerous area or not according to the driving path;
and determining that the vehicle is in a dangerous state when the vehicle is determined to run into the dangerous area or the vehicle runs into the dangerous area within a preset time period.
3. The method according to claim 1, wherein the surrounding information of the vehicle includes: information of other vehicles present within a preset range centered on the vehicle; determining whether the vehicle is in a dangerous state according to the driving path and/or the surrounding information of the vehicle in the driving process, including:
identifying whether dangerous vehicles exist in the other vehicles according to the information of the other vehicles;
determining that the vehicle is in a dangerous state when the dangerous vehicle is determined.
4. The method of claim 3, wherein the information of other vehicles comprises at least one or a combination of the following:
license plate number, vehicle model, vehicle color, vehicle travel track, and facial features of the driver in the vehicle.
5. The method of claim 4, wherein when the information of the other vehicles includes facial features of a driver in the vehicle, the identifying whether there is a dangerous vehicle in the other vehicles based on the information of the other vehicles comprises:
determining whether the driver is a dangerous driver or not according to the facial features of the driver in the vehicle;
and when the driver is determined to be a dangerous driver, identifying that the vehicle driven by the driver is a dangerous vehicle.
6. The method according to claim 1, wherein the determining whether the vehicle is in a dangerous state according to the traveling path and/or the surrounding information of the vehicle during traveling includes:
determining whether the vehicle is in a preset scene or not according to the peripheral information of the vehicle in the driving process;
determining that the vehicle is in a dangerous state when the vehicle is determined to be in a preset scene;
the peripheral information of the vehicle comprises one or a combination of the following information: weather information and information of the road section where the weather information is located.
7. The method of any of claims 1 to 6, further comprising:
when the vehicle driving path is determined to pass through or reach an infrastructure area, acquiring information of the infrastructure area and prompting the information to a driver of the vehicle;
alternatively, the first and second electrodes may be,
if the vehicle driving route or the vehicle driving route reaches the infrastructure area, acquiring the time of the vehicle driving to the infrastructure area; and generating a reminding message to remind a driver of the vehicle when the time is determined to be within a preset time period.
8. The method of any of claims 1 to 6, further comprising:
when the cell area to which the destination address of the vehicle driving path belongs is determined, acquiring related information inside and/or around the cell area;
and determining the parking position of the vehicle according to the related information inside and/or around the cell area.
9. The method of any of claims 1 to 6, further comprising:
acquiring health parameters of all parts of the vehicle, and determining the state of the vehicle according to the health parameters;
and generating a reminding message when the state of the vehicle is determined to be the unhealthy state.
10. A vehicle-based travel processing device, characterized by comprising:
the system comprises an acquisition module, a processing module and a control module, wherein the acquisition module is used for acquiring a driving path of a vehicle and/or peripheral information of the vehicle in the driving process;
the determining module is used for determining whether the vehicle is in a dangerous state or not according to the running path and/or the peripheral information of the vehicle in the running process;
and the reminding module is used for generating a reminding message when the vehicle is determined to be in the dangerous state.
11. A vehicle-based travel processing system, comprising: the device comprises a memory and a processor, wherein the memory stores executable instructions of the processor; wherein the processor is configured to perform the vehicle-based travel processing method of any of claims 1-9 via execution of the executable instructions.
12. A computer-readable storage medium on which a computer program is stored, characterized in that the program, when executed by a processor, implements the vehicle-based travel processing method according to any one of claims 1 to 9.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911301140.1A CN110949409A (en) | 2019-12-17 | 2019-12-17 | Vehicle-based driving processing method, device and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911301140.1A CN110949409A (en) | 2019-12-17 | 2019-12-17 | Vehicle-based driving processing method, device and system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN110949409A true CN110949409A (en) | 2020-04-03 |
Family
ID=69982060
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201911301140.1A Pending CN110949409A (en) | 2019-12-17 | 2019-12-17 | Vehicle-based driving processing method, device and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110949409A (en) |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102897127A (en) * | 2012-10-19 | 2013-01-30 | 杭州速景科技有限公司 | Safety pre-warning system for vehicle |
| CN103208205A (en) * | 2013-03-20 | 2013-07-17 | 北京航空航天大学 | Vehicle safety driving early warning method based on vehicle internet |
| CN103338974A (en) * | 2010-11-24 | 2013-10-02 | Bcs商业咨询服务私人有限公司 | Hazard warning system for vehicles |
| CN104590095A (en) * | 2015-01-06 | 2015-05-06 | 浙江工业大学 | Warning method for dangerous region in running process of large-sized vehicle and warning lamp system |
| CN105023394A (en) * | 2015-06-23 | 2015-11-04 | 南京理工大学 | Dangerous driving reminding and controlling method based on portable intelligent device |
| CN205131082U (en) * | 2015-09-23 | 2016-04-06 | 张坤 | On -vehiclely prevent bumping porcelain device |
| CN106080609A (en) * | 2016-06-30 | 2016-11-09 | 深圳市赛格导航科技股份有限公司 | A kind of method and system of safe driving based on ADAS module |
| CN106128140A (en) * | 2016-08-11 | 2016-11-16 | 江苏大学 | Car networked environment down train service active perception system and method |
| TW201738828A (en) * | 2016-04-20 | 2017-11-01 | Zebred Network Technology Co Ltd | Message pushing method, device, and apparatus |
| WO2018092265A1 (en) * | 2016-11-18 | 2018-05-24 | 三菱電機株式会社 | Driving assistance device and driving assistance method |
-
2019
- 2019-12-17 CN CN201911301140.1A patent/CN110949409A/en active Pending
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103338974A (en) * | 2010-11-24 | 2013-10-02 | Bcs商业咨询服务私人有限公司 | Hazard warning system for vehicles |
| CN102897127A (en) * | 2012-10-19 | 2013-01-30 | 杭州速景科技有限公司 | Safety pre-warning system for vehicle |
| CN103208205A (en) * | 2013-03-20 | 2013-07-17 | 北京航空航天大学 | Vehicle safety driving early warning method based on vehicle internet |
| CN104590095A (en) * | 2015-01-06 | 2015-05-06 | 浙江工业大学 | Warning method for dangerous region in running process of large-sized vehicle and warning lamp system |
| CN105023394A (en) * | 2015-06-23 | 2015-11-04 | 南京理工大学 | Dangerous driving reminding and controlling method based on portable intelligent device |
| CN205131082U (en) * | 2015-09-23 | 2016-04-06 | 张坤 | On -vehiclely prevent bumping porcelain device |
| TW201738828A (en) * | 2016-04-20 | 2017-11-01 | Zebred Network Technology Co Ltd | Message pushing method, device, and apparatus |
| CN106080609A (en) * | 2016-06-30 | 2016-11-09 | 深圳市赛格导航科技股份有限公司 | A kind of method and system of safe driving based on ADAS module |
| CN106128140A (en) * | 2016-08-11 | 2016-11-16 | 江苏大学 | Car networked environment down train service active perception system and method |
| WO2018092265A1 (en) * | 2016-11-18 | 2018-05-24 | 三菱電機株式会社 | Driving assistance device and driving assistance method |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11069159B1 (en) | Driving trip and pattern analysis | |
| US11118923B2 (en) | Data processing system communicating with a map data processing system to determine or alter a navigation path based on one or more road segments | |
| CN107784587B (en) | Driving behavior evaluation system | |
| CN109919347B (en) | Road condition generation method, related device and equipment | |
| US10163275B1 (en) | Driving trip and pattern analysis | |
| CN108074396A (en) | The evaluation method that drives safely and system | |
| US11836985B2 (en) | Identifying suspicious entities using autonomous vehicles | |
| CN104508719A (en) | Driving assistance system and driving assistance method | |
| US20170115126A1 (en) | Smart vehicle navigation and tracking system | |
| CN105144259A (en) | A traffic surveillance and guidance system | |
| CN114140300A (en) | Method, device, storage medium and terminal for identifying vehicle stop points based on GPS data | |
| CN112734242A (en) | Method and device for analyzing availability of vehicle running track data, storage medium and terminal | |
| Jones et al. | Parkus 2.0: Automated cruise detection for parking availability inference | |
| CN117836829A (en) | System and method for monitoring a vehicle | |
| KR101498582B1 (en) | System and Method for Providing Traffic Accident Data | |
| CN112215481A (en) | Method for determining business capability of ride-on test and driving test and business capability display system | |
| CN105976453A (en) | Image transformation-based driving alarm method and apparatus thereof | |
| CN110949409A (en) | Vehicle-based driving processing method, device and system | |
| CN112362076B (en) | Intelligent display method and related device for navigation information of non-recommended road section | |
| CN110458459B (en) | Visual analysis method, device and equipment for traffic data and readable storage medium | |
| CN113469232A (en) | Vehicle user classification method, apparatus, and computer-readable storage medium | |
| US11800065B2 (en) | Mobile image surveillance systems and methods | |
| CN115995151B (en) | Network vehicle-closing abnormal behavior detection method applied to city management | |
| US20240015265A1 (en) | Mobile Image Surveillance Methods | |
| JP6704568B1 (en) | Information processing system, information processing device, terminal device, server device, program, or method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20200403 |