CN108120999B - Vehicle-mounted navigation equipment and parking lot guiding method - Google Patents
Vehicle-mounted navigation equipment and parking lot guiding method Download PDFInfo
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- CN108120999B CN108120999B CN201711373825.8A CN201711373825A CN108120999B CN 108120999 B CN108120999 B CN 108120999B CN 201711373825 A CN201711373825 A CN 201711373825A CN 108120999 B CN108120999 B CN 108120999B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/20—Instruments for performing navigational calculations
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/20—Instruments for performing navigational calculations
- G01C21/206—Instruments for performing navigational calculations specially adapted for indoor navigation
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- 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
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- 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
Abstract
An in-vehicle navigation apparatus and a parking lot guidance method, the guidance method comprising: when the distance between the vehicle and the travel destination is within a preset range, obtaining expected parking time of parking lots around the destination, wherein the expected parking time of the parking lots around the destination is the parking time required by the vehicle to park in the parking lot on the same day and at the current time; the obtained expected parking time of the surrounding parking lot is provided to the user for selection by the user. The parking times specific to the day and the current time provided herein may give the user prompt guidance information that is more intuitive and more consistent with the user's actual needs than the vacancy information that has no direct relationship with the parking time. Therefore, the user experience is improved.
Description
Technical Field
The invention relates to development of navigation technology, in particular to vehicle-mounted navigation equipment and a parking lot guiding method.
Background
In the current navigation service, not only a route guidance service from a start point to an end point but also a route guidance service from an end point to a parking lot may be recommended to a user. However, the arrival of the user at the parking lot often does not mean that the purpose of parking is immediately achieved. For urban parking lots, particularly parking lots located in urban central areas, it has become common for users to wait in line at the entrances of these parking lots and to find a parking space in the parking lot. Thus, how to provide an effective parking lot guidance service in the navigation service has become a focus.
Most of the existing parking lot systems can provide dynamic vacant parking space information. However, when a user wants to achieve the purpose of parking as soon as possible, the information of the vacant parking spaces in the parking lots in the area where the user is located cannot provide a real and effective help for the user to select a proper parking lot.
Disclosure of Invention
The invention aims to provide vehicle-mounted navigation equipment and a parking lot guiding method, so that a user can obtain expectable and quantitative accurate parking prompt information.
In order to solve the above problem, the present invention provides a parking lot guidance method, including: when the distance between the vehicle and the travel destination is within a preset range, obtaining expected parking time of parking lots around the destination, wherein the expected parking time of the parking lots around the destination is the parking time required by the vehicle to park in the parking lot on the same day and at the current time; the obtained expected parking time of the surrounding parking lot is provided to the user for selection by the user.
The invention also provides vehicle-mounted navigation equipment which provides navigation service for a user according to a destination set by the user, wherein the vehicle-mounted navigation equipment integrates parking lot guide service in the navigation service by applying the parking lot guide method; the vehicle-mounted navigation equipment is connected with the vehicle networking communication box through a vehicle bus, and vehicle operation data are obtained from the vehicle networking communication box.
Compared with the prior art, the scheme has the following advantages: the parking times specific to the day and the current time provided herein may give the user prompt guidance information that is more intuitive and more consistent with the user's actual needs than the vacancy information that has no direct relationship with the parking time. Therefore, the user experience is improved.
Drawings
Fig. 1 is a schematic flow diagram of a parking lot guidance method according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of communication between an in-vehicle navigation device and an in-vehicle networking communication box according to an embodiment of the invention;
fig. 3 is a schematic diagram illustrating collection of vehicle operation data and issued parking time data in a parking lot guidance method according to an embodiment of the present invention;
fig. 4 is a schematic view of parking time, the current day, and the parking time required by each parking lot obtained by the parking lot guidance method according to the embodiment of the present invention.
Detailed Description
In the following description, numerous specific details are set forth in order to provide a more thorough understanding of the present invention to those skilled in the art. It will be apparent, however, to one skilled in the art that the present invention may be practiced without some of these specific details. Furthermore, it should be understood that the invention is not limited to the specific embodiments described. Rather, it is contemplated that the invention may be practiced with any combination of the following features and elements, whether or not they relate to different embodiments. Thus, the following aspects, features, embodiments and advantages are merely illustrative and should not be considered elements or limitations of the claims except where explicitly recited in a claim.
As mentioned in the background, the available parking space information provided by the current parking lot system does not give the user an intuitive help to select which parking lot to use. Generally, users want to achieve parking in parking lots in as short a time as possible. The time required for parking may vary depending on the internal structure of each parking lot, and the time required for parking in different time periods on different dates may vary for the same parking lot. Therefore, the most important reference factor for the user to select a parking lot for the purpose of parking is time.
And the parking lot guidance method of the present invention provides time information for refining classification to address this problem. Referring to fig. 1, a parking lot guidance method according to an embodiment of the present invention includes: step s10, when the distance between the vehicle and the travel destination is in a preset range, obtaining the expected parking time of the parking lots around the destination, wherein the expected parking time of the parking lots around the destination is the parking time required by the vehicle to park in the parking lot on the same day and the current time; step s20, the obtained expected parking time of the surrounding parking lot is provided to the user for selection by the user.
According to the embodiment of the present invention, the expected parking time of the parking lot around the destination can be obtained not depending on the parking lot system but depending on the operation data of the vehicle itself. Whether the vehicle is parked in a parking lot can be known from the last position of each trip, and the final action of parking in the parking lot is flameout. Therefore, the expected parking time of the parking lot around the destination can be obtained based on the key-off time and the vehicle position at the key-off time.
Referring to fig. 3, specifically, vehicle operation data is collected by the cloud server for each vehicle in a single driving trip, so as to obtain vehicle operation data of a large number of different vehicles in different historical trips. The collected vehicle operation data includes at least a vehicle location and a time-off. The vehicle position may be a GPS position or the position of other satellite positioning systems. The flame out time may be obtained from an engine system of the vehicle. Referring to fig. 2, in the case of the current mainstream vehicle configuration, such vehicle operation data can be generally obtained through a Telematics Box (generally referred to as a T-Box). The internet of vehicles communication box is connected to a vehicle bus (e.g., CAN) to obtain data uploaded to the vehicle bus from various vehicle subsystems.
As described above, it is possible to know whether the vehicle is parked at a certain parking lot through the last position of each trip. In essence, it is known whether or not the vehicle is parked in a parking lot from the position where the vehicle is turned off. For the vehicle operation data of a certain vehicle in a certain travel, after the flameout time is obtained, the vehicle position of the time is the position when flameout occurs. The vehicle operation data associated with each parking lot can be obtained by individually collecting the vehicle operation data of each parking lot to which the position at the time of key-off belongs. Assuming that the position at the time of key-off among the large amount of collected vehicle operation data points to 10 parking lots, the vehicle operation data associated with the 10 parking lots can be obtained after the aggregation.
Next, vehicle operation data associated with each parking lot is modeled by the cloud server. Taking the vehicle operation data associated with any one of the parking lots as an example, the parking time history data for the parking lot is obtained by calculating the vehicle operation data. The parking time history data may be obtained in two ways.
The first method is as follows: for an indoor parking lot, the vehicle speed is considered to be low when the vehicle searches for a parking space in the parking lot and parks in a garage, and the vehicle position belongs to the parking lot at the moment. Therefore, when the vehicle speed of the vehicle is lower than a speed threshold (for example, 10 km/h) and the vehicle position during this time is in the parking lot, the time when the vehicle speed starts to be lower than the speed threshold (which may be regarded as the time of entering the parking lot) is taken as a calculation start point, and the stall time of the vehicle is taken as a calculation end point, and the parking time for the parking lot is obtained.
The second method comprises the following steps: for an outdoor parking lot, a virtual boundary may be set that triggers the calculation of parking time. The virtual boundary corresponds to an actual geographic location and is adjacent to the parking lot. When the vehicle reaches the virtual boundary, timing is started until the vehicle is turned off and the location at which the vehicle is turned off belongs to the parking lot. Thereby obtaining the parking time for the parking lot. With continued reference to fig. 3, in particular, the map area may be divided into a plurality of geo-fences, each of which covers a certain map area (e.g., a map area corresponding to a 1 km square range), and various places in the area of the region also belong to the geo-fence. The size of the map area covered by each geographic fence is generally the same. And after the geofence is divided, taking the time when the vehicle enters the geofence where the parking lot is located as a calculation starting point.
Because the dates and the times of different trips of each vehicle are different, after the parking time is obtained through calculation in the mode, a large amount of parking time historical data aiming at different dates and different time periods of the parking lot can be obtained. Therefore, a prediction model for predicting the parking time of the parking lot at each date and each time period can be trained according to the historical data in a machine learning mode.
The above-described obtaining of the prediction model may be processed by, for example:
first, a large amount of historical data obtained as described above is subjected to preliminary statistical analysis to obtain training data that can be used to import candidate model algorithms. The statistical analysis of this portion may employ a classification algorithm or a clustering algorithm to obtain training data from the large amount of historical data described above. For example, the obtained training data includes data of the longest parking time of a certain parking lot in a certain day, data of the parking time of a certain parking lot at 12 pm in each day, and the like. The classification algorithm may employ, for example, the KNN (K-Nearest Neighbor) algorithm, and the clustering algorithm may employ, for example, the K-means algorithm.
The method comprises the steps of setting two data sets, namely a test set and a verification set, putting training data (real data from historical data) into the verification set, then correspondingly importing proper data from the training data into one or more model algorithms, putting data of the predicted parking time output by the candidate model algorithms into the test set, evaluating the accuracy of the predicted parking time of the candidate model algorithms by comparing the data belonging to the same class in the verification set and the test set, and adjusting evaluation indexes used for evaluation according to actual conditions.
And finally, selecting the model algorithm with the accuracy most meeting the current requirement from the candidate model algorithms according to the various evaluation processes to serve as a prediction model. The prediction data can be obtained by importing specific time information into the prediction model. For example, the parking time required to park a car in a parking lot between 8 am on X days of the month can be predicted by the model.
Because the basis of the prediction model is a large amount of real historical data of finely divided dates and time periods, the predicted parking time has quite high accuracy. According to this method, a prediction model of the parking time of each parking lot can be obtained. The prediction models of the parking lots can be issued to the vehicles by the cloud server or stored in the cloud server.
The following will further describe the execution process of the parking lot guidance method of the present invention by taking the process from the beginning of a driving journey to the final arrival of parking at the parking lot as an example.
With reference to fig. 1, 3 and 4, by applying the setting of the geo-fence, after the user sets the travel destination, the geo-fence where the travel destination is located is determined, and then each neighboring geo-fence is obtained. Each adjacent geofence is contiguous with the boundary of the geofence on the map area where the travel destination is located. Then, the parking lot is found from each adjacent geo-fence. Assume here that there are a total of three parking lots (parking lot 1, parking lot 2, and parking lot 3) in all adjacent geofences.
When a vehicle enters a geographic fence of a travel destination, inputting the current day (X month and X day) and the current time (20 o' clock at night) into each corresponding prediction model of the parking lots 1-3 so as to respectively predict the expected parking time of the parking lots 1-3. For example, as shown in fig. 4, the expected parking time predicted by the prediction model of the parking lot 1 is 18 minutes, the expected parking time predicted by the prediction model of the parking lot 2 is 31 minutes, and the expected parking time predicted by the prediction model of the parking lot 3 is 40 minutes. The predicted expected parking times of the three parking lots are provided to the user for selection. The user can easily select the parking lot 1 to park by means of this intuitive expected parking time. The actual parking time in the parking lot 1 at this time can also be used as data for machine learning to continue training the prediction model for next parking time prediction. Therefore, the prediction accuracy of the prediction model is improved through continuous iteration.
The parking lot guidance method can also be integrated in the current vehicle navigation equipment as a software service. As shown with continued reference to fig. 2 and 3, the navigation device according to an embodiment of the present invention may integrate the above-described parking lot guidance method into a parking lot guidance service in the navigation service, in addition to providing the user with the navigation service according to the destination set by the user. The vehicle-mounted navigation equipment is connected with the vehicle networking communication box through a vehicle bus.
In a specific application example, the map built in the vehicle-mounted navigation device is divided into a plurality of geo-fences in advance. After obtaining a travel destination set by a user, the vehicle-mounted navigation device determines a geo-fence where the travel destination is located, and further finds information of each parking lot in adjacent geo-fences. The vehicle-mounted navigation device obtains real-time GPS data of the vehicle through the vehicle networking communication box to determine the current position of the vehicle. When the vehicle enters the geographic fence where the travel destination is located, the vehicle-mounted navigation equipment sends the information of the current day and the current time and the information of each parking lot to the cloud server through the vehicle networking communication box. And the cloud server selects the corresponding prediction model to predict the expected parking time of each parking lot and then issues the predicted parking time to each vehicle. The vehicle-mounted navigation equipment obtains expected parking time through the vehicle networking communication box and then presents the expected parking time to a user through a display screen of the vehicle-mounted navigation equipment. When the user selects a certain parking lot, the vehicle-mounted navigation device can continue to plan a path from the current position of the vehicle to the parking lot selected by the user, and further provide path navigation service.
Although the present invention has been described with reference to the preferred embodiments, it is not limited thereto. Various changes and modifications within the spirit and scope of the present invention will become apparent to those skilled in the art from this disclosure, and it is intended that the scope of the present invention be defined by the appended claims.
Claims (6)
1. A parking lot guidance method, comprising: when the distance between the vehicle and the travel destination is within a preset range, obtaining expected parking time of parking lots around the destination, wherein the expected parking time of the parking lots around the destination is the parking time required by the vehicle to park in the parking lot on the same day and the current time; providing the obtained expected parking time of the surrounding parking lot to the user for selection by the user;
wherein the expected parking time of the peripheral parking lot is obtained by: collecting vehicle operation data of a plurality of vehicles in different historical trips, wherein the vehicle operation data at least comprises vehicle positions and flameout time; according to the flameout time, respectively collecting the vehicle operation data of the vehicle position belonging to each parking lot when the flameout time is carried out so as to obtain the vehicle operation data related to each parking lot; obtaining parking time history data for each parking lot with flameout time as a calculation destination for vehicle operation data associated with the parking lot; training a prediction model for predicting the parking time of the parking lot at each date and each time period according to the historical data of the parking time of the parking lot at different dates and different time periods; and predicting the expected parking time of the parking lot by using the prediction model.
2. The parking lot guidance method according to claim 1, wherein the map area is divided into a plurality of geo-fences, and when the vehicle enters the geo-fence where the travel destination is located, expected parking times of the parking lots in the respective geo-fences adjacent to the geo-fence where the destination is located are acquired.
3. The parking lot guidance method according to claim 1, wherein an actual parking time of the parking lot on the present trip is used as history data for establishing a prediction model for predicting a next parking time of the parking lot.
4. The parking lot guidance method according to claim 1, wherein the history data of the parking time for the parking lot is obtained by any one of: dividing a map area into a plurality of geo-fences, taking the time of a vehicle entering the geo-fence where the parking lot is located as a calculation starting point, and taking the flameout time of the vehicle as a calculation terminal point to obtain parking time; or when the vehicle speed of the vehicle is lower than the speed threshold value and the vehicle position is in the parking lot in the period, taking the time when the vehicle speed starts to be lower than the speed threshold value as a calculation starting point and taking the flameout time of the vehicle as a calculation end point, and obtaining the parking time.
5. The parking lot guidance method according to claim 2 or 4, wherein the size of the map area covered by each of the geo-fences is the same.
6. An in-vehicle navigation apparatus that provides a navigation service to a user according to a destination set by the user, characterized in that the in-vehicle navigation apparatus integrates a parking lot guidance service in the navigation service by applying the parking lot guidance method according to any one of claims 1 to 5; the vehicle-mounted navigation equipment is connected with the vehicle networking communication box through a vehicle bus.
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Families Citing this family (8)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN110674962A (en) * | 2018-07-03 | 2020-01-10 | 百度在线网络技术（北京）有限公司 | Vehicle journey prediction processing method and device and storage medium |
| US20220165155A1 (en) * | 2019-05-08 | 2022-05-26 | Shenzhen Institutes Of Advanced Technology | Parking Guidance Method Based on Temporal and Spatial Features and Its Device, Equipment, and Storage Medium |
| US11639168B2 (en) | 2019-11-27 | 2023-05-02 | Toyota Motor North America, Inc. | Systems and methods for automatic vehicle loading and unloading on vehicle transports |
| CN111081056B (en) * | 2019-12-16 | 2021-08-24 | 青岛海信网络科技股份有限公司 | Intelligent intelligent big data analysis-based temporary parking management system for smart community |
| CN111508262B (en) * | 2020-04-01 | 2021-11-09 | 杨金奎 | Intelligent management method for urban parking space resources |
| CN111968401B (en) * | 2020-08-11 | 2021-09-28 | 支付宝(杭州)信息技术有限公司 | Parking space recommendation method and device, and parking space prediction method and device of parking lot |
| CN113570899B (en) * | 2021-07-16 | 2023-03-31 | 广州小鹏自动驾驶科技有限公司 | Parking lot list generation method and device, service equipment and storage medium |
| CN116182891B (en) * | 2023-04-24 | 2023-08-04 | 深圳市科莱德电子有限公司 | Vehicle navigation method, system, equipment and computer readable storage medium |
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