WO2018232991A1 - 一种基于自选车位的停车收费管控方法及系统 - Google Patents

一种基于自选车位的停车收费管控方法及系统 Download PDF

Info

Publication number
WO2018232991A1
WO2018232991A1 PCT/CN2017/099128 CN2017099128W WO2018232991A1 WO 2018232991 A1 WO2018232991 A1 WO 2018232991A1 CN 2017099128 W CN2017099128 W CN 2017099128W WO 2018232991 A1 WO2018232991 A1 WO 2018232991A1
Authority
WO
WIPO (PCT)
Prior art keywords
vehicle
wireless
parking space
terminal
parking
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.)
Ceased
Application number
PCT/CN2017/099128
Other languages
English (en)
French (fr)
Inventor
杜光东
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Shenzhen Shenglu IoT Communication Technology Co Ltd
Original Assignee
Shenzhen Shenglu IoT Communication Technology Co Ltd
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Shenzhen Shenglu IoT Communication Technology Co Ltd filed Critical Shenzhen Shenglu IoT Communication Technology Co Ltd
Publication of WO2018232991A1 publication Critical patent/WO2018232991A1/zh
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

Links

Images

Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/16—Devices for psychotechnics; Testing reaction times ; Devices for evaluating the psychological state
    • A61B5/168—Evaluating attention deficit, hyperactivity
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/16—Devices for psychotechnics; Testing reaction times ; Devices for evaluating the psychological state
    • A61B5/18—Devices for psychotechnics; Testing reaction times ; Devices for evaluating the psychological state for vehicle drivers or machine operators
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]
    • A61B5/33—Heart-related electrical modalities, e.g. electrocardiography [ECG] specially adapted for cooperation with other devices
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7271—Specific aspects of physiological measurement analysis
    • A61B5/7285—Specific aspects of physiological measurement analysis for synchronizing or triggering a physiological measurement or image acquisition with a physiological event or waveform, e.g. an ECG signal
    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07B—TICKET-ISSUING APPARATUS; FARE-REGISTERING APPARATUS; FRANKING APPARATUS
    • G07B15/00—Arrangements or apparatus for collecting fares, tolls or entrance fees at one or more control points
    • G07B15/02—Arrangements or apparatus for collecting fares, tolls or entrance fees at one or more control points taking into account a variable factor such as distance or time, e.g. for passenger transport, parking systems or car rental systems
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING SYSTEMS, e.g. PERSONAL CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
    • G08B21/02—Alarms for ensuring the safety of persons
    • G08B21/06—Alarms for ensuring the safety of persons indicating a condition of sleep, e.g. anti-dozing alarms
    • 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
    • G08G1/143—Traffic control systems for road vehicles indicating individual free spaces in parking areas with means giving the indication of available parking spaces inside the vehicles
    • 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
    • G08G1/145—Traffic control systems for road vehicles indicating individual free spaces in parking areas where the indication depends on the parking areas
    • G08G1/148—Management of a network of parking areas

Definitions

  • the invention relates to the technical field of internet of things, in particular to a parking charging control method and system based on a self-selected parking space.
  • the embodiment of the invention discloses a parking charging control method and system based on the self-selected parking space, which can accurately navigate the vehicle to the parking space of the driver's choice which is most suitable for the vehicle size, and can also realize the unmanned parking fee and improve the charging management efficiency. .
  • the first aspect of the embodiments of the present invention discloses a parking fee management and control method based on a self-selected parking space, including:
  • the wireless vehicle-mounted terminal reports the current vehicle location of the vehicle in which the wireless vehicle-mounted terminal is located and the vehicle identity of the vehicle to the big data analysis system;
  • the big data analysis system identifies a vehicle type of the vehicle according to the vehicle identification, and identifies a parking space type applicable to the vehicle type according to the vehicle type;
  • the big data analysis system searches for all the free parking spaces corresponding to the parking space type in its own jurisdiction, and sends the found location identifiers of all the free parking spaces to the wireless vehicle terminal, so that the wireless vehicle The driver of the vehicle where the terminal is located selects any free parking space as the target parking space from all the idle parking spaces found based on the location identification of all the free parking spaces;
  • the big data analysis system generates a navigation path between the target parking space and the current vehicle location, and sends the navigation path to the wireless vehicle terminal for parking navigation;
  • the big data analysis system deducts a corresponding parking fee from the electronic account number bound by the wireless vehicle terminal according to the actual parking time of the vehicle at the target parking space.
  • the wireless in-vehicle terminal reports the current vehicle location of the vehicle where the wireless vehicle-mounted terminal is located and the vehicle identifier of the vehicle to the big data analysis system.
  • the method further includes:
  • the wireless vehicle-mounted terminal identifies whether the emotion of the driver of the vehicle in which the wireless vehicle-mounted terminal is located is Stable, if the mood is unstable, the wireless vehicle terminal prompts the driver to stop; if the mood is stable, the wireless vehicle terminal collects a frame of the driver's face image at a specified time, and determines from the face image Positioning a rectangle of a human eye, calculating an area of the human eye positioning rectangle, determining a degree of closure of the driver's eyes according to a threshold value, and evaluating a degree of eye fatigue according to a degree of closure of the driver's eyes, based on The human eye fatigue level value determines whether the driver's eyes are fatigued, and if fatigued, the wireless vehicle terminal prompts the driver to stop;
  • the wireless vehicle-mounted terminal detects a parking space search command input by a driver of the vehicle in which the wireless vehicle-mounted terminal is located, and collects a current vehicle position.
  • the wireless vehicle-mounted terminal identifies whether the emotion of the driver of the vehicle where the wireless vehicle-mounted terminal is located is stable, including:
  • the wireless in-vehicle terminal detects electrocardiogram data of the driver transmitted by a wearable device worn by a driver of a vehicle in which the wireless in-vehicle terminal is located;
  • the wireless vehicle terminal performs denoising processing on the electrocardiogram data
  • the wireless vehicle-mounted terminal extracts an R-wave peak value in the ECG data subjected to the denoising process by using an electrocardiogram R-wave extraction algorithm, and calculates an RR distance between adjacent R-waves in the de-noised ECG data;
  • the wireless vehicle-mounted terminal calculates a frequency domain index, a time domain index, and a non-linear index of the RR interval; wherein the frequency domain indicator includes a parasympathetic nerve activity index, and the time domain indicator includes a short-range heart rate variability indicator;
  • the short-range heart rate variability index is calculated by obtaining a root mean square of the sum of the squares of the RR gap differences;
  • the parasympathetic nerve activity index is calculated by a fast Fourier transform;
  • the nonlinear index is calculated by a fractal dimension calculation method;
  • the wireless vehicle-mounted terminal analyzes the vitality value of the user's emotion according to the frequency domain index, the time domain index, and the non-linear index; the vitality value is established according to the time domain index, the frequency domain index, and the nonlinear indicator.
  • the calculated value of the multiple linear regression equation
  • the wireless vehicle-mounted terminal identifies whether the emotion of the driver is unstable according to the vitality value.
  • the wireless in-vehicle terminal reports the current vehicle location of the vehicle where the wireless vehicle-mounted terminal is located and the vehicle identifier of the vehicle to the big data analysis system.
  • the wireless vehicle-mounted terminal scans whether a routing node is preset in the surrounding environment, and if the routing node is set in advance, detecting whether the routing node is configured with an open access period, if the routing node is configured to be open An access period, identifying whether a current system time of the wireless in-vehicle terminal is located in the open access period in which the routing node is configured;
  • the routing node If the current system time of the wireless in-vehicle terminal is located in the open access period in which the routing node is configured, detecting whether the number of terminals currently accessed by the routing node exceeds a maximum terminal access specified by the routing node Quantity
  • the wireless in-vehicle terminal establishes a wireless connection with the routing node, and the wireless in-vehicle terminal A current vehicle location of the vehicle in which the vehicle is located and a vehicle identification of the vehicle are transmitted to the routing node, and the routing node transmits a current vehicle location of the vehicle in which the wireless vehicle-mounted terminal is located and a vehicle identification of the vehicle to the big data analysis system.
  • the big data analysis system generates a navigation path between the target parking space and the current vehicle location, and sends the navigation path After performing parking navigation on the wireless vehicle terminal, the method further includes:
  • the big data analysis system determines whether a current workload of the big data analysis system exceeds a workload specified by the big data analysis system
  • the big data analysis system initiates the inclusion of the weather service platform corresponding to the weather information query port through the weather information query port. a weather information inquiry request for the target parking space;
  • the big data analysis system receives the weather information of the preset duration corresponding to the target parking space returned by the weather service platform through the weather information inquiry port;
  • the big data analysis system sends the weather information of the preset duration corresponding to the target parking space to the wireless vehicle-mounted terminal;
  • the big data analysis system deducts the corresponding parking fee from the electronic account bound to the wireless vehicle terminal according to the actual parking time of the vehicle in the target parking space, including:
  • the big data analysis system discriminates whether the target parking space belongs to a parking space rented according to a preset time period, and if the target parking space does not belong to a parking space rented according to a preset time period, according to the ordinary charging corresponding to the target parking space
  • the normal charging rule includes a first charging amount corresponding to the unit time
  • the preset time period, the corresponding parking fee is calculated according to the high charging rule corresponding to the target parking space and the actual parking time
  • the high charging rule includes a second charging amount corresponding to the unit time, and the The second charge amount is equal to several times the first charge amount;
  • a second aspect of the embodiments of the present invention discloses a parking charging control system based on a self-selected parking space, including a wireless vehicle terminal and a big data analysis system, wherein:
  • the wireless vehicle-mounted terminal is configured to report the current vehicle location of the vehicle where the wireless vehicle-mounted terminal is located and the vehicle identity of the vehicle to the big data analysis system;
  • the big data analysis system is configured to identify a vehicle type of the vehicle according to the vehicle identifier, and identify a parking space type applicable to the vehicle type according to the vehicle type;
  • the big data analysis system is further configured to find all the free parking spaces of the parking space type corresponding to the size of the parking space, and send the location identifiers of all the idle parking spaces that are found out to the wireless vehicle terminal, so that The driver of the vehicle in which the wireless vehicle-mounted terminal is located selects any one of the free parking spaces as the target parking space based on the location identifiers of all the free parking spaces;
  • the big data analysis system is further configured to generate a navigation path between the target parking space and the current vehicle location, and send the navigation path to the wireless vehicle terminal for parking navigation;
  • the big data analysis system is further configured to actually stop according to the vehicle at the target parking space
  • the length of the car is deducted from the electronic account bound to the wireless vehicle terminal.
  • the wireless in-vehicle terminal is further configured to identify an emotion of a driver of the vehicle where the wireless in-vehicle terminal is located before reporting the current vehicle location of the vehicle in which the wireless in-vehicle terminal is located and the vehicle identification of the vehicle to the big data analysis system Whether it is stable, if the mood is unstable, prompting the driver to stop; if the mood is stable, collect a frame of the driver's face image at a specified time, and determine the human eye positioning rectangle from the face image, the calculation center Describe the area of the human eye positioning rectangle, determine the degree of clogging of the driver's eyes according to the threshold value, and evaluate the eye fatigue degree value according to the degree of clogging of the driver's eyes, based on the human eye fatigue degree value Determining whether the driver's eyes are fatigued, if fatigue, prompting the driver to stop; and detecting a parking space search command input by the driver of the vehicle in which the wireless vehicle-mounted terminal is located, and collecting the current vehicle position.
  • the wireless vehicle-mounted terminal is configured to detect electrocardiogram data of the driver sent by a wearable device worn by a driver of a vehicle where the wireless vehicle-mounted terminal is located; perform denoising processing on the electrocardiogram data; and extract by using an electrocardiogram R-wave extraction algorithm R-wave peak value in the degaussed ECG data, and calculating the RR spacing between adjacent R waves in the denoised ECG data; calculating the frequency domain index, time domain index and nonlinearity of the RR spacing An index; wherein the frequency domain indicator includes a parasympathetic nerve activity index, the time domain indicator includes a short-range heart rate variability indicator; and the short-range heart rate variability index is calculated by obtaining a root mean square of a square sum of the RR gap differences; The parasympathetic nerve activity index is calculated by a fast Fourier transform; the nonlinear index is calculated by a fractal dimension calculation method; and the user's emotion is analyzed according to the frequency domain index, the time domain index, and the nonlinear index Vital
  • the wireless vehicle-mounted terminal reports the current vehicle location of the vehicle where the wireless vehicle-mounted terminal is located and the vehicle identity of the vehicle to the big data analysis system.
  • the method is specifically as follows:
  • the wireless in-vehicle terminal is configured to scan whether a routing node is preset in the surrounding environment, and if the routing node is preset, detecting whether the routing node is configured with an open access period, if the routing node is configured to have Determining, by the open access period, whether a current system time of the wireless in-vehicle terminal is located in the open access period in which the routing node is configured; if a current system time of the wireless in-vehicle terminal is located in the routing node Detecting, in the configured open access period, whether the number of terminals currently accessed by the routing node exceeds the maximum number of terminal accesses specified by the routing node; if the number of currently accessed terminals of the routing node does not exceed Transmitting, by the routing node, a maximum number of terminal accesses, establishing a wireless connection with the routing node, and transmitting a current vehicle location of the vehicle in which the wireless vehicle-mounted terminal is located and a vehicle identity of the vehicle to the routing no
  • the big data analysis system is further configured to: after generating a navigation path between the target parking space and the current vehicle location, and send the navigation path to the wireless vehicle terminal for parking navigation, determine the Whether the current workload of the big data analysis system exceeds the workload specified by the big data analysis system, and if the current workload of the big data analysis system does not exceed the workload specified by the big data analysis system, query the port through the weather information And generating, by the weather service platform corresponding to the weather information query port, a weather information query request including the target parking space; and receiving, by the weather service platform, a preset time period corresponding to the target parking space returned by the weather information query port Weather information; the weather information of the preset duration corresponding to the target parking space is sent to the wireless vehicle terminal;
  • the method for deducting the corresponding parking fee from the electronic account bound by the wireless vehicle terminal according to the actual parking duration of the vehicle in the target parking space is specifically as follows:
  • the big data analysis system is configured to identify whether the target parking space belongs to a parking space rented according to a preset time period, and if the target parking space does not belong to a parking space rented according to a preset time period, corresponding to the target parking space
  • the normal charging rule and the actual parking time are calculated corresponding to the parking fee, and the ordinary charging rule includes a first charging amount corresponding to the unit time; if the target parking space belongs to the parking space rented according to the preset time period, determining the Whether the actual parking time of the vehicle in the target parking space exceeds the preset time period, and if the preset time period is not exceeded, the corresponding parking fee is calculated according to the ordinary charging rule corresponding to the target parking space and the actual parking time.
  • the corresponding parking fee is calculated according to the high charging rule corresponding to the target parking space and the actual parking time, and the high charging rule includes a second charging amount corresponding to the unit time, and The second charging amount is equal to a plurality of multiples of the first charging amount; and, from the wireless Carrier terminal binding electronic account to deduct the appropriate parking fee.
  • the embodiment of the invention has the following beneficial effects:
  • the big data analysis system can identify the vehicle type of the vehicle where the wireless vehicle-mounted terminal is located according to the vehicle identification, and can be based on the vehicle type. Identifying the type of parking space applicable to the vehicle type.
  • the big data analysis system can find all the free parking spaces corresponding to the parking space type within its own jurisdiction, and send the location identification of all the free parking spaces that are found out to The wireless vehicle terminal, such that the driver of the vehicle where the wireless vehicle terminal is located can independently select any free parking space as the target parking space according to the location identifier of all the free parking spaces found; and the big data analysis system can generate the target parking space and the current
  • the navigation path between the vehicle positions is sent to the wireless vehicle terminal for parking navigation, and the corresponding parking fee is deducted from the electronic account bound by the wireless vehicle terminal according to the actual parking time of the vehicle at the target parking space. It can be seen that the embodiment of the present invention can not only accurately navigate the vehicle to the parking space that is optimal for the vehicle size selected by the driver, but also realize the unmanned parking fee and improve the charging management efficiency.
  • FIG. 1 is a schematic flow chart of a parking fee management and control method based on a self-selected parking space according to an embodiment of the present invention
  • FIG. 2 is a schematic flowchart of a method for a wireless vehicle terminal to identify whether a driver's emotion is stable according to an embodiment of the present invention
  • FIG. 3 is a schematic flow chart of another parking charge management and control method based on a self-selected parking space according to an embodiment of the present invention
  • FIG. 4 is a schematic structural diagram of a parking fee management and control system based on a self-selected parking space according to an embodiment of the present invention.
  • the embodiment of the invention discloses a parking charging control method and system based on the self-selected parking space, which can accurately navigate the vehicle to the parking space of the driver's choice which is most suitable for the vehicle size, and can also realize the unmanned parking fee and improve the charging management efficiency. .
  • the details are described below separately.
  • FIG. 1 is a schematic flow chart of a parking fee management and control method based on a self-selected parking space according to an embodiment of the present invention.
  • the parking charge control method based on the self-selected parking space may include the following steps:
  • the wireless vehicle-mounted terminal reports the current vehicle location of the vehicle where the wireless vehicle-mounted terminal is located and the vehicle identity of the vehicle to the big data analysis system.
  • the wireless communication module built in the wireless vehicle terminal can input the upper frequency point 470MHz and the lower frequency point 510MHz during production, so that the wireless communication module can automatically define the communication frequency band as 470MHz ⁇ 510MHz to conform to the Chinese SRRC standard.
  • the wireless communication module can automatically define the communication frequency band as 868MHz ⁇ 908MHz, in order to comply with the European ETSI standard; or, you can input the upper frequency point 918MHz, The lower frequency point is 928MHz, so the wireless communication module can automatically define the communication frequency band as 918MHz ⁇ 928MHz to meet the requirements of the US FCC standard; or, the communication frequency band of the wireless communication module can also be defined as complying with the Japanese ARIB standard or the Canadian IC standard.
  • the embodiment of the invention is not limited.
  • the wireless vehicle terminal may use Frequency Division Multiple Access (FDMA), Frequency-Hopping Spread Spectrum (FHSS), and Dynamic Time Division Multiple Access (DTDMA).
  • FDMA Frequency Division Multiple Access
  • FHSS Frequency-Hopping Spread Spectrum
  • DTDMA Dynamic Time Division Multiple Access
  • the method of combining the back-off multiplexing (CSMA) to solve the interference problem is not limited in the embodiment of the present invention.
  • the wireless vehicle-mounted terminal may perform the following steps:
  • the wireless vehicle-mounted terminal identifies whether the mood of the driver of the vehicle in which the wireless vehicle-mounted terminal is located is stable, such as If the emotion is unstable, the wireless vehicle terminal prompts the driver to stop; if the mood is stable, the wireless vehicle terminal collects a frame of the driver's face image every specified time (eg, 120 milliseconds), and determines the human eye position from the face image.
  • the wireless vehicle terminal collects a frame of the driver's face image every specified time (eg, 120 milliseconds), and determines the human eye position from the face image.
  • Rectangularity calculating the area of the human eye positioning rectangle, judging the degree of closure of the driver's eyes according to the threshold value, and evaluating the degree of human eye fatigue according to the degree of blindness of the driver's eyes, and judging the driver's based on the degree of human eye fatigue Whether the eyes are fatigued, if fatigue, the wireless vehicle terminal prompts the driver to stop, and the driver can input a parking space search command to the wireless vehicle terminal according to the prompt, thereby avoiding a driving accident easily caused by the driver's eye fatigue or emotional instability;
  • the wireless vehicle-mounted terminal detects a parking space search command input by a driver of the vehicle in which the wireless vehicle-mounted terminal is located, and acquires a current vehicle position.
  • the manner in which the wireless vehicle terminal collects the current vehicle location may be:
  • the wireless vehicle terminal acquires at least two different positioning interfaces configured by the wireless vehicle terminal; for example, at least two different positioning interfaces may include a nlpservice positioning interface of Baidu, a nlpservice positioning interface of Gaode, and a nlpservice positioning interface of Google.
  • the embodiment of the present invention is not limited; and the wireless in-vehicle terminal may send the positioning request to the at least two different positioning interfaces, so as to trigger each positioning interface to separately send the received positioning request to the corresponding positioning server; Obtaining location information sent by the positioning server corresponding to the at least one positioning interface, and acquiring a response time from the first time to the second time, where the first time is a time for sending a positioning request for each positioning interface, and the second time is each positioning interface Receiving the time of the location information; and comparing the response time corresponding to each positioning interface with the response threshold, and extracting the location information with the highest positioning accuracy from the location information received by the positioning interface whose response time does not exceed the response threshold Current vehicle location.
  • the implementation of the foregoing embodiment can accurately acquire the parking position and improve the positioning accuracy.
  • the method for the wireless vehicle-mounted terminal to identify whether the emotion of the driver of the vehicle where the wireless vehicle-mounted terminal is located may be stable as shown in FIG. 2, and includes the following steps:
  • the wireless vehicle-mounted terminal detects electrocardiogram data of the driver transmitted by a wearable device (such as a wristband) worn by a driver of the vehicle in which the wireless vehicle-mounted terminal is located.
  • a wearable device such as a wristband
  • the wireless vehicle terminal can perform denoising processing on the electrocardiogram data, and extract an R wave peak in the degaussed ECG data by using an electrocardiogram R wave extraction algorithm, and calculate adjacent R waves in the degaussed ECG data.
  • Inter-RR spacing and, calculating the frequency domain index, time domain index and non-linear index of RR spacing; wherein, the frequency domain index includes the parasympathetic nerve activity index, the time domain index includes the short-range heart rate variability index; the short-range heart rate variability index is obtained
  • the root mean square of the sum of the squares of the RR spacing differences is calculated; the parasympathetic nerve activity index is calculated by the fast Fourier transform; the nonlinear index is calculated by the fractal dimension calculation method.
  • the wireless vehicle terminal can analyze the emotional activity value of the user according to the frequency domain index, the time domain index, and the non-linear index; wherein the vitality value is a multiple linear regression established according to the time domain index, the frequency domain index, and the nonlinear index. The value calculated by the equation; and, based on the vitality value, whether the emotion of the user is unstable.
  • the method described in FIG. 2 described above can accurately identify the driver. Is the mood stable?
  • the wireless vehicle-mounted terminal reports the current vehicle position of the vehicle in which the wireless vehicle-mounted terminal is located and the vehicle identification of the vehicle to the big data analysis system, including:
  • the wireless vehicle terminal scans whether a routing node is preset in the surrounding environment. If a routing node is set in advance, whether the routing node is configured to have an open access period, and if the routing node is configured with an open access period, the current wireless vehicle terminal is identified. Whether the system time is within an open access period in which the routing node is configured;
  • the routing node If the current system time of the wireless vehicle terminal is located in the open access period in which the routing node is configured, detecting whether the number of terminals currently accessed by the routing node exceeds the maximum terminal access number specified by the routing node;
  • the wireless in-vehicle terminal establishes a wireless connection with the routing node, and the current vehicle location of the vehicle in which the wireless in-vehicle terminal is located and the vehicle of the vehicle.
  • the identification is sent to the routing node, and the routing node transmits the current vehicle location of the vehicle in which the wireless vehicle-mounted terminal is located and the vehicle identification of the vehicle to the big data analysis system.
  • the routing node sends the current vehicle location of the vehicle where the wireless vehicle-mounted terminal is located and the vehicle identification of the vehicle to the big data analysis system, so that the wireless vehicle-mounted terminal can directly establish a long-distance communication connection with the big data analysis system. Therefore, it is possible to avoid the large power consumption caused by the wireless vehicle terminal directly communicating with the big data analysis system.
  • the big data analysis system identifies the vehicle type of the vehicle according to the vehicle identification, and identifies the type of parking space applicable to the vehicle type according to the type of the vehicle.
  • the vehicle type may include a car, a truck, a passenger car, a trailer, a motorcycle, etc., which are not limited in the embodiment of the present invention.
  • the big data analysis system searches for all the free parking spaces corresponding to the parking space type in its own jurisdiction, and sends the location identifiers of all the idle parking spaces found to the wireless vehicle terminal, so that the driving of the vehicle where the wireless vehicle terminal is located Based on the location identification of all the free parking spaces found, the staff selects any free parking space from the found all available parking spaces as the target parking space.
  • the location identifier of the free parking space may include the number of the free parking space and the parking lot name or street name where the free parking space is located.
  • the parking space corresponding to the size of the motorcycle is smaller than the parking space corresponding to the size of the car, and the parking space corresponding to the size of the car is smaller than the parking space corresponding to the size of the truck, and the parking space corresponding to the size of the truck is smaller than the corresponding size of the passenger car.
  • the parking space of the passenger car is smaller than the parking space corresponding to the size of the trailer.
  • the big data analysis system generates a navigation path between the target parking space and the current vehicle location, and sends the navigation path to the wireless vehicle terminal for parking navigation.
  • the big data analysis system deducts the corresponding parking fee from the electronic account bound to the wireless vehicle terminal according to the actual parking time of the vehicle in the target parking space.
  • the big data analysis system may deduct the corresponding parking fee from the electronic account bound to the wireless vehicle terminal according to the actual parking time of the vehicle in the target parking space:
  • the big data analysis system can distinguish whether the target parking space belongs to the parking space rented according to the preset time period. If the target parking space does not belong to the parking space rented according to the preset time period, the general parking fee corresponding to the target parking space and the actual parking time can be calculated. The corresponding parking fee, wherein the ordinary charging rule includes the first charging amount corresponding to the unit time;
  • the target parking space belongs to the parking space rented according to the preset time period, it is determined whether the actual parking time of the vehicle in the target parking space exceeds the preset time period, and if the preset time period is not exceeded, the ordinary charging rule corresponding to the target parking space and the actual parking time period are Calculate the corresponding parking fee;
  • the corresponding parking fee may be calculated according to the high charging rule corresponding to the target parking space and the actual parking time, wherein the high charging rule includes a second charging amount corresponding to the unit time, and the second charging amount is equal to several The first charge amount of the multiple; and the corresponding parking fee is deducted from the electronic account bound to the wireless vehicle terminal.
  • the implementation of such an optional embodiment can encourage the driver to drive the vehicle away from the target parking position in time before the vehicle is parked for longer than the preset rental period of the target parking space, so as not to cause a huge parking fee.
  • each of the free parking spaces can be rented according to a preset time period, that is, each idle parking space can be preset with a rental time (for example, 08:30 to 18:00).
  • a rental time for example, 08:30 to 18:00.
  • the owner can rent out his free parking space, and the owner can report to the big data analysis system the rental duration preset by the owner for his free parking space (eg 08:30 ⁇ 18:00).
  • FIG. 3 is a schematic flow chart of another parking charging control method based on a self-selected parking space according to an embodiment of the present invention.
  • the parking charge control method based on the self-selected parking space may include the following steps:
  • the wireless vehicle-mounted terminal reports the current vehicle location of the vehicle where the wireless vehicle-mounted terminal is located and the vehicle identity of the vehicle to the big data analysis system.
  • the wireless vehicle-mounted terminal may perform the following steps:
  • the wireless vehicle-mounted terminal identifies whether the mood of the driver of the vehicle in which the wireless vehicle-mounted terminal is located is stable, and if the mood is unstable, the wireless vehicle-mounted terminal prompts the driver to stop; if the mood is stable, the wireless vehicle-mounted terminal collects one frame of driving every specified time (eg, 120 milliseconds).
  • the face image of the person, and the human eye positioning rectangle is determined from the face image, the area of the human eye positioning rectangle is calculated, and the driver is judged according to the threshold value.
  • the degree of eyelid closure, and the degree of eye fatigue according to the degree of closure of the driver's eyes the driver's eye is judged to be fatigued based on the degree of human eye fatigue, and if fatigue occurs, the wireless vehicle terminal prompts the driver to stop.
  • the driver can input a parking space search command to the wireless vehicle terminal according to the prompt, thereby avoiding a driving accident easily caused by the driver's eye fatigue or emotional instability;
  • the wireless vehicle-mounted terminal detects a parking space search command input by a driver of the vehicle in which the wireless vehicle-mounted terminal is located, and acquires a current vehicle position.
  • the manner in which the wireless vehicle terminal collects the current vehicle location may be:
  • the wireless vehicle terminal acquires at least two different positioning interfaces configured by the wireless vehicle terminal; for example, at least two different positioning interfaces may include a nlpservice positioning interface of Baidu, a nlpservice positioning interface of Gaode, and a nlpservice positioning interface of Google.
  • the embodiment of the present invention is not limited; and the wireless in-vehicle terminal may send the positioning request to the at least two different positioning interfaces, so as to trigger each positioning interface to separately send the received positioning request to the corresponding positioning server; Obtaining location information sent by the positioning server corresponding to the at least one positioning interface, and acquiring a response time from the first time to the second time, where the first time is a time for sending a positioning request for each positioning interface, and the second time is each positioning interface Receiving the time of the location information; and comparing the response time corresponding to each positioning interface with the response threshold, and extracting the location information with the highest positioning accuracy from the location information received by the positioning interface whose response time does not exceed the response threshold Current vehicle location.
  • the implementation of the foregoing embodiment can accurately acquire the parking position and improve the positioning accuracy.
  • the manner in which the wireless in-vehicle terminal recognizes whether the mood of the driver of the vehicle where the wireless in-vehicle terminal is located is stable:
  • the wireless vehicle-mounted terminal detects the driver's electrocardiogram data transmitted by the wearable device (such as a wristband) worn by the driver of the vehicle in which the wireless vehicle-mounted terminal is located; for example, the wireless vehicle-mounted terminal can detect whether the travel time of the vehicle in which the wireless vehicle-mounted terminal is located exceeds a preset The duration, if the preset duration is exceeded, the wireless vehicle terminal can detect whether the wireless vehicle terminal establishes a communication connection with a wearable device (such as a wristband) worn by the driver of the vehicle where the wireless vehicle terminal is located, and if so, the wireless vehicle terminal can notify the driver to wear
  • the wearable device transmits the driver's electrocardiogram data to the wireless vehicle terminal;
  • the wireless vehicle terminal can perform denoising processing on the electrocardiogram data, and extract an R wave peak in the degaussed ECG data by using an electrocardiogram R wave extraction algorithm, and calculate adjacent R waves in the degaussed ECG data.
  • Inter-RR spacing and, calculating the frequency domain index, time domain index and non-linear index of RR spacing; wherein, the frequency domain index includes the parasympathetic nerve activity index, the time domain index includes the short-range heart rate variability index; the short-range heart rate variability index is obtained
  • the root mean square of the sum of the squares of the RR spacing differences is calculated; the parasympathetic nerve activity index is calculated by the fast Fourier transform; the nonlinear index is calculated by the fractal dimension calculation method;
  • the wireless vehicle terminal can analyze the emotional activity value of the user according to the frequency domain indicator, the time domain indicator and the non-linear indicator; wherein the vitality value is a multiple linear regression established according to the time domain index, the frequency domain index and the non-linear index The value calculated by the equation; and, based on the vitality value, whether the emotion of the user is unstable.
  • the implementation of the above embodiment can accurately identify whether the driver's emotion is stable.
  • the big data analysis system identifies the vehicle type of the vehicle according to the vehicle identification, and identifies the type of parking space applicable to the vehicle type according to the type of the vehicle.
  • the vehicle type may include a car, a truck, a passenger car, a trailer, a motorcycle, etc., which are not limited in the embodiment of the present invention.
  • the big data analysis system searches for all the free parking spaces corresponding to the parking space type in its own jurisdiction, and sends the location identifiers of all the idle parking spaces found to the wireless vehicle terminal, so that the driving of the vehicle where the wireless vehicle terminal is located Based on the location identification of all the free parking spaces found, the staff selects any free parking space from the found all available parking spaces as the target parking space.
  • the parking space corresponding to the size of the motorcycle is smaller than the parking space corresponding to the size of the car, and the parking space corresponding to the size of the car is smaller than the parking space corresponding to the size of the truck, and the parking space corresponding to the size of the truck is smaller than the corresponding size of the passenger car.
  • the parking space of the passenger car is smaller than the parking space corresponding to the size of the trailer.
  • the big data analysis system generates a navigation path between the target parking space and the current vehicle location, and sends the navigation path to the wireless vehicle terminal for parking navigation.
  • the big data analysis system determines whether the current workload of the big data analysis system exceeds the workload specified by the big data analysis system. If not, the weather information inquiry port initiates the target parking space to the weather service platform corresponding to the weather information inquiry port. The weather information inquiry request, and receiving the weather information of the preset time period corresponding to the target parking space returned by the weather service platform through the weather information inquiry port.
  • the big data analysis system sends the weather information of the preset time period corresponding to the target parking space to the wireless vehicle terminal, so that the driver can prepare the vehicle for protection according to the weather information, so as to prevent the vehicle from being damaged by bad weather.
  • the big data analysis system deducts the corresponding parking fee from the electronic account bound by the wireless vehicle terminal according to the actual parking time of the vehicle in the target parking space.
  • the big data analysis system may deduct the corresponding parking fee from the electronic account bound to the wireless vehicle terminal according to the actual parking time of the vehicle in the target parking space:
  • the big data analysis system can distinguish whether the target parking space belongs to the parking space rented according to the preset time period. If the target parking space does not belong to the parking space rented according to the preset time period, the general parking fee corresponding to the target parking space and the actual parking time can be calculated. The corresponding parking fee, wherein the ordinary charging rule includes the first charging amount corresponding to the unit time;
  • the target parking space belongs to the parking space rented according to the preset time period, it is determined whether the actual parking time of the vehicle in the target parking space exceeds the preset time period, and if the preset time period is not exceeded, the ordinary charging rule corresponding to the target parking space and the actual parking time period are Calculate the corresponding parking fee;
  • the corresponding parking fee may be calculated according to the high charging rule corresponding to the target parking space and the actual parking time, wherein the high charging rule includes a second charging amount corresponding to the unit time, and the second charging amount is equal to several The first charge amount of the multiple; and the corresponding parking fee is deducted from the electronic account bound to the wireless vehicle terminal.
  • the implementation of such an optional embodiment can encourage the driver to drive the vehicle away from the target parking position in time before the vehicle is parked for longer than the preset rental period of the target parking space, so as not to cause a huge parking fee.
  • each of the free parking spaces can be rented according to a preset time period, that is, each idle parking space can be preset with a rental time (for example, 08:30 to 18:00).
  • a rental time for example, 08:30 to 18:00.
  • the owner can rent out his free parking space, and the owner can report to the big data analysis system the rental duration preset by the owner for his free parking space (eg 08:30 ⁇ 18:00).
  • the driver can prepare for vehicle protection when parking according to weather information, so as to avoid damage caused by bad weather.
  • FIG. 4 is a schematic structural diagram of a parking fee management and control system based on a self-selected parking space according to an embodiment of the present invention.
  • the system can include:
  • Wireless vehicle terminal 401 and big data analysis system 402 wherein:
  • the wireless vehicle-mounted terminal 401 is configured to report the current vehicle position of the vehicle where the wireless vehicle-mounted terminal 401 is located and the vehicle identification of the vehicle to the big data analysis system 402;
  • the big data analysis system 402 is configured to identify the vehicle type of the vehicle according to the vehicle identification, and identify the type of the parking space applicable to the vehicle type according to the vehicle type;
  • the big data analysis system 402 is further configured to find all the free parking spaces corresponding to the parking space type in its own jurisdiction, and send the found location identifiers of all the free parking spaces to the wireless vehicle terminal 401, so as to enable the wireless vehicle terminal.
  • the driver of the vehicle in which 401 is located selects any free parking space as the target parking space from all the idle parking spaces found based on the location identifiers of all the free parking spaces found;
  • the big data analysis system 402 is further configured to generate a navigation path between the target parking space and the current vehicle location, and send the navigation path to the wireless vehicle terminal 401 for parking navigation;
  • the big data analysis system 402 is further configured to deduct the corresponding parking fee from the electronic account number bound by the wireless vehicle terminal 401 according to the actual parking time of the vehicle at the target parking space.
  • the wireless in-vehicle terminal 401 is further configured to identify whether the mood of the driver of the vehicle where the wireless in-vehicle terminal is located is stable before the current vehicle position of the vehicle in which the wireless in-vehicle terminal 401 is located and the vehicle identification of the vehicle are reported to the big data analysis system, if the mood is not Stable, prompting the driver to stop; if The emotion is stable, and a face image of the driver is collected every specified time, and the human eye positioning rectangle is determined from the face image, the area of the human eye positioning rectangle is calculated, and the degree of the driver's eyes is determined according to the threshold value.
  • the parking space search command entered by the member collects the current vehicle position.
  • the manner in which the wireless vehicle-mounted terminal 401 identifies whether the emotion of the driver of the vehicle in which the wireless vehicle-mounted terminal 401 is located is stable:
  • the wireless vehicle-mounted terminal 401 is configured to detect electrocardiogram data of the driver sent by the wearable device worn by the driver of the vehicle where the wireless vehicle-mounted terminal is located; perform denoising processing on the electrocardiogram data; and extract the electrocardiogram data subjected to the denoising process by using an electrocardiogram R-wave extraction algorithm
  • the number calculation method is used to calculate; the vitality value of the user's emotion is analyzed according to the frequency domain index, the time domain index and the non-linear index
  • the wireless vehicle-mounted terminal 401 reports the current vehicle position of the vehicle where the wireless vehicle-mounted terminal is located and the vehicle identification of the vehicle to the big data analysis system.
  • the specific way is:
  • the wireless vehicle-mounted terminal 401 is configured to scan whether a routing node is preset in the surrounding environment. If a routing node is preset, detecting whether the routing node is configured with an open access period, if the routing node is configured with an open access period, identifying the wireless Whether the current system time of the in-vehicle terminal is located in the open access period in which the routing node is configured; if the current system time of the wireless in-vehicle terminal is located in the open access period in which the routing node is configured, detecting whether the number of terminals currently accessed by the routing node is Exceeding the maximum number of terminal accesses specified by the routing node; if the number of terminals currently accessed by the routing node does not exceed the maximum number of terminal accesses specified by the routing node, establish a wireless connection with the routing node, and the vehicle where the wireless vehicle terminal is located
  • the current vehicle location and the vehicle identity of the vehicle are sent to the routing node, and the routing node transmits the current vehicle location of
  • the big data analysis system 402 is further configured to: after generating a navigation path between the target parking space and the current vehicle position, and transmitting the navigation path to the wireless vehicle terminal for parking navigation, determining whether the current workload of the big data analysis system exceeds a large The workload specified by the data analysis system. If the current workload of the big data analysis system does not exceed the workload specified by the big data analysis system, the weather information query port is used to initiate the target to the weather service platform corresponding to the weather information query port.
  • the weather information inquiry request of the parking space receiving the weather information of the preset time period corresponding to the target parking space returned by the weather information inquiry port; and transmitting the weather information of the preset time length corresponding to the target parking space to the wireless vehicle terminal;
  • the big data analysis system 402 deducts the corresponding parking fee from the electronic account bound to the wireless vehicle terminal according to the actual parking time of the vehicle in the target parking space, and specifically:
  • the big data analysis system 402 is configured to identify whether the target parking space belongs to a parking space rented according to a preset time period. If the target parking space does not belong to the parking space rented according to the preset time period, the ordinary charging rule corresponding to the target parking space and the actual parking The duration calculates the corresponding parking fee.
  • the ordinary charging rule includes the first charging amount corresponding to the unit time; if the target parking space belongs to the parking space rented according to the preset time period, it is determined whether the actual parking time of the vehicle in the target parking space exceeds the preset time period.
  • the corresponding parking fee is calculated according to the general charging rule corresponding to the target parking space and the actual parking time; if the preset time period is exceeded, the corresponding parking is calculated according to the high charging rule corresponding to the target parking space and the actual parking time.
  • the fee, the high charging rule includes a second charging amount corresponding to the unit time, and the second charging amount is equal to a plurality of multiple first charging amount; and the corresponding parking fee is deducted from the electronic account bound to the wireless vehicle terminal.
  • implementing the system described in FIG. 4 not only can accurately navigate the vehicle to the driver's choice of the most suitable parking space for the vehicle, but also can realize the unmanned parking fee and improve the charging management efficiency. It can be seen that implementing the system described in FIG. 4 can accurately identify whether the driver's eyes are fatigued and can accurately recognize whether the driver's mood is stable. It can be seen that implementing the system described in FIG. 4 can encourage the driver to drive the vehicle away from the target parking position in time before the vehicle is parked for longer than the preset rental period of the target parking space, so as not to cause a huge parking fee. It can be seen that, implementing the system described in FIG. 4, the driver can prepare for vehicle protection when parking according to weather information, so as to avoid damage caused by bad weather.
  • ROM Read-Only Memory
  • RAM Random Access Memory
  • PROM Programmable Read-Only Memory
  • EPROM Erasable Programmable Read Only Memory
  • OTPROM One-Time Programmable Read-Only Memory
  • EEPROM Electronically-Erasable Programmable Read-Only Memory
  • CD-ROM Compact Disc Read-Only Memory

Landscapes

  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Public Health (AREA)
  • Biophysics (AREA)
  • Biomedical Technology (AREA)
  • Veterinary Medicine (AREA)
  • Medical Informatics (AREA)
  • Molecular Biology (AREA)
  • Surgery (AREA)
  • Animal Behavior & Ethology (AREA)
  • General Health & Medical Sciences (AREA)
  • Pathology (AREA)
  • General Physics & Mathematics (AREA)
  • Psychiatry (AREA)
  • Developmental Disabilities (AREA)
  • Child & Adolescent Psychology (AREA)
  • Hospice & Palliative Care (AREA)
  • Educational Technology (AREA)
  • Psychology (AREA)
  • Social Psychology (AREA)
  • Business, Economics & Management (AREA)
  • Cardiology (AREA)
  • Finance (AREA)
  • Artificial Intelligence (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Physiology (AREA)
  • Signal Processing (AREA)
  • Emergency Management (AREA)
  • Traffic Control Systems (AREA)

Abstract

一种基于自选车位的停车收费管控方法及系统，包括：无线车载终端将当前车辆位置及车辆标识上报给大数据分析系统（101），大数据分析系统根据车辆标识可以辨别出车辆类型，并根据车辆类型辨别出车辆类型适用的车位类型（102），在自身管辖范围内查找出车位类型对应大小的所有空闲停车位，将查找出的所有空闲停车位的位置标识发送给无线车载终端，由驾驶员选择任一个空闲停车位作为目标停车位（103）；生成目标停车位与当前车辆位置之间的导航路径并发送给无线车载终端进行停车导航（104）；根据车辆在目标停车位的实际停车时长，从无线车载终端绑定的电子账号中扣除相应的停车费用（105）。该方法和系统可准确的将车辆导航至最适合车辆大小的停车位，实现无人停车收费，提高收费管理效率。

Description

一种基于自选车位的停车收费管控方法及系统 技术领域
本发明涉及物联网技术领域，尤其涉及一种基于自选车位的停车收费管控方法及系统。
背景技术
当前，随着群众生活水平的不断提升，我国的汽车刚性需求保持旺盛，汽车保有量保持迅猛增长趋势，2016年新注册登记的汽车达2752万辆，保有量净增2212万辆，均为历史最高水平。全国有49个城市的汽车保有量超过100万辆，18个城市的汽车保有量超200万辆，6个城市的汽车保有量超300万辆。其中，汽车保有量超过200万辆的18个城市依次是北京、成都、重庆、上海、深圳、苏州、天津、郑州、西安、杭州、武汉、广州、石家庄、东莞、南京、青岛、宁波、佛山。
在汽车保有量保持迅猛增长的过程中，为了便于群众停车，越来越多的停车场被逐渐的开发出来。在实践中发现，很多停车场均采用人工收费，难以提升收费管理效率；此外，很多时候用户难以准确的在停车场中找到最适合车辆大小的停车位。
发明内容
本发明实施例公开了一种基于自选车位的停车收费管控方法及系统，可以准确的将车辆导航至驾驶员自选的最适合车辆大小的停车位，还可以实现无人停车收费，提高收费管理效率。
本发明实施例第一方面公开一种基于自选车位的停车收费管控方法，包括：
无线车载终端将所述无线车载终端所在车辆的当前车辆位置以及所述车辆的车辆标识上报给大数据分析系统；
所述大数据分析系统根据所述车辆标识辨别出所述车辆的车辆类型，并根据所述车辆类型辨别出所述车辆类型适用的车位类型；
所述大数据分析系统在自身管辖范围内查找出所述车位类型对应大小的所有空闲停车位，将查找出的所有空闲停车位的位置标识发送给所述无线车载终端，以使所述无线车载终端所在车辆的驾驶员以所述所有空闲停车位的位置标识为依据，从查找出的所有空闲停车中选择任一个空闲停车位作为目标停车位；
所述大数据分析系统生成所述目标停车位与所述当前车辆位置之间的导航路径，并将所述导航路径发送给所述无线车载终端进行停车导航；
所述大数据分析系统根据所述车辆在所述目标停车位的实际停车时长，从无线车载终端绑定的电子账号中扣除相应的停车费用。
作为一种可选的实施方式，在本发明实施例第一方面中，所述无线车载终端将所述无线车载终端所在车辆的当前车辆位置以及所述车辆的车辆标识上报给大数据分析系统之前，所述方法还包括：
所述无线车载终端识别所述无线车载终端所在车辆的驾驶员的情绪是否 稳定，如果情绪不稳定，无线车载终端提示驾驶员停车；如果情绪稳定，所述无线车载终端每隔指定时间采集一帧所述驾驶员的人脸图像，并从所述人脸图像中确定出人眼定位矩形，计算所述人眼定位矩形的面积，根据阈值判断所述驾驶员的眼睛的睁闭程度，以及根据所述驾驶员的眼睛的睁闭程度评价出人眼疲劳程度值，基于所述人眼疲劳程度值判断所述驾驶员的眼睛是否疲劳，如果疲劳，所述无线车载终端提示驾驶员停车；
所述无线车载终端检测所述无线车载终端所在车辆的驾驶员输入的停车位搜索指令，采集当前车辆位置。
作为一种可选的实施方式，在本发明实施例第一方面中，所述无线车载终端识别所述无线车载终端所在车辆的驾驶员的情绪是否稳定，包括：
所述无线车载终端检测所述无线车载终端所在车辆的驾驶员佩戴的穿戴设备发送的所述驾驶员的心电图数据；
所述无线车载终端对所述心电图数据进行去噪处理；
所述无线车载终端采用心电图R波提取算法提取经过去噪处理的心电图数据中的R波峰值，以及计算所述经过去噪处理的心电图数据中相邻R波之间RR间距；
所述无线车载终端计算所述RR间距的频域指标、时域指标及非线性指标；其中，所述频域指标包括副交感神经活性指标，所述时域指标包括短程心率变动性指标；所述短程心率变动性指标通过获取所述RR间距差值平方和的均方根来计算；所述副交感神经活性指标通过快速傅里叶变换来计算；所述非线性指标通过分形维数计算方法来计算；
所述无线车载终端根据所述频域指标、时域指标及非线性指标，分析所述用户的情绪的活力值；所述活力值为根据所述时域指标、频域指标及非线性指标建立的多元线性回归方程计算得到的值；
所述无线车载终端根据所述活力值识别所述驾驶员的情绪是否不稳定。
作为一种可选的实施方式，在本发明实施例第一方面中，所述无线车载终端将所述无线车载终端所在车辆的当前车辆位置以及所述车辆的车辆标识上报给大数据分析系统，包括：
所述无线车载终端扫描周围环境中是否预先设置有路由节点，如果预先设置有所述路由节点，检测所述路由节点是否被配置有开放接入时段，如果所述路由节点被配置有所述开放接入时段，识别所述无线车载终端的当前系统时间是否位于所述路由节点被配置的所述开放接入时段内；
如果所述无线车载终端的当前系统时间位于所述路由节点被配置的所述开放接入时段内，检测所述路由节点的当前接入的终端数量是否超过所述路由节点指定的最大终端接入数量；
如果所述路由节点的当前接入的终端数量未超过所述路由节点指定的最大终端接入数量，所述无线车载终端建立与所述路由节点之间的无线连接，并且将所述无线车载终端所在车辆的当前车辆位置以及所述车辆的车辆标识发送给所述路由节点，由所述路由节点将所述无线车载终端所在车辆的当前车辆位置以及所述车辆的车辆标识发送给所述大数据分析系统。
作为一种可选的实施方式，在本发明实施例第一方面中，所述大数据分析系统生成所述目标停车位与所述当前车辆位置之间的导航路径，并将所述导航路径发送给所述无线车载终端进行停车导航之后，所述方法还包括:
所述大数据分析系统判断所述大数据分析系统的当前工作负荷是否超过所述大数据分析系统指定的工作负荷；
如果所述大数据分析系统的当前工作负荷未超过所述大数据分析系统指定的工作负荷，所述大数据分析系统通过天气信息查询端口向所述天气信息查询端口对应的天气服务平台发起包括所述目标停车位的天气信息查询请求；
以及，所述大数据分析系统接收所述天气服务平台通过所述天气信息查询端口返回的所述目标停车位对应的预设时长的天气信息；
以及，所述大数据分析系统将所述目标停车位对应的预设时长的天气信息下发给所述无线车载终端；
其中，所述大数据分析系统根据所述车辆在所述目标停车位的实际停车时长，从无线车载终端绑定的电子账号中扣除相应的停车费用，包括：
所述大数据分析系统辨别所述目标停车位是否属于按预设时段出租的停车位，如果所述目标停车位不属于按预设时段出租的停车位，按照所述目标停车位对应的普通收费规则以及所述实际停车时长计算相应的停车费用，所述普通收费规则包括单位时间对应的第一收费金额；如果所述目标停车位属于按预设时段出租的停车位，判断所述车辆在所述目标停车位的实际停车时长是否超出所述预设时段，如果未超出所述预设时段，按照所述目标停车位对应的普通收费规则以及所述实际停车时长计算相应的停车费用；如果超过所述预设时段，按照所述目标停车位对应的高额收费规则以及所述实际停车时长计算相应的停车费用，所述高额收费规则包括单位时间对应的第二收费金额，并且所述第二收费金额等于若干倍数的所述第一收费金额；以及，从无线车载终端绑定的电子账号中扣除所述相应的停车费用。
本发明实施例第二方面公开一种基于自选车位的停车收费管控系统，包括无线车载终端和大数据分析系统，其中：
所述无线车载终端，用于将所述无线车载终端所在车辆的当前车辆位置以及所述车辆的车辆标识上报给大数据分析系统；
所述大数据分析系统，用于根据所述车辆标识辨别出所述车辆的车辆类型，并根据所述车辆类型辨别出所述车辆类型适用的车位类型；
所述大数据分析系统，还用于在自身管辖范围内查找出所述车位类型对应大小的所有空闲停车位，将查找出的所有空闲停车位的位置标识发送给所述无线车载终端，以使所述无线车载终端所在车辆的驾驶员以所述所有空闲停车位的位置标识为依据，从查找出的所有空闲停车中选择任一个空闲停车位作为目标停车位；
所述大数据分析系统，还用于生成所述目标停车位与所述当前车辆位置之间的导航路径，并将所述导航路径发送给所述无线车载终端进行停车导航；
所述大数据分析系统，还用于根据所述车辆在所述目标停车位的实际停 车时长，从无线车载终端绑定的电子账号中扣除相应的停车费用。
作为一种可选的实施方式，在本发明实施例第二方面中：
所述无线车载终端，还用于在将所述无线车载终端所在车辆的当前车辆位置以及所述车辆的车辆标识上报给大数据分析系统之前，识别所述无线车载终端所在车辆的驾驶员的情绪是否稳定，如果情绪不稳定，提示驾驶员停车；如果情绪稳定，每隔指定时间采集一帧所述驾驶员的人脸图像，并从所述人脸图像中确定出人眼定位矩形，计算所述人眼定位矩形的面积，根据阈值判断所述驾驶员的眼睛的睁闭程度，以及根据所述驾驶员的眼睛的睁闭程度评价出人眼疲劳程度值，基于所述人眼疲劳程度值判断所述驾驶员的眼睛是否疲劳，如果疲劳，提示驾驶员停车；以及，检测所述无线车载终端所在车辆的驾驶员输入的停车位搜索指令，采集当前车辆位置。
作为一种可选的实施方式，在本发明实施例第二方面中：
所述无线车载终端识别所述无线车载终端所在车辆的驾驶员的情绪是否稳定的方式具体为：
所述无线车载终端，用于检测所述无线车载终端所在车辆的驾驶员佩戴的穿戴设备发送的所述驾驶员的心电图数据；对所述心电图数据进行去噪处理；采用心电图R波提取算法提取经过去噪处理的心电图数据中的R波峰值，以及计算所述经过去噪处理的心电图数据中相邻R波之间RR间距；计算所述RR间距的频域指标、时域指标及非线性指标；其中，所述频域指标包括副交感神经活性指标，所述时域指标包括短程心率变动性指标；所述短程心率变动性指标通过获取所述RR间距差值平方和的均方根来计算；所述副交感神经活性指标通过快速傅里叶变换来计算；所述非线性指标通过分形维数计算方法来计算；根据所述频域指标、时域指标及非线性指标，分析所述用户的情绪的活力值；所述活力值为根据所述时域指标、频域指标及非线性指标建立的多元线性回归方程计算得到的值；根据所述活力值识别所述驾驶员的情绪是否不稳定。
作为一种可选的实施方式，在本发明实施例第二方面中，所述无线车载终端将所述无线车载终端所在车辆的当前车辆位置以及所述车辆的车辆标识上报给大数据分析系统的方式具体为：
所述无线车载终端，用于扫描周围环境中是否预先设置有路由节点，如果预先设置有所述路由节点，检测所述路由节点是否被配置有开放接入时段，如果所述路由节点被配置有所述开放接入时段，识别所述无线车载终端的当前系统时间是否位于所述路由节点被配置的所述开放接入时段内；如果所述无线车载终端的当前系统时间位于所述路由节点被配置的所述开放接入时段内，检测所述路由节点的当前接入的终端数量是否超过所述路由节点指定的最大终端接入数量；如果所述路由节点的当前接入的终端数量未超过所述路由节点指定的最大终端接入数量，建立与所述路由节点之间的无线连接，并且将所述无线车载终端所在车辆的当前车辆位置以及所述车辆的车辆标识发送给所述路由节点，由所述路由节点将所述无线车载终端所在车辆的当前车辆位置以及所述车辆的车辆标识发送给所述大数据分析系统。
作为一种可选的实施方式，在本发明实施例第二方面中：
所述大数据分析系统，还用于在生成所述目标停车位与所述当前车辆位置之间的导航路径，并将所述导航路径发送给所述无线车载终端进行停车导航之后，判断所述大数据分析系统的当前工作负荷是否超过所述大数据分析系统指定的工作负荷，如果所述大数据分析系统的当前工作负荷未超过所述大数据分析系统指定的工作负荷，通过天气信息查询端口向所述天气信息查询端口对应的天气服务平台发起包括所述目标停车位的天气信息查询请求；接收所述天气服务平台通过所述天气信息查询端口返回的所述目标停车位对应的预设时长的天气信息；将所述目标停车位对应的预设时长的天气信息下发给所述无线车载终端；
其中，所述大数据分析系统根据所述车辆在所述目标停车位的实际停车时长，从无线车载终端绑定的电子账号中扣除相应的停车费用的方式具体为：
所述大数据分析系统，用于辨别所述目标停车位是否属于按预设时段出租的停车位，如果所述目标停车位不属于按预设时段出租的停车位，按照所述目标停车位对应的普通收费规则以及所述实际停车时长计算相应的停车费用，所述普通收费规则包括单位时间对应的第一收费金额；如果所述目标停车位属于按预设时段出租的停车位，判断所述车辆在所述目标停车位的实际停车时长是否超出所述预设时段，如果未超出所述预设时段，按照所述目标停车位对应的普通收费规则以及所述实际停车时长计算相应的停车费用；如果超过所述预设时段，按照所述目标停车位对应的高额收费规则以及所述实际停车时长计算相应的停车费用，所述高额收费规则包括单位时间对应的第二收费金额，并且所述第二收费金额等于若干倍数的所述第一收费金额；以及，从无线车载终端绑定的电子账号中扣除所述相应的停车费用。
与现有技术相比，本发明实施例具有以下有益效果：
本发明实施例中，无线车载终端将当前车辆位置及车辆标识上报给大数据分析系统之后，大数据分析系统可以根据车辆标识可以辨别出无线车载终端所在车辆的车辆类型，并且可以根据该车辆类型辨别出该车辆类型适用的车位类型，进一步地，大数据分析系统可以在自身管辖范围内查找出该车位类型对应大小的所有空闲停车位，并将查找出的所有空闲停车位的位置标识发送给无线车载终端，这样无线车载终端所在车辆的驾驶员可以根据查找出的所有空闲停车位的位置标识，自主选择任一个空闲停车位作为目标停车位；而大数据分析系统可以生成目标停车位与当前车辆位置之间的导航路径并发送给无线车载终端进行停车导航，以及根据车辆在目标停车位的实际停车时长，从无线车载终端绑定的电子账号中扣除相应的停车费用。可见，实施本发明实施例，不仅可以准确的将车辆导航至驾驶员自选的最适合车辆大小的停车位，还可以实现无人停车收费，提高收费管理效率。
附图说明
为了更清楚地说明本发明实施例中的技术方案，下面将对实施例中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本发明的一些实施例，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是本发明实施例公开的一种基于自选车位的停车收费管控方法的流程示意图；
图2是本发明实施例公开的一种无线车载终端识别驾驶员的情绪是否稳定的方法的流程示意图；
图3是本发明实施例公开的另一种基于自选车位的停车收费管控方法的流程示意图；
图4是本发明实施例公开的一种基于自选车位的停车收费管控系统的结构示意图。
具体实施方式
下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅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。
本发明实施例公开了一种基于自选车位的停车收费管控方法及系统，可以准确的将车辆导航至驾驶员自选的最适合车辆大小的停车位，还可以实现无人停车收费，提高收费管理效率。以下分别进行详细说明。
实施例一
请参阅图1，图1是本发明实施例公开的一种基于自选车位的停车收费管控方法的流程示意图。如图1所示，该基于自选车位的停车收费管控方法可以包括以下步骤：
101、无线车载终端将无线车载终端所在车辆的当前车辆位置以及车辆的车辆标识上报给大数据分析系统。
本发明实施例中，无线车载终端内置的无线通讯模块在生产时，可以输入上频点470MHz，下频点510MHz，这样无线通讯模块可以自动将通讯频段定义为470MHz～510MHz，以符合中国SRRC标准的规定；或者，也可以输入上频点868MHz，下频点908MHz，这样无线通讯模块可以自动将通讯频段定义为868MHz～908MHz，以符合欧洲ETSI标准的规定；或者，可以输入上频点918MHz，下频点928MHz，这样无线通讯模块可以自动将通讯频段定义为918MHz～928MHz，以符合美国FCC标准的规定；或者，无线通讯模块的通讯频段也可以定义为符合日本ARIB标准或加拿大IC标准的规定，本发明实施例不作限定。
本发明实施例中，无线车载终端可以采用频分复用(Frequency Division Multiple Access，FDMA)、跳频(Frequency-Hopping Spread Spectrum，FHSS)、动态时分复用(Dynamic Time Division Multiple Access，DTDMA)、退避复用(CSMA)相结合的方法来解决干扰问题，本发明实施例不作限定。
作为一种可选的实施方式，无线车载终端将无线车载终端所在车辆的当前车辆位置以及车辆的车辆标识上报给大数据分析系统之前，无线车载终端还可以执行以下步骤：
无线车载终端识别无线车载终端所在车辆的驾驶员的情绪是否稳定，如 果情绪不稳定，无线车载终端提示驾驶员停车；如果情绪稳定，无线车载终端每隔指定时间(如120毫秒)采集一帧驾驶员的人脸图像，并从人脸图像中确定出人眼定位矩形，计算人眼定位矩形的面积，根据阈值判断驾驶员的眼睛的睁闭程度，以及根据驾驶员的眼睛的睁闭程度评价出人眼疲劳程度值，基于人眼疲劳程度值判断驾驶员的眼睛是否疲劳，如果疲劳，无线车载终端提示驾驶员停车，而驾驶员可以根据提示向无线车载终端输入停车位搜索指令，从而可以避免因驾驶员的眼睛疲劳或情绪不稳定而容易发生驾驶事故；
以及，无线车载终端检测所述无线车载终端所在车辆的驾驶员输入的停车位搜索指令，采集当前车辆位置。
作为一种可选的实施方式，无线车载终端采集当前车辆位置的方式可以为：
无线车载终端获取无线车载终端配置的至少两个不同的定位接口；举例来说，至少两个不同的定位接口可以包括百度的nlpservice定位接口、高德的nlpservice定位接口、谷歌的nlpservice定位接口等，本发明实施例不作限定；以及，无线车载终端可以将定位请求发送至上述至少两个不同的定位接口，以触发每个定位接口分别将接收到的定位请求发送给各自对应的定位服务器；以及，获取至少一个定位接口对应的定位服务器发送的位置信息，并获取从第一时刻到第二时刻的响应时间，第一时刻为每个定位接口发送定位请求的时刻，第二时刻为每个定位接口接收到位置信息的时刻；以及，将与每个定位接口对应的响应时间与响应阈值进行比较，并从响应时间未超过响应阈值的定位接口所接收的位置信息中提取定位精度最高的位置信息作为当前车辆位置。
本发明实施例中，实施上述实施方式可以精确的获取停车位置，提高定位精确度。
作为一种可选的实施方式，无线车载终端识别无线车载终端所在车辆的驾驶员的情绪是否稳定的方法可以如图2所示，包括以下步骤：
S201、无线车载终端检测无线车载终端所在车辆的驾驶员佩戴的穿戴设备(如手环)发送的驾驶员的心电图数据。
S202、无线车载终端可以对心电图数据进行去噪处理，并采用心电图R波提取算法提取经过去噪处理的心电图数据中的R波峰值，以及计算经过去噪处理的心电图数据中相邻R波之间RR间距；以及，计算RR间距的频域指标、时域指标及非线性指标；其中，频域指标包括副交感神经活性指标，时域指标包括短程心率变动性指标；短程心率变动性指标通过获取RR间距差值平方和的均方根来计算；副交感神经活性指标通过快速傅里叶变换来计算；非线性指标通过分形维数计算方法来计算。
S203、无线车载终端可以根据频域指标、时域指标及非线性指标，分析该用户的情绪的活力值；其中，活力值为根据时域指标、频域指标及非线性指标建立的多元线性回归方程计算得到的值；以及，根据活力值识别该用户的情绪是否不稳定。
本发明实施例中，实施上述图2所描述的方法可以精确的识别出驾驶员 的情绪是否稳定。
本发明实施例中，无线车载终端将无线车载终端所在车辆的当前车辆位置以及车辆的车辆标识上报给大数据分析系统，包括：
无线车载终端扫描周围环境中是否预先设置有路由节点，如果预先设置有路由节点，检测路由节点是否被配置有开放接入时段，如果路由节点被配置有开放接入时段，识别无线车载终端的当前系统时间是否位于路由节点被配置的开放接入时段内；
如果无线车载终端的当前系统时间位于路由节点被配置的开放接入时段内，检测路由节点的当前接入的终端数量是否超过路由节点指定的最大终端接入数量；
如果路由节点的当前接入的终端数量未超过路由节点指定的最大终端接入数量，无线车载终端建立与路由节点之间的无线连接，并且将无线车载终端所在车辆的当前车辆位置以及车辆的车辆标识发送给路由节点，由路由节点将无线车载终端所在车辆的当前车辆位置以及所述车辆的车辆标识发送给大数据分析系统。
本发明实施例中，由路由节点将无线车载终端所在车辆的当前车辆位置以及所述车辆的车辆标识发送给大数据分析系统可以避免无线车载终端直接与大数据分析系统建立较长距离的通信连接，从而可以避免无线车载终端直接与大数据分析系统通信带来的较大功耗。
102、大数据分析系统根据车辆标识辨别出车辆的车辆类型，并根据车辆类型辨别出车辆类型适用的车位类型。
本发明实施例中，车辆类型可以包括轿车、载货车、客车、挂车、摩托车等，本发明实施例不作限定。
103、大数据分析系统在自身管辖范围内查找出该车位类型对应大小的所有空闲停车位，将查找出的所有空闲停车位的位置标识发送给无线车载终端，以使无线车载终端所在车辆的驾驶员以查找出的所有空闲停车位的位置标识为依据，从查找出的所有空闲停车中选择任一个空闲停车位作为目标停车位。
本发明实施例中，空闲停车位的位置标识可以包括空闲停车位的编号以及空闲停车位所在的停车场名称或街道名称。
在实际应用中，摩托车对应大小的停车位小于轿车对应大小的停车位，而轿车对应大小的停车位小于载货车对应大小的停车位，而载货车对应大小的停车位小于客车对应大小的停车位，而客车对应大小的停车位小于挂车对应大小的停车位。
104、大数据分析系统生成目标停车位与当前车辆位置之间的导航路径，并将导航路径发送给无线车载终端进行停车导航。
105、大数据分析系统根据车辆在目标停车位的实际停车时长，从无线车载终端绑定的电子账号中扣除相应的停车费用。
作为一种可选的实施方式，大数据分析系统根据车辆在目标停车位的实际停车时长，从无线车载终端绑定的电子账号中扣除相应的停车费用的方式可以为：
大数据分析系统可以辨别目标停车位是否属于按预设时段出租的停车位，如果目标停车位不属于按预设时段出租的停车位，可以按照目标停车位对应的普通收费规则以及实际停车时长计算相应的停车费用，其中，普通收费规则包括单位时间对应的第一收费金额；
如果目标停车位属于按预设时段出租的停车位，判断车辆在目标停车位的实际停车时长是否超出预设时段，如果未超出预设时段，按照目标停车位对应的普通收费规则以及实际停车时长计算相应的停车费用；
如果超过预设时段，可以按照目标停车位对应的高额收费规则以及实际停车时长计算相应的停车费用，其中，高额收费规则包括单位时间对应的第二收费金额，并且第二收费金额等于若干倍数的第一收费金额；以及，从无线车载终端绑定的电子账号中扣除相应的停车费用。
其中，实施这种可选的实施方式，可以鼓励驾驶员在其车辆停放时长超出目标停车位预设的出租时段之前，及时将车辆驶离目标停车位置，以免导致巨额的停车费用。
本发明实施例中，每一个空闲的停车位可以按预设时段进行出租，也即是说，每一个空闲的停车位可以预设出租时长(例如08：30～18：00)。举例来说，某一车主在早上8点钟开车上班之后，车主可以将其空闲的停车位进行出租，并车主可以向大数据分析系统上报车主为其空闲的停车位预设的出租时长(例如08：30～18：00)。
可见，实施图1所描述的方法，不仅可以准确的将车辆导航至驾驶员自选的最适合车辆大小的停车位，还可以实现无人停车收费，提高收费管理效率。
可见，实施图1所描述的方法，可以精确的识别出驾驶员的眼睛是否疲劳，以及可以精确的识别出驾驶员的情绪是否稳定。
可见，实施图1所描述的方法，可以鼓励驾驶员在其车辆停放时长超出目标停车位预设的出租时段之前，及时将车辆驶离目标停车位置，以免导致巨额的停车费用。
实施例二
请参阅图3，图3是本发明实施例公开的另一种基于自选车位的停车收费管控方法的流程示意图。如图3所示，该基于自选车位的停车收费管控方法可以包括以下步骤：
301、无线车载终端将无线车载终端所在车辆的当前车辆位置以及车辆的车辆标识上报给大数据分析系统。
作为一种可选的实施方式，无线车载终端将无线车载终端所在车辆的当前车辆位置以及车辆的车辆标识上报给大数据分析系统之前，无线车载终端还可以执行以下步骤：
无线车载终端识别无线车载终端所在车辆的驾驶员的情绪是否稳定，如果情绪不稳定，无线车载终端提示驾驶员停车；如果情绪稳定，无线车载终端每隔指定时间(如120毫秒)采集一帧驾驶员的人脸图像，并从人脸图像中确定出人眼定位矩形，计算人眼定位矩形的面积，根据阈值判断驾驶员的 眼睛的睁闭程度，以及根据驾驶员的眼睛的睁闭程度评价出人眼疲劳程度值，基于人眼疲劳程度值判断驾驶员的眼睛是否疲劳，如果疲劳，无线车载终端提示驾驶员停车，而驾驶员可以根据提示向无线车载终端输入停车位搜索指令，从而可以避免因驾驶员的眼睛疲劳或情绪不稳定而容易发生驾驶事故；
以及，无线车载终端检测所述无线车载终端所在车辆的驾驶员输入的停车位搜索指令，采集当前车辆位置。
作为一种可选的实施方式，无线车载终端采集当前车辆位置的方式可以为：
无线车载终端获取无线车载终端配置的至少两个不同的定位接口；举例来说，至少两个不同的定位接口可以包括百度的nlpservice定位接口、高德的nlpservice定位接口、谷歌的nlpservice定位接口等，本发明实施例不作限定；以及，无线车载终端可以将定位请求发送至上述至少两个不同的定位接口，以触发每个定位接口分别将接收到的定位请求发送给各自对应的定位服务器；以及，获取至少一个定位接口对应的定位服务器发送的位置信息，并获取从第一时刻到第二时刻的响应时间，第一时刻为每个定位接口发送定位请求的时刻，第二时刻为每个定位接口接收到位置信息的时刻；以及，将与每个定位接口对应的响应时间与响应阈值进行比较，并从响应时间未超过响应阈值的定位接口所接收的位置信息中提取定位精度最高的位置信息作为当前车辆位置。
本发明实施例中，实施上述实施方式可以精确的获取停车位置，提高定位精确度。
作为一种可选的实施方式，无线车载终端识别无线车载终端所在车辆的驾驶员的情绪是否稳定的方式可以为：
无线车载终端检测无线车载终端所在车辆的驾驶员佩戴的穿戴设备(如手环)发送的驾驶员的心电图数据；举例来说，无线车载终端可以检测无线车载终端所在车辆的行驶时长是否超过预设时长，如果超过预设时长，无线车载终端可以检测无线车载终端是否与无线车载终端所在车辆的驾驶员佩戴的穿戴设备(如手环)建立通讯连接，如果是，无线车载终端可以通知驾驶员佩戴的穿戴设备向无线车载终端发送驾驶员的心电图数据；
以及，无线车载终端可以对心电图数据进行去噪处理，并采用心电图R波提取算法提取经过去噪处理的心电图数据中的R波峰值，以及计算经过去噪处理的心电图数据中相邻R波之间RR间距；以及，计算RR间距的频域指标、时域指标及非线性指标；其中，频域指标包括副交感神经活性指标，时域指标包括短程心率变动性指标；短程心率变动性指标通过获取RR间距差值平方和的均方根来计算；副交感神经活性指标通过快速傅里叶变换来计算；非线性指标通过分形维数计算方法来计算；
以及，无线车载终端可以根据频域指标、时域指标及非线性指标，分析该用户的情绪的活力值；其中，活力值为根据时域指标、频域指标及非线性指标建立的多元线性回归方程计算得到的值；以及，根据活力值识别该用户的情绪是否不稳定。
本发明实施例中，实施上述实施方式可以精确的识别出驾驶员的情绪是否稳定。
302、大数据分析系统根据车辆标识辨别出车辆的车辆类型，并根据车辆类型辨别出车辆类型适用的车位类型。
本发明实施例中，车辆类型可以包括轿车、载货车、客车、挂车、摩托车等，本发明实施例不作限定。
303、大数据分析系统在自身管辖范围内查找出该车位类型对应大小的所有空闲停车位，将查找出的所有空闲停车位的位置标识发送给无线车载终端，以使无线车载终端所在车辆的驾驶员以查找出的所有空闲停车位的位置标识为依据，从查找出的所有空闲停车中选择任一个空闲停车位作为目标停车位。
在实际应用中，摩托车对应大小的停车位小于轿车对应大小的停车位，而轿车对应大小的停车位小于载货车对应大小的停车位，而载货车对应大小的停车位小于客车对应大小的停车位，而客车对应大小的停车位小于挂车对应大小的停车位。
304、大数据分析系统生成目标停车位与当前车辆位置之间的导航路径，并将导航路径发送给无线车载终端进行停车导航。
305、大数据分析系统判断大数据分析系统的当前工作负荷是否超过大数据分析系统指定的工作负荷，如果未超过，通过天气信息查询端口向天气信息查询端口对应的天气服务平台发起包括目标停车位的天气信息查询请求，以及，接收天气服务平台通过天气信息查询端口返回的目标停车位对应的预设时长的天气信息。
306、大数据分析系统将目标停车位对应的预设时长的天气信息下发给无线车载终端，从而使得驾驶员可以根据天气信息做好停车时的车辆防护准备，以免车辆被恶劣天气造成损伤。
307、大数据分析系统根据车辆在目标停车位的实际停车时长，从无线车载终端绑定的电子账号中扣除相应的停车费用。
作为一种可选的实施方式，大数据分析系统根据车辆在目标停车位的实际停车时长，从无线车载终端绑定的电子账号中扣除相应的停车费用的方式可以为：
大数据分析系统可以辨别目标停车位是否属于按预设时段出租的停车位，如果目标停车位不属于按预设时段出租的停车位，可以按照目标停车位对应的普通收费规则以及实际停车时长计算相应的停车费用，其中，普通收费规则包括单位时间对应的第一收费金额；
如果目标停车位属于按预设时段出租的停车位，判断车辆在目标停车位的实际停车时长是否超出预设时段，如果未超出预设时段，按照目标停车位对应的普通收费规则以及实际停车时长计算相应的停车费用；
如果超过预设时段，可以按照目标停车位对应的高额收费规则以及实际停车时长计算相应的停车费用，其中，高额收费规则包括单位时间对应的第二收费金额，并且第二收费金额等于若干倍数的第一收费金额；以及，从无线车载终端绑定的电子账号中扣除相应的停车费用。
其中，实施这种可选的实施方式，可以鼓励驾驶员在其车辆停放时长超出目标停车位预设的出租时段之前，及时将车辆驶离目标停车位置，以免导致巨额的停车费用。
本发明实施例中，每一个空闲的停车位可以按预设时段进行出租，也即是说，每一个空闲的停车位可以预设出租时长(例如08：30～18：00)。举例来说，某一车主在早上8点钟开车上班之后，车主可以将其空闲的停车位进行出租，并车主可以向大数据分析系统上报车主为其空闲的停车位预设的出租时长(例如08：30～18：00)。
可见，实施图3所描述的方法，不仅可以准确的将车辆导航至驾驶员自选的最适合车辆大小的停车位，还可以实现无人停车收费，提高收费管理效率。
可见，实施图3所描述的方法，可以精确的识别出驾驶员的眼睛是否疲劳，以及可以精确的识别出驾驶员的情绪是否稳定。
可见，实施图3所描述的方法，可以鼓励驾驶员在其车辆停放时长超出目标停车位预设的出租时段之前，及时将车辆驶离目标停车位置，以免导致巨额的停车费用。
可见，实施图3所描述的方法，驾驶员可以根据天气信息做好停车时的车辆防护准备，以免车辆被恶劣天气造成损伤。
实施例三
请参阅图4，图4是本发明实施例公开的一种基于自选车位的停车收费管控系统的结构示意图。如图4所示，该系统可以包括：
无线车载终端401和大数据分析系统402，其中：
无线车载终端401，用于将无线车载终端401所在车辆的当前车辆位置以及车辆的车辆标识上报给大数据分析系统402；
大数据分析系统402，用于根据车辆标识辨别出车辆的车辆类型，并根据车辆类型辨别出车辆类型适用的车位类型；
大数据分析系统402，还用于在自身管辖范围内查找出该车位类型对应大小的所有空闲停车位，将查找出的所有空闲停车位的位置标识发送给无线车载终端401，以使无线车载终端401所在车辆的驾驶员以查找出的所有空闲停车位的位置标识为依据，从查找出的所有空闲停车中选择任一个空闲停车位作为目标停车位；
大数据分析系统402，还用于生成目标停车位与当前车辆位置之间的导航路径，并将导航路径发送给无线车载终端401进行停车导航；
大数据分析系统402，还用于根据车辆在目标停车位的实际停车时长，从无线车载终端401绑定的电子账号中扣除相应的停车费用。
作为一种可选的实施方式，在图4所示的基于自选车位的停车收费管控系统中：
无线车载终端401，还用于在将无线车载终端401所在车辆的当前车辆位置以及车辆的车辆标识上报给大数据分析系统之前，识别无线车载终端所在车辆的驾驶员的情绪是否稳定，如果情绪不稳定，提示驾驶员停车；如果 情绪稳定，每隔指定时间采集一帧驾驶员的人脸图像，并从人脸图像中确定出人眼定位矩形，计算人眼定位矩形的面积，根据阈值判断驾驶员的眼睛的睁闭程度，以及根据驾驶员的眼睛的睁闭程度评价出人眼疲劳程度值，基于人眼疲劳程度值判断驾驶员的眼睛是否疲劳，如果疲劳，提示驾驶员停车；以及，检测无线车载终端所在车辆的驾驶员输入的停车位搜索指令，采集当前车辆位置。
作为一种可选的实施方式，在图4所示的基于自选车位的停车收费管控系统中：无线车载终端401识别无线车载终端401所在车辆的驾驶员的情绪是否稳定的方式具体为：
无线车载终端401，用于检测无线车载终端所在车辆的驾驶员佩戴的穿戴设备发送的驾驶员的心电图数据；对心电图数据进行去噪处理；采用心电图R波提取算法提取经过去噪处理的心电图数据中的R波峰值，以及计算经过去噪处理的心电图数据中相邻R波之间RR间距；计算RR间距的频域指标、时域指标及非线性指标；其中，频域指标包括副交感神经活性指标，时域指标包括短程心率变动性指标；短程心率变动性指标通过获取RR间距差值平方和的均方根来计算；副交感神经活性指标通过快速傅里叶变换来计算；非线性指标通过分形维数计算方法来计算；根据频域指标、时域指标及非线性指标，分析用户的情绪的活力值；活力值为根据时域指标、频域指标及非线性指标建立的多元线性回归方程计算得到的值；根据活力值识别驾驶员的情绪是否不稳定。
作为一种可选的实施方式，在图4所示的基于自选车位的停车收费管控系统中：无线车载终端401将无线车载终端所在车辆的当前车辆位置以及车辆的车辆标识上报给大数据分析系统的方式具体为：
无线车载终端401，用于扫描周围环境中是否预先设置有路由节点，如果预先设置有路由节点，检测路由节点是否被配置有开放接入时段，如果路由节点被配置有开放接入时段，识别无线车载终端的当前系统时间是否位于路由节点被配置的开放接入时段内；如果无线车载终端的当前系统时间位于路由节点被配置的开放接入时段内，检测路由节点的当前接入的终端数量是否超过路由节点指定的最大终端接入数量；如果路由节点的当前接入的终端数量未超过路由节点指定的最大终端接入数量，建立与路由节点之间的无线连接，并且将无线车载终端所在车辆的当前车辆位置以及车辆的车辆标识发送给路由节点，由路由节点将无线车载终端所在车辆的当前车辆位置以及车辆的车辆标识发送给大数据分析系统。
作为一种可选的实施方式，在图4所示的基于自选车位的停车收费管控系统中：
大数据分析系统402，还用于在生成目标停车位与当前车辆位置之间的导航路径，并将导航路径发送给无线车载终端进行停车导航之后，判断大数据分析系统的当前工作负荷是否超过大数据分析系统指定的工作负荷，如果大数据分析系统的当前工作负荷未超过大数据分析系统指定的工作负荷，通过天气信息查询端口向天气信息查询端口对应的天气服务平台发起包括目标 停车位的天气信息查询请求；接收天气服务平台通过天气信息查询端口返回的目标停车位对应的预设时长的天气信息；将目标停车位对应的预设时长的天气信息下发给无线车载终端；其中，大数据分析系统402根据车辆在目标停车位的实际停车时长，从无线车载终端绑定的电子账号中扣除相应的停车费用的方式具体为：
大数据分析系统402，用于辨别目标停车位是否属于按预设时段出租的停车位，如果目标停车位不属于按预设时段出租的停车位，按照目标停车位对应的普通收费规则以及实际停车时长计算相应的停车费用，普通收费规则包括单位时间对应的第一收费金额；如果目标停车位属于按预设时段出租的停车位，判断车辆在目标停车位的实际停车时长是否超出预设时段，如果未超出预设时段，按照目标停车位对应的普通收费规则以及实际停车时长计算相应的停车费用；如果超过预设时段，按照目标停车位对应的高额收费规则以及实际停车时长计算相应的停车费用，高额收费规则包括单位时间对应的第二收费金额，并且第二收费金额等于若干倍数的第一收费金额；以及，从无线车载终端绑定的电子账号中扣除相应的停车费用。
可见，实施图4所描述的系统，不仅可以准确的将车辆导航至驾驶员自选的最适合车辆大小的停车位，还可以实现无人停车收费，提高收费管理效率。可见，实施图4所描述的系统，可以精确的识别出驾驶员的眼睛是否疲劳，以及可以精确的识别出驾驶员的情绪是否稳定。可见，实施图4所描述的系统，可以鼓励驾驶员在其车辆停放时长超出目标停车位预设的出租时段之前，及时将车辆驶离目标停车位置，以免导致巨额的停车费用。可见，实施图4所描述的系统，驾驶员可以根据天气信息做好停车时的车辆防护准备，以免车辆被恶劣天气造成损伤。
本领域普通技术人员可以理解上述实施例的各种方法中的全部或部分步骤是可以通过程序来指令相关的硬件来完成，该程序可以存储于一计算机可读存储介质中，存储介质包括只读存储器(Read-Only Memory，ROM)、随机存储器(Random Access Memory，RAM)、可编程只读存储器(Programmable Read-only Memory，PROM)、可擦除可编程只读存储器(Erasable Programmable Read Only Memory，EPROM)、一次可编程只读存储器(One-time Programmable Read-Only Memory，OTPROM)、电子抹除式可复写只读存储器(Electrically-Erasable Programmable Read-Only Memory，EEPROM)、只读光盘(Compact Disc Read-Only Memory，CD-ROM)或其他光盘存储器、磁盘存储器、磁带存储器、或者能够用于携带或存储数据的计算机可读的任何其他介质。
以上对本发明实施例公开的一种基于自选车位的停车收费管控方法及系统进行了详细介绍，本文中应用了具体个例对本发明的原理及实施方式进行了阐述，以上实施例的说明只是用于帮助理解本发明的方法及其核心思想；同时，对于本领域的一般技术人员，依据本发明的思想，在具体实施方式及应用范围上均会有改变之处，综上所述，本说明书内容不应理解为对本发明的限制。

Claims (10)

  1. 一种基于自选车位的停车收费管控方法，其特征在于，包括：
    无线车载终端将所述无线车载终端所在车辆的当前车辆位置以及所述车辆的车辆标识上报给大数据分析系统；
    所述大数据分析系统根据所述车辆标识辨别出所述车辆的车辆类型，并根据所述车辆类型辨别出所述车辆类型适用的车位类型；
    所述大数据分析系统在自身管辖范围内查找出所述车位类型对应大小的所有空闲停车位，将查找出的所有空闲停车位的位置标识发送给所述无线车载终端，以使所述无线车载终端所在车辆的驾驶员以所述所有空闲停车位的位置标识为依据，从查找出的所有空闲停车中选择任一个空闲停车位作为目标停车位；
    所述大数据分析系统生成所述目标停车位与所述当前车辆位置之间的导航路径，并将所述导航路径发送给所述无线车载终端进行停车导航；
    所述大数据分析系统根据所述车辆在所述目标停车位的实际停车时长，从无线车载终端绑定的电子账号中扣除相应的停车费用。
  2. 根据权利要求1所述的基于自选车位的停车收费管控方法，其特征在于，所述无线车载终端将所述无线车载终端所在车辆的当前车辆位置以及所述车辆的车辆标识上报给大数据分析系统之前，所述方法还包括：
    所述无线车载终端识别所述无线车载终端所在车辆的驾驶员的情绪是否稳定，如果情绪不稳定，无线车载终端提示驾驶员停车；如果情绪稳定，所述无线车载终端每隔指定时间采集一帧所述驾驶员的人脸图像，并从所述人脸图像中确定出人眼定位矩形，计算所述人眼定位矩形的面积，根据阈值判断所述驾驶员的眼睛的睁闭程度，以及根据所述驾驶员的眼睛的睁闭程度评价出人眼疲劳程度值，基于所述人眼疲劳程度值判断所述驾驶员的眼睛是否疲劳，如果疲劳，所述无线车载终端提示驾驶员停车；
    所述无线车载终端检测所述无线车载终端所在车辆的驾驶员输入的停车位搜索指令，采集当前车辆位置。
  3. 根据权利要求2所述的基于自选车位的停车收费管控方法，其特征在于，所述无线车载终端识别所述无线车载终端所在车辆的驾驶员的情绪是否稳定，包括：
    所述无线车载终端检测所述无线车载终端所在车辆的驾驶员佩戴的穿戴设备发送的所述驾驶员的心电图数据；
    所述无线车载终端对所述心电图数据进行去噪处理；
    所述无线车载终端采用心电图R波提取算法提取经过去噪处理的心电图数据中的R波峰值，以及计算所述经过去噪处理的心电图数据中相邻R波之间RR间距；
    所述无线车载终端计算所述RR间距的频域指标、时域指标及非线性指 标；其中，所述频域指标包括副交感神经活性指标，所述时域指标包括短程心率变动性指标；所述短程心率变动性指标通过获取所述RR间距差值平方和的均方根来计算；所述副交感神经活性指标通过快速傅里叶变换来计算；所述非线性指标通过分形维数计算方法来计算；
    所述无线车载终端根据所述频域指标、时域指标及非线性指标，分析所述用户的情绪的活力值；所述活力值为根据所述时域指标、频域指标及非线性指标建立的多元线性回归方程计算得到的值；
    所述无线车载终端根据所述活力值识别所述驾驶员的情绪是否不稳定。
  4. 根据权利要求1～3任一项所述的基于自选车位的停车收费管控方法，其特征在于，所述无线车载终端将所述无线车载终端所在车辆的当前车辆位置以及所述车辆的车辆标识上报给大数据分析系统，包括：
    所述无线车载终端扫描周围环境中是否预先设置有路由节点，如果预先设置有所述路由节点，检测所述路由节点是否被配置有开放接入时段，如果所述路由节点被配置有所述开放接入时段，识别所述无线车载终端的当前系统时间是否位于所述路由节点被配置的所述开放接入时段内；
    如果所述无线车载终端的当前系统时间位于所述路由节点被配置的所述开放接入时段内，检测所述路由节点的当前接入的终端数量是否超过所述路由节点指定的最大终端接入数量；
    如果所述路由节点的当前接入的终端数量未超过所述路由节点指定的最大终端接入数量，所述无线车载终端建立与所述路由节点之间的无线连接，并且将所述无线车载终端所在车辆的当前车辆位置以及所述车辆的车辆标识发送给所述路由节点，由所述路由节点将所述无线车载终端所在车辆的当前车辆位置以及所述车辆的车辆标识发送给所述大数据分析系统。
  5. 根据权利要求1～4所述的基于自选车位的停车收费管控方法，其特征在于，所述大数据分析系统生成所述目标停车位与所述当前车辆位置之间的导航路径，并将所述导航路径发送给所述无线车载终端进行停车导航之后，所述方法还包括:
    所述大数据分析系统判断所述大数据分析系统的当前工作负荷是否超过所述大数据分析系统指定的工作负荷；
    如果所述大数据分析系统的当前工作负荷未超过所述大数据分析系统指定的工作负荷，所述大数据分析系统通过天气信息查询端口向所述天气信息查询端口对应的天气服务平台发起包括所述目标停车位的天气信息查询请求；
    以及，所述大数据分析系统接收所述天气服务平台通过所述天气信息查询端口返回的所述目标停车位对应的预设时长的天气信息；
    以及，所述大数据分析系统将所述目标停车位对应的预设时长的天气信 息下发给所述无线车载终端；
    其中，所述大数据分析系统根据所述车辆在所述目标停车位的实际停车时长，从无线车载终端绑定的电子账号中扣除相应的停车费用，包括：
    所述大数据分析系统辨别所述目标停车位是否属于按预设时段出租的停车位，如果所述目标停车位不属于按预设时段出租的停车位，按照所述目标停车位对应的普通收费规则以及所述实际停车时长计算相应的停车费用，所述普通收费规则包括单位时间对应的第一收费金额；如果所述目标停车位属于按预设时段出租的停车位，判断所述车辆在所述目标停车位的实际停车时长是否超出所述预设时段，如果未超出所述预设时段，按照所述目标停车位对应的普通收费规则以及所述实际停车时长计算相应的停车费用；如果超过所述预设时段，按照所述目标停车位对应的高额收费规则以及所述实际停车时长计算相应的停车费用，所述高额收费规则包括单位时间对应的第二收费金额，并且所述第二收费金额等于若干倍数的所述第一收费金额；以及，从无线车载终端绑定的电子账号中扣除所述相应的停车费用。
  6. 一种基于自选车位的停车收费管控系统，其特征在于，包括无线车载终端和大数据分析系统，其中：
    所述无线车载终端，用于将所述无线车载终端所在车辆的当前车辆位置以及所述车辆的车辆标识上报给大数据分析系统；
    所述大数据分析系统，用于根据所述车辆标识辨别出所述车辆的车辆类型，并根据所述车辆类型辨别出所述车辆类型适用的车位类型；
    所述大数据分析系统，还用于在自身管辖范围内查找出所述车位类型对应大小的所有空闲停车位，将查找出的所有空闲停车位的位置标识发送给所述无线车载终端，以使所述无线车载终端所在车辆的驾驶员以所述所有空闲停车位的位置标识为依据，从查找出的所有空闲停车中选择任一个空闲停车位作为目标停车位；
    所述大数据分析系统，还用于生成所述目标停车位与所述当前车辆位置之间的导航路径，并将所述导航路径发送给所述无线车载终端进行停车导航；
    所述大数据分析系统，还用于根据所述车辆在所述目标停车位的实际停车时长，从无线车载终端绑定的电子账号中扣除相应的停车费用。
  7. 根据权利要求6所述的基于自选车位的停车收费管控系统，其特征在于：
    所述无线车载终端，还用于在将所述无线车载终端所在车辆的当前车辆位置以及所述车辆的车辆标识上报给大数据分析系统之前，识别所述无线车载终端所在车辆的驾驶员的情绪是否稳定，如果情绪不稳定，提示驾驶员停车；如果情绪稳定，每隔指定时间采集一帧所述驾驶员的人脸图像，并从所述人脸图像中确定出人眼定位矩形，计算所述人眼定位矩形的面积，根据阈 值判断所述驾驶员的眼睛的睁闭程度，以及根据所述驾驶员的眼睛的睁闭程度评价出人眼疲劳程度值，基于所述人眼疲劳程度值判断所述驾驶员的眼睛是否疲劳，如果疲劳，提示驾驶员停车；以及，检测所述无线车载终端所在车辆的驾驶员输入的停车位搜索指令，采集当前车辆位置。
  8. 根据权利要求7所述的基于自选车位的停车收费管控系统，其特征在于，所述无线车载终端识别所述无线车载终端所在车辆的驾驶员的情绪是否稳定的方式具体为：
    所述无线车载终端，用于检测所述无线车载终端所在车辆的驾驶员佩戴的穿戴设备发送的所述驾驶员的心电图数据；对所述心电图数据进行去噪处理；采用心电图R波提取算法提取经过去噪处理的心电图数据中的R波峰值，以及计算所述经过去噪处理的心电图数据中相邻R波之间RR间距；计算所述RR间距的频域指标、时域指标及非线性指标；其中，所述频域指标包括副交感神经活性指标，所述时域指标包括短程心率变动性指标；所述短程心率变动性指标通过获取所述RR间距差值平方和的均方根来计算；所述副交感神经活性指标通过快速傅里叶变换来计算；所述非线性指标通过分形维数计算方法来计算；根据所述频域指标、时域指标及非线性指标，分析所述用户的情绪的活力值；所述活力值为根据所述时域指标、频域指标及非线性指标建立的多元线性回归方程计算得到的值；根据所述活力值识别所述驾驶员的情绪是否不稳定。
  9. 根据权利要求6～8任一项所述的基于自选车位的停车收费管控系统，其特征在于，所述无线车载终端将所述无线车载终端所在车辆的当前车辆位置以及所述车辆的车辆标识上报给大数据分析系统的方式具体为：
    所述无线车载终端，用于扫描周围环境中是否预先设置有路由节点，如果预先设置有所述路由节点，检测所述路由节点是否被配置有开放接入时段，如果所述路由节点被配置有所述开放接入时段，识别所述无线车载终端的当前系统时间是否位于所述路由节点被配置的所述开放接入时段内；如果所述无线车载终端的当前系统时间位于所述路由节点被配置的所述开放接入时段内，检测所述路由节点的当前接入的终端数量是否超过所述路由节点指定的最大终端接入数量；如果所述路由节点的当前接入的终端数量未超过所述路由节点指定的最大终端接入数量，建立与所述路由节点之间的无线连接，并且将所述无线车载终端所在车辆的当前车辆位置以及所述车辆的车辆标识发送给所述路由节点，由所述路由节点将所述无线车载终端所在车辆的当前车辆位置以及所述车辆的车辆标识发送给所述大数据分析系统。
  10. 根据权利要求6～9所述的基于自选车位的停车收费管控系统，其特征在于：
    所述大数据分析系统，还用于在生成所述目标停车位与所述当前车辆位 置之间的导航路径，并将所述导航路径发送给所述无线车载终端进行停车导航之后，判断所述大数据分析系统的当前工作负荷是否超过所述大数据分析系统指定的工作负荷，如果所述大数据分析系统的当前工作负荷未超过所述大数据分析系统指定的工作负荷，通过天气信息查询端口向所述天气信息查询端口对应的天气服务平台发起包括所述目标停车位的天气信息查询请求；接收所述天气服务平台通过所述天气信息查询端口返回的所述目标停车位对应的预设时长的天气信息；将所述目标停车位对应的预设时长的天气信息下发给所述无线车载终端；
    其中，所述大数据分析系统根据所述车辆在所述目标停车位的实际停车时长，从无线车载终端绑定的电子账号中扣除相应的停车费用的方式具体为：
    所述大数据分析系统，用于辨别所述目标停车位是否属于按预设时段出租的停车位，如果所述目标停车位不属于按预设时段出租的停车位，按照所述目标停车位对应的普通收费规则以及所述实际停车时长计算相应的停车费用，所述普通收费规则包括单位时间对应的第一收费金额；如果所述目标停车位属于按预设时段出租的停车位，判断所述车辆在所述目标停车位的实际停车时长是否超出所述预设时段，如果未超出所述预设时段，按照所述目标停车位对应的普通收费规则以及所述实际停车时长计算相应的停车费用；如果超过所述预设时段，按照所述目标停车位对应的高额收费规则以及所述实际停车时长计算相应的停车费用，所述高额收费规则包括单位时间对应的第二收费金额，并且所述第二收费金额等于若干倍数的所述第一收费金额；以及，从无线车载终端绑定的电子账号中扣除所述相应的停车费用。
PCT/CN2017/099128 2017-06-19 2017-08-25 一种基于自选车位的停车收费管控方法及系统 Ceased WO2018232991A1 (zh)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN201710463082.7A CN107248310A (zh) 2017-06-19 2017-06-19 一种基于自选车位的停车收费管控方法及系统
CN201710463082.7 2017-06-19

Publications (1)

Publication Number Publication Date
WO2018232991A1 true WO2018232991A1 (zh) 2018-12-27

Family

ID=60019252

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2017/099128 Ceased WO2018232991A1 (zh) 2017-06-19 2017-08-25 一种基于自选车位的停车收费管控方法及系统

Country Status (2)

Country Link
CN (1) CN107248310A (zh)
WO (1) WO2018232991A1 (zh)

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111739337A (zh) * 2020-05-27 2020-10-02 深圳市元征科技股份有限公司 一种车位管理方法、服务器、用户终端及存储介质
US12346943B2 (en) 2019-04-30 2025-07-01 Pied Parker, Inc. Image-based parking recognition and navigation
US12493900B2 (en) 2018-12-28 2025-12-09 Pied Parker, Inc. Image-based parking recognition and navigation

Families Citing this family (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2019100272A1 (zh) * 2017-11-23 2019-05-31 华平智慧信息技术（深圳）有限公司 智慧城市路边停车方法及相关产品
CN111754643A (zh) * 2018-03-16 2020-10-09 西安艾润物联网技术服务有限责任公司 停车场收费分账方法、装置及计算机可读存储介质
CN108766014A (zh) * 2018-04-27 2018-11-06 甘应来 一种车辆管理方法
CN109191601B (zh) * 2018-10-30 2021-10-08 神州天衡科技(深圳)有限公司 智能停车管理方法、系统、存储介质及设备
CN110062353A (zh) * 2019-03-14 2019-07-26 西安艾润物联网技术服务有限责任公司 通信连接方法及相关设备
CN111915926A (zh) * 2020-08-14 2020-11-10 中国工商银行股份有限公司 停车位智能指引系统及方法
JP7552463B2 (ja) * 2021-03-17 2024-09-18 トヨタ自動車株式会社 制御装置、システム、及び制御方法

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2004030163A (ja) * 2002-06-25 2004-01-29 Nec Corp 駐車場利用情報提供・誘導方法およびシステム
CN201169238Y (zh) * 2008-07-02 2008-12-24 邓细波 一种汽车安全装置
CN103871270A (zh) * 2014-02-28 2014-06-18 张剑锋 基于云计算和大数据的停车方法和系统
CN104036659A (zh) * 2014-05-28 2014-09-10 江苏科技大学 一种停车场车位引导及管理系统及方法
CN106157681A (zh) * 2015-04-08 2016-11-23 腾石智能科技（上海）有限公司 停车区域管理系统及方法
CN106652506A (zh) * 2017-01-22 2017-05-10 斑马信息科技有限公司 停车管理方法及其管理系统

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101030316B (zh) * 2007-04-17 2010-04-21 北京中星微电子有限公司 一种汽车安全驾驶监控系统和方法
KR101372120B1 (ko) * 2011-06-23 2014-03-07 현대자동차주식회사 차량 운전자의 생체정보 획득 장치 및 그 방법
CN104867189A (zh) * 2015-04-29 2015-08-26 奇瑞汽车股份有限公司 一种停车场收费的方法和装置
CN105120430A (zh) * 2015-07-23 2015-12-02 小米科技有限责任公司 终端定位方法、装置及终端
CN106686537B (zh) * 2017-02-27 2020-07-03 广东小天才科技有限公司 一种基于nfc的信息交换方法及系统

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2004030163A (ja) * 2002-06-25 2004-01-29 Nec Corp 駐車場利用情報提供・誘導方法およびシステム
CN201169238Y (zh) * 2008-07-02 2008-12-24 邓细波 一种汽车安全装置
CN103871270A (zh) * 2014-02-28 2014-06-18 张剑锋 基于云计算和大数据的停车方法和系统
CN104036659A (zh) * 2014-05-28 2014-09-10 江苏科技大学 一种停车场车位引导及管理系统及方法
CN106157681A (zh) * 2015-04-08 2016-11-23 腾石智能科技（上海）有限公司 停车区域管理系统及方法
CN106652506A (zh) * 2017-01-22 2017-05-10 斑马信息科技有限公司 停车管理方法及其管理系统

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US12493900B2 (en) 2018-12-28 2025-12-09 Pied Parker, Inc. Image-based parking recognition and navigation
US12346943B2 (en) 2019-04-30 2025-07-01 Pied Parker, Inc. Image-based parking recognition and navigation
CN111739337A (zh) * 2020-05-27 2020-10-02 深圳市元征科技股份有限公司 一种车位管理方法、服务器、用户终端及存储介质
CN111739337B (zh) * 2020-05-27 2021-08-10 深圳市元征科技股份有限公司 一种车位管理方法、服务器、用户终端及存储介质

Also Published As

Publication number Publication date
CN107248310A (zh) 2017-10-13

Similar Documents

Publication Publication Date Title
WO2018233074A1 (zh) 一种停车导航路径的推荐系统及方法
CN107248310A (zh) 一种基于自选车位的停车收费管控方法及系统
WO2018233064A1 (zh) 一种基于驾驶员报价的停车引导方法及系统
WO2018233084A1 (zh) 基于驾驶员报价与自选出租车位的停车引导方法及系统
WO2018233003A1 (zh) 一种智慧城市的停车管理方法及系统
WO2018233000A1 (zh) 一种多停车场场景下的收费管理方法及系统
WO2018232994A1 (zh) 一种停车收费方法及系统
WO2018232993A1 (zh) 一种智能化的停车收费方法及系统
WO2018233002A1 (zh) 一种停车管理及收费一体化方法及系统
WO2018233081A1 (zh) 一种基于车场的停车诱导系统及方法
WO2018233086A1 (zh) 一种基于数据分析的停车引导系统及方法
WO2018232992A1 (zh) 一种无人管理式的停车收费系统及方法
WO2018233033A1 (zh) 一种户外停车的集中式管理方法及系统
WO2018233004A1 (zh) 一种停车管理方法及系统
WO2018233072A1 (zh) 一种结合天气信息的车辆停车引导系统及方法
WO2018232981A1 (zh) 一种临时路边停车引起的信息公告方法及系统
WO2018232995A1 (zh) 一种基于汇聚平台的停车管理方法及系统
WO2018233065A1 (zh) 一种停车位指引方法及系统
WO2018233047A1 (zh) 一种由停车引起的数据处理方法及系统
WO2018233073A1 (zh) 一种可自选车位的停车导航路径生成系统及方法
WO2018232988A1 (zh) 一种基于物联网接入点的信息发布方法及系统
WO2018233060A1 (zh) 一种报价与抢答相结合的停车引导方法及系统
WO2018233058A1 (zh) 一种基于期望停车时长的停车诱导方法及系统
WO2018233075A1 (zh) 一种停车位预订方法及系统
WO2018233085A1 (zh) 一种基于移动网络的车位预订方法及系统

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 17914554

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

32PN Ep: public notification in the ep bulletin as address of the adressee cannot be established

Free format text: NOTING OF LOSS OF RIGHTS PURSUANT TO RULE 112(1) EPC (EPO FORM1205 DATED 15/05/2020)

122 Ep: pct application non-entry in european phase

Ref document number: 17914554

Country of ref document: EP

Kind code of ref document: A1