CN115116258A - Bus operation state identification method and device and processing equipment - Google Patents

Bus operation state identification method and device and processing equipment Download PDF

Info

Publication number
CN115116258A
CN115116258A CN202210728089.8A CN202210728089A CN115116258A CN 115116258 A CN115116258 A CN 115116258A CN 202210728089 A CN202210728089 A CN 202210728089A CN 115116258 A CN115116258 A CN 115116258A
Authority
CN
China
Prior art keywords
line
bus
deviated
operation state
determining
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202210728089.8A
Other languages
Chinese (zh)
Inventor
余爱军
孙熙
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.)
Wuhan Yuanguang Technology Co ltd
Original Assignee
Wuhan Yuanguang 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 Wuhan Yuanguang Technology Co ltd filed Critical Wuhan Yuanguang Technology Co ltd
Priority to CN202210728089.8A priority Critical patent/CN115116258A/en
Publication of CN115116258A publication Critical patent/CN115116258A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles
    • G08G1/123Traffic control systems for road vehicles indicating the position of vehicles, e.g. scheduled vehicles; Managing passenger vehicles circulating according to a fixed timetable, e.g. buses, trains, trams
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/10Services
    • G06Q50/26Government or public services

Landscapes

  • Business, Economics & Management (AREA)
  • Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Tourism & Hospitality (AREA)
  • Physics & Mathematics (AREA)
  • Marketing (AREA)
  • General Business, Economics & Management (AREA)
  • Human Resources & Organizations (AREA)
  • Economics (AREA)
  • Primary Health Care (AREA)
  • Strategic Management (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Educational Administration (AREA)
  • Development Economics (AREA)
  • Theoretical Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Traffic Control Systems (AREA)

Abstract

The application provides a method, a device and a processing device for identifying the operation state of a bus, which are used for providing a set of more accurate identification mechanism for the operation state of the bus aiming at a line deviation scene, so that new information support can be supplemented for bus information service on a system, and the operation state of the bus can be determined more accurately. The method comprises the following steps: acquiring an actual driving route of a bus; comparing the actual driving route with the preset driving route, and determining whether the bus deviates from the preset driving route according to the comparison result; if the deviation is detected, determining a deviation line of the bus, wherein the deviation line refers to a line which is driven when the bus returns to the preset driving line after deviating from the preset driving line; judging whether the deviated lines have matched lines in a deviated line set, wherein the deviated line set refers to a set of different deviated lines of different buses in a historical time period; and if so, determining that the bus is in a normal operation state.

Description

Method and device for identifying bus operation state and processing equipment
Technical Field
The application relates to the field of buses, in particular to a method and a device for identifying the operation state of a bus and processing equipment.
Background
Public transport trip is a trip mode of the public, and due to economic development and environmental pressure, the demand of preferentially developing public transport also exists in urban traffic, and the public is guided to select more public trips.
Under the background, the traditional public transportation system is upgraded by using an information technology, so that a user can know road conditions and vehicle conditions in time, good riding experience of the user is guaranteed, and the traditional public transportation system can be used as one of guarantee measures for effectively improving public trip rate.
However, in the existing research process of related technologies, the inventor finds that, in the actual operation of a public transportation system, due to complex road conditions such as line maintenance, road construction and traffic conditions, as well as the self state of a bus or subjective selection of a driver, the bus may not travel according to a preset planned route, so that a user cannot accurately know the travel condition of the bus in time, and the travel experience of the user is easily influenced by the condition in actual application.
Disclosure of Invention
The application provides a method, a device and a processing device for identifying the operation state of a bus, which are used for providing a set of more accurate identification mechanism for the operation state of the bus aiming at a line deviation scene, so that new information support can be supplemented for bus information service on a system, and the operation state of the bus can be determined more accurately.
In a first aspect, the present application provides a method for identifying a bus operating state, where the method includes:
acquiring an actual driving route of a bus;
comparing the actual driving route with a preset driving route, and determining whether the bus deviates from the preset driving route according to a comparison result;
if the deviation is detected, determining a deviation line of the bus, wherein the deviation line refers to a line which is driven when the bus returns to the preset driving line after deviating from the preset driving line;
judging whether the deviated lines have matched lines in a deviated line set, wherein the deviated line set refers to a set of different deviated lines of different buses in a historical time period;
and if so, determining that the bus is in a normal operation state.
With reference to the first aspect of the present application, in a first possible implementation manner of the first aspect of the present application, determining whether there is a matched line in the deviated line set, includes:
calculating the similarity between the deviated line and the line in the deviated line set;
and if the similarity calculation result is greater than the similarity threshold, determining that the deviated line has a matched line in the deviated line set.
With reference to the first possible implementation manner of the first aspect of the present application, in a second possible implementation manner of the first aspect of the present application, a similarity calculation formula involved in the similarity calculation process is specifically:
μ12=size(U12)/size(route1),
wherein μ 12 is the similarity of the first line to the second line, the size symbol is the operation of taking the size of the set, U12 is the set of all nodes with the distance from the first line to the second line less than 80 meters, route1 is the first line,
μ21=size(U21)/size(route2),
wherein μ 12 is the similarity of the second line to the first line, U21 is the set of all nodes with the distance of the second line from the first line being less than 80 meters, route2 is the second line,
the minimum similarity μ is taken as the final similarity, μ ═ min (μ 12, μ 21).
With reference to the first possible implementation manner of the first aspect of the present application, in a third possible implementation manner of the first aspect of the present application, the similarity threshold is 0.8.
With reference to the first aspect of the present application, in a fourth possible implementation manner of the first aspect of the present application, the method further includes:
and if not, adding the deviated line as a new line into the deviated line set.
With reference to the first aspect of the present application, in a fifth possible implementation manner of the first aspect of the present application, the method further includes:
judging whether a target deviated line with matching times larger than preset matching times exists in the deviated line set or not;
and if so, determining that the target deviated line is a normal operation line.
With reference to the first aspect of the present application, in a sixth possible implementation manner of the first aspect of the present application, after determining that the bus is in a normal operation state, the method further includes:
and pushing a notification that the bus is in a normal operation state to User Equipment (UE) which refers to or subscribes to the operation state of the bus, wherein if the UE is or will be at a target station which is bypassed by a deviated line, the notification content also comprises the content that the bus does not pass through the target station.
In a second aspect, the present application provides a device for identifying a bus operation state, the device comprising:
the bus driving control device comprises an acquisition unit, a control unit and a control unit, wherein the acquisition unit is used for acquiring an actual driving route of a bus;
the comparison unit is used for comparing the actual driving route with the preset driving route, determining whether the bus deviates from the preset driving route according to a comparison result, and triggering the determination unit if the bus deviates from the preset driving route;
the determining unit is used for determining a deviation line of the bus, wherein the deviation line refers to a line which is driven when the bus returns to the preset driving line after deviating from the preset driving line;
the matching unit is used for judging whether a matched line exists in a deviated line set or not, wherein the deviated line set refers to a set of different deviated lines of different buses in a historical time period, and if the deviated lines are matched, the determining unit is triggered;
and the determining unit is also used for determining that the bus is in a normal operation state.
With reference to the second aspect of the present application, in a first possible implementation manner of the second aspect of the present application, the matching unit is specifically configured to:
calculating the similarity between the deviated line and the line in the deviated line set;
and if the similarity calculation result is greater than the similarity threshold, determining that the deviated line has a matched line in the deviated line set.
With reference to the first possible implementation manner of the second aspect of the present application, in a second possible implementation manner of the second aspect of the present application, a similarity calculation formula involved in the similarity calculation process is specifically:
μ12=size(U12)/size(route1),
wherein μ 12 is the similarity of the first line to the second line, the size symbol is the operation of taking the size of the set, U12 is the set of all nodes with the distance from the first line to the second line less than 80 meters, route1 is the first line,
μ21=size(U21)/size(route2),
wherein μ 12 is the similarity of the second line to the first line, U21 is the set of all nodes with the distance of the second line from the first line being less than 80 meters, route2 is the second line,
the minimum similarity μ is taken as the final similarity, μ ═ min (μ 12, μ 21).
With reference to the first possible implementation manner of the second aspect of the present application, in a third possible implementation manner of the second aspect of the present application, the similarity threshold is 0.8.
With reference to the second aspect of the present application, in a fourth possible implementation manner of the second aspect of the present application, the apparatus further includes a joining unit, and if the joining unit is not matched, the joining unit is triggered;
and the adding unit is used for adding the deviated line into the deviated line set as a new line.
With reference to the second aspect of the present application, in a fifth possible implementation manner of the second aspect of the present application, the apparatus further includes a determining unit, configured to:
judging whether a target deviated line with matching times larger than preset matching times exists in the deviated line set or not;
and if so, determining that the target deviated line is a normal operation line.
With reference to the second aspect of the present application, in a sixth possible implementation manner of the second aspect of the present application, the apparatus further includes a pushing unit, configured to:
and pushing a notice that the bus is in a normal operation state to the UE which refers for or subscribes the operation state of the bus, wherein if the UE is at or is about to be at a target station which is bypassed by a deviated line, the notice content also comprises the content that the bus does not pass through the target station.
In a third aspect, the present application provides a processing device, including a processor and a memory, where the memory stores a computer program, and the processor executes the method provided in the first aspect of the present application or any one of the possible implementation manners of the first aspect of the present application when calling the computer program in the memory.
In a fourth aspect, the present application provides a computer-readable storage medium storing a plurality of instructions adapted to be loaded by a processor to perform the method provided in the first aspect of the present application or any one of the possible implementations of the first aspect of the present application.
From the above, the present application has the following advantageous effects:
aiming at a route deviation scene which may occur in a bus in practical application, the method does not simply judge that the bus is in an abnormal operation state, but analyzes whether a deviation route is matched with a route in a deviation route set configured on a system, wherein the deviation route set comprises different deviation routes of different buses in a historical time period, if a matching route exists, the bus can be considered that a special driving condition of the bus route needs to be flexibly reflected, and a driver can make a relatively consistent driving route, so that the bus can be determined to be still in a normal operation state.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic flow chart of a method for identifying a bus operation state according to the present application;
fig. 2 is a schematic structural diagram of the bus operation state identification device according to the present application;
FIG. 3 is a schematic diagram of a processing apparatus according to the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The terms "first," "second," and the like in the description and in the claims of the present application and in the above-described drawings are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged under appropriate circumstances such that the embodiments described herein may be practiced otherwise than as specifically illustrated or described herein. Moreover, the terms "comprises," "comprising," and any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or modules is not necessarily limited to those steps or modules explicitly listed, but may include other steps or modules not expressly listed or inherent to such process, method, article, or apparatus. The naming or numbering of the steps appearing in the present application does not mean that the steps in the method flow have to be executed in the chronological/logical order indicated by the naming or numbering, and the named or numbered process steps may be executed in a modified order depending on the technical purpose to be achieved, as long as the same or similar technical effects are achieved.
The division of the modules presented in this application is a logical division, and in practical applications, there may be another division, for example, multiple modules may be combined or integrated into another system, or some features may be omitted, or not executed, and in addition, the shown or discussed coupling or direct coupling or communication connection between each other may be through some interfaces, and the indirect coupling or communication connection between the modules may be in an electrical or other similar form, which is not limited in this application. Moreover, the modules or sub-modules described as separate components may or may not be physically separated, may or may not be physical modules, or may be distributed in a plurality of circuit modules, and some or all of the modules may be selected according to actual needs to achieve the purpose of the present application.
Before describing the method for identifying the bus operation state provided by the present application, first, the background content related to the present application is described.
As a technical solution in the prior art (CN110718088A — method and apparatus for monitoring operation state of bus), it mainly provides a method to monitor operation state of bus, and after studying, the inventor of the present application finds that there are the prior technical problems addressed by the present application, such as:
the method is characterized in that only the running route of one bus is utilized to monitor in an isolated manner, all buses on one route serve as a group of operation entities, the behavior modes of the buses have high similarity, and the single bus is monitored in an isolated manner, so that the data acquisition aspect is not comprehensive; secondly, whether the vehicle is in operation or not is judged only by adopting a threshold matching mode, the method has no representativeness in the actual operation, the correctness of the method needs to be further verified, and the method has no actual application value.
It is clear from the document that once it is determined that a vehicle is operated under a condition deviating from an original route, that is, the original route is modified to a real-time travel route, which is logically wrong in practical application, actually, most bus lines are used as a trackless operation bus system, the actual travel route of which has certain flexibility and cannot be operated according to the deviating original route with certain frequency, the original route is proved to be modified, and the application finds out in the actual data analysis that a plurality of routes actually have the condition: that is, some vehicles operate along the original route, while some other vehicles operate on a more flexible route, or the same vehicle may be operated at different times.
Under the condition that the running condition of the bus cannot be determined accurately in time in the prior art, the method, the device and the computer-readable storage medium for identifying the bus running state are provided, and can be applied to processing equipment and used for providing a set of more accurate identification mechanism for the bus running state aiming at a line deviation scene, so that new information support can be supplemented for bus information service on a system, and the bus running state can be determined more accurately.
According to the method for identifying the bus operation state, the execution main body can be an identification device of the bus operation state, or different types of processing equipment such as a server, a physical host or UE (user equipment) integrated with the identification device of the bus operation state. The device for identifying the operation state of the bus can be realized in a hardware or software mode, the UE can be a terminal device such as a smart phone, a tablet computer, a notebook computer, a desktop computer or a Personal Digital Assistant (PDA), and the processing device can be set in a device cluster mode.
In particular, in the application, the processing device related to the application can be a server of a bus operator, the server in the cloud can provide bus information services in aspects of bus travel position, bus operation state and the like for a user at the background, and in this case, more accurate information services of the bus operation state can be provided through the identification method of the bus operation state provided by the application.
Next, the method for identifying the bus operating state provided by the present application is described.
First, referring to fig. 1, fig. 1 shows a schematic flow chart of the method for identifying a bus operating state according to the present application, and the method for identifying a bus operating state according to the present application may specifically include the following steps S101 to S105:
step S101, acquiring an actual driving route of a bus;
it can be understood that in a specific application, the actual driving route of the bus can be acquired through the related positioning device, and of course, the actual driving route of the bus can also be acquired directly or indirectly through other positioning technologies.
Here, in a specific application, the step S101 may be to acquire the actual driving route of the bus, and the acquisition may be data retrieval processing (obtained by processing by other devices or systems) or positioning processing (obtained by processing by itself).
Step S102, comparing the actual driving route with a preset driving route, determining whether the bus deviates from the preset driving route according to a comparison result, and if so, triggering step S103;
it can be understood that the real-time track (actual driving route and) of the bus and the preset track (preset driving route) can be compared or matched to determine whether the bus drives out or deviates from the preset form route.
When the actual driving route is within the range of the preset driving route, the bus can be determined to be in a normal operation state.
When the actual driving route exceeds the range of the preset driving route, the deviation condition of the bus can be determined, and at the moment, whether the operation state of the bus is normal or not can be continuously determined through the subsequent steps of the application.
Step S103, determining a deviation route of the bus, wherein the deviation route is a route which is driven when the bus returns to the preset driving route after deviating from the preset driving route;
it can be understood that after the deviation of the bus from the preset driving route is determined, the deviation of the bus from the preset driving route can be determined.
In the application, the bus can return to the preset running line to continue running after the special running condition is overcome subsequently even if the bus deviates in the running process due to the special running condition based on the running purpose in the running process.
Therefore, the route of the bus outside the preset form route can be obtained, namely the route which is driven when the bus returns to the preset driving route after the bus is driven by deviating from the preset driving route is obtained and is used as the deviating route which is required to judge whether the bus is in a normal operation state at this time.
Step S104, judging whether the deviated lines have matched lines in a deviated line set, wherein the deviated line set refers to a set of different deviated lines of different buses in a historical time period, and if the deviated lines are matched, triggering the step S105;
it should be understood that, in the application, the bus driver may adjust the driving state of the bus according to the specific driving condition during the actual driving process, if the bus may deviate from the preset driving route due to the complex road conditions (such as route maintenance, road construction, and traffic conditions) or even the self-state of the bus or the subjective selection of the driver, the operation requirement of the bus can be completed, and in this case, the bus is also in the normal operation state under the deviation condition.
Under the strategy, different deviation routes of different buses can be recorded to form a deviation route set, different deviation behaviors of different drivers under different driving conditions are corresponded, and the different deviation behaviors are matched in the follow-up process.
Therefore, when the currently-occurring deviated line is captured, the currently-occurring deviated line can be matched with the line in the deviated line set to see whether the historical deviated line also appears at the place, and therefore whether the current deviating behavior also accords with the category of the normal operation state is determined.
In addition, it can be understood that in the deviated line set, the time period and the dividing elements such as the bus line number may be specifically combined for division, and the subsequent matching processing may also be performed on the basis of the dividing elements for finer and finer matching processing, thereby obtaining a more accurate matching effect.
And step S105, determining that the bus is in a normal operation state.
When it is determined that the current deviated line has a matched line in the preset deviated line set, it can be known from the above contents that the current deviated line corresponds to the same or relatively same special driving condition, which is essentially a behavior for normal operation of the bus, and therefore, it can be confirmed that the bus is still in a normal operation state.
It should be understood that, the processing of determining that the bus is in the normal operation state herein may also be performed in combination with a specific related application in practical applications, for example, the operation state of the bus may be specifically identified as an "operation deviation state" as a specific "normal operation state", so that the specific state that the bus is in the deviation route may also be known while the normal operation state of the bus is known systematically, which not only facilitates the knowledge of the specific operation state of the bus, but also facilitates the related more exquisite information processing.
As can be seen from the embodiment shown in fig. 1, for the line deviation scenario that may occur in the bus in practical application, the application does not simply determine that the bus is in an abnormal operation state, but rather analyzes whether its deviating wire matches a wire in a set of deviating wires configured on the system, the deviated line set comprises different deviated lines of different buses in historical time periods, if matched lines exist, the bus route is considered to have special driving conditions and needs to be flexibly reflected, so that the driver can make relatively consistent driving routes, the bus can be determined to be still in a normal operation state, under the more accurate identification mechanism of the operation state of the bus, new information support can be supplemented for the bus information service on the system, and the operation state of the bus can be further accurately determined.
Further, in the matching process related to step S104 above, a similarity policy may be specifically adopted to perform matching of the lines, that is, step S104 may specifically include the following:
calculating the similarity between the deviated line and the line in the deviated line set;
and if the similarity calculation result is greater than the similarity threshold, determining that the deviated line has a matched line in the deviated line set.
It is understood that, for the lines referred to in the present application, it is possible to specifically quantify the lines in the form of coordinate points, and to form lines on the basis of a large number of coordinate points, and in the matching process, the similarity between two lines is calculated based on these coordinate points, thereby determining whether the lines are matched.
In this similarity application, it is obvious that higher similarity means better matching.
In addition, the similarity calculation is easy to understand and is usually embodied by quantifying the distance between coordinate points, and on the basis, the application also continues to provide a practical quantification scheme.
That is, as a specific implementation manner, the similarity calculation formula involved in the similarity calculation process of the present application may specifically be:
μ12=size(U12)/size(route1),
wherein μ 12 is the similarity of the first line to the second line, the size symbol is the operation of taking the size of the set, U12 is the set of all nodes with the distance from the first line to the second line less than 80 meters, route1 is the first line,
μ21=size(U21)/size(route2),
wherein, mu 12 is the similarity of the second line to the first line, U21 is the set of all nodes with the distance from the second line to the first line less than 80 meters, route2 is the second line,
the minimum similarity μ is taken as the similarity finally adopted, and μ ═ min (μ 12, μ 21).
It can be understood that in the tracked lines, the distance between the acquisition nodes is selected to be larger, in this case, it is considered that the node distance between the equivalent or similar lines is less than 80 meters, so the distance between the similar nodes is 80 meters or less, and therefore the occupation ratio of the similar nodes in the deviated line set to be matched is the similarity between the deviated line and the line to be matched, under this mechanism, a better balance is achieved between a larger sampling range and higher similarity calculation accuracy.
The calculation of the similarity may be specifically realized by performing spatial indexing through K-DTree, and a point set meeting the condition is searched according to the point-to-point distance, and of course, in a specific application, the processing of the similarity may also be completed by adopting other different types of search strategies.
In addition, in a specific operation, the similarity threshold may be specifically configured to be 0.8, and of course, in an actual application, the similarity threshold may also be adjusted and configured according to specific requirements and specific situations.
In addition, in the above matching process, if the deviated line is a line searched for matching in the deviated line set, the deviated line may be added as a new line to expand the deviated line set, so as to provide a new line to be matched for the subsequent matching process.
That is, after step S104, the present application may further include:
and if not, adding the deviated line as a new line into the deviated line set.
Furthermore, in order to more flexibly apply the application of the deviated lines, in the process of planning the operation lines of the bus on the system, the deviated lines appearing at high frequency can be used as supplement and perfection of the preset running lines and added to the corresponding running line positions.
Specifically, as another practical implementation, the policy may be implemented based on a line in the deviated line set, for example, the application may further include:
judging whether a target deviated line with matching times larger than preset matching times exists in the deviated line set or not;
and if so, determining that the target deviated line is a normal operation line.
It can be understood that, in the set of deviated routes, the application considers that the route which is easily selected by the driver for the special driving situation will be reflected from the matching result of the high frequency, therefore, in consideration of the automatic updating requirement of the driving route, a specific frequency threshold or preset matching number can be configured, and when the matching number of a certain deviated route is greater than the value, the target deviated route can be determined as the normal operating route as the supplement and improvement of the preset driving route.
And after the fact that the bus is actually in the normal operation state is determined through the matching processing, the notification pushing of the operation state of the bus can be normally carried out on the system so as to inform the system and/or the user.
For example, a notification that the bus is in a normal operation state may be pushed to a UE that consults or subscribes to the operation state of the bus.
The UE may determine the user identifier by using a related login user account, a device identifier, or a lookup request.
In addition, under the pushing mechanism, the pushing content can be further supplemented and perfected based on flexible application of the deviated line.
Specifically, if the UE is located at or will be located at a target station that is bypassed by the off-route, the notification content may further include content that the bus does not pass through the target station.
Whether the UE is in a target station bypassed by a deviated line or not can be determined through the real-time positioning of the UE or the inquiry position reported by the UE.
Under the optimization of the pushing mechanism, obviously, more accurate content pushing of the bus operation state can be provided for the user, and the user can more clearly learn whether the bus can normally reach the related station, so that good bus taking experience is guaranteed.
For further understanding of the above, reference may also be made to a set of exemplary applications.
Firstly, the relevant data or data model concerned is defined:
(1) in operation, the bus can be understood as running along the ridge line of the line basically, stopping at most stops and carrying and unloading passengers normally.
(2) The ridge line can be understood as the stop points of the bus which stop in sequence during the process of advancing, an appointed preset driving line is arranged between two continuous stop points, the driving lines between all the stop points are connected to form the ridge line of the whole bus line, and the bus drives along the ridge line and is one of the important marks for judging that the bus is in operation.
(3) The mileage, which can be understood as the mileage of the bus on the ridge line, is defined as the distance from the current position point of the bus to the head stop along the ridge line.
(4) The bus line can be understood as an abstraction of bus system line information, and generally includes a ridge line in the up-down direction and a station with a sequence number sequentially increasing on the ridge line, the ridge line is represented as a smooth curve formed by connecting a series of coordinate points, and the station information includes a station sequence, a station name, a position point coordinate and a mileage on the ridge line.
(5) The driving route can be understood as all roads covered by the driving track when the bus operates.
(6) A shift, which is understood to mean the normal operation of a bus, forms a shift from the starting station to the destination station, which should include the time information of the arrival and departure of all stops.
For the number of shifts, the definition of the judgment condition of the complete shift of the bus operation in the application can be as follows:
the coverage of the trace points of the ridge line is more than 0.80 in the running of the vehicle;
the utilization rate of the trace points by the ridge lines is more than 0.85 when the vehicle runs for business;
the running time of the vehicle is more than 0.60 of the coverage of all the stations of the route;
the rate of parking of the vehicle for the covered station is >0.90 for the operation lap.
The main data processing of the application comprises the following contents:
1. generating an offset route
1.1. Tracking the positions of all vehicles judged to be operated on a bus line in real time;
1.2. once any bus deviates from the ridge line, recording the mileage at the moment of deviation, and starting to record track points when the state enters 'driving off the ridge line';
1.3. if the vehicle with the state of 'driving deviating from the ridge line' does not return to the ridge line all the time, namely, a complete shift is not executed any more, all recorded track points are abandoned;
1.4. if the vehicle in the state of 'deviated course driving' returns to the ridge line, the mileage at the returning time is recorded immediately, and the Douglas compression is performed on all the recorded track points to generate a smooth 'deviated course'.
2. Preserving deviated course
Continuing to track the returning bus until it succeeds a complete operating shift, and storing its "off-routes" in storage, including but not limited to the following information:
2.1. the serial number of the bus line;
2.2. the direction of the operation;
2.3. the mileage at the deviated time is recorded as: mileagedepart;
2.4. the mileage at the time of regression is recorded as: mileagereturn;
2.5. the site set located between the two mileage is named as 'station jumping set';
2.6. the node sequence of the whole "" off-course "";
2.7. the length of the whole line;
2.8. a confirmation factor, noted as confirm, with an initial value of 0;
3. identifying operational deviation from route
3.1. The work is initiated in the process of saving the 'deviation course';
3.2. matching the deviation routes which need to be stored currently with all the deviation routes which are stored before in the same direction of the bus line, and matching rules:
Δmileagedepart=Math.abs(mileage1depart-mileage2depart)
Δmileagereturn=Math.abs(mileage1return-mileage2return)
Δ mileagedepart <50 meters and Δ milegereturn <50 meters;
3.3 if 3.2, if no result is matched, directly saving the current 'deviation path';
3.4 if 3.2. the result is matched, then the similarity calculation is performed between the matched result and the current "off-route", and the similarity between route1 and route2 is defined as:
μ12=size(U12)/size(route1),
wherein μ 12 is the similarity of the first line to the second line, the size symbol is the operation of taking the size of the set, U12 is the set of all nodes with the distance from the first line to the second line less than 80 meters, route1 is the first line,
μ21=size(U21)/size(route2),
wherein μ 12 is the similarity of the second line to the first line, U21 is the set of all nodes with the distance of the second line from the first line being less than 80 meters, route2 is the second line,
the minimum similarity μ is taken as the final similarity, μ ═ min (μ 12, μ 21).
3.5. If the similarity μ between the "deviation route" and the current "deviation route" is not stored in the matching result and is greater than 0.8, directly storing the current "deviation route";
3.6. if there is a "off course" with a similarity μ >0.8 in the matching result, adding 1 to the confirmation factor confirm of the existing "off course" while abandoning the saving of the current "off course";
3.7. "off-course" with a confirmation factor confirm greater than 10 is marked with "off-course in service".
4. Using operating deviation circuits
4.1. If any vehicle in operation deviates from the ridge line but the track does not deviate from an existing 'operation deviation line', the vehicle state is judged to be the continuous operation;
4.2. if the matched 'jumping station set' of 'operation off-line' is not empty, then the passengers at these stations are informed at the same time: vehicles are operated upstream, but do not stop at the site where they are located.
In specific application, the method for identifying the bus operation state includes the steps that the state that the bus deviates from a ridge line but continues to operate is caught through real-time calculation and intelligent analysis, the judgment duration of the online bus is prolonged by more than 3%, passengers who are skipped to wait at a stop are accurately reminded, and the riding experience of the user is effectively improved.
The method for identifying the bus operation state is introduced, so that the method for identifying the bus operation state is better implemented, and the device for identifying the bus operation state is further provided from the perspective of a functional module.
Referring to fig. 2, fig. 2 is a schematic structural diagram of the identification apparatus for a bus operation state in the present application, the identification apparatus 200 for a bus operation state specifically may include the following structure:
an acquisition unit 201 for acquiring an actual travel route of a bus;
a comparison unit 202, configured to compare the actual driving route with a preset driving route, determine whether the bus deviates from the preset driving route according to a comparison result, and trigger the determination unit 203 if the bus deviates from the preset driving route;
the determining unit 203 is configured to determine a deviation route of the bus, where the deviation route is a route traveled by the bus when the bus deviates from the preset travel route and then returns to the preset travel route;
the matching unit 204 is configured to determine whether a matching route exists in a deviated route set of the deviated routes, where the deviated route set is a set of different deviated routes of different buses in a historical time period, and if the deviation route set is matched, the determining unit 203 is triggered;
the determining unit 203 is further configured to determine that the bus is in a normal operation state.
In an exemplary implementation manner, the matching unit 204 is specifically configured to:
calculating the similarity between the deviated line and the line in the deviated line set;
and if the similarity calculation result is greater than the similarity threshold, determining that the deviated line has a matched line in the deviated line set.
In another exemplary implementation manner, the similarity calculation formula involved in the similarity calculation process is specifically:
μ12=size(U12)/size(route1),
wherein μ 12 is the similarity of the first line to the second line, the size symbol is the operation of taking the size of the set, U12 is the set of all nodes with the distance from the first line to the second line less than 80 meters, route1 is the first line,
μ21=size(U21)/size(route2),
wherein μ 12 is the similarity of the second line to the first line, U21 is the set of all nodes with the distance of the second line from the first line being less than 80 meters, route2 is the second line,
the minimum similarity μ is taken as the final similarity, μ ═ min (μ 12, μ 21).
In yet another exemplary implementation, the similarity threshold is 0.8.
In yet another exemplary implementation manner, the apparatus further includes a joining unit 204, and if not matched, the joining unit 205 is triggered;
and the adding unit is used for adding the deviated line into the deviated line set as a new line.
In yet another exemplary implementation, the apparatus further includes a determining unit 206 configured to:
judging whether a target deviated line with the matching times larger than the preset matching times exists in the deviated line set or not;
and if so, determining that the target deviated line is a normal operation line.
In yet another exemplary implementation, the apparatus further includes a pushing unit 207 configured to:
and pushing a notice that the bus is in a normal operation state to the UE which refers for or subscribes the operation state of the bus, wherein if the UE is at or is about to be at a target station which is bypassed by a deviated line, the notice content also comprises the content that the bus does not pass through the target station.
The present application further provides a processing device from a hardware structure perspective, referring to fig. 3, fig. 3 shows a schematic structural diagram of the processing device of the present application, specifically, the processing device of the present application may include a processor 301, a memory 302, and an input/output device 303, where the processor 301 is configured to implement, when executing a computer program stored in the memory 302, the steps of the method for identifying the bus operation state in the embodiment corresponding to fig. 1; alternatively, the processor 301 is configured to implement the functions of the units in the embodiment corresponding to fig. 2 when executing the computer program stored in the memory 302, and the memory 302 is configured to store the computer program required by the processor 301 to execute the method for identifying the bus operation state in the embodiment corresponding to fig. 1.
Illustratively, the computer program may be divided into one or more modules/units, which are stored in the memory 302 and executed by the processor 301 to accomplish the present application. One or more modules/units may be a series of computer program instruction segments capable of performing certain functions, the instruction segments being used to describe the execution of a computer program in a computer device.
The processing devices may include, but are not limited to, a processor 301, a memory 302, and an input-output device 303. It will be appreciated by a person skilled in the art that the illustration is merely an example of a processing device and does not constitute a limitation of a processing device and may comprise more or less components than those illustrated, or some components may be combined, or different components, e.g. the processing device may further comprise a network access device, a bus, etc. via which the processor 301, the memory 302, the input output device 303, etc. are connected.
The Processor 301 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, etc. The general purpose processor may be a microprocessor or the processor may be any conventional processor or the like, the processor being the control center for the processing device and the various interfaces and lines connecting the various parts of the overall device.
The memory 302 may be used to store computer programs and/or modules, and the processor 301 implements various functions of the computer device by running or executing the computer programs and/or modules stored in the memory 302 and invoking data stored in the memory 302. The memory 302 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required for at least one function, and the like; the storage data area may store data created according to use of the processing apparatus, and the like. In addition, the memory may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.
When the processor 301 is used to execute the computer program stored in the memory 302, the following functions may be specifically realized:
acquiring an actual driving route of a bus;
comparing the actual driving route with the preset driving route, and determining whether the bus deviates from the preset driving route according to the comparison result;
if the deviation is detected, determining a deviation line of the bus, wherein the deviation line refers to a line which is driven when the bus returns to the preset driving line after deviating from the preset driving line;
judging whether the deviated lines have matched lines in a deviated line set, wherein the deviated line set refers to a set of different deviated lines of different buses in a historical time period;
and if so, determining that the bus is in a normal operation state.
It can be clearly understood by those skilled in the art that, for convenience and simplicity of description, for the specific working processes of the above-described identification apparatus for an operating state of a bus, the processing device and the corresponding units thereof, reference may be made to the description of the identification method for an operating state of a bus in the embodiment corresponding to fig. 1, which is not described herein again in detail.
It will be understood by those skilled in the art that all or part of the steps of the methods of the above embodiments may be performed by instructions or by associated hardware controlled by the instructions, which may be stored in a computer readable storage medium and loaded and executed by a processor.
For this reason, the present application provides a computer-readable storage medium, where a plurality of instructions are stored, where the instructions can be loaded by a processor to execute the steps of the method for identifying a bus operation state in the embodiment corresponding to fig. 1 in the present application, and specific operations may refer to the description of the method for identifying a bus operation state in the embodiment corresponding to fig. 1, and are not described herein again.
Wherein the computer-readable storage medium may include: read Only Memory (ROM), Random Access Memory (RAM), magnetic or optical disks, and the like.
Since the instructions stored in the computer-readable storage medium can execute the steps of the method for identifying the bus operation state in the embodiment corresponding to fig. 1, the beneficial effects that can be achieved by the method for identifying the bus operation state in the embodiment corresponding to fig. 1 can be achieved, and the detailed description is omitted here.
The method, the device, the processing device and the computer-readable storage medium for identifying the bus operation state provided by the application are introduced in detail, a specific example is applied in the description to explain the principle and the implementation of the application, and the description of the embodiment is only used for helping to understand the method and the core idea of the application; meanwhile, for those skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.

Claims (10)

1. A method for identifying the operation state of a bus is characterized by comprising the following steps:
acquiring an actual driving route of a bus;
comparing the actual driving route with a preset driving route, and determining whether the bus deviates from the preset driving route according to a comparison result;
if the deviation is detected, determining a deviation line of the bus, wherein the deviation line refers to a line which is driven when the bus returns to the preset driving line after deviating from the preset driving line;
judging whether the deviated lines have matched lines in a deviated line set, wherein the deviated line set refers to a set of different deviated lines of different buses in a historical time period;
and if the bus is matched with the bus, determining that the bus is in a normal operation state.
2. The method of claim 1, wherein the determining whether the deviating route has a matching route in a deviating route set comprises:
calculating the similarity of the deviated line and the lines in the deviated line set;
and if the similarity calculation result is greater than the similarity threshold, determining that the deviated line has a matched line in the deviated line set.
3. The method according to claim 2, wherein the similarity calculation formula involved in the similarity calculation process is specifically:
μ12=size(U12)/size(route1),
wherein μ 12 is the similarity of the first line to the second line, the size symbol is the operation of taking the size of the set, U12 is the set of all nodes with the distance from the first line to the second line being less than 80 meters, route1 is the first line,
μ21=size(U21)/size(route2),
wherein μ 12 is the similarity of the second line to the first line, U21 is the set of all nodes with the distance of the second line from the first line being less than 80 meters, route2 is the second line,
the minimum similarity μ is taken as the final similarity, μ ═ min (μ 12, μ 21).
4. The method of claim 2, wherein the similarity threshold is 0.8.
5. The method of claim 1, further comprising:
and if not, taking the deviated line as a new line and adding the new line into the deviated line set.
6. The method of claim 1, further comprising:
judging whether a target deviated line with matching times larger than preset matching times exists in the deviated line set or not;
and if so, determining that the target deviated line is a normal operation line.
7. The method of claim 1, wherein after determining that the bus is in a normal operating state, the method further comprises:
and pushing a notification that the bus is in a normal operation state to User Equipment (UE) which refers to or subscribes the operation state of the bus, wherein if the UE is at or is about to be at a target station which is bypassed by the deviated line, the notification content also comprises the content that the bus does not pass through the target station.
8. An identification device for the operation state of a bus, characterized in that the device comprises:
the bus driving control device comprises an acquisition unit, a control unit and a control unit, wherein the acquisition unit is used for acquiring an actual driving route of a bus;
the comparison unit is used for comparing the actual driving route with a preset driving route, determining whether the bus deviates from the preset driving route according to a comparison result, and triggering the determination unit if the bus deviates;
the determining unit is used for determining a deviation line of the bus, wherein the deviation line refers to a line which is driven by the bus when the bus deviates from the preset driving line and then returns to the preset driving line;
the matching unit is used for judging whether the deviated line has a matched line in a deviated line set, wherein the deviated line set refers to a set of different deviated lines of different buses in a historical time period, and if the deviated line set is matched with the different deviated lines, the determining unit is triggered;
the determining unit is further used for determining that the bus is in a normal operation state.
9. A processing device comprising a processor and a memory, a computer program being stored in the memory, the processor performing the method according to any of claims 1 to 7 when calling the computer program in the memory.
10. A computer-readable storage medium storing a plurality of instructions adapted to be loaded by a processor to perform the method of any one of claims 1 to 7.
CN202210728089.8A 2022-06-24 2022-06-24 Bus operation state identification method and device and processing equipment Pending CN115116258A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202210728089.8A CN115116258A (en) 2022-06-24 2022-06-24 Bus operation state identification method and device and processing equipment

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202210728089.8A CN115116258A (en) 2022-06-24 2022-06-24 Bus operation state identification method and device and processing equipment

Publications (1)

Publication Number Publication Date
CN115116258A true CN115116258A (en) 2022-09-27

Family

ID=83329084

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202210728089.8A Pending CN115116258A (en) 2022-06-24 2022-06-24 Bus operation state identification method and device and processing equipment

Country Status (1)

Country Link
CN (1) CN115116258A (en)

Citations (37)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20030094579A (en) * 2002-06-04 2003-12-18 케이비 테크놀러지 (주) Apparatus and method for tracking of bus running route
US20090326798A1 (en) * 2007-05-02 2009-12-31 International Business Machines Corporation Method, computer program and system for optimising routes provided by navigation systems
WO2011160687A1 (en) * 2010-06-23 2011-12-29 Tomtom International B.V. System and method of optimizing and dynamically updating route information
JP2012233725A (en) * 2011-04-28 2012-11-29 Fujitsu Ten Ltd Information processor, program, and information processing system
US20130030683A1 (en) * 2010-04-27 2013-01-31 Morad Tomer Y Method For Accurately Timing Stations On A Public Transportation Route
US20130304382A1 (en) * 2010-12-21 2013-11-14 Aisin Aw Co., Ltd. Navigation device, navigation method, and program
DE102012220134A1 (en) * 2012-11-06 2014-05-08 Robert Bosch Gmbh Method for detecting deliberate deviation from optimum travel route of vehicle between start point and target point, involves determining deviation from optimal travel route of vehicle, if probability satisfies predetermined criterion
CN104260686A (en) * 2014-10-20 2015-01-07 李铁基 Bus safety control method and system
US20160061617A1 (en) * 2014-09-02 2016-03-03 Microsoft Corporation Providing in-navigation search results that reduce route disruption
CA2908592A1 (en) * 2015-10-15 2017-04-15 Trapeze Software Ulc System and method for managing transit service interruptions
US20170108341A1 (en) * 2015-10-15 2017-04-20 Trapeze Software Ulc System and method for managing transit service interruptions
US20170138744A1 (en) * 2015-11-12 2017-05-18 International Business Machines Corporation Personalized optimal travel route planning
US20170255966A1 (en) * 2014-03-28 2017-09-07 Joseph Khoury Methods and systems for collecting driving information and classifying drivers and self-driving systems
US20170370735A1 (en) * 2016-06-23 2017-12-28 Microsoft Technology Licensing, Llc Detecting deviation from planned public transit route
US20180003516A1 (en) * 2016-03-11 2018-01-04 Route4Me, Inc. Methods and systems for detecting and verifying route deviations
US20180051997A1 (en) * 2016-08-22 2018-02-22 Microsoft Technology Licensing, Llc Generating personalized routes with route deviation information
CN107886706A (en) * 2016-09-30 2018-04-06 河南星云慧通信技术有限公司 A kind of public transit vehicle route monitoring method based on Beidou navigation
CN108922173A (en) * 2018-06-20 2018-11-30 青岛海信网络科技股份有限公司 A kind of vehicle deviation detection method and device
CN109637112A (en) * 2018-11-23 2019-04-16 江苏省南京市公安局交通管理局车辆管理所 Emphasis vehicle source dynamic supervision system and monitoring method
CN109754630A (en) * 2019-02-02 2019-05-14 武汉元光科技有限公司 The method and apparatus for determining car operation route
CN109871423A (en) * 2019-02-26 2019-06-11 武汉元光科技有限公司 The update method and device of public bus network crestal line
CN110232474A (en) * 2019-05-24 2019-09-13 深圳市元征科技股份有限公司 Lap guard path method, device, server and storage medium
US20200013287A1 (en) * 2018-07-06 2020-01-09 Toyota Jidosha Kabushiki Kaisha Information processing apparatus and information processing method
CN110718087A (en) * 2018-07-11 2020-01-21 北京嘀嘀无限科技发展有限公司 Data fusion processing method and device
CN110718088A (en) * 2018-07-12 2020-01-21 北京嘀嘀无限科技发展有限公司 Bus running state monitoring method and device
US10573184B1 (en) * 2018-11-26 2020-02-25 Internatioinal Business Machines Corpoation Monitoring security threat during travel
CN111323035A (en) * 2019-12-18 2020-06-23 北京嘀嘀无限科技发展有限公司 Detection method and detection device for driving yaw and readable storage medium
CN111405473A (en) * 2020-03-10 2020-07-10 南京智鹤电子科技有限公司 Line deviation detection method and device and electronic equipment
CN111435570A (en) * 2019-01-11 2020-07-21 阿里巴巴集团控股有限公司 Bus route matching method and device
US20200240791A1 (en) * 2019-01-25 2020-07-30 Uber Technologies, Inc. Determining dissimilarities between digital maps and a road network using predicted route data and real trace data
CN111489460A (en) * 2019-01-28 2020-08-04 北京嘀嘀无限科技发展有限公司 Travel data processing method, travel data processing device, navigation equipment and computer storage medium
KR20200109427A (en) * 2019-03-12 2020-09-23 주식회사 코어시스템즈 Bus operation management method and system
CN111856541A (en) * 2020-07-24 2020-10-30 苏州中亿通智能系统有限公司 Fixed line vehicle track monitoring system and method
CN113129588A (en) * 2021-03-26 2021-07-16 武汉元光科技有限公司 Method and device for determining bus running line and electronic equipment
CN113256982A (en) * 2021-06-18 2021-08-13 城云科技(中国)有限公司 Vehicle illegal driving detection method and device, computer equipment and storage medium
CN114543824A (en) * 2022-01-14 2022-05-27 北京百度网讯科技有限公司 Method, device, equipment, medium and product for determining vehicle driving route
CN114627645A (en) * 2022-03-04 2022-06-14 北京百度网讯科技有限公司 Method, device and equipment for determining real-time running line of vehicle and storage medium

Patent Citations (38)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20030094579A (en) * 2002-06-04 2003-12-18 케이비 테크놀러지 (주) Apparatus and method for tracking of bus running route
US20090326798A1 (en) * 2007-05-02 2009-12-31 International Business Machines Corporation Method, computer program and system for optimising routes provided by navigation systems
US20130030683A1 (en) * 2010-04-27 2013-01-31 Morad Tomer Y Method For Accurately Timing Stations On A Public Transportation Route
WO2011160687A1 (en) * 2010-06-23 2011-12-29 Tomtom International B.V. System and method of optimizing and dynamically updating route information
US20130304382A1 (en) * 2010-12-21 2013-11-14 Aisin Aw Co., Ltd. Navigation device, navigation method, and program
JP2012233725A (en) * 2011-04-28 2012-11-29 Fujitsu Ten Ltd Information processor, program, and information processing system
DE102012220134A1 (en) * 2012-11-06 2014-05-08 Robert Bosch Gmbh Method for detecting deliberate deviation from optimum travel route of vehicle between start point and target point, involves determining deviation from optimal travel route of vehicle, if probability satisfies predetermined criterion
US20170255966A1 (en) * 2014-03-28 2017-09-07 Joseph Khoury Methods and systems for collecting driving information and classifying drivers and self-driving systems
US20160061617A1 (en) * 2014-09-02 2016-03-03 Microsoft Corporation Providing in-navigation search results that reduce route disruption
CN104260686A (en) * 2014-10-20 2015-01-07 李铁基 Bus safety control method and system
US20170108341A1 (en) * 2015-10-15 2017-04-20 Trapeze Software Ulc System and method for managing transit service interruptions
CA2908592A1 (en) * 2015-10-15 2017-04-15 Trapeze Software Ulc System and method for managing transit service interruptions
US20170138744A1 (en) * 2015-11-12 2017-05-18 International Business Machines Corporation Personalized optimal travel route planning
US20180003516A1 (en) * 2016-03-11 2018-01-04 Route4Me, Inc. Methods and systems for detecting and verifying route deviations
US20170370735A1 (en) * 2016-06-23 2017-12-28 Microsoft Technology Licensing, Llc Detecting deviation from planned public transit route
US20180051997A1 (en) * 2016-08-22 2018-02-22 Microsoft Technology Licensing, Llc Generating personalized routes with route deviation information
CN107886706A (en) * 2016-09-30 2018-04-06 河南星云慧通信技术有限公司 A kind of public transit vehicle route monitoring method based on Beidou navigation
CN108922173A (en) * 2018-06-20 2018-11-30 青岛海信网络科技股份有限公司 A kind of vehicle deviation detection method and device
US20200013287A1 (en) * 2018-07-06 2020-01-09 Toyota Jidosha Kabushiki Kaisha Information processing apparatus and information processing method
CN112863223A (en) * 2018-07-11 2021-05-28 北京嘀嘀无限科技发展有限公司 Bus information prompting method, device, storage medium and program product
CN110718087A (en) * 2018-07-11 2020-01-21 北京嘀嘀无限科技发展有限公司 Data fusion processing method and device
CN110718088A (en) * 2018-07-12 2020-01-21 北京嘀嘀无限科技发展有限公司 Bus running state monitoring method and device
CN109637112A (en) * 2018-11-23 2019-04-16 江苏省南京市公安局交通管理局车辆管理所 Emphasis vehicle source dynamic supervision system and monitoring method
US10573184B1 (en) * 2018-11-26 2020-02-25 Internatioinal Business Machines Corpoation Monitoring security threat during travel
CN111435570A (en) * 2019-01-11 2020-07-21 阿里巴巴集团控股有限公司 Bus route matching method and device
US20200240791A1 (en) * 2019-01-25 2020-07-30 Uber Technologies, Inc. Determining dissimilarities between digital maps and a road network using predicted route data and real trace data
CN111489460A (en) * 2019-01-28 2020-08-04 北京嘀嘀无限科技发展有限公司 Travel data processing method, travel data processing device, navigation equipment and computer storage medium
CN109754630A (en) * 2019-02-02 2019-05-14 武汉元光科技有限公司 The method and apparatus for determining car operation route
CN109871423A (en) * 2019-02-26 2019-06-11 武汉元光科技有限公司 The update method and device of public bus network crestal line
KR20200109427A (en) * 2019-03-12 2020-09-23 주식회사 코어시스템즈 Bus operation management method and system
CN110232474A (en) * 2019-05-24 2019-09-13 深圳市元征科技股份有限公司 Lap guard path method, device, server and storage medium
CN111323035A (en) * 2019-12-18 2020-06-23 北京嘀嘀无限科技发展有限公司 Detection method and detection device for driving yaw and readable storage medium
CN111405473A (en) * 2020-03-10 2020-07-10 南京智鹤电子科技有限公司 Line deviation detection method and device and electronic equipment
CN111856541A (en) * 2020-07-24 2020-10-30 苏州中亿通智能系统有限公司 Fixed line vehicle track monitoring system and method
CN113129588A (en) * 2021-03-26 2021-07-16 武汉元光科技有限公司 Method and device for determining bus running line and electronic equipment
CN113256982A (en) * 2021-06-18 2021-08-13 城云科技(中国)有限公司 Vehicle illegal driving detection method and device, computer equipment and storage medium
CN114543824A (en) * 2022-01-14 2022-05-27 北京百度网讯科技有限公司 Method, device, equipment, medium and product for determining vehicle driving route
CN114627645A (en) * 2022-03-04 2022-06-14 北京百度网讯科技有限公司 Method, device and equipment for determining real-time running line of vehicle and storage medium

Similar Documents

Publication Publication Date Title
CN109767646B (en) Parking method and device
CN105160880A (en) Method and device for estimating vehicle passenger state
CN105683712A (en) Methods and systems for obtaining a multi-modal route
CN106228848B (en) A kind of parking navigation method and apparatus
CN113847925A (en) Method, device, equipment and medium for detecting vehicle yaw based on track data
CN113129588B (en) Method and device for determining bus running line and electronic equipment
CN109658724B (en) Method and device for providing public transport trip information of user
CN105528907A (en) Parking lot management system and parking lot management method
CN112215382B (en) Network appointment vehicle dispatching method, system, electronic equipment and storage medium
CN109840632A (en) A kind of traffic route assessment method and device for planning
CN111091215A (en) Vehicle identification method and device, computer equipment and storage medium
CN110162719A (en) Content delivery method, device, storage medium and computer equipment, vehicle
CN109855641B (en) Method, device, storage medium and terminal equipment for predicting motion trail
CN110113716B (en) Path state information acquisition method and device and storage medium
CN109945880A (en) Paths planning method, relevant device and readable storage medium storing program for executing
CN115116258A (en) Bus operation state identification method and device and processing equipment
CN111132212A (en) Unmanned vehicle network exception handling method, device, equipment and storage medium
CN114049757B (en) Regular bus arrival time estimation method and device, computer equipment and storage medium
CN110017842B (en) Freight vehicle navigation method, terminal device and storage medium
CN114459495B (en) Displacement information generation method, device and computer readable storage medium
CN112750328B (en) Driving path recommendation method, device, equipment and medium
CN112991712B (en) Method, system, computer device and storage medium for predicting traffic density
CN104596532B (en) A kind of section transfer value determines method and device
CN109727332B (en) Method and system for calculating sanitation operation times of sanitation vehicle
CN110718087B (en) Data fusion processing method and device

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination