Method, device, equipment, medium and product for determining vehicle driving route

Abstract

The present disclosure provides a method, device, equipment, medium and product for determining a vehicle's driving route, and relates to the field of computer technology, in particular to the field of intelligent transportation and big data. The specific implementation scheme is: a method for determining a vehicle's driving route, including: determining a preset route for the vehicle to travel, and a site set consisting of all sites on the preset route; monitoring the actual driving trajectory of the vehicle on the preset route, and determining the number of times the vehicle traveling according to the actual driving trajectory passes through each site in the site set; if it is determined based on the number of times that there are abnormal sites in the site set, then the sites of the preset route are updated, and the abnormal sites are sites where the difference between the number of times passed and the standard number of times exceeds the difference threshold, and the standard number of times is a reference value determined based on the number of times each site on the preset route is passed. The present disclosure can find abnormal sites in the vehicle's driving route by comparing the actual trajectory of the vehicle with the preset route of the vehicle, thereby updating the preset route of the vehicle.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technology, and in particular to the fields of intelligent transportation and big data. Background Art

[0002] Smart public transportation is an important direction for the development of urban transportation informatization. Through the construction of public transportation informatization, people's public transportation travel can be effectively guided.

[0003] As an important navigation part of public transportation, bus navigation relies on the operation time and route of bus routes in the map data to plan travel routes for pedestrians. The actual bus routes may be adjusted for various reasons, such as changes in stop sites, line suspension, etc. In order to provide effective guidance for pedestrians, the bus route information recorded in the map data should be consistent with the actual bus routes. Summary of the invention

[0004] The present disclosure provides a method, apparatus, device, medium and product for determining a vehicle driving route.

[0005] According to one aspect of the present disclosure, a method for determining a vehicle driving route is provided, comprising: determining a preset route for vehicle driving, and a site set consisting of all sites on the preset route; monitoring the actual driving trajectory of the vehicle on the preset route, and determining the number of times the vehicle traveling according to the actual driving trajectory passes through each site in the site set; if it is determined based on the number of times that an abnormal site exists in the site set, updating the sites of the preset route, the abnormal site being a site for which the difference between the number of times the site is passed and the standard number exceeds a difference threshold, and the standard number is a reference value determined based on the number of times each site on the preset route is passed.

[0006] According to another aspect of the present disclosure, a device for determining a vehicle driving route is provided, comprising: a determination module, for determining a preset route for vehicle driving, and a site set consisting of all sites on the preset route, and monitoring the actual driving trajectory of the vehicle on the preset route, and determining the number of times the vehicle traveling according to the actual driving trajectory passes through each site in the site set; an update module, for updating the sites of the preset route when it is determined based on the number that there are abnormal sites among the sites, the abnormal site being a site for which the difference between the number of times the site is passed and the standard number exceeds a difference threshold, and the standard number is a reference value determined based on the number of times each site on the preset route is passed.

[0007] According to another aspect of the present disclosure, an electronic device is provided, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute any one of the methods for determining a vehicle's driving route described in the present disclosure.

[0008] According to another aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to enable the computer to execute any one of the methods for determining a vehicle driving route described in the present disclosure.

[0009] According to another aspect of the present disclosure, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the computer program implements any one of the methods for determining a vehicle driving route described in the present disclosure.

[0010] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present disclosure, nor is it intended to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The accompanying drawings are used to better understand the present solution and do not constitute a limitation of the present disclosure.

[0012] Figure 1a and Figure 1b A schematic diagram showing changes in bus routes is shown;

[0013] Figure 2 is a flow chart of a method for determining a vehicle driving route according to the present disclosure;

[0014] Figure 3 is a flow chart of a method for determining the number of times a vehicle passes through each station in a station set in the form of an actual driving trajectory according to the present disclosure;

[0015] Figure 4 is a flow chart of a method for determining an actual driving trajectory intersecting with a first area based on a first area and a second area according to the present disclosure;

[0016] Figure 5 is a schematic diagram of determining a first area and a second area according to the method disclosed herein;

[0017] Figure 6 is a schematic diagram of determining an actual driving trajectory intersecting with a first area according to the method of the present disclosure;

[0018] Figure 7is a flow chart of a method for determining the presence of an abnormal site in a site based on the number of times according to the present disclosure;

[0019] Figure 8 It is a flow chart of a method for determining the probability that a site corresponding to the number of abnormalities is an abnormal site based on the number of abnormalities and the average number of times according to the present disclosure;

[0020] Fig. 9 is a quantile statistical distribution diagram of the number of times each station is passed on a preset route according to the present disclosure;

[0021] Fig.10 is a statistical schematic diagram of the number of times a vehicle traveling according to an actual driving trajectory of the vehicle passes through each station according to the present disclosure;

[0022] Fig.11 is a flow chart of a method for determining a vehicle driving route according to the present disclosure;

[0023] Fig.12 is a schematic diagram of abnormal sites obtained according to the method for determining a vehicle travel route disclosed in the present invention;

[0024] Fig.13 is a block diagram of an apparatus for determining a vehicle driving route according to the present disclosure;

[0025] Fig.14 The present invention is a block diagram of an electronic device for implementing the method for determining a vehicle driving route according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0026] The following is a description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0027] Public transportation navigation is closely related to the accuracy of the data of the bus routes in the map data it uses. When users use the public transportation navigation function, they plan their routes based on the operating time and routes of each bus route in the map data, and recommend reasonable travel routes for users. Errors in the route information of the bus routes recorded in the map data will directly lead to the generation of unreasonable navigation routes, seriously affecting the user experience.

[0028] The actual bus routes may be changed due to various reasons. Figure 1a and Figure 1b A schematic diagram showing changes to bus routes.

[0029] Figure 1a It shows the situation where the bus route has detoured, that is, the actual driving trajectory of the vehicle bypasses the preset route of the vehicle, that is, it does not pass through a certain section of the preset route. The hexagons represent the stations on the preset route, the lines connecting the hexagons are the preset routes of the buses on this route, and the circles represent the track points on the actual driving trajectory of the vehicle. It can be seen that in the actual driving of the vehicle, after passing "Site 3", it did not continue to move forward, but detoured and passed "Site 6" after the detour. "Site 4" and "Site 5" in the original route were not passed, that is, "Site 4" and "Site 5" in the preset route may be abnormal.

[0030] Figure 1b It shows the situation where the bus line stops prematurely, that is, the vehicle stops prematurely before reaching the terminal station of the preset line, and the actual driving trajectory of the vehicle ends prematurely at the position of "Stop 15". The stations "Stop 16", "Stop 17" and "Stop 18" on the preset line are not actually passed by the vehicle.

[0031] In the case of a bus route change, the current technology updates the actual route based on user feedback. That is, when using the bus navigation application, the user finds that the bus route stored in the map is inconsistent with the actual route, and feeds back the inconsistent information to the application backend. Specialized personnel organize and classify this part of user feedback, and after further verification, confirm the correctness of the feedback information and update the route information.

[0032] It is also possible to update routes by obtaining route change information publicly available on the Internet, but route change information is not released in a timely manner and cannot fully cover changes in bus routes.

[0033] In view of this, an embodiment of the present disclosure provides a method for determining a vehicle driving route, which can accurately and timely update a preset vehicle driving route according to the actual trajectory of the vehicle.

[0034] Figure 2 FIG. 1 is a flow chart of a method for determining a vehicle driving route according to the present disclosure. Figure 3 As shown, the method of the present disclosure includes the following steps.

[0035] In step S101, a preset route for the vehicle to travel and a site set consisting of all sites on the preset route are determined.

[0036] In the disclosed embodiment, the preset route of the vehicle and the stations on the preset route can be determined based on the vehicle route information stored in the map data, and all the stations on the preset route constitute a station set. For example, the starting and ending stations of a bus route, the stations along the way, and other information can be determined through the map data used for navigation.

[0037] In step S102, the actual driving trajectory of the vehicle on the preset route is monitored, and the number of times the vehicle traveling according to the actual driving trajectory passes through each station in the station set is determined.

[0038] In the disclosed embodiment, the actual driving trajectory of the vehicle on the preset route can be determined by obtaining the real-time bus trajectory. The real-time bus trajectory refers to a series of data with coordinates, timestamps, speed and other information generated by a real-time bus equipped with a GPS locator, which can reflect the running trajectory of a certain bus route. The number of times the vehicle passes through each station along the route during actual driving is determined by the actual driving trajectory of the vehicle. It can be understood that the number of times the vehicle passing through each station in the station set on the preset route according to the actual driving trajectory during the preset time period can be monitored. For example, within three days, the number of times the vehicle traveling on the route passes through each station such as the starting station, the second station, ... the terminal station. It can be understood that due to problems such as GPS signal stability and real-time bus trajectory errors, the number of times the vehicle passing through each station according to the actual driving trajectory can be different.

[0039] In step S103, if it is determined based on the number of times that there are abnormal sites in the site concentration, the sites of the preset route are updated.

[0040] If the vehicle runs normally along the preset route, the number of times the vehicle visits all the stations on the route should be in a distribution with little difference. If the number of visits to a certain station decreases sharply, the probability of these stations being changed increases. In the embodiment of the present disclosure, an abnormal station is a station on the preset route on which the vehicle travels, and the number of times the vehicle actually passes by the station differs greatly from the number of times other stations are passed by the station, that is, the number of times the station is actually passed by the vehicle, and the difference between the standard number of times exceeds the difference threshold. Among them, the standard number is determined by the actual number of times the vehicle passes by each station on the preset route according to the actual driving trajectory. If the station is determined to be an abnormal station based on the number of times the vehicle actually passes by the station, that is, the station where the location of the station has changed, the corresponding position of the station on the preset route is updated to determine the correct driving route of the bus vehicle after the station has changed.

[0041] In summary, according to the method for determining the vehicle driving route disclosed in the present invention, the actual driving trajectory of the vehicle on the preset route is monitored, and the trajectory can truly and accurately reflect the actual operation of the vehicle, and determine the number of times the vehicle traveling according to the actual driving trajectory passes through each station in the route, and then determine the stations with abnormal distribution of the number of passes, and promptly discover the changed stations in the route, and update the information of the changed stations on the route to obtain accurate route information, and promptly grasp the changes in the vehicle's driving route, so as to effectively provide route guidance services through accurate route station information.

[0042] Figure 3 is a flow chart of a method for determining the number of times a vehicle traveling along an actual driving trajectory passes through each station in a station set according to the present disclosure. Figure 3 As shown, the method of the present disclosure includes the following steps.

[0043] In step S201 , the longitude and latitude positions of the track points included in the actual driving track are determined, and the longitude and latitude positions of the station are determined.

[0044] In the disclosed embodiment, a route matching step may also be included. For example, the trajectory point sequences of all bus routes in a city may be obtained, and each trajectory sequence may be matched with its corresponding bus route, thereby obtaining multiple actual driving trajectories corresponding to the same bus route.

[0045] In the disclosed embodiments, the actual driving trajectory of the vehicle may also include pre-processing steps such as trajectory slicing and trajectory denoising. For example, when a trajectory interruption phenomenon occurs in the acquired actual driving trajectory, that is, the time interval corresponding to the trajectory point in the actual driving trajectory is too long, and no new trajectory point appears within the preset time, the actual driving trajectory is sliced. Alternatively, when the trajectory turning angle in the acquired actual driving trajectory is too large and exceeds the preset angle threshold, the actual driving trajectory is sliced. The actual driving trajectory includes multiple trajectory points, and the longitude and latitude positions of the trajectory points are determined, and the longitude and latitude positions of the stations are determined. The actual driving trajectory and the station positions on the preset route of the vehicle can be represented by their longitude and latitude positions.

[0046] In step S202, a first area including the site is determined based on the latitude and longitude positions of the site, where the first area is a rectangular area with the site as the center and a side length of a preset value.

[0047] In step S203, based on the longitude and latitude positions of the track points, a second area including the actual driving track is determined, where the second area is a minimum rectangular area circumscribed with the actual driving track.

[0048] In step S204, based on the first area and the second area, an actual driving trajectory intersecting the first area is determined.

[0049] In step S205, the number of actual driving trajectories intersecting the first area is counted, and the number is determined as the number of times the vehicle traveling according to the actual driving trajectory passes through each station in the station set.

[0050] In the embodiment of the present disclosure, the first area is a rectangular area centered on the site, and the preset value is the side length. The first area including the site is determined based on the longitude and latitude position of the site, and the preset value can be determined according to actual use requirements. And based on the longitude and latitude position of the track point on the actual driving trajectory, the minimum rectangular area circumscribed with the actual driving trajectory, that is, the second area, is determined. It can be understood that the number of actual driving trajectories of the vehicle obtained is large, and the number of times the vehicle actually drives through each site is determined by the distance between the track point and the site, which requires a large amount of calculation and the process is cumbersome. It can be a first area determined based on the longitude and latitude position of the site, and a second area determined based on the longitude and latitude position of the track point. By judging the positional relationship between the first area and the second area, the number of times the vehicle actually drives through each site is determined, thereby speeding up the processing speed.

[0051] In an embodiment of the present disclosure, actual driving trajectories intersecting the first area are determined based on the first area and the second area, and the number of actual driving trajectories intersecting the first area is counted, and the number is determined as the number of times a vehicle traveling along the actual driving trajectory passes through each station in the station set.

[0052] In summary, according to the method for determining the vehicle's driving route disclosed in the present invention, the first area is determined based on the latitude and longitude positions of the station, and the second area is determined based on the latitude and longitude positions of the trajectory points. By judging the positional relationship between the first area and the second area, the speed of determining the number of times a vehicle traveling along the actual driving trajectory passes through each station can be improved.

[0053] Figure 4 FIG. 1 is a flow chart of a method for determining an actual driving trajectory intersecting with a first area based on a first area and a second area according to the present disclosure. Figure 4 As shown, the method of the present disclosure includes the following steps.

[0054] In step S301 , a second area that overlaps with the first area is determined.

[0055] In step S302 , among actual driving trajectories included in a second area having an overlapping area with the first area, an actual driving trajectory intersecting with the first area is determined.

[0056] In the embodiment of the present disclosure, the first area is determined based on the longitude and latitude position of the site, and the second area is determined based on the longitude and latitude position of the trajectory point, and the second area having an overlapping area with the first area is determined. It can be understood that the determination that the first area and the second area have an overlapping relationship can be achieved by any method that can determine the positional relationship between the areas, and the second area and the first area can be overlapping or partially overlapping. It can also be understood that when the actual driving trajectory of the vehicle intersects with the first area, the corresponding second area must have an overlapping area with the first area, but the actual driving trajectory corresponding to the second area having an overlapping area with the first area does not necessarily intersect with the first area. In the actual driving trajectory included in the second area having an overlapping area with the first area, when determining the actual driving trajectory that intersects with the first area, it can be determined whether the actual driving trajectory intersects with the first area through the positional relationship between the actual driving trajectory and the rectangular area.

[0057] In summary, according to the method for determining a vehicle driving route disclosed in the present invention, in the second area corresponding to all actual driving trajectories of the vehicle, the second area having an overlapping area with the first area is determined, and the actual driving trajectory intersecting with the first area is determined only among the actual driving trajectories included in the second area having an overlapping area with the first area. This can reduce the number of times the corresponding actual driving trajectory is judged to intersect with the first area, thereby improving the processing speed.

[0058] In the disclosed embodiment, an R-tree index relationship may be established through the longitude and latitude of the track point in the actual driving track and the longitude and latitude of the station. The R-tree is a widely used spatial index structure, a highly balanced tree, and a natural extension of the B-tree in k-dimension. The minimum bounding rectangle (MBR) of the spatial object is used to approximate the spatial object. By establishing the R-tree based on the MBR, the spatial objects occupying a certain range in the space can be directly indexed. When searching through the R-tree, the input may be a rectangle, called the search rectangle. Starting from the root node of the R-tree, the matrix that overlaps with the search rectangle is searched until a leaf node is found and the corresponding record is returned.

[0059] Based on the latitude and longitude positions of the stations on the preset route of the vehicle, the first area including the stations is determined, and the second area is established according to the actual driving trajectory of the vehicle on the preset route. That is, the first area is used as a search rectangle, and the second area intersecting with the first area is searched from the top to the bottom of the R tree.

[0060] In summary, according to the method for determining the vehicle driving route disclosed in the present invention, all second areas overlapping with the first area including the station can be quickly searched through the R-tree, thereby determining the number of times the vehicle traveling according to the actual driving trajectory passes through each station, reducing the time consumed in calculation and improving calculation efficiency.

[0061] Figure 5 is a schematic diagram of determining the first area and the second area according to the method disclosed in the present invention. Figure 5 , based on the longitude and latitude of the site, the first area is determined, and the first area is a rectangular area with the site as the center and the preset value as the side length. Based on the longitude and latitude of the trajectory point, the minimum rectangular area circumscribed with the actual driving trajectory is determined. The positional relationship between the first area and the second area can be determined, that is, whether there is an overlapping area between the first area and the second area.

[0062] Figure 6 is a schematic diagram of determining an actual driving trajectory intersecting with the first area according to the method disclosed in the present invention. Figure 6 As shown, there are three second areas that overlap with the first area, and the three second areas include actual vehicle driving trajectories, and the actual vehicle driving trajectories included in two of the second areas intersect with the first area. That is, the number of times the vehicle actually drives through the station in the figure is 2.

[0063] Figure 7 FIG. 1 is a flow chart of a method for determining the presence of abnormal sites in a site based on the number of times according to the present disclosure. Figure 7 As shown, the method of the present disclosure includes the following steps.

[0064] In step S401, quantile statistics are performed on the number of times each station on the preset line is passed, and the number of times exceeding the maximum and minimum values ​​of the quantile statistics is determined, and the number is taken as the abnormal number.

[0065] In the disclosed embodiment, the number of times a vehicle traveling along the actual driving trajectory passes through each station is determined, and based on the number of times passing through each station, the abnormal stations existing in the station are determined, and the abnormal stations largely correspond to stations that have changed during actual driving. There is a problem of calculation accuracy when judging a station where the number of times the vehicle actually passes through the station is 0. In order to increase the robustness of the method for determining abnormal stations, quantile statistics can be performed on the number of times each station on the preset route is passed. That is, the vehicle driving route is operating normally, and the number of times the vehicle traveling along the actual driving trajectory passes through each station in the station set should be in a distribution that is not much different. If the number of times a station is passed by is sharply reduced, the probability of these stations being changed becomes greater.

[0066] The quartile statistics of the number of times each station on the preset route is passed can be performed, that is, the number of times each station on the preset route is passed is sorted according to the number of times passed, and the median, upper quartile and lower quartile of the number of times each station is passed are calculated. Among them, the median is the number of times passed in the middle position after the number of times passed is sorted, the upper quartile is the number of times passed in the fourth position after the number of times passed is sorted, and the lower quartile is the number of times passed in the third position after the number of times passed is sorted. The number of times exceeding the maximum and minimum values ​​of the quantile statistics is regarded as the abnormal number.

[0067] In step S402, the average number of times each station on the preset route is passed is determined.

[0068] In the embodiment of the present disclosure, the average number of times each station on the preset route is passed may be a median value determined from quartile statistics of the number of times each station on the preset route is passed.

[0069] In step S403, based on the number of abnormal times and the average number of times, the probability that the site corresponding to the number of abnormal times is an abnormal site is determined.

[0070] In step S404, the sites corresponding to the abnormal times with probabilities greater than the probability threshold are determined as abnormal sites.

[0071] In the embodiment of the present disclosure, when it is determined that there is an abnormal station based on the number of times the vehicle traveling along the actual driving trajectory passes through each station, the probability that the station corresponding to the abnormal number of times is an abnormal station is further determined based on the abnormal number of times and the average number of times. When the probability of the abnormal station is greater than the probability threshold, the station corresponding to the abnormal number of times is determined as an abnormal station.

[0072] According to the method for determining a vehicle driving route disclosed in the present invention, the actual driving trajectory of the vehicle on the preset route is monitored, and the number of times the vehicle actually drives through each station is determined, and then the quantile statistics of the number of times each station on the preset route is passed is determined, and the abnormal number of times is determined, that is, the number of times the number of times the station is passed is very small compared with other stations on the route, and the probability that the station corresponding to the abnormal number of times is an abnormal station is determined, and the station corresponding to the abnormal number of times with a probability greater than a probability threshold is determined as an abnormal station, and the abnormal station on the preset route is accurately determined, so as to obtain accurate route information of the vehicle driving.

[0073] Figure 8 FIG. 1 is a flow chart of a method for determining the probability that a site corresponding to the number of abnormalities is an abnormal site based on the number of abnormalities and the average number of times according to the present disclosure. Figure 8 As shown, the method of the present disclosure includes the following steps.

[0074] In step S501, the difference between the average number of times value and the abnormal number of times value is determined.

[0075] In step S502, the ratio between the difference value and the average number of times is determined as the probability that the station corresponding to the abnormal number of times is an abnormal station.

[0076] Fig. 9 is a quantile statistical distribution diagram of the number of times each station is passed on the preset route according to the present disclosure, Fig. 9 It can be seen that on October 21, 2021, there are two stations that are passed by 2 and 3 times, on October 22, 2021, there is a station that is passed by 1 time, and on October 23, 2021, there are two stations that are passed by 2 and 3 times. For example, on October 21, 2021, there are two stations that are passed by 2 and 3 times.

[0077] Fig.10 is a statistical diagram of the number of times a vehicle traveling along an actual driving trajectory passes through each station according to the present disclosure, Fig.10 The figure shows the number of times vehicles actually passed through each station on a certain line for three consecutive days. Among stations 1 to 12, the number of times stations 8 and 9 were passed was significantly lower than the number of times other stations were passed, that is, stations 8 and 9 may be abnormal stations.

[0078] Combination Fig. 9 as well as Fig.10 It can be seen that on October 21, 2021, the two sites that were passed 2 and 3 times were Site 8 and Site 9.

[0079] The probability that the site corresponding to the abnormal number is an abnormal site can be determined by the following formula:

[0080]

[0081] Among them, AbnormalProb represents the probability that the station corresponding to the abnormal number of times is an abnormal station, average count is the average number of times each station on the preset line is visited, and visited count is the abnormal number of times. Through the above formula, the probability that the station corresponding to the abnormal number of times is an abnormal station is determined, and the station corresponding to the abnormal number of times with a probability greater than the probability threshold is determined as an abnormal station.

[0082] According to the method for determining a vehicle driving route disclosed in the present invention, the actual driving trajectory of the vehicle on a preset route is monitored, the number of times the vehicle traveling according to the actual driving trajectory passes through each station is determined, and the quantile statistics of the number of times each station on the preset route is passed is determined, the number of abnormal times is determined, and the probability that the station corresponding to the abnormal number of times is an abnormal station is determined, and the station corresponding to the abnormal number of times with a probability greater than a probability threshold is determined as an abnormal station, which can accurately determine the abnormal stations on the preset route, thereby obtaining accurate vehicle driving route information.

[0083] Fig.11 is a flow chart of a method for determining a vehicle driving route according to the present disclosure, referring to Fig.11 , determine the preset route for the bus and the stations on the preset route, and monitor the actual driving trajectory of the vehicle on the preset route. For the acquired trajectory point sequences of all bus routes, match each trajectory sequence with its corresponding bus route, so as to obtain multiple actual driving trajectories corresponding to the same bus route. Perform trajectory slicing, trajectory denoising and other preprocessing on the actual driving trajectory of the vehicle to determine whether the number of actual driving trajectories is too small. It can be understood that when the number of actual driving trajectories is too small, it is impossible to calculate the number of times the vehicle actually passes through each station. By establishing an R-tree index relationship between the longitude and latitude of the trajectory points in the actual driving trajectory and the longitude and latitude of the station, the number of times the vehicle actually passes through each station is determined through the established R-tree index relationship, which can reduce the time consumed in calculation and improve calculation efficiency. Quartile statistics are performed on the number of times each station on the preset route is passed, and the abnormal number of passing times is determined. Based on the abnormal number of times and the average number of times each station on the preset route is passed, the probability that the station corresponding to the abnormal number of times is an abnormal station is determined, and the station corresponding to the abnormal number of times with a probability greater than the probability threshold is determined as an abnormal station. Based on the abnormal stations existing in each station in the station set passed by the vehicle traveling according to the actual driving trajectory, the preset route is updated.

[0084] In summary, according to the method for determining the vehicle driving route disclosed in the present invention, the actual driving trajectory of the bus is monitored, and the trajectory can truly and accurately reflect the actual operation of the bus, and determine the number of times the bus actually passes through each station in the station concentration, and then determine the stations with abnormal distribution of passing times, and promptly discover the changed stations in the route, and update the information of the changed stations on the route, so as to obtain accurate bus route information, timely grasp the route changes of the bus, and effectively provide bus navigation services through accurate bus route station information.

[0085] Fig.12 It is a schematic diagram of abnormal sites obtained according to the method for determining a vehicle travel route disclosed in the present invention. Fig.12 The actual driving trajectory of the vehicle is shown in FIG. 1 , and the abnormal site determined according to the method disclosed in the present invention is represented by a rectangular frame. It can be seen that the actual driving trajectory of the vehicle partially detoured and no longer passed through the abnormal site.

[0086] According to the method for determining the vehicle driving route disclosed in the present invention, it is possible to intuitively see that the actual driving trajectory of the vehicle on the preset route has behaviors such as detouring around stations and stopping early, so as to be sure that the route has changed, and to quickly understand the changes and timely update the preset route information of the vehicle in the map database.

[0087] Based on the same concept, an embodiment of the present disclosure also provides a device for determining a vehicle driving route.

[0088] It is understandable that the device provided by the embodiment of the present disclosure includes hardware structures and / or software modules corresponding to the execution of each function in order to realize the above functions. In combination with the units and algorithm steps of each example disclosed in the embodiment of the present disclosure, the embodiment of the present disclosure can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the technical solution of the embodiment of the present disclosure.

[0089] Fig.13 is a block diagram of an apparatus for determining a vehicle driving route according to the present disclosure.

[0090] like Fig.13 As shown, the device 600 for determining a vehicle driving route according to an embodiment of the present disclosure includes: a determination module 601 and an update module 602 .

[0091] The determination module 601 is used to determine a preset route for the vehicle and a site set consisting of all sites on the preset route, and to monitor the actual driving trajectory of the vehicle on the preset route and determine the number of times the vehicle traveling according to the actual driving trajectory passes through each site in the site set;

[0092] The updating module 602 is used to update the stations of the preset route when it is determined based on the number of times that there are abnormal stations in the station concentration. The abnormal station is a station whose difference between the number of times it has been passed and the standard number of times exceeds the difference threshold. The standard number of times is a benchmark value determined based on the number of times each station on the preset route has been passed.

[0093] In an exemplary embodiment of the present disclosure, the determination module 601 is also used to: determine the latitude and longitude positions of the trajectory points included in the actual driving trajectory and determine the latitude and longitude positions of the site; determine a first area including the site based on the latitude and longitude positions of the site, the first area being a rectangular area centered on the site with a preset value as the side length; determine a second area including the actual driving trajectory based on the latitude and longitude positions of the trajectory points, the second area being the minimum rectangular area circumscribed with the actual driving trajectory; determine the actual driving trajectory intersecting with the first area based on the first area and the second area; count the number of actual driving trajectories intersecting with the first area, and determine the number as the number of times a vehicle traveling along the actual driving trajectory passes through each site in the site set.

[0094] In an exemplary embodiment of the present disclosure, the determination module 601 is also used to: determine a second area that overlaps with the first area; and determine an actual driving trajectory that intersects with the first area among the actual driving trajectories included in the second area that overlaps with the first area.

[0095] In an exemplary embodiment of the present disclosure, the determination module 601 is also used to: perform quantile statistics on the number of times each station on a preset route is passed, determine the number of times that exceed the maximum and minimum values ​​of the quantile statistics, and use the number as the abnormal number; determine the average number of times each station on the preset route is passed; based on the abnormal number of times and the average number of times, determine the probability that the station corresponding to the abnormal number of times is an abnormal station; determine the station corresponding to the abnormal number of times with a probability greater than a probability threshold as an abnormal station.

[0096] In an exemplary embodiment of the present disclosure, the determination module 601 is further used to: determine the difference between the average number of times and the abnormal number of times; and determine the ratio between the difference and the average number of times as the probability that the site corresponding to the abnormal number of times is an abnormal site.

[0097] In the technical solution disclosed herein, the acquisition, storage and application of user personal information involved are in compliance with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0098] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium and a computer program product.

[0099] Fig.14 A schematic block diagram of an example electronic device 700 that can be used to implement an embodiment of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or required herein.

[0100] like Fig.14As shown, the device 700 includes a computing unit 701, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 702 or a computer program loaded from a storage unit 708 into a random access memory (RAM) 703. In the RAM 703, various programs and data required for the operation of the device 700 can also be stored. The computing unit 701, the ROM 702, and the RAM 703 are connected to each other via a bus 704. An input / output (I / O) interface 705 is also connected to the bus 704.

[0101] A number of components in the device 700 are connected to the I / O interface 705, including: an input unit 706, such as a keyboard, a mouse, etc.; an output unit 707, such as various types of displays, speakers, etc.; a storage unit 708, such as a disk, an optical disk, etc.; and a communication unit 709, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 709 allows the device 700 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0102] The computing unit 701 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 701 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 701 performs the various methods and processes described above, such as a method for determining a vehicle driving route. For example, in some embodiments, the method for determining a vehicle driving route may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 708. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 700 via ROM 702 and / or a communication unit 709. When the computer program is loaded into RAM 703 and executed by the computing unit 701, one or more steps of the method for determining a vehicle driving route described above may be performed. Alternatively, in other embodiments, the computing unit 701 may be configured to perform a method for determining a vehicle driving route in any other appropriate manner (e.g., by means of firmware).

[0103] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0104] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0105] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0106] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0107] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communications network). Examples of communications networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0108] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, a server of a distributed system, or a server combined with a blockchain.

[0109] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.

[0110] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A method for determining a vehicle driving route, comprising: Determine a preset route for the vehicle to travel, and a site set consisting of all sites on the preset route; Monitoring the actual driving trajectory of the vehicle on the preset route, and determining the number of times the vehicle traveling along the actual driving trajectory passes through each station in the station set; If it is determined based on the number of times that there is an abnormal site in the site set, then updating the sites of the preset route, wherein the abnormal site is a site whose difference between the number of times it has been passed and the standard number of times exceeds a difference threshold, and the standard number of times is a reference value determined based on the number of times each site on the preset route has been passed; Wherein, determining the number of times the vehicle traveling according to the actual driving trajectory passes through each station in the station set includes: Determining the longitude and latitude positions of the track points included in the actual driving track and determining the longitude and latitude positions of the site; Determine a first area including the site based on the latitude and longitude of the site, where the first area is a rectangular area with the site as the center and a preset value of the side length; Based on the latitude and longitude positions of the track points, determining a second area including the actual driving track, the second area being a minimum rectangular area circumscribed with the actual driving track; Based on the first area and the second area, determining an actual driving trajectory intersecting the first area; The number of actual driving trajectories intersecting the first area is counted, and the number is determined as the number of times the vehicle traveling according to the actual driving trajectory passes through each station in the station set.

2. The method according to claim 1, wherein: The determining, based on the first area and the second area, an actual driving trajectory intersecting the first area includes: Determine a second area that overlaps with the first area; Among the actual driving trajectories included in the second area having an overlapping area with the first area, the actual driving trajectories intersecting the first area are determined.

3. The method according to claim 1, wherein: Determining that there is an abnormal site among the sites based on the number of times includes: Performing quantile statistics on the number of times each station on the preset route is passed, determining the number of times exceeding the maximum and minimum values ​​of the quantile statistics, and taking the number as the abnormal number; Determine the average number of times each station on the preset route is passed; Based on the number of abnormal times and the average number of times, determining the probability that the site corresponding to the number of abnormal times is an abnormal site; The sites corresponding to the number of abnormalities with probabilities greater than the probability threshold are determined as abnormal sites.

4. The method according to claim 3, wherein: Determining, based on the number of abnormal times and the average number of times, a probability that a site corresponding to the number of abnormal times is an abnormal site includes: Determining a difference between the average number of times and the abnormal number of times; The ratio between the difference and the average number of times is determined as the probability that the site corresponding to the abnormal number of times is an abnormal site.

5. A device for determining a vehicle driving route, comprising: A determination module, used to determine a preset route for a vehicle to travel, and a site set consisting of all sites on the preset route, and to monitor an actual travel trajectory of the vehicle on the preset route, and to determine the number of times the vehicle traveling according to the actual travel trajectory passes through each site in the site set; An updating module, configured to update the stations of the preset route when it is determined based on the number that there are abnormal stations in the station set, wherein the abnormal station is a station whose difference between the number of times it has been passed and the standard number of times exceeds a difference threshold, and the standard number of times is a reference value determined based on the number of times each station on the preset route has been passed; The determining module is also used for: Determining the longitude and latitude positions of the track points included in the actual driving track and determining the longitude and latitude positions of the site; Determine a first area including the site based on the latitude and longitude of the site, where the first area is a rectangular area with the site as the center and a preset value of the side length; Based on the latitude and longitude positions of the track points, determining a second area including the actual driving track, the second area being a minimum rectangular area circumscribed with the actual driving track; Based on the first area and the second area, determining an actual driving trajectory intersecting the first area; The number of actual driving trajectories intersecting the first area is counted, and the number is determined as the number of times the vehicle traveling according to the actual driving trajectory passes through each station in the station set.

6. The device according to claim 5, wherein: The determining module is also used for: Determine a second area that overlaps with the first area; Among the actual driving trajectories included in the second area having an overlapping area with the first area, the actual driving trajectories intersecting the first area are determined.

7. The device according to claim 5, wherein: The determining module is also used for: Performing quantile statistics on the number of times each station on the preset route is passed, determining the number of times exceeding the maximum and minimum values ​​of the quantile statistics, and taking the number as the abnormal number; Determine the average number of times each station on the preset route is passed; Based on the number of abnormal times and the average number of times, determining the probability that the site corresponding to the number of abnormal times is an abnormal site; The sites corresponding to the number of abnormalities with probabilities greater than the probability threshold are determined as abnormal sites.

8. The device according to claim 7, wherein: The determining module is also used for: Determining a difference between the average number of times and the abnormal number of times; The ratio between the difference and the average number of times is determined as the probability that the site corresponding to the abnormal number of times is an abnormal site.

9. An electronic device, comprising: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the method for determining a vehicle driving route according to any one of claims 1 to 4.

10. A non-transitory computer-readable storage medium storing computer instructions, wherein: The computer instructions are used to enable the computer to execute the method for determining a vehicle driving route according to any one of claims 1-4.

11. A computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the method for determining a vehicle driving route according to any one of claims 1 to 4 is implemented.

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