CN111696376A - Method for determining arrival sequence of buses - Google Patents
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Abstract
The invention discloses a method for determining the arrival sequence of buses, which comprises the following steps: in thatTracking and sampling data parameters of the running state of the bus in a preset area within time to obtain running data of each bus at the current sampling moment; the method comprises the steps that GPS position information of each bus at a reference time is estimated based on running data of each bus at the current sampling time and the previous sampling time, and then the running sequence of the bus is arranged to obtain a vehicle running sequence; and determining the arrival sequence of the vehicles and issuing dynamic arrival information of the vehicles based on the entering conditions and the sequencing results of the buses in the second preset area. Wherein, the first preset area and the second preset area are both connected with the busThe parking platform of the vehicle is related to the position of the parking platform. The invention can effectively provide accurate and real-time vehicle arrival information for passengers on the site of the platform, provides necessary information support for standardizing passenger riding behaviors, and further effectively improves passenger riding efficiency and bus running efficiency.
Description
Technical Field
The invention relates to the technical field of intelligent transportation, in particular to a method for determining a bus arrival sequence.
Background
With the development of national economy, the quantity of motor vehicles kept is higher and higher, and the existing infrastructure construction cannot meet the increasing traffic demand, so that the serious traffic jam problem is caused. The public transportation service is vigorously developed, the road utilization rate and the resident trip efficiency are improved, the method is an important measure for relieving traffic problems, and the method has important significance for constructing a good urban transportation system.
In the existing public transport system, the passenger information service platform can provide approximate time for passengers to get in the bus, and the order of getting in the bus when a plurality of buses get in the bus cannot be determined. Typically, when multiple buses simultaneously arrive at a station, passengers can only judge the stop position of the buses according to personal visual senses, so that the phenomena of vehicle chasing, vehicle interception, crowded boarding and the like are generated. In places such as BRT closed platforms, the accurate order of entering the station of the vehicle is lacked, and the normal queuing and taking of the vehicle can be influenced. Not only influences passenger efficiency of taking a bus and the whole operating efficiency of bus, still can arouse certain safety problem.
At present, in an intelligent bus system, buses are provided with positioning devices such as a GPS (global positioning system) and the like, and the intelligent bus system has the function of recording the full-time empty running state data of the buses. In general, the vehicle driving data collected by the GPS device includes: data sampling time, operation lines, vehicle numbers, current longitude and latitude positions, operation speed, visitor getting-on and getting-off records and the like. The information can provide basis for judging the arrival sequence of the buses.
Disclosure of Invention
In view of the above, the present invention provides a method for determining a stop order of a bus, which fully utilizes a bus GPS device to collect vehicle travel track data, determines a sequence of incoming vehicles, and provides a refined information service for passengers, thereby providing necessary information support for standardizing passenger riding behaviors.
In order to achieve the purpose, the invention provides the following technical scheme:
in thatWithin time, the running state of the public transport vehicles in the preset areaTracking and sampling the data parameters to obtain the running data of each vehicle at the current sampling moment; the driving data mainly comprises the current sampling time, longitude and latitude position data of the vehicle at the current sampling time, a route to which the vehicle belongs and the driving speed of the vehicle; estimating GPS position information of each bus at a reference time based on the running data of each bus at the current sampling time and the previous sampling time, and further arranging the running sequence of the plurality of buses to obtain a vehicle running sequence; and determining the arrival sequence of the vehicles and issuing the arrival information of the vehicles in real time based on the condition that the bus drives into the second preset area and the sequencing result.
Accordingly, the present invention provides a first possible embodiment, wherein the above is described inThe method comprises the following steps of tracking and sampling data parameters of the running state of the bus in a preset area within time to obtain the running data of the bus at the current sampling moment, wherein the steps comprise: acquiring a bus stop line of the station which normally runs; a first preset area and a second preset area are defined; the setting of parameters such as the position, the size, the shape and the like of a preset area is related to the basic conditions of the platform and the target vehicle; and based on the parking route and the preset area, screening and accessing the sampling data of the target vehicle which runs in the preset area and has the right of parking at the platform by taking the GPS coordinates as a division basis. And preprocessing the data, including abnormal processing operations such as data redundancy, data loss, GPS data drift and the like.
With reference to the first possibility, the present invention provides a second possible implementation manner, wherein the step of estimating GPS position information of each bus at a reference time based on travel data of each bus at a current sampling time and a previous sampling time, and further ranking a travel sequence of a plurality of buses to obtain a vehicle travel sequence includes: determining a reference time according to the current sampling time of each target vehicle; calculating longitude and latitude data of each target vehicle at the reference time according to the running data of each target vehicle at the current sampling time and the previous sampling time; and arranging the running sequence of the target vehicles based on the longitude and latitude data of the target vehicles at the reference time to obtain a vehicle sequencing result.
With reference to the second possible implementation manner, the present invention provides a third possible implementation manner, wherein the step of determining the reference time according to the current sampling time of each target vehicle specifically includes: and selecting the earliest moment in the current sampling moments of the target vehicles as a reference moment.
With reference to the second possible implementation manner, the present invention further provides a fourth possible implementation manner, where the step of calculating the longitude and latitude data of each target vehicle at the reference time according to the traveling data of each target vehicle at the current sampling time and the previous sampling time includes: searching driving data corresponding to each target vehicle at a sampling moment before the current sampling moment; calculating the absolute driving distance of each target vehicle in the time interval between the current sampling moment and the previous sampling moment according to the longitude and latitude data of each target vehicle at the current sampling moment and the longitude and latitude data of the previous sampling moment; calculating the relative travel distance of each target vehicle in the time interval between the current sampling moment and the reference moment according to the reference moment, the travel speed of each target vehicle at the current sampling moment and the travel speed of each target vehicle at the previous sampling moment; and determining the longitude and latitude data of each target vehicle at the reference time according to the absolute driving distance, the relative driving distance, the longitude and latitude data of each target vehicle at the current sampling time and the longitude and latitude data of the previous sampling time.
With reference to the fourth possible implementation manner, the present invention provides a fifth possible implementation manner, wherein the step of calculating the absolute travel distance of each target vehicle in the time interval between the current sampling time and the previous sampling time includes: the absolute travel distance is calculated according to the following formula:
wherein,it is indicated that the absolute distance traveled,which represents the radius of the earth and is,representing the longitude of each of the target vehicles at the current sampling time,representing the longitude of each of the target vehicles at the previous sample time,indicating the latitude of each of the target vehicles at the current sampling time,indicating the latitude of each of the target vehicles at the previous sampling time.
With reference to the fourth possible implementation manner, the present invention further provides a sixth possible implementation manner, wherein the step of calculating the relative travel distance of each target vehicle in the time interval between the current sampling time and the reference time includes: the relative travel distance is calculated according to the following formula,
wherein,the relative distance of travel is indicated by,indicating the traveling speed of each of the target vehicles at the current sampling time,representing the travel speed of each of the target vehicles at the previous sampling time,which is indicative of the current sampling instant,a representation of a previous sampling instant is represented,indicating the reference time.
With reference to the fourth possible implementation manner, the present invention further provides a seventh possible implementation manner, wherein the step of determining longitude and latitude data of each target vehicle at the reference time includes: calculating the longitude and latitude data of each target vehicle at the reference moment according to the following formula:
wherein,indicates the longitude of each of the target vehicles at the reference time,indicating the latitude of each of the target vehicles at the reference time.
With reference to the foregoing technical solution, the present invention provides an eighth possible implementation manner, wherein the second preset implementation manner is based on the fact that the bus drives into the second preset configuration mannerThe step of determining the arrival sequence of the vehicles according to the conditions of the areas and the sequencing result comprises the following steps: after the vehicles are sequenced, if the vehicles enter a second preset area in the data at the current sampling moment, issuing a line to which the first vehicle in the queuing sequence belongs based on the queuing result; if the difference between the GPS coordinates of the second vehicle and the third vehicle at the reference moment and the coordinates of the first vehicle is within a certain threshold value, sequentially issuing arrival information; if no vehicle enters the second area in the data of the current sampling moment, returning to execute the initial step, namely, executing the next stepVehicle sequencing is performed again within time.
The embodiment of the invention has the following beneficial effects:
the method for determining the bus stop sequence comprises the steps of sampling and tracking the running data of the buses, utilizing the current sampling time data and the running data of the previous sampling time to presume the longitude and latitude coordinates of the buses at the reference time so as to obtain the sequencing result of a plurality of buses reaching the station, and then carrying out dynamic information release at the station based on the condition that the buses enter a second preset area and the queuing result. The invention can fully utilize the running data regularly issued by the public transport vehicles, and effectively guide passengers to queue for taking by time and place in order by predicting the arrival sequence of multiple vehicles and issuing information on site. In addition, the passengers can save the stop time of the public transport vehicles and shorten the running time by civilized and orderly taking the bus, thereby improving the running efficiency and having obvious effects on improving the service quality of public transport, relieving traffic jam and reducing the occurrence rate of traffic accidents.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a flowchart of a method for determining a bus arrival sequence according to an embodiment of the present invention;
FIG. 2 is a schematic view of a docking station according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a default region according to an embodiment of the present invention;
FIG. 4 is a flowchart illustrating specific steps for determining longitude and latitude coordinates of a vehicle at a reference time according to an embodiment of the present invention;
fig. 5 is a schematic diagram of another preset area provided in the embodiment of the present invention.
Detailed Description
To make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
At present, some unexplained phenomena generally exist in the field of public transportation: passengers are willing to chase a vehicle to be parked or force a bus to be parked without entering a station and get on without being crowded and queued. These phenomena occur especially at busy sites where there is a dense stream of people or who meet peak hours of work. When one bus stops, the stop and the operation of the next bus can be influenced due to the crowding of passengers, so that the stop efficiency of the bus is reduced, the operation time is increased, and even traffic accidents occur. Based on this, the method for determining the bus arrival sequence provided by the embodiment of the invention predicts the bus arrival sequence through the internet of vehicles technology, issues dynamic information in real time, effectively guides the riding behavior of passengers by combining with the channelization of the parking spaces of the platform, can shorten the vehicle stopping time, improves the operation efficiency and relieves traffic jam.
To facilitate understanding of the present embodiment, a method for determining a sequence of bus stops disclosed in the present embodiment is described in detail with reference to a flowchart of a method for determining a sequence of bus stops shown in fig. 1, where the method is executed by a processing system of each stop, and the method may include the following steps:
and S102, sampling and tracking the traffic vehicles in the preset area within 16S to obtain the running data of each traffic vehicle at the current sampling time.
Under the environment of the internet of vehicles, the bus is provided with a running state information acquisition device and a wireless communication terminal device, the running state of the bus can be acquired in real time through the running state information acquisition device, then the acquired running state is sent to a bus center system through the wireless communication terminal device, and the bus center system forwards the running state to a processing system of a stop platform in a wireless mode. Specifically, the driving state information acquisition device may be a GPS (Global Positioning System), a beidou satellite navigation System or a galileo Positioning System; the processing system for the docking station comprises a data processing center and a processing terminal, wherein the data processing center is used for analyzing and calculating the driving state to obtain driving data, the driving data comprise a line to which a vehicle belongs, longitude and latitude of a position where the vehicle is located at the current sampling moment and driving speed of the vehicle, and the processing terminal is used for further processing the driving data.
Further, the sampling interval of the running data is ideally 15s, and actually ranges from 14s to 16 s;the target vehicle can be guaranteed to sample data once theoretically, and the time format of the data is 00:00: 00 actual retrieval of the StoryIs 16 s. Because the data uploading time of each vehicle is inconsistent, the driving sequence of the vehicles cannot be directly compared, so the longitude and latitude positions of the vehicles need to be normalized to the same time, namely the reference time.
The processing of the driving data is relative to each platform processor, so in order to reduce the data calculation amount of the processor, only the vehicle data in the preset area is processed. Therefore, based on the basic situation of the platform of the setting processing system, the preset area is actually defined, and after the longitude and latitude coordinates of the target vehicle accord with the range threshold value of the preset area, the subsequent processing is carried out.
And step S104, determining the longitude and latitude coordinates of each vehicle at the reference moment, and arranging the vehicle form sequence first based on the longitude and latitude coordinates.
In the implementation, the determined reference time is the earliest time in the current sampling time of each vehicle if the determined reference time is the earliest time in the current sampling time of each vehicleAnd in time, if the data are uploaded twice by the vehicle, taking the second-time running data as the current sampling time data, and taking the first-time running data as the previous sampling data. For example, the processing system at the stop collects the traveling data of 3 transportation vehicles, the sampling time 1 of the vehicle a is 00:00:05, the sampling time 2 of the vehicle a is 00:00:19, the sampling time of the transportation vehicle B is 00:00:21, and the sampling time of the transportation vehicle C is 00:00:20, and then the sampling time 2 of the transportation vehicle a is taken as the reference time.
And after the reference time is determined, calculating the longitude and latitude coordinates of each vehicle at the reference time according to the running data of the current sampling time and the running data of the previous sampling time of each vehicle so as to judge the sequence of the vehicle forms.
And step S106, judging whether a vehicle enters a second preset area or not at the current sampling moment.
In the implementation, when a vehicle enters a second preset area, the vehicle enters a parking state in a short time, and the parking positions of the vehicle are issued to the platform system as early as possible according to the queuing sequence of the vehicle so as to reserve time for queuing passengers on the route. If no vehicle enters the second preset area, indicating that a period of time is left for the vehicle to enter the station and stop, and continuing to execute the step S102; if the vehicle enters the second preset area, step S108 is executed.
And step S108, outputting one or more routes to which the vehicles to arrive at the station belong based on the sequencing result.
And after the sequencing is finished, if the running data at the current sampling moment shows that the vehicle enters a second preset area, carrying out passenger information guidance display. If the data uploading time of each vehicle is inconsistent, the first vehicle entering the second preset area is displayed, so that the first vehicle in the queuing sequence is displayed, and the vehicle parking position information is issued on site at the platform; and for the second vehicle, the third vehicle and the subsequent vehicles in the sequence, if the difference value between the longitude and latitude coordinates of the second vehicle at the reference time and the longitude and latitude coordinates of the first vehicle at the reference time is within a certain threshold value range, the line parking information of the second vehicle and the third vehicle is also displayed and induced. Specifically, the value of the threshold value should ensure that the form sequence of the currently-sorted vehicles is not disturbed by the 'strange vehicles' (vehicles which do not appear or collect the driving data before sorting) which are driven into the preset area in the next sorting.
It can be understood that after the vehicle driving sequence is obtained, parking spaces need to be arranged in sequence according to the vehicle driving sequence when the parking information is issued. In actual operation, the vehicle stops for a certain time, the parking stall can be divided into occupied parking stall and unoccupied parking stall, and the parking stall can be flexibly processed according to requirements. For example, the number of parking spaces occupied in unoccupied parking spaces isVehicleThe number of vehicles in the driving sequence isWhen is coming into contact withWhen the number of the idle parking spaces is larger than or equal to the number of the vehicles, the traffic vehicles stop at the parking spaces in sequence according to the driving sequence of the vehicles; when in useWhen the number of idle parking spaces is less than the number of vehicles, the vehicle is the front in the driving sequenceThe vehicle provides a parking space and thenThe traffic vehicle will wait outside the docking station when it is the firstWhen the fixed detector on each parking space detects that the traffic vehicle on the parking space drives away, the traffic vehicle on the parking space is driven away according to the follow-upThe queuing state of the vehicles and the traveling direction of the platform vehicles provide parking positions from front to back in sequence.
The method for determining the bus arrival sequence provided by the embodiment of the invention can be used for sampling and tracking the vehicle running state in the preset area, so as to obtain the running data of each vehicle in the preset area at the current sampling moment, and arranging the running sequences of a plurality of vehicles in the preset area according to the running data of each vehicle at the current sampling moment, so as to obtain the vehicle running sequence, and then, the target stop position of each bus can be actually determined according to the vehicle running sequence and the occupation condition of the stop parking spaces. According to the embodiment of the invention, the driving data of the public transport vehicle is acquired by an informatization means, the arrival sequence of the vehicle is predicted, and the dynamic information is issued in real time, so that necessary information support is provided for standardizing the riding behavior of passengers, and the riding efficiency of the passengers and the running efficiency of the public transport vehicle are effectively improved.
In order to make the aforementioned preset region easy to understand, the basic principle and the dividing method of the preset region are described with reference to fig. 3.
In order to reduce the amount of calculation of the driving data in the platform processor, the vehicles far away from the target platform should be stopped at the platform in a short time without considering the current driving condition, i.e. the vehicles enter the target range (preset area), and the vehicles have the value of predicting the driving sequence. When the vehicle enters a second preset area, the station information display device outputs the vehicle about to arrive at the station, and the passengers are guided to queue according to the actual situation, and the division principle of the second preset area reasonably ensures the identification information and the queuing time of the passengers. The dividing method comprises the following steps:
the method comprises the following steps: spatial geographical area division is utilized.
Referring to fig. 3, the schematic diagram of the predetermined area is centered on the docking station, and two circular areas are defined according to the positioning position of the docking station, and the circular radius is determined according to the actual situation. For example, the average traveling speed of the vehicle is 9m/s, and if the vehicle is about to process its traveling state 50s away from the platform, the first preset area radius may be 450 m; if the queue inducement information is to be displayed 15s further from the station, the second predetermined area has a radius of 135 m. If other factors are considered, corresponding modifications should be made to 450m and 135 m.
The second method comprises the following steps: segment length division is utilized.
Referring to fig. 5, another schematic diagram of a preset area is shown, taking the stop station position as a terminal point, tracing back to an upstream road along the route direction of the traffic vehicle, and assuming a road section length threshold valueWhen the traffic vehicle reaches the parking platform along the line direction, the total distance is less thanThen, the section of the road is a preset area. When the sum of the distances between the traffic vehicles and the parking platform isAnd then, acquiring the running state of the traffic vehicle. In particular, the method comprises the following steps of,and is ofThe calculation formula is as follows:
wherein,representing the number of road segments in the direction of the traffic route between the arrival of the traffic vehicle at the parking platforms,indicating the length of each road segment.
The third method comprises the following steps: utilizing upstream station partitioning.
The intermediate area of the two parking platforms is defined as a preset area by taking the upstream parking platform of the traffic line as a starting point and the current parking platform as a terminal point. When the traffic vehicle exits from the upstream parking platform, the traffic vehicle enters the detection area.
To facilitate understanding of the above embodiments, the embodiment of the present invention further provides a specific method for determining the longitude and latitude of the vehicle at the reference time, and refer to a flowchart of a specific method for determining the longitude and latitude coordinates of the vehicle at the reference time shown in fig. 4. The method can be understood as backtracking the driving state of each target vehicle. Assuming that the running data of N vehicles is collected, the running state corresponding to each vehicle is. In thatSelect the reference timeBacktracking the running states of the other N-1 target vehicles and judging the running states to be at the reference timeThe longitude and latitude coordinates of the positions of the target vehicles are expressed asThe method specifically comprises the following steps:
(1) in step S402, the travel data of each target vehicle at the sampling time immediately before the current sampling time is acquired.
Wherein the running data of the previous sampling time comprises、Andwhereinrepresents latitude and longitude data of a previous sampling time,which represents the time of the previous sampling instant,representing the speed of travel at the previous sample time.
(2) Step S404, calculating the absolute driving distance of each target vehicle in the time interval between the current sampling time and the previous sampling time according to the longitude and latitude data of each target vehicle at the current sampling time and the longitude and latitude data of the previous sampling time.
The absolute travel distance is calculated according to the following formula:
wherein,a first distance of travel is indicated and,which represents the radius of the earth and is,indicating the longitude of each target vehicle at the current sample time,representing the longitude of each target vehicle at the previous sample time,indicating the latitude of each target vehicle at the current sampling instant,indicating the latitude of each target vehicle at the previous sample time.
(3) In step S406, the relative travel distance of each target vehicle in the time interval between the current sampling time and the reference time is calculated based on the reference time, the travel speed of each target vehicle at the current sampling time, and the travel speed at the previous sampling time.
And then calculating to obtain the relative driving distance of each target vehicle:
obtaining:
wherein,it is indicated that the second distance of travel,representing the traveling speed of each target vehicle at the current sampling time,representing the travel speed of each target vehicle at the previous sampling time,which is indicative of the current sampling instant,a representation of a previous sampling instant is represented,indicating the reference time.
(4) Step S408, determining the longitude and latitude data of each target vehicle at the reference time according to the absolute driving distance, the relative driving distance, the longitude and latitude data of each target vehicle at the current sampling time and the longitude and latitude data of the previous sampling time.
Calculating the longitude and latitude data of each target vehicle at the reference moment according to the following formula:
wherein,indicates the longitude of each target vehicle at a preset reference time,indicating the latitude of each target vehicle at a preset reference time.
According to N target vehiclesAnd determining the vehicle running sequence of the N target vehicles according to the synchronous positions of the time.
It should be noted that: the above-mentioned embodiments are only specific embodiments of the present invention, which are used for illustrating the technical solutions of the present invention and not for limiting the same, and the protection scope of the present invention is not limited thereto, although the present invention is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the embodiments of the present invention, and they should be construed as being included therein. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
Claims (9)
1. A method for determining the arrival sequence of buses is characterized by comprising the following steps:
in thatTracking and sampling data parameters of the running state of the bus in a preset area within time to obtain the running data of each bus at the current sampling moment; the driving data mainly comprises the current sampling time, longitude and latitude position data of the vehicle at the current sampling time, a route to which the vehicle belongs and the driving speed of the vehicle;
estimating GPS position information of each bus at a reference time based on the running data of each bus at the current sampling time and the previous sampling time, and further arranging the running sequence of the plurality of buses to obtain a vehicle running sequence;
and determining the arrival sequence of the vehicles and issuing the arrival information of the vehicles in real time based on the condition that the bus drives into the second preset area and the sequencing result.
2. The method of claim 1, wherein the step of applying is performed atThe method comprises the following steps of tracking and sampling data parameters of the running state of the bus in a preset area within time to obtain the running data of the bus at the current sampling moment, wherein the steps comprise:
acquiring a bus stop line of the station which normally runs;
a first preset area and a second preset area are defined; the setting of parameters such as the position, the size, the shape and the like of a preset area is related to the basic conditions of the platform and the target vehicle;
based on the parking route and the preset area, screening and accessing sampling data of a target vehicle which runs in the preset area and has a parking right at the platform according to the GPS coordinates;
and preprocessing the data, including abnormal processing operations such as data redundancy, data loss, GPS data drift and the like.
3. The method as claimed in claim 1, wherein the step of estimating the GPS position information of each bus at the reference time based on the travel data of each bus at the current sampling time and the previous sampling time, and further ranking the travel sequence of the plurality of buses to obtain the vehicle travel sequence comprises:
determining a reference time according to the current sampling time of each target vehicle;
calculating longitude and latitude data of each target vehicle at the reference time according to the running data of each target vehicle at the current sampling time and the previous sampling time;
and arranging the running sequence of the target vehicles based on the longitude and latitude data of the target vehicles at the reference time to obtain a vehicle sequencing result.
4. The method of claim 3, wherein said step of determining a reference time based on a current sample time for each of said target vehicles comprises:
and selecting the earliest moment in the current sampling moments of the target vehicles as a reference moment.
5. The method of claim 3, wherein the step of calculating the longitude and latitude position of each of the target vehicles at the reference time based on the travel data of each of the target vehicles at the current sampling time and the previous sampling time comprises:
searching driving data corresponding to each target vehicle at a sampling moment before the current sampling moment;
calculating the absolute driving distance of each target vehicle in the time interval between the current sampling moment and the previous sampling moment according to the longitude and latitude data of each target vehicle at the current sampling moment and the longitude and latitude data of the previous sampling moment;
calculating the relative travel distance of each target vehicle in the time interval between the current sampling moment and the reference moment according to the reference moment, the travel speed of each target vehicle at the current sampling moment and the travel speed of each target vehicle at the previous sampling moment;
and determining the longitude and latitude data of each target vehicle at the reference time according to the absolute driving distance, the relative driving distance, the longitude and latitude data of each target vehicle at the current sampling time and the longitude and latitude data of the previous sampling time.
6. The method of claim 5, wherein the step of calculating the absolute distance traveled by each of the target vehicles in the time interval between the current sample time and the previous sample time comprises:
the absolute travel distance is calculated according to the following formula:
wherein,it is indicated that the absolute distance traveled,which represents the radius of the earth and is,representing the longitude of each of the target vehicles at the current sampling time,indicating a previous sample for each of the target vehiclesThe longitude of the time of day is,indicating the latitude of each of the target vehicles at the current sampling time,indicating the latitude of each of the target vehicles at the previous sampling time.
7. The method of claim 4, wherein said step of calculating the relative travel distance of each of said target vehicles within the time interval between said current sample time and said reference time comprises:
the relative travel distance is calculated according to the following formula:
wherein,the relative distance of travel is indicated by,indicating the traveling speed of each of the target vehicles at the current sampling time,representing the travel speed of each of the target vehicles at the previous sampling time,which is indicative of the current sampling instant,a representation of a previous sampling instant is represented,indicating the reference time.
8. The method of claim 5, wherein the step of determining longitude and latitude data for each of the target vehicles at the reference time comprises:
calculating the longitude and latitude data of each target vehicle at the reference moment according to the following formula:
9. The method according to claim 1, wherein the step of determining the arrival sequence of the vehicles based on the condition that the buses drive into the second preset area and the sequencing result comprises the steps of:
after the vehicles are sequenced, if the vehicles enter a second preset area in the data at the current sampling moment, issuing a line to which the first vehicle in the queuing sequence belongs based on the queuing result; if the difference between the GPS coordinates of the second vehicle and the third vehicle at the reference moment and the coordinates of the first vehicle is within a certain threshold value, sequentially issuing arrival information;
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Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN113066302A (en) * | 2021-03-24 | 2021-07-02 | 北京百度网讯科技有限公司 | Vehicle information prediction method and device and electronic equipment |
CN113658429A (en) * | 2021-08-11 | 2021-11-16 | 青岛海信网络科技股份有限公司 | Cooperative scheduling method and related device for bus corridor |
CN113888894A (en) * | 2021-10-14 | 2022-01-04 | 英博超算(南京)科技有限公司 | Intelligent bus stop system based on unmanned driving |
Citations (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2013073833A1 (en) * | 2011-11-14 | 2013-05-23 | 한국과학기술원 | Method and system for guidance to a destination using public displays or public speakers |
CN103593988A (en) * | 2013-11-08 | 2014-02-19 | 东南大学 | Method for arranging steering buses in sequence in bus stop at inner side of road |
CN103605725A (en) * | 2013-11-15 | 2014-02-26 | 中国联合网络通信集团有限公司 | Bus arrival time inquiring method, NFC terminal and server |
CN103838868A (en) * | 2014-03-21 | 2014-06-04 | 东南大学 | Urban bus arrival time predicting method based on multi-bus-route operating data fusion |
CN105810011A (en) * | 2016-05-26 | 2016-07-27 | 南京信息工程大学 | Dynamic parking space allocation method and intelligent vehicle parking guide system |
CN206628086U (en) * | 2016-12-27 | 2017-11-10 | 山东科技大学 | Bus travels green ripple optimization system on a kind of public transportation lane |
CN107452215A (en) * | 2017-07-31 | 2017-12-08 | 河南城建学院 | A kind of public transport, which pulls in, stops berth allocation and passenger's bootstrap technique and its intelligent bus platform |
CN108978516A (en) * | 2018-07-10 | 2018-12-11 | 上海电机学院 | Intelligent queuing guides system and method |
CN109448431A (en) * | 2018-12-05 | 2019-03-08 | 山东科技大学 | It waits method for determining position, device and intelligent terminal |
-
2019
- 2019-03-12 CN CN201910182610.0A patent/CN111696376A/en active Pending
Patent Citations (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2013073833A1 (en) * | 2011-11-14 | 2013-05-23 | 한국과학기술원 | Method and system for guidance to a destination using public displays or public speakers |
CN103593988A (en) * | 2013-11-08 | 2014-02-19 | 东南大学 | Method for arranging steering buses in sequence in bus stop at inner side of road |
CN103605725A (en) * | 2013-11-15 | 2014-02-26 | 中国联合网络通信集团有限公司 | Bus arrival time inquiring method, NFC terminal and server |
CN103838868A (en) * | 2014-03-21 | 2014-06-04 | 东南大学 | Urban bus arrival time predicting method based on multi-bus-route operating data fusion |
CN105810011A (en) * | 2016-05-26 | 2016-07-27 | 南京信息工程大学 | Dynamic parking space allocation method and intelligent vehicle parking guide system |
CN206628086U (en) * | 2016-12-27 | 2017-11-10 | 山东科技大学 | Bus travels green ripple optimization system on a kind of public transportation lane |
CN107452215A (en) * | 2017-07-31 | 2017-12-08 | 河南城建学院 | A kind of public transport, which pulls in, stops berth allocation and passenger's bootstrap technique and its intelligent bus platform |
CN108978516A (en) * | 2018-07-10 | 2018-12-11 | 上海电机学院 | Intelligent queuing guides system and method |
CN109448431A (en) * | 2018-12-05 | 2019-03-08 | 山东科技大学 | It waits method for determining position, device and intelligent terminal |
Non-Patent Citations (1)
Title |
---|
李少伟等: "基于GPS轨迹数据的公交到站时间预测方法研究", 《软件工程》 * |
Cited By (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN113066302A (en) * | 2021-03-24 | 2021-07-02 | 北京百度网讯科技有限公司 | Vehicle information prediction method and device and electronic equipment |
CN113066302B (en) * | 2021-03-24 | 2022-05-20 | 北京百度网讯科技有限公司 | Vehicle information prediction method and device and electronic equipment |
CN113658429A (en) * | 2021-08-11 | 2021-11-16 | 青岛海信网络科技股份有限公司 | Cooperative scheduling method and related device for bus corridor |
CN113658429B (en) * | 2021-08-11 | 2022-06-07 | 青岛海信网络科技股份有限公司 | Cooperative scheduling method and related device for bus corridor |
CN113888894A (en) * | 2021-10-14 | 2022-01-04 | 英博超算(南京)科技有限公司 | Intelligent bus stop system based on unmanned driving |
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