CN114822061A - Arrival time estimation method and device, electronic equipment and computer program product - Google Patents
Arrival time estimation method and device, electronic equipment and computer program product Download PDFInfo
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- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/0968—Systems involving transmission of navigation instructions to the vehicle
- G08G1/096805—Systems involving transmission of navigation instructions to the vehicle where the transmitted instructions are used to compute a route
- G08G1/096811—Systems involving transmission of navigation instructions to the vehicle where the transmitted instructions are used to compute a route where the route is computed offboard
- G08G1/096822—Systems involving transmission of navigation instructions to the vehicle where the transmitted instructions are used to compute a route where the route is computed offboard where the segments of the route are transmitted to the vehicle at different locations and times
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
- G08G1/0129—Traffic data processing for creating historical data or processing based on historical data
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/0968—Systems involving transmission of navigation instructions to the vehicle
- G08G1/096805—Systems involving transmission of navigation instructions to the vehicle where the transmitted instructions are used to compute a route
- G08G1/096827—Systems involving transmission of navigation instructions to the vehicle where the transmitted instructions are used to compute a route where the route is computed onboard
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Abstract
The embodiment of the disclosure discloses a method and a device for estimating arrival time, electronic equipment and a computer program product, wherein the method comprises the following steps: determining a target route, wherein the target route contains one or more target road segments; estimating and obtaining the predicted passing time of the target road section based on the real-time passing time and the historical passing time corresponding to the target road section; and adding the departure time of the target route and the expected passing time of the target road section contained in the target route to obtain the estimated arrival time of the target route. According to the technical scheme, the estimation accuracy of the time required for reaching the destination can be effectively improved, the influence of low estimation accuracy of the time of reaching on traffic road conditions is avoided, meanwhile, the service quality of a traffic navigation service platform can be improved, and the use experience of a user is improved.
Description
Technical Field
The disclosed embodiments relate to the field of navigation technologies, and in particular, to a method and an apparatus for estimating arrival time, an electronic device, and a computer program product.
Background
With the development and progress of society, vehicles on roads are more and more, and many users can check navigation routes and time required for reaching destinations through application software with a map navigation function before going out. Due to the fact that the traffic conditions of the road are suddenly changed compared with the daily traffic conditions of the road due to the conditions of the peak at morning and evening, holidays, traffic accidents and the like, the sudden change of the traffic conditions can affect the accuracy of the estimation of the time needed for reaching the destination. In turn, the accuracy of the time required to reach the destination can affect the user's decision to go out, and thus affect the traffic conditions. Therefore, it is an important issue to improve the accuracy of the estimation of the time required to reach the destination.
Disclosure of Invention
The embodiment of the disclosure provides an arrival time estimation method and device, electronic equipment and a computer program product.
In a first aspect, an arrival time estimation method is provided in the embodiments of the present disclosure.
Specifically, the arrival time estimation method includes:
determining a target route, wherein the target route contains one or more target road segments;
estimating and obtaining the predicted passing time of the target road section based on the real-time passing time and the historical passing time corresponding to the target road section;
and adding the departure time of the target route and the expected passing time of the target road section contained in the target route to obtain the estimated arrival time of the target route.
With reference to the first aspect, in a first implementation manner of the first aspect, the estimating to obtain the predicted passing time of the target road segment based on the real-time passing time and the historical passing time corresponding to the target road segment includes:
determining an expected time of entry for the target road segment;
determining real-time passing time of a target real-time batch of the target road section to which the predicted entry time belongs;
acquiring historical transit time of the target road section in a historical time batch corresponding to the estimated entry time;
and performing weighted calculation on the real-time passing time and the historical passing time to obtain the predicted passing time of the target road section.
With reference to the first aspect and the first implementation manner of the first aspect, in a second implementation manner of the first aspect, the determining a real-time transit time of a target real-time batch of the target road segment to which the predicted entry time belongs includes:
acquiring position data of a traveling object traveling on the target road section in a target real-time batch to which the estimated entry time belongs;
determining real-time passing time for the traveling object to pass through the target road section according to the position data of the traveling object;
and determining the average value of the real-time passing time of the traveling object, and taking the average value as the real-time passing time of the target real-time batch of the target road section to which the predicted entering time belongs.
With reference to the first aspect and the foregoing implementation manner of the first aspect, in a third implementation manner of the first aspect, the determining an average value of real-time transit times of the traveling objects includes:
removing a deviation value in a real-time transit time of the traveling object;
an average of the remaining real-time transit times is determined.
With reference to the first aspect and the foregoing implementation manner of the first aspect, in a fourth implementation manner of the first aspect, the obtaining the historical transit time of the historical time batch corresponding to the estimated time of entering the target road segment includes:
acquiring position data of the traveling object traveling on the target road section in different historical time batches corresponding to the estimated entry time;
according to the position data of the travelling object, determining the historical passing time of the travelling object corresponding to the historical time batch for passing through the target road section;
and determining the average value of the historical passing time of the travelling object to obtain the historical passing time of different historical time batches on the target road section.
With reference to the first aspect and the foregoing implementation manner of the first aspect, in a fifth implementation manner of the first aspect, the determining an average value of the historical transit times of the traveling objects includes:
removing a deviation value in the historical transit time of the traveling object;
an average of the remaining historical transit times is determined.
With reference to the first aspect and the foregoing implementation manner of the first aspect, in a sixth implementation manner of the first aspect, the performing weighted calculation on the real-time transit time and the historical transit time to obtain an estimated transit time of the target road segment includes:
setting a first initial weight of real-time passing time and a second initial weight of historical passing time, wherein the sum of the first initial weight and the second initial weight is 1;
determining a first product of the first initial weight and real-time transit time;
determining a second product of the second initial weight and the historical transit time;
and determining the sum of the first product and the second product to obtain the predicted passing time of the target road section.
With reference to the first aspect and the foregoing implementation manners of the first aspect, in a seventh implementation manner of the first aspect, the method further includes:
correcting the first initial weight value based on speed curves of the target road section in different historical time batches;
the determining a first product of the first initial weight and the real-time transit time specifically includes:
and determining a first product of the corrected first initial weight and the real-time transit time.
With reference to the first aspect and the foregoing implementation manner of the first aspect, in an eighth implementation manner of the first aspect, the modifying the first initial weight based on the speed curves of the target road segment in different historical time batches includes:
determining speed curves of the target road section in different historical time batches;
detecting to obtain a speed abrupt change point set on the speed curve, wherein the speed abrupt change point set comprises a speed abrupt rising point and a speed abrupt falling point which are crossed;
determining a target historical time batch corresponding to the target real-time batch;
detecting the speed mutation time corresponding to the speed mutation point on the right side of the target historical time batch on the speed curve and closest to the target historical time batch;
determining an absolute time difference between the speed mutation time and the target historical time batch ending time, and determining a weight correction coefficient according to the absolute time difference;
and correcting the first initial weight value into the product of the first initial weight value and the weight value correction coefficient.
With reference to the first aspect and the foregoing implementation manner of the first aspect, in a ninth implementation manner of the first aspect, the determining a speed curve of the target road segment in different historical time batches includes:
determining historical passing speeds of different historical time batches on the target road section based on the length of the target road section and the historical passing times of different historical time batches on the target road section;
generating speed curves of the target road section in different historical time batches based on the historical passing speed;
and smoothing the speed curve.
In a second aspect, an arrival time estimation apparatus is provided in the embodiments of the present disclosure.
Specifically, the arrival time estimation apparatus includes:
a determination module configured to determine a target route, wherein the target route contains one or more target road segments;
the estimation module is configured to estimate to obtain the predicted passing time of the target road section based on the real-time passing time and the historical passing time corresponding to the target road section;
the addition module is configured to add the departure time of the target route and the expected passing time of a target road section contained in the target route to obtain the estimated arrival time of the target route.
In a third aspect, the disclosed embodiments provide an electronic device, including a memory for storing one or more computer instructions that support an arrival time estimation apparatus to perform the above arrival time estimation method, and a processor configured to execute the computer instructions stored in the memory. The arrival time estimation device can also comprise a communication interface for communicating with other equipment or a communication network.
In a fourth aspect, the disclosed embodiments provide a computer-readable storage medium for storing computer instructions for an arrival time estimation apparatus, which includes computer instructions for performing the arrival time estimation method described above as related to the arrival time estimation apparatus.
In a fifth aspect, the present disclosure provides a computer program product, which includes a computer program/instruction, where the computer program/instruction when executed by a processor implements the steps of the above arrival time estimation method.
The technical scheme provided by the embodiment of the disclosure can have the following beneficial effects:
the technical scheme determines the estimated passing time of the target road section based on the real-time passing time and the historical passing time corresponding to the target road section, and further obtains the estimated value of the arrival time of the target route. According to the technical scheme, the estimation accuracy of the time required for reaching the destination can be effectively improved, the influence of low estimation accuracy of the time of reaching on traffic road conditions is avoided, meanwhile, the service quality of a traffic navigation service platform can be improved, and the use experience of a user is improved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of embodiments of the disclosure.
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Other features, objects, and advantages of embodiments of the disclosure will become more apparent from the following detailed description of non-limiting embodiments when taken in conjunction with the accompanying drawings. In the drawings:
FIG. 1 illustrates a flow diagram of a time of arrival estimation method according to an embodiment of the present disclosure;
FIG. 2 shows a block diagram of an arrival time estimation apparatus according to an embodiment of the present disclosure;
FIG. 3 shows a block diagram of an electronic device according to an embodiment of the present disclosure;
fig. 4 is a schematic structural diagram of a computer system suitable for implementing a time-of-arrival estimation method according to an embodiment of the present disclosure.
Detailed Description
Hereinafter, exemplary embodiments of the disclosed embodiments will be described in detail with reference to the accompanying drawings so that they can be easily implemented by those skilled in the art. Also, for the sake of clarity, parts not relevant to the description of the exemplary embodiments are omitted in the drawings.
In the disclosed embodiments, it is to be understood that terms such as "including" or "having," etc., are intended to indicate the presence of the disclosed features, numbers, steps, behaviors, components, parts, or combinations thereof, and are not intended to preclude the possibility that one or more other features, numbers, steps, behaviors, components, parts, or combinations thereof may be present or added.
It should be further noted that the embodiments and features of the embodiments in the present disclosure may be combined with each other without conflict. The embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
The technical scheme provided by the embodiment of the disclosure determines the predicted passing time of the target road section based on the real-time passing time and the historical passing time corresponding to the target road section, and further obtains the estimated value of the arrival time of the target route. According to the technical scheme, the estimation accuracy of the time required for reaching the destination can be effectively improved, the influence of low estimation accuracy of the time of reaching on traffic road conditions is avoided, meanwhile, the service quality of a traffic navigation service platform can be improved, and the use experience of a user is improved.
Fig. 1 shows a flowchart of a method for estimating arrival time according to an embodiment of the present disclosure, as shown in fig. 1, the method for estimating arrival time includes the following steps S101 to S103:
in step S101, a target route is determined, wherein the target route contains one or more target road segments;
in step S102, estimating an estimated transit time of the target road segment based on the real-time transit time and the historical transit time corresponding to the target road segment;
in step S103, the departure time of the target route is added to the expected transit time of the target link included in the target route, so as to obtain the estimated arrival time of the target route.
As mentioned above, as society develops and progresses, vehicles on roads are increasing, and many users view a navigation route and time required for reaching a destination through application software having a map navigation function before traveling. Due to the fact that the traffic conditions of the road are suddenly changed compared with the daily traffic conditions of the road due to the conditions of the peak at morning and evening, holidays, traffic accidents and the like, the sudden change of the traffic conditions can affect the accuracy of the estimation of the time needed for reaching the destination. In turn, the accuracy of the time required to reach the destination can affect the user's decision to go out, and thus affect the traffic conditions. Therefore, it is an important subject to improve the accuracy of the estimation of the time required to reach the destination.
In view of the above problem, in this embodiment, an arrival time estimation method is proposed, which determines an estimated transit time of a target link based on a real-time transit time and a historical transit time corresponding to the target link, and further obtains an estimated value of the arrival time of the target route. According to the technical scheme, the estimation accuracy of the time required for reaching the destination can be effectively improved, the influence of low estimation accuracy of the time of reaching on traffic road conditions is avoided, meanwhile, the service quality of a traffic navigation service platform can be improved, and the use experience of a user is improved.
In an embodiment of the present disclosure, the arrival time estimation method may be applied to a computer, a computing device, an electronic device, a server, a service cluster, and the like, which may perform arrival time estimation.
In one embodiment of the present disclosure, the target route refers to a route for which it is necessary to determine a transit time, i.e., a time required from a start point to an end point of the target route. In an embodiment of the present disclosure, the target route may include one or more target road segments, that is, the target route may be composed of one or more target road segments, where the target road segment may be one road segment in the road network data. In the disclosure, the passing time of the target road section is respectively estimated, and the passing time of the target route is finally obtained.
In an embodiment of the present disclosure, the real-time transit time corresponding to the target road segment refers to a determined time required for a traveling object such as a vehicle to pass through the target road segment within a certain short time period closest to the departure time of the target route, where a duration of the short time period may be set by a person skilled in the art according to a requirement of an actual application, for example, the short time period may be set to a time period as long as several minutes.
In an embodiment of the present disclosure, the historical transit time corresponding to the target road segment refers to a determined time required for a traveling object such as a vehicle to pass through the target road segment within a certain historical longer time period, where a duration of the longer time period may be set by a person skilled in the art according to a requirement of an actual application, for example, the longer time period may be set to a time period of several weeks or several days.
In an embodiment of the present disclosure, the traveling object refers to a sample object that can be observed and counted and can travel in a certain traveling direction. The traveling object may be a vehicle, for example, but in other application scenarios, the traveling object may also be a pedestrian, a bicycle, or another statistically traveling object.
Considering that the navigation route planning is divided into two cases, one is that the route is requested to be started at present, and the other is that the route is started at a future time through the navigation software, in an embodiment of the present disclosure, the starting time of the target route may be the current time or a future time specified by the user.
In the above embodiment, after a target route and one or more target road segments included in the target route are determined, taking each target road segment as an analysis object, obtaining real-time passing time and historical passing time corresponding to the target road segment, and estimating to obtain predicted passing time of the target road segment based on the real-time passing time and the historical passing time corresponding to the target road segment, where a sum of the predicted passing times of the one or more target road segments is the predicted passing time of the target route; and finally, adding the departure time of the target route and the expected passing time of the target route to obtain the estimated arrival time of the target route.
In an embodiment of the present disclosure, the step S102 of estimating the predicted transit time of the target road segment based on the real-time transit time and the historical transit time corresponding to the target road segment may include the following steps:
determining an expected time of entry for the target road segment;
determining real-time passing time of a target real-time batch of the target road section to which the predicted entry time belongs;
obtaining historical passing time of a historical time batch corresponding to the estimated entering time of the target road section;
and performing weighted calculation on the real-time passing time and the historical passing time to obtain the predicted passing time of the target road section.
In an embodiment of the present disclosure, the predicted time of entering the target road segment refers to a predicted time of entering the target road segment, and the predicted time of entering the target road segment is related to a relationship between the target road segment and a current road segment where the traveling object is located, for example, when the target road segment is a road segment where the traveling object requests to plan a navigation route, that is, an initial road segment, the predicted time of entering the target road segment may be considered as a time when the traveling object requests to plan the navigation route; when the target segment is a segment following the starting segment in the target route, such as a segment next to the starting segment or another segment between the starting segment and the target route destination, the predicted time of entry for the target segment may be considered to be the sum of the time when planning the navigation route is requested and the predicted transit time for one or more intermediate segments, where the intermediate segments refer to the segments between the starting segment and the target segment. For example, if the time when the navigation route is requested to be planned is 10 a.m.: 00, the target route comprises 3 target road sections, wherein the predicted passing time of the first target road section and the target road section 1 is 2 minutes, the predicted passing time of the second target road section and the target road section 2 is 1 minute, the predicted passing time of the third target road section and the target road section 3 is 3 minutes, and then the predicted entering time of the target road section 1 is the time 10 when the navigation route is requested to be planned: 00, the predicted entering time of the target road section 2 is the sum of the time when the navigation route is requested to be planned and the predicted passing time of the target road section 1, namely 10: 02, the predicted entry time of the target road segment 3 is the sum of the time when the navigation route is requested to be planned and the predicted passing time of the target road segment 1 and the target road segment 2, namely 10: 03.
in order to improve the accuracy of determining the predicted passing time of the target road section, in the embodiment, the predicted passing time of the target road section is determined by combining the real-time passing time and the historical passing time. Specifically, the predicted entry time of the target road segment is first determined according to the method described above; then, determining real-time passing time of a target real-time batch of the target road section, which can embody real-time passing characteristics, to which the predicted entry time belongs, wherein the real-time batch refers to a time batch for performing real-time data calculation, into which a certain fixed time duration is divided, for example, if the fixed time duration is one day, the real-time batch may be a time batch obtained by dividing 24 hours a day by one minute, and at this time, if the predicted entry time is 10: 01: 15 seconds, the target real-time batch to which the predicted entry time belongs is a time batch in which 10: 01: 10: 02: 10; then, acquiring historical passage time of a historical time batch corresponding to the predicted entry time of the target road section, wherein the historical passage time batch can represent historical passage characteristics, the historical time batch refers to a time batch which is used for historical data calculation and is obtained by dividing a certain fixed time length in a certain historical time length, for example, if the historical time length is a month and the fixed time length is a day, the historical time batch can be a time batch obtained by dividing 24 hours of each day of a month by ten minutes, and at this time, if the predicted entry time is 10 am 01 pm of the first week of the month for 15 seconds, the historical time batch corresponding to the predicted entry time is a time batch from 10 pm 00 pm to 10 pm of the first week of the month for 10 pm; and finally, performing weighted calculation on the real-time passing time and the historical passing time to obtain the predicted passing time of the target road section.
In an embodiment of the present disclosure, the step of determining the real-time transit time of the target real-time batch of the target road segment to which the predicted entry time belongs may include the following steps:
acquiring position data of the traveling object which runs on the target road section in the target real-time batch to which the estimated entering time belongs;
determining real-time passing time for the traveling object to pass through the target road section according to the position data of the traveling object;
and determining the average value of the real-time passing time of the traveling object, and taking the average value as the real-time passing time of the target real-time batch of the target road section to which the predicted entering time belongs.
In this embodiment, in order to obtain the real-time transit time of the target real-time batch to which the predicted entry time belongs, which is capable of embodying the real-time transit feature, first, position data of one or more traveling objects traveling on the target road segment in the target real-time batch is obtained, and a position data set is obtained, where the position data set includes the position data of the one or more traveling objects; then, according to the position data of the one or more traveling objects in the position data set, the real-time passing time of the one or more traveling objects corresponding to the target real-time batch respectively passing through the target road section can be determined; and finally, determining the average value of the real-time passing time of the one or more traveling objects, so as to obtain the real-time passing time of the target real-time batch of the target road section to which the predicted entering time belongs.
In consideration of the fact that the traveling objects may have special situations such as faults and accidents, and the corresponding transit times thereof may also greatly deviate from the median of the transit times, in an embodiment of the present disclosure, the deviation value in the real-time transit times of the one or more traveling objects is removed, and then the average value of the real-time transit times is determined. That is, in an embodiment of the present disclosure, the step of determining the average value of the real-time transit times of the one or more traveling objects may include the steps of:
removing a deviation value in a real-time transit time of the traveling object;
an average of the remaining real-time transit times is determined.
The deviation value refers to the real-time passing time of which the difference value between the real-time passing time value and the real-time passing time median value is larger than a first preset threshold value.
In an embodiment of the present disclosure, obtaining the historical transit time of the historical time batch corresponding to the estimated time of entering the target road segment may include:
acquiring position data of the traveling object traveling on the target road section in different historical time batches corresponding to the estimated entry time;
according to the position data of the travelling object, determining the historical passing time of the travelling object corresponding to the historical time batch for passing through the target road section;
and determining the average value of the historical passing time of the travelling object to obtain the historical passing time of different historical time batches on the target road section.
In this embodiment, in order to obtain the historical transit time of the historical time batch corresponding to the predicted entry time of the target road segment, which can embody the historical transit characteristics, it is necessary to first determine the historical transit time of different historical time batches on the target road segment, and then obtain the historical transit time of the historical time batch corresponding to the predicted entry time according to the predicted entry time. When determining the historical transit time of different historical time batches on the target road section, firstly, acquiring the position data of one or more traveling objects traveling on the target road section in different historical time batches corresponding to the estimated entry time to obtain a position data set, wherein the position data set comprises the position data of the one or more traveling objects; then, according to the position data of the one or more traveling objects in the position data set, the historical transit time for the one or more traveling objects corresponding to the historical time batch to respectively pass through the target road section can be determined; and finally, determining the average value of the historical passing time of the one or more traveling objects, so as to obtain the historical passing time of different historical time batches on the target road section.
In the embodiment of the present disclosure, it is also necessary to determine the average value of the historical transit times after removing the deviation value in the historical transit times of the one or more traveling objects, because the corresponding transit times of the traveling objects may also deviate from the median value of the transit times in consideration of the possible special situations such as faults and accidents. That is, in an embodiment of the present disclosure, the step of determining the average value of the historical transit times of the traveling object may include the steps of:
removing a deviation value in the historical transit time of the traveling object;
an average of the remaining historical transit times is determined.
Wherein, the deviation value refers to the historical transit time of which the difference value between the historical transit time numerical value and the historical transit time median value is larger than a first preset threshold value.
In an embodiment of the present disclosure, the step of performing a weighted calculation on the real-time transit time and the historical transit time to obtain the predicted transit time of the target road segment may include the following steps:
setting a first initial weight of real-time passing time and a second initial weight of historical passing time, wherein the sum of the first initial weight and the second initial weight is 1;
determining a first product of the first initial weight and real-time transit time;
determining a second product of the second initial weight and the historical transit time;
and determining the sum of the first product and the second product to obtain the predicted passing time of the target road section.
In this embodiment, the real-time transit time and the historical transit time are weighted to obtain the predicted transit time of the target road segment, specifically, a first initial weight corresponding to the real-time transit time and a second initial weight corresponding to the historical transit time are first set, where a sum of the first initial weight and the second initial weight is 1, for example, if the first initial weight is represented as w, the second initial weight may be represented as 1-w; then determining a first product of the first initial weight and the real-time transit time; determining a second product of the second initial weight and the historical transit time; and finally, determining the sum of the first product and the second product to obtain the predicted passing time of the target road section.
In an embodiment of the present disclosure, the method may further include the steps of:
and correcting the first initial weight value based on the speed curves of the target road section in different historical time batches.
As mentioned above, sudden changes in traffic conditions brought by the peak, holiday, traffic accident and other situations in the morning and evening affect the accuracy of the estimation of the time required to reach the destination, and the data associated with the peak, holiday and traffic accident in the morning and evening are different, for example, the peak and holiday in the morning and evening are relatively regular, the real-time transit time is of little significance to the determination of the estimated transit time, the historical transit time is more important to the determination of the estimated transit time, and the historical transit time should be paid more attention to, so the determination weight of the historical transit time should become larger. Therefore, in order to improve the accuracy of determining the predicted transit time of the target link, in this embodiment, the first initial weight value needs to be further modified based on the speed curves of the target link in different historical time batches.
In this embodiment, the determining a first product of the first initial weight and the real-time transit time specifically includes:
and determining a first product of the corrected first initial weight and the real-time transit time.
In an embodiment of the present disclosure, the step of correcting the first initial weight based on the speed curves of the target road segment in different historical time batches may include the following steps:
determining speed curves of the target road section in different historical time batches;
detecting to obtain a speed abrupt change point set on the speed curve, wherein the speed abrupt change point set comprises a speed abrupt rising point and a speed abrupt falling point which are crossed;
determining a target historical time batch corresponding to the target real-time batch;
detecting the speed mutation time corresponding to the speed mutation point on the right side of the target historical time batch on the speed curve and closest to the target historical time batch;
determining an absolute time difference between the speed mutation time and the target historical time batch ending time, and determining a weight correction coefficient according to the absolute time difference;
and correcting the first initial weight value into the product of the first initial weight value and the weight value correction coefficient.
In this embodiment, the weight is corrected by means of the speed profiles of the target road sections in different historical time batches. Specifically, the method comprises the following steps: firstly, determining speed curves of different historical time batches of the target road section, wherein the speed curves consist of speed points corresponding to the different historical time batches of the target road section, and detecting a speed mutation point set on the speed curves by using algorithms such as a mutation point detection algorithm based on a gradient correlation matrix determinant, wherein the speed mutation point set comprises speed sudden-rise points and speed sudden-fall points which appear in a cross manner; then, determining a target historical time batch corresponding to the target real-time batch, similar to the above, wherein the correspondence not only refers to the correspondence of time but also includes the correspondence of characteristic days, for example, if the target real-time batch is a time batch in which the target real-time batch is located at 10 am 01 minutes to 10 am of the first monday of the month, the target historical time batch corresponding to the target real-time batch is a time batch in which the target real-time batch is located at 10 pm 00 minutes to 10 am of the first monday of the last month; then, detecting the speed mutation time corresponding to the speed mutation point which is closest to the target historical time batch in the time which is the future relative to the target historical time batch and is on the right side of the target historical time batch on the speed curve; then, an absolute time difference between the speed mutation time and the target historical time batch ending time is determined, and a weight correction coefficient is determined according to the absolute time difference, for example, if the target historical time batch is a time batch in which 10: 00 to 10: 10 of the first monday morning of the last month are located, if the first speed mutation time is detected to be 10: 40 of the first monday morning of the last month after 10: 10 of the first monday morning of the last month, the absolute time difference between the speed mutation time 10: 40 and the target historical time batch ending time 10: 10 is 30 minutes, and the weight correction coefficient may be set to be an absolute time difference/60, that is, 30/60 is 0.5; and finally, multiplying the first initial weight by the weight correction coefficient to realize the correction of the first initial weight.
It should be noted that, after the speed curves of different historical time batches of the target road segment are obtained initially, the speed sudden-rise point and the speed sudden-fall point on the speed curve may not appear in a cross manner, but two or more speed sudden-rise points are adjacent, or two or more speed sudden-fall points are adjacent, and considering that an inflection point of the speed curve is more meaningful for correcting the weight, the speed sudden-rise point and the speed sudden-fall point of the speed curve may be processed using a local extremum method, so that the speed sudden-rise point and the speed sudden-fall point are finally in a cross manner.
In an embodiment of the present disclosure, the step of determining the speed curves of the target road segment in different historical time batches may include the following steps:
determining historical passing speeds of different historical time batches on the target road section based on the length of the target road section and the historical passing times of different historical time batches on the target road section;
generating speed curves of the target road section in different historical time batches based on the historical passing speed;
and smoothing the speed curve.
In the above, the historical transit times of different historical time batches on the target road segment are obtained, and in this embodiment, based on the length of the target road segment and the historical transit times of different historical time batches on the target road segment, the historical transit speeds corresponding to different historical time batches on the target road segment can be determined; taking the historical time batch or the end time of the historical time batch as a horizontal axis, and taking the historical passing speed corresponding to the historical time batch as a vertical axis, so as to obtain speed curves of the target road section in different historical time batches; in order to avoid the influence of the abnormal speed point, the speed curve can be smoothed by a smoothing method such as C-time Gaussian smoothing and the like.
The following are embodiments of the disclosed apparatus that may be used to perform embodiments of the disclosed methods.
Fig. 2 shows a block diagram of an arrival time estimation apparatus according to an embodiment of the present disclosure, which may be implemented as part or all of an electronic device by software, hardware, or a combination of the two. As shown in fig. 2, the arrival time estimation apparatus includes:
a determination module 201 configured to determine a target route, wherein the target route contains one or more target road segments;
the estimation module 202 is configured to estimate a predicted passing time of the target road section based on the real-time passing time and the historical passing time corresponding to the target road section;
the adding module 203 is configured to add the departure time of the target route and the expected passing time of the target road segment included in the target route to obtain the estimated arrival time of the target route.
As mentioned above, as society develops and progresses, vehicles on roads are increasing, and many users view a navigation route and time required for reaching a destination through application software having a map navigation function before traveling. Due to the fact that the traffic conditions of the road are suddenly changed compared with the daily traffic conditions of the road due to the conditions of the peak at morning and evening, holidays, traffic accidents and the like, the sudden change of the traffic conditions can affect the accuracy of the estimation of the time needed for reaching the destination. In turn, the accuracy of the time required to reach the destination can affect the user's decision to go out, and thus affect the traffic conditions. Therefore, it is an important subject to improve the accuracy of the estimation of the time required to reach the destination.
In view of the above problem, in this embodiment, an arrival time estimation device is proposed, which determines an estimated time of passage of a target link based on a real-time of passage and a historical time of passage corresponding to the target link, and further obtains an estimated value of arrival time of a target route. According to the technical scheme, the estimation accuracy of the time required for reaching the destination can be effectively improved, the influence of low estimation accuracy of the time of reaching on traffic road conditions is avoided, meanwhile, the service quality of a traffic navigation service platform can be improved, and the use experience of a user is improved.
In an embodiment of the present disclosure, the arrival time estimation apparatus may be implemented as a computer, a computing device, an electronic device, a server, a service cluster, and the like, which can perform arrival time estimation.
Technical terms and technical features related to the above-described apparatus-related embodiments are the same as or similar to those mentioned in the above-described method-related embodiments, and for the explanation and description of the technical terms and technical features related to the above-described apparatus-related embodiments, reference may be made to the above-described explanation of the method-related embodiments, and no further description is given here.
The present disclosure also discloses an electronic device, fig. 3 shows a block diagram of an electronic device according to an embodiment of the present disclosure, and as shown in fig. 3, the electronic device 300 includes a memory 301 and a processor 302; wherein, the first and the second end of the pipe are connected with each other,
the memory 301 is used to store one or more computer instructions, which are executed by the processor 302 to implement the above-described method steps.
Fig. 4 is a schematic structural diagram of a computer system suitable for implementing a time-of-arrival estimation method according to an embodiment of the present disclosure.
As shown in fig. 4, the computer system 400 includes a processing unit 401 that can execute various processes in the above-described embodiments according to a program stored in a Read Only Memory (ROM)402 or a program loaded from a storage section 408 into a Random Access Memory (RAM) 403. In the RAM403, various programs and data necessary for the operation of the computer system 400 are also stored. The processing unit 401, the ROM402, and the RAM403 are connected to each other via a bus 404. An input/output (I/O) interface 405 is also connected to bus 404.
The following components are connected to the I/O interface 405: an input section 406 including a keyboard, a mouse, and the like; an output section 407 including a display device such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage section 408 including a hard disk and the like; and a communication section 409 including a network interface card such as a LAN card, a modem, or the like. The communication section 409 performs communication processing via a network such as the internet. A drive 410 is also connected to the I/O interface 405 as needed. A removable medium 411 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 410 as necessary, so that a computer program read out therefrom is mounted into the storage section 408 as necessary. The processing unit 401 may be implemented as a CPU, a GPU, a TPU, an FPGA, an NPU, or other processing units.
In particular, the above described methods may be implemented as computer software programs, according to embodiments of the present disclosure. For example, embodiments of the present disclosure include a computer program product comprising a computer program tangibly embodied on a medium readable thereby, the computer program comprising program code for performing the time of arrival estimation method. In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 409, and/or installed from the removable medium 411.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowcharts or block diagrams may represent a module, a program segment, or a portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units or modules described in the embodiments of the present disclosure may be implemented by software or hardware. The units or modules described may also be provided in a processor, and the names of the units or modules do not in some cases constitute a limitation of the units or modules themselves.
As another aspect, the disclosed embodiment also provides a computer-readable storage medium, which may be the computer-readable storage medium included in the apparatus in the foregoing embodiment; or it may be a separate computer readable storage medium not incorporated into the device. The computer readable storage medium stores one or more programs for use by one or more processors in performing the methods described in the embodiments of the present disclosure.
The foregoing description is only exemplary of the preferred embodiments of the disclosure and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the invention in the embodiments of the present disclosure is not limited to the specific combination of the above-mentioned features, but also encompasses other embodiments in which any combination of the above-mentioned features or their equivalents is made without departing from the inventive concept. For example, the above features and (but not limited to) the features with similar functions disclosed in the embodiments of the present disclosure are mutually replaced to form the technical solution.
Claims (13)
1. A method of time of arrival estimation, comprising:
determining a target route, wherein the target route contains one or more target road segments;
estimating and obtaining the predicted passing time of the target road section based on the real-time passing time and the historical passing time corresponding to the target road section;
and adding the departure time of the target route and the expected passing time of the target road section contained in the target route to obtain the estimated arrival time of the target route.
2. The method of claim 1, wherein estimating the predicted transit time for the target road segment based on the real-time transit time and historical transit time for the target road segment comprises:
determining an expected time of entry for the target road segment;
determining real-time passing time of a target real-time batch of the target road section to which the predicted entry time belongs;
acquiring historical transit time of the target road section in a historical time batch corresponding to the estimated entry time;
and performing weighted calculation on the real-time passing time and the historical passing time to obtain the predicted passing time of the target road section.
3. The method of claim 2, the determining a real-time transit time for a target real-time batch of the target road segment to which the projected time of entry belongs, comprising:
acquiring position data of a traveling object traveling on the target road section in a target real-time batch to which the estimated entry time belongs;
determining real-time passing time for the traveling object to pass through the target road section according to the position data of the traveling object;
and determining the average value of the real-time passing time of the traveling object, and taking the average value as the real-time passing time of the target real-time batch of the target road section to which the predicted entering time belongs.
4. The method of claim 3, the determining an average of real-time transit times of the traveling object, comprising:
removing a deviation value in a real-time transit time of the traveling object;
an average of the remaining real-time transit times is determined.
5. The method of claim 2, wherein obtaining the historical transit time of the historical time batch corresponding to the estimated time of entry for the target road segment comprises:
acquiring position data of the traveling object traveling on the target road section in different historical time batches corresponding to the estimated entry time;
according to the position data of the travelling object, determining the historical passing time of the travelling object corresponding to the historical time batch for passing through the target road section;
and determining the average value of the historical passing time of the travelling object to obtain the historical passing time of different historical time batches on the target road section.
6. The method of claim 5, the determining an average of historical transit times of the traveling object, comprising:
removing a deviation value in the historical transit time of the traveling object;
an average of the remaining historical transit times is determined.
7. The method of claim 5 or 6, wherein the weighting the real-time transit time and the historical transit time to obtain the predicted transit time of the target road segment comprises:
setting a first initial weight of real-time passing time and a second initial weight of historical passing time, wherein the sum of the first initial weight and the second initial weight is 1;
determining a first product of the first initial weight and real-time transit time;
determining a second product of the second initial weight and the historical transit time;
and determining the sum of the first product and the second product to obtain the predicted passing time of the target road section.
8. The method of claim 7, further comprising:
correcting the first initial weight value based on speed curves of the target road section in different historical time batches;
the determining a first product of the first initial weight and the real-time transit time specifically includes:
and determining a first product of the corrected first initial weight and the real-time transit time.
9. The method of claim 8, wherein the modifying the first initial weight based on the speed profile of the target road segment over different historical time batches comprises:
determining speed curves of the target road section in different historical time batches;
detecting to obtain a speed abrupt change point set on the speed curve, wherein the speed abrupt change point set comprises a speed abrupt rising point and a speed abrupt falling point which are crossed;
determining a target historical time batch corresponding to the target real-time batch;
detecting the speed mutation time corresponding to the speed mutation point on the right side of the target historical time batch on the speed curve and closest to the target historical time batch;
determining an absolute time difference between the speed mutation time and the target historical time batch ending time, and determining a weight correction coefficient according to the absolute time difference;
and correcting the first initial weight value into the product of the first initial weight value and the weight value correction coefficient.
10. The method of claim 9, the determining speed profiles over different historical time batches of the target road segment, comprising:
determining historical passing speeds of different historical time batches on the target road section based on the length of the target road section and the historical passing times of different historical time batches on the target road section;
generating speed curves of the target road section in different historical time batches based on the historical passing speed;
and smoothing the speed curve.
11. A time of arrival estimation apparatus, comprising:
a determination module configured to determine a target route, wherein the target route contains one or more target road segments;
the estimation module is configured to estimate to obtain the predicted passing time of the target road section based on the real-time passing time and the historical passing time corresponding to the target road section;
the addition module is configured to add the departure time of the target route and the expected passing time of a target road section contained in the target route to obtain the estimated arrival time of the target route.
12. An electronic device comprising a memory and at least one processor; wherein the memory is to store one or more computer instructions, wherein the one or more computer instructions are to be executed by the at least one processor to implement the method steps of any one of claims 1-10.
13. A computer program product comprising computer programs/instructions, wherein the computer programs/instructions, when executed by a processor, implement the method steps of any of claims 1-10.
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