CN113776555A - Method for calculating automatic driving road coverage mileage based on road network slice - Google Patents
Method for calculating automatic driving road coverage mileage based on road network slice Download PDFInfo
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- CN113776555A CN113776555A CN202110950167.4A CN202110950167A CN113776555A CN 113776555 A CN113776555 A CN 113776555A CN 202110950167 A CN202110950167 A CN 202110950167A CN 113776555 A CN113776555 A CN 113776555A
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- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C22/00—Measuring distance traversed on the ground by vehicles, persons, animals or other moving solid bodies, e.g. using odometers, using pedometers
Abstract
A method for calculating the road coverage mileage of automatic driving based on road network slice, the vehicle carried terminal of the automatic driving vehicle wants the server to upload the vehicle CAN data periodically, the server stores the vehicle CAN data; slicing and dividing roads in the operation area according to a preset rule, and storing and indexing road slice information; the server counts the CAN data of the vehicles according to a preset period, and obtains the number of times of reporting data of each vehicle on each road slice according to the road slice information; and (5) all the data generated in S300 are loaded, and the automatic driving road coverage mileage and automatic driving road section distribution frequency of each vehicle are counted. The method has simple logic and easy realization, calculates and counts the road coverage mileage of the automatic driving vehicle by the road network slice, and calculates the distribution frequency of the automatic driving vehicle road section by the road network slice. The problem of prior art can't judge the region that automatic driving covered and automatic driving road cover mileage is solved.
Description
Technical Field
The invention relates to the field of Internet of vehicles and automatic driving, in particular to a method for calculating the covered mileage of an automatic driving road based on a road network slice.
Background
With the development and application of automatic driving technology, more and more automatic driving vehicles are put into real road conditions for operation. Different automatic driving suppliers and different vehicle enterprises have different automatic driving abilities and coverage areas and road mileage.
The automatic driving road coverage mileage is also an important index for judging the automatic driving capability of the vehicle enterprises and suppliers. When an automatic driving operator accesses different vehicles of different automatic driving suppliers of different vehicle enterprises, the automatic driving capability of different vehicles, different vehicle enterprises or automatic driving suppliers, an automatic driving coverage area and an automatic driving road coverage mileage are important evaluation indexes. However, in the prior art, no specific calculation method for the automatic driving covered area and the automatic driving road covered mileage exists.
Disclosure of Invention
In view of the above, the present invention has been made to provide a method for calculating an automated driving road coverage mileage based on a road network slice that overcomes or at least partially solves the above-mentioned problems.
In order to solve the technical problem, the embodiment of the application discloses the following technical scheme:
a method of calculating an autonomous road coverage distance based on a road network slice, comprising:
s100, a vehicle-mounted terminal of an automatic driving vehicle periodically uploads vehicle CAN data to a server, and the server stores the vehicle CAN data;
s200, slicing and dividing roads in the operation area according to a preset rule, and storing and indexing road slice information;
s300, the server counts the CAN data of the vehicles according to a preset period, and the number of times of reporting data of each vehicle on each road slice is obtained according to the road slice information;
and S400, loading all data generated in S300, and counting the covered mileage of the automatic driving road and the distribution frequency of the automatic driving road section of each vehicle.
Further, in S100, the vehicle CAN data at least includes: frame number, longitude and latitude, speed, driving mode, total current, total voltage and acquisition time.
Further, the specific method of S200 is: loading data of each road in an operation area, processing longitude and latitude list data of the road by using a Douglas pock algorithm to identify each inflection point in the road, then segmenting two adjacent points with fixed step length, finally calculating vertex and central point coordinates of a slice according to the road width, and performing index storage on the slice data of the road by using the central point coordinates and corresponding GEOHASH.
And further, performing fixed-step segmentation on the two adjacent points, wherein the fixed step is 5m, and when the step of the last road is less than 5m, directly recording the length of the last road.
Further, the method for index-storing the road slice data by using the center point coordinates and the corresponding geoaccess comprises the following steps: indexes are respectively established for the first 7 bits, the first 8 bits and the first 9 bits of the GEOHASH length.
Further, the specific method of S300 is: the server counts the longitude and latitude, the driving mode and the acquisition time of the vehicle in the CAN data of the vehicle according to the day, sorts the data according to the acquisition time, and filters out the data of which the driving mode in the operation area is automatic driving according to the driving mode; and calculating the geohash corresponding to the longitude and latitude of each datum, taking a road slice list according to the front 9 bits of the geohash, sequentially traversing the rectangular electronic fence blocked according to the top point of the slice, and judging whether the current vehicle is in the electronic fence or not.
Further, if the road slice list is taken according to the first 9 bits of the geohash, and the corresponding road slice cannot be found, the road slice list is taken according to the first 8 bits of the geohash to be circularly matched until the road slice is matched, and the frequency of reporting automatic data in each road slice by each vehicle is counted according to the day.
Further, the method for counting the road coverage mileage of each vehicle during automatic driving comprises the following steps: and S300, loading to obtain data, counting different road slices passed by each vehicle, and accumulating the lengths of all the road slices to obtain the road coverage mileage of the automatic driving of the vehicle.
Further, the method for counting the distribution frequency of the automatic driving area of each vehicle comprises the following steps: and S300, loading the data, counting the frequency of each vehicle passing through each road slice, and calculating the distribution frequency of the automatic driving area.
The technical scheme provided by the embodiment of the invention has the beneficial effects that at least:
the invention discloses a method for calculating the road coverage mileage of an automatic driving vehicle based on a road network slice, wherein a vehicle-mounted terminal of the automatic driving vehicle periodically uploads vehicle CAN data to a server, and the server stores the vehicle CAN data; slicing and dividing roads in the operation area according to a preset rule, and storing and indexing road slice information; the server counts the CAN data of the vehicles according to a preset period, and obtains the number of times of reporting data of each vehicle on each road slice according to the road slice information; and loading all the generated data, and counting the covered mileage of the automatic driving road and the distribution frequency of the automatic driving road section of each vehicle. The method has simple logic and easy realization, calculates and counts the road coverage mileage of the automatic driving vehicle by the road network slice, and calculates the distribution frequency of the automatic driving vehicle road section by the road network slice. The problem of prior art can't judge the region that automatic driving covered and automatic driving road cover mileage is solved.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
fig. 1 is a flowchart of calculating an automatic driving road coverage mileage based on a road network slice in embodiment 1 of the present invention;
fig. 2 is a flowchart of a method for calculating an automatic driving road coverage mileage by a road network slice in embodiment 1 of the present invention.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
In order to solve the problems in the prior art, the embodiment of the invention provides a method for calculating the automatic driving road coverage mileage based on a road network slice.
Example 1
The embodiment discloses a method for calculating an automatic driving road coverage mileage based on a road network slice, as shown in fig. 1, the method comprises the following steps:
s100, a vehicle-mounted terminal of an automatic driving vehicle periodically uploads vehicle CAN data to a server, and the server stores the vehicle CAN data; in the present embodiment, the vehicle CAN data includes at least: frame number, longitude and latitude, speed, driving mode, total current, total voltage and acquisition time.
Specifically, the automatic driving vehicle terminal periodically reports vehicle networking CAN data such as vehicle frame number, longitude and latitude, speed, driving mode, total current, total voltage, acquisition time and the like to the server, the server performs authentication according to vehicle registration information, marks specific supplier information of the vehicle after the authentication is passed, and then stores the information in a warehouse.
S200, slicing and dividing roads in the operation area according to a preset rule, and storing and indexing road slice information; in this embodiment, as shown in fig. 2, the specific method of S200 is: loading data of each road in an operation area, processing longitude and latitude list data of the road by a Douglas-Pock algorithm to identify each inflection point in the road, then segmenting adjacent two points by a fixed step length, finally calculating the vertex and the central point coordinate of the segment according to the road width, and performing index storage on the segment data of the road by using the central point coordinate and the corresponding GEOHASH. The Douglas-pock algorithm (Douglas-Peucker algorithm, also known as the larmer-Douglas-pock algorithm, the iterative adapted point algorithm, the split and merge algorithm) is an algorithm that approximates a curve as a series of points and reduces the number of points. Its advantages are translation and rotation invariance, and constant sampling result after curve and threshold are given.
Specifically, loading data of each road in an operation area, processing and identifying each inflection point in the road by a Douglas-Puck algorithm on road longitude and latitude list data, sequentially calculating the distance and azimuth angle between two adjacent points, wherein the two points are actual road center points, the road is sliced and divided by a fixed step length of 5m between the two points to obtain a series of longitude and latitude coordinates, the last section of the record length is less than 5m, the standard width of a lane is 2 x 7.5 m by referring to a bidirectional four-lane, 2 x 11.25 m by referring to a bidirectional six-lane, 2 x 15 m by referring to a bidirectional eight-lane, sequentially calculating coordinates and center points of 4 vertexes of each road slice (slice is a rectangle) according to the road width (default bidirectional eight-lane when the two-way lane cannot be obtained), then indexing the slice according to a center point GEOHASH and the vertex coordinates, and taking the center point coordinates as a unique road slice identifier, the precision takes the first 8 decimal places. And respectively establishing indexes for the first 7 bits, the first 8 bits and the first 9 bits of the GEOHASH with the same length.
S300, the server counts the CAN data of the vehicles according to a preset period, and the number of times of reporting data of each vehicle on each road slice is obtained according to the road slice information; in this embodiment, the specific method of S300 is as follows: the server counts the longitude and latitude, the driving mode and the acquisition time of the vehicle in the CAN data of the vehicle according to the day, sorts the data according to the acquisition time, and filters out the data of which the driving mode in the operation area is automatic driving according to the driving mode; and calculating the geohash corresponding to the longitude and latitude of each datum, taking a road slice list according to the front 9 bits of the geohash, sequentially traversing the rectangular electronic fence blocked according to the top point of the slice, and judging whether the current vehicle is in the electronic fence or not.
Specifically, information such as vehicle frame numbers, longitude and latitude, driving modes, acquisition time and the like is loaded according to the days, data in an automatic driving mode are filtered, information such as vehicle enterprise numbers and automatic driving supplier numbers is associated according to the frame numbers, a road slice list is loaded according to the geohash, and then whether the current coordinates are in a rectangular electronic fence packaged by 4 vertexes of a road slice or not is sequentially judged. Grouping is carried out according to the unique identification of the road section, and the number of times that each vehicle falls on the corresponding road section is counted. And warehousing and storing the carriage number, the carriage opening number, the automatic driving supplier number, the unique road section identification, the road section length and the date after the slicing times.
And S400, loading all data generated in S300, and counting the covered mileage of the automatic driving road and the distribution frequency of the automatic driving road section of each vehicle. In this embodiment, the method for counting the distance covered by the autonomous driving road of each vehicle includes: and S300, loading to obtain data, counting different road slices passed by each vehicle, and accumulating the lengths of all the road slices to obtain the road coverage mileage of the automatic driving of the vehicle. The method for counting the distribution frequency of the automatic driving area of each vehicle comprises the following steps: and S300, loading the data, counting the frequency of each vehicle passing through each road slice, and calculating the distribution frequency of the automatic driving area.
In the method for calculating the road coverage mileage of the automatic driving based on the road network slice, the vehicle-mounted terminal of the automatic driving vehicle periodically uploads the vehicle CAN data to the server, and the server stores the vehicle CAN data; slicing and dividing roads in the operation area according to a preset rule, and storing and indexing road slice information; the server counts the CAN data of the vehicles according to a preset period, and obtains the number of times of reporting data of each vehicle on each road slice according to the road slice information; and loading all the generated data, and counting the covered mileage of the automatic driving road and the distribution frequency of the automatic driving road section of each vehicle. The method has simple logic and easy realization, calculates and counts the road coverage mileage of the automatic driving vehicle by the road network slice, and calculates the distribution frequency of the automatic driving vehicle road section by the road network slice. The problem of prior art can't judge the region that automatic driving covered and automatic driving road cover mileage is solved.
It should be understood that the specific order or hierarchy of steps in the processes disclosed is an example of exemplary approaches. Based upon design preferences, it is understood that the specific order or hierarchy of steps in the processes may be rearranged without departing from the scope of the present disclosure. The accompanying method claims present elements of the various steps in a sample order, and are not intended to be limited to the specific order or hierarchy presented.
In the foregoing detailed description, various features are grouped together in a single embodiment for the purpose of streamlining the disclosure. This method of disclosure is not to be interpreted as reflecting an intention that the claimed embodiments of the subject matter require more features than are expressly recited in each claim. Rather, as the following claims reflect, invention lies in less than all features of a single disclosed embodiment. Thus, the following claims are hereby expressly incorporated into the detailed description, with each claim standing on its own as a separate preferred embodiment of the invention.
Those of skill would further appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present disclosure.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor such the processor can read information from, and write information to, the storage medium. Of course, the storage medium may also be integral to the processor. The processor and the storage medium may reside in an ASIC. The ASIC may reside in a user terminal. Of course, the processor and the storage medium may reside as discrete components in a user terminal.
For a software implementation, the techniques described herein may be implemented with modules (e.g., procedures, functions, and so on) that perform the functions described herein. The software codes may be stored in memory units and executed by processors. The memory unit may be implemented within the processor or external to the processor, in which case it can be communicatively coupled to the processor via various means as is known in the art.
What has been described above includes examples of one or more embodiments. It is, of course, not possible to describe every conceivable combination of components or methodologies for purposes of describing the aforementioned embodiments, but one of ordinary skill in the art may recognize that many further combinations and permutations of various embodiments are possible. Accordingly, the embodiments described herein are intended to embrace all such alterations, modifications and variations that fall within the scope of the appended claims. Furthermore, to the extent that the term "includes" is used in either the detailed description or the claims, such term is intended to be inclusive in a manner similar to the term "comprising" as "comprising" is interpreted when employed as a transitional word in a claim. Furthermore, any use of the term "or" in the specification of the claims is intended to mean a "non-exclusive or".
Claims (9)
1. A method for calculating an automatic driving road coverage mileage based on a road network slice is characterized by comprising the following steps:
s100, a vehicle-mounted terminal of an automatic driving vehicle periodically uploads vehicle CAN data to a server, and the server stores the vehicle CAN data;
s200, slicing and dividing roads in the operation area according to a preset rule, and storing and indexing road slice information;
s300, the server counts the CAN data of the vehicles according to a preset period, and the number of times of reporting data of each vehicle on each road slice is obtained according to the road slice information;
and S400, loading all data generated in S300, and counting the covered mileage of the automatic driving road and the distribution frequency of the automatic driving road section of each vehicle.
2. The method of claim 1, wherein in S100, the vehicle CAN data at least comprises: frame number, longitude and latitude, speed, driving mode, total current, total voltage and acquisition time.
3. The method for calculating the road network covered mileage based on the road network slice as claimed in claim 1, wherein the specific method of S200 is: loading data of each road in an operation area, processing longitude and latitude list data of the road by a Douglas-Pock algorithm to identify each inflection point in the road, then segmenting adjacent two points by a fixed step length, finally calculating the vertex and the central point coordinate of the segment according to the road width, and performing index storage on the segment data of the road by using the central point coordinate and the corresponding GEOHASH.
4. The method as claimed in claim 3, wherein the two adjacent points are divided into fixed steps, the fixed step is 5m, and when the step of the last road is less than 5m, the length of the last road is directly recorded.
5. The method of claim 3, wherein the road slice data is indexed and stored by the coordinates of the center point and the corresponding GEOHASH by the method of calculating the road network slice-based automatic driving road coverage mileage: indexes are respectively established for the first 7 bits, the first 8 bits and the first 9 bits of the GEOHASH length.
6. The method for calculating the road network covered mileage based on the road network slice as claimed in claim 1, wherein the specific method of S300 is: the server counts the longitude and latitude, the driving mode and the acquisition time of the vehicle in the CAN data of the vehicle according to the day, sorts the data according to the acquisition time, and filters out the data of which the driving mode in the operation area is automatic driving according to the driving mode; and calculating the geohash corresponding to the longitude and latitude of each datum, taking a road slice list according to the front 9 bits of the geohash, sequentially traversing the rectangular electronic fence blocked according to the top point of the slice, and judging whether the current vehicle is in the electronic fence or not.
7. The method for calculating the road network segment-based automatic driving road coverage mileage as claimed in claim 6, wherein if the road segment list is taken according to the first 9 bits of the geohash, and the corresponding road segment cannot be found, the circular matching is continued according to the road segment list taken according to the first 8 bits of the geohash until the road segment is matched, and the frequency of reporting automatic data in each road segment by each vehicle is counted by day.
8. The method for calculating the road network covered mileage based on the road network slice as claimed in claim 1, wherein the method for counting the road covered mileage of each vehicle comprises: and S300, loading to obtain data, counting different road slices passed by each vehicle, and accumulating the lengths of all the road slices to obtain the road coverage mileage of the automatic driving of the vehicle.
9. The method for calculating the road network covered mileage based on the road network slice as claimed in claim 1, wherein the method for counting the distribution frequency of the automatic driving area of each vehicle is as follows: and S300, loading the data, counting the frequency of each vehicle passing through each road slice, and calculating the distribution frequency of the automatic driving area.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107316354A (en) * | 2017-07-12 | 2017-11-03 | 哈尔滨工业大学 | A kind of method for detecting fatigue driving based on steering wheel and GNSS data |
| CN110864704A (en) * | 2018-08-28 | 2020-03-06 | 百度在线网络技术（北京）有限公司 | Automatic driving mileage statistical method, device and equipment |
| CN111649750A (en) * | 2020-04-29 | 2020-09-11 | 中国平安财产保险股份有限公司 | Vehicle GPS data map matching method, device, terminal and storage medium |
| CN112050820A (en) * | 2020-09-02 | 2020-12-08 | 平安科技（深圳）有限公司 | Road matching method and device, electronic equipment and readable storage medium |
| CN112146671A (en) * | 2020-08-31 | 2020-12-29 | 华为技术有限公司 | Path planning method, related equipment and computer readable storage medium |
| US20210012584A1 (en) * | 2019-07-10 | 2021-01-14 | Toyota Motor North America, Inc. | Driving range based on past and future data |
-
2021
- 2021-08-18 CN CN202110950167.4A patent/CN113776555A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107316354A (en) * | 2017-07-12 | 2017-11-03 | 哈尔滨工业大学 | A kind of method for detecting fatigue driving based on steering wheel and GNSS data |
| CN110864704A (en) * | 2018-08-28 | 2020-03-06 | 百度在线网络技术（北京）有限公司 | Automatic driving mileage statistical method, device and equipment |
| US20210012584A1 (en) * | 2019-07-10 | 2021-01-14 | Toyota Motor North America, Inc. | Driving range based on past and future data |
| CN111649750A (en) * | 2020-04-29 | 2020-09-11 | 中国平安财产保险股份有限公司 | Vehicle GPS data map matching method, device, terminal and storage medium |
| CN112146671A (en) * | 2020-08-31 | 2020-12-29 | 华为技术有限公司 | Path planning method, related equipment and computer readable storage medium |
| CN112050820A (en) * | 2020-09-02 | 2020-12-08 | 平安科技（深圳）有限公司 | Road matching method and device, electronic equipment and readable storage medium |
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