Method for estimating a travel route

Abstract

The invention relates to a method for estimating a travel route. The present disclosure is directed to a method for estimating a route of an object. The method includes determining a first position of the object at a first time, determining a second position of the object at a second time after the first time, automatically simulating a plurality of possible routes between the first position and the second position, ranking the plurality of possible routes between the first position and the second position, and displaying the ranked routes. And estimating a most probable route from among the plurality of probable routes between the first position and the second position.

Description

Technical Field

[0001] The present disclosure relates to a method for estimating a driving route. Background Art

[0002] The location data may be used to track travel routes in order to create a record of where an object has traveled and / or to track where an object is currently traveling. The travel record or current travel path may be plotted, such as on a pre-made road map. Positioning methods, such as global positioning systems (GPS), may sometimes be erroneous, lack precision, and / or have lost or distorted signals, such as when an object is in a busy area, so travel routes must be estimated when detected positions are lost or incorrect. Conventional route estimation methods may involve quickly estimating a route that an object is following or may have taken, even if that route is not necessarily based on object data or enhanced route simulation. Summary of the invention

[0003] Object position detection systems can have errors or can be interfered with, for example, by tall buildings in urban environments. Object position detection systems can be used to determine the route that an object has traveled and / or to determine the current route that an object is traveling. Therefore, when the position data is temporarily unknown or distorted, methods must be used to estimate the object route. The object route can be estimated by comparing the object's last known position to the nearest possible route. This ignores the object's movement characteristics, such as the object's speed, acceleration, and / or travel history. In addition, this can determine the object route too quickly before the object route can be more accurately estimated. Therefore, a travel route estimation method is needed that can utilize more object data and more accurately estimate the travel route.

[0004] Compared with conventional driving route estimation methods, the present method can estimate a driving route more accurately than conventional driving route estimation methods by utilizing object dynamic data and enhanced route simulation.

[0005] The system generally includes a position determining device, a processor, and a map of an area and / or road network. The position determining device, the processor, and the map may be connected to each other, such as via a wired connection or a wireless network. The position determining device may be associated with an object. In some embodiments, the position determining device may be associated with a vehicle. The processor may compare data generated from the position determining device with the map. When an error is detected between the generated data and the map, or when the data is distorted, incomplete, or missing, the processor may estimate the actual current location of the object or the route taken.

[0006] According to one embodiment, a method includes: determining a first position of an object at a first time; determining a second position of the object at a second time after the first time; automatically simulating multiple possible routes between the first position and the second position; ranking the multiple possible routes between the first position and the second position; and estimating the most likely route from among the multiple possible routes between the first position and the second position.

[0007] According to another embodiment, a method includes: tracking the route of an object along a drawn path to determine the tracked route of the object; determining the difference between the drawn path and the tracked route of the object; simulating multiple possible corrected routes from the tracked route to the drawn path; ranking the multiple possible corrected routes between the tracked route and the drawn path; and estimating the most likely corrected route from the multiple possible corrected routes between the tracked route and the drawn path.

[0008] Additional features and advantages of the techniques described in the present disclosure will be set forth in the detailed description which follows, and in part will become apparent to those skilled in the art from the description or by practice of the techniques described in the present disclosure, including the detailed description which follows, the claims, and the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] The following detailed description of the present disclosure may be better understood when read in conjunction with the following drawings, in which: Figure 1 schematically depicts a diagram of a network of devices for performing a method according to one or more embodiments shown and described herein; Figure 2 schematically depicts a diagram of a plurality of possible estimated routes between a first location and a second location according to one or more embodiments shown and described herein; Figure 3 schematically depicts a diagram of a plurality of possible estimated routes between a first location and a second location along a mapped path according to one or more embodiments shown and described herein; Figure 4 schematically depicts a view of a plurality of possible estimated routes along a mapped path according to one or more embodiments shown and described herein; Figure 5 schematically depicts a flow chart of a method according to one or more embodiments shown and described herein; and Figure 6 A flow chart of a method according to one or more embodiments shown and described herein is schematically depicted.

[0010] Reference will now be made in more detail to various embodiments of the present disclosure, some of which are illustrated in the accompanying drawings. Whenever possible, the same reference numerals will be used throughout the drawings to refer to the same or like parts. DETAILED DESCRIPTION

[0011] Embodiments of the present disclosure are directed to methods for estimating the route of an object. The method may include determining at least one position of the object, such as using a position determination device. The at least one determined position of the object may be compared by a processor to a map of the area. When the position data is missing or the position data is in error, the processor may estimate the possible route or position of the object. In embodiments, the method may include simulating possible routes between determined positions, ranking possible routes, and estimating which route is the most likely route to be taken. In other embodiments, the method may include determining the route taken by the object, determining the difference between the determined route and the map, and estimating the most likely actual route taken by the object.

[0012] Conventional route estimation methods may estimate routes that are not feasible. For example, conventional systems may estimate routes that are not on a path or road, or involve unlikely or impossible maneuvers of an object, such as estimating a route with sharp turns when the object is traveling at a high rate of speed. In addition, conventional route estimation methods may not simulate a route long enough, and may estimate too quickly that a route has been taken. An embodiment may improve route estimation by using vehicle data (such as driving history and dynamic data) and enhanced route simulation. The present system may produce more accurate and realistic route estimates in real time and after the journey is over.

[0013] Reference now Figure 1 , shows an example of a system 100 for estimating a route consistent with the disclosed embodiments. Figure 1 As shown in FIG. 1 , processor 110, location determining device 120, dynamic sensor 130, mapping device 140, and display 114 are communicatively coupled to one another via network 150. Figure 1 A specific number of processors, location determination devices, dynamic sensors, displays, and mapping devices are depicted in the system 100, but any number of these devices may be provided. In addition, the functionality provided by one or more devices of the system 100 may be combined, and the functionality of any one or more components of the system 100 may be implemented by any suitable computing environment.

[0014] The network 150 facilitates communication between various devices in the system 100, such as the processor 110, the location determination device 120, the dynamic sensor 130, the mapping device 140, and the display 114. The network 150 may be a shared, public, or private network, may cover a wide area or a local area, and may be implemented by any suitable combination of wired and / or wireless communication networks. In addition, the network 150 may include a local area network (LAN), a wide area network (WAN), an intranet, or the Internet. The network 150 may allow near real-time communication between devices connected via the network.

[0015] The processor 110 may include a non-transitory, processor-readable storage medium 112 for storing program modules that, when executed by the processor 110, perform one or more of the processes described herein. The non-transitory, processor-readable storage medium 112 may store data from other devices, such as the position-determining device 120 and the dynamic sensor 130. The non-transitory, processor-readable storage medium 112 may be one or more memory devices that store data as well as software, and may also include, for example, one or more of RAM, ROM, magnetic storage, or optical storage. Because the disclosed embodiments may be implemented using an HTTPS (secure hypertext transfer protocol) environment, data transmission may be performed over a network, such as the Internet, in a secure manner.

[0016] The position determination device 120 may be a device associated with the object 102 (described and illustrated herein) for determining the position of the object 102. The position determination device 120 may be a global positioning system (GPS) sensor, a global navigation satellite system (GNSS), or any other suitable device for determining the position of an object. The position determination device 120 may determine the position of the object 102 at a single point, multiple points, in order to determine the route taken by the object 102, or any other position of the object 102.

[0017] The dynamic sensor 130 may be a device associated with the object 102 for determining a dynamic characteristic of the object 102. The dynamic characteristic may be, for example, the direction of travel of the object 102, the speed of the object 102, the acceleration of the object 102, the yaw of the object 102, or other dynamic characteristics of the object 102. The dynamic sensor 130 may be a velocity sensor, an accelerometer, a yaw sensor, or any other suitable type of sensor. In some embodiments, the dynamic sensor may have a combined functionality of a velocity sensor, an accelerometer, and a yaw sensor so that data may be captured simultaneously. In an embodiment, the position determination device 120 and the dynamic sensor 130 may be combined into a single device for determining the position and dynamic characteristics of the object 102.

[0018] Map device 140 may be a computing device having a non-transitory, processor-readable storage medium. The non-transitory, processor-readable storage medium may contain map data 142. Map data 142 may be a map of a road, path, trail, or other area with multiple possible routes. Map data 142 may be downloaded from a commercial map database, created by object 102, or derived from any other suitable source.

[0019] Display 114 may be a screen or interface for displaying information about object 102, such as a detected location, route, or dynamic data. As a non-limiting example, when object 102 is a vehicle, the display may be an infotainment screen. In another embodiment, display 114 may be a mobile device, such as a smart phone.

[0020] Reference now Figure 2 , shows an illustration of the operation of system 100 with object 102 consistent with the disclosed embodiments. Object 102 may be a car, a bicycle, a person, an autonomous vehicle, or any other suitable object whose position may be tracked. System 100 may determine a first position 152 of object 102 at a first point in time, designated as point A. System 100 may determine a second position 154 of object 102 at a subsequent second point in time, designated as point B.

[0021] The position of object 102 may not be known explicitly between first position 152 of object 102 and second position 154 of object 102. For example, signals from position-determining device 120 may be lost or data from position-determining device 120 may be distorted, such as in an urban environment or an area with heavy interference.

[0022] The system 100 estimates a route that an object travels between a first location 152 and a second location 154 of the object 102. The first location 152 and the second location 154 of the object 102 may be any two detected locations of the object 102, such as locations detected in a field. The system 100 determines one or more possible routes between the first location 152 of the object 102 and the second location 154 of the object 102. As shown, the system 100 may determine a first possible route 156 (labeled as route 1), a second possible route 158 (labeled as route 2), and a third possible route 160 (labeled as route 3). However, it should be understood that the system 100 may determine any number of possible routes, such as one possible route, two possible routes, four possible routes, five possible routes, ten possible routes, fifty possible routes, one hundred possible routes, one thousand possible routes, or any other suitable number of routes.

[0023] The system 100 ranks possible routes between the first location 152 and the second location 154 of the object 102. The system 100 may rank the possible routes by any suitable criteria, including, but not limited to, the distance of the possible routes, the dynamics of the object 102 at the first location 152 of the object 102 and / or the second location 154 of the object 102, the object's travel history between the first location 152 of the object 102 and the second location 154 of the object 102, or any other suitable criteria. As a non-limiting example, the system 100 may rank a possible route with a shorter distance as more likely than a possible route with a longer distance.

[0024] The system 100 may determine the dynamics of the object 102 at the first location 152 and the second location 154 of the object 102. As a non-limiting example, the system 100 may determine the speed of the object 102 at the first location 152 and the second location 154 of the object 102 using the dynamic sensor 130. The system 100 may compare the corresponding speeds to a plurality of possible routes in order to rank the routes.

[0025] As a non-limiting example, if the velocity of object 102 is determined to be at a 45 degree angle relative to the axes shown at first location 152 and second location 154, then system 100 may rank second possible route 158 as most likely because second possible route 158 follows the velocity determined at first location 152 and second location 154 of object 102. In another embodiment, system 100 may determine the yaw of object 102 at first location 152 of object 102. If the yaw detected at first location 152 of object 102 indicates that object 102 turned right at first location 152, then system 100 may rank third possible route 160 as most likely.

[0026] In an embodiment, the system 100 may store known routes that the object 102 has previously taken between the first location 152 of the object 102 and the second location 154 of the object 102. The known routes may also be referred to as the travel history of the object 102. The system 100 may rank possible routes that more closely match the travel history of the object 102 as more likely than possible routes that differ from the travel history of the object 102.

[0027] In an embodiment, system 100 may use a combination of criteria to rank multiple possible routes, such as using a combination of object dynamics data, driving history, route distance, and / or any other suitable criteria.

[0028] Reference now Figure 3, a diagram of the operation of the system 100 consistent with the disclosed embodiments is shown. A first location 252 of an object 102 may be located at an intersection 248 of two roads of a drawn road network 244, such that the roads constituting the drawn road network 244 are shown as solid lines. A second location 254 of the object 102 may be another location along the drawn road network 244. The system 100 may determine one or more possible routes between the first location 252 of the object 102 and the second location 254 of the object 102 along the drawn road network 244. The system 100 may recognize that the object 102 is traveling in the drawn road network 244 and determine one or more possible routes along the drawn road network 244. In other words, the system 100 may not generate a route that deviates from the drawn road network 244. Multiple possible routes are shown in dashed lines. As shown, the system 100 may generate a first possible route 256 and a second possible route 258. The system 100 may rank multiple possible routes between the first location 252 and the second location 254 of the object 102.

[0029] In an embodiment, the system 100 may rank the multiple possible routes using similar criteria as discussed above. For example, the system 100 may rank the multiple possible routes based on object dynamic data, object travel history, route distance, and / or other suitable criteria. In an embodiment, the system 100 may rank the multiple possible routes based on a combination of more than one criteria.

[0030] Reference now Figure 4 , a diagram of the operation of the system 100 consistent with the disclosed embodiments is shown. The object 102 is shown traveling along the drawn path 346. As a non-limiting example, the drawn path 346 can be a series of roads, a series of walking paths, or any other suitable series of paths. The system 100 tracks the route of the object 102. The actual route 362 of the object 102 shows the actual route taken by the object 102. The position determination device 120 may temporarily lose the signal or receive a distorted signal, such as in a densely populated urban area. The point 364 where the signal is lost or distorted is shown as point C. The detected route 366 is shown with a dashed line. The system 100 can recognize that the detected route 366 is outside the drawn path 346, and therefore the actual route 362 taken by the object 102 is different from the detected route 366. Therefore, the system 100 will need to estimate the corrected route taken by the object 102.

[0031] The system 100 can simulate multiple possible corrected routes originating from the point 364 where the signal is lost or distorted. As shown, the system 100 can simulate a first simulated route 368, a second simulated route 370, and a third simulated route 372. Multiple simulated routes can be projected in various directions from the point 364 where the signal is lost or distorted. Compared to conventional route estimation systems, the system 100 can simulate multiple possible routes so that the routes extend further from the point 364 where the signal is lost or distorted. This can provide a more detailed simulated route to more accurately estimate the actual route taken by the object 102.

[0032] The system 100 may rank multiple possible corrected routes. That is, the system 100 may determine which of the multiple simulated routes is the route that the object 102 is most likely to take. In one embodiment, the system 100 may rank multiple possible corrected routes based on the object's driving history. That is, the system 100 may store records of previous routes taken by the object 102 along the same segment of the drawn path 346. The system 100 may rank simulated routes that are more similar to the records of previous routes taken by the object 102 as more likely than simulated routes that are not similar to the records of previous routes taken by the object 102. As a non-limiting example, if the object 102 frequently turns left through the intersection 348, the system 100 may rank the first simulated route 368 as more likely than the second simulated route 370 or the third simulated route 372.

[0033] In another embodiment, the system 100 may rank the plurality of possible corrected routes based on the speed of the object 102 at the point 364 where the signal is lost or distorted. That is, the dynamic sensor 130 may determine the speed of the object 102 at the point 364 where the signal is lost or distorted, and the system 100 may rank the plurality of simulated routes using the speed of the object 102. As a non-limiting example, if the speed of the object 102 at the point 364 where the signal is lost or distorted is too high for the object 102 to turn, the system 100 may rank the second simulated route 370 (the object 102 goes straight through the intersection 348) as more likely than the first simulated route 368 and the third simulated route 372 (the object 102 turns through the intersection 348).

[0034] In yet another embodiment, the system 100 may rank the plurality of possible corrected routes based on the acceleration of the object 102 at the point 364 where the signal is lost or distorted. That is, the dynamic sensor 130 may determine the acceleration of the object 102 at the point 364 where the signal is lost or distorted, and the system 100 may rank the plurality of simulated routes using the acceleration of the object 102. As a non-limiting example, if the object 102 is detected by the dynamic sensor 130 to decelerate at the point 364 where the signal is lost or distorted, and the map data 142 indicates that there is no stop sign or traffic light at the intersection 348, then the system 100 may rank the first simulated route 368 and the third simulated route 372 (where the object 102 turns through the intersection 348) as more likely than the second simulated route 370 (where the object 102 goes straight through the intersection 348).

[0035] refer to Figure 2-4 , the system 100 may display the tracked route and / or position of the object 102 on the display 114. In an embodiment, the system 100 may display multiple simulated routes on the display 114. In other embodiments, the system 100 may display an estimated route on the display 114.

[0036] Reference now Figure 5 , illustrates an illustration of a method 500 consistent with the disclosed embodiments. The method 500 is directed to estimating a route traveled by an object 102 between known locations of the object 102, which may be performed by the system 100. At step 510, the method 500 includes tracking a travel history of the object 102. That is, the system may track and store past routes taken by the object 102 in the same area as the location of the object 102.

[0037] At step 520, method 500 includes determining a first location 152 of object 102 at a first time. That is, location-determining device 120 may determine a location of object 102 at the first time.

[0038] At step 530, method 500 includes determining a second location 154 of object 102 at a second time after the first time. That is, location-determining device 120 may determine the location of object 102 at the second time after the first time.

[0039] At step 540 , method 500 includes determining a dynamic characteristic of object 102 . That is, dynamic sensor 130 may determine a velocity and / or an acceleration of object 102 .

[0040] In step 550, the method 500 includes automatically simulating a plurality of possible routes of the object 102 between a first determined location at a first time and a second determined location at a second time. That is, the system 100 may simulate a plurality of possible routes between the first determined location and the second determined location. In an embodiment, the system 100 may reference the map data 142 stored on the map device 140 to simulate a plurality of possible routes between the first determined location at a first time and the second determined location at a second time.

[0041] At step 560 , method 500 includes ranking the plurality of possible routes between the first determined location and the second determined location. That is, system 100 may rank the plurality of possible routes based on the travel history of object 102 , the dynamic characteristics of object 102 , or other possible criteria.

[0042] At step 570, method 500 includes estimating a most likely route between the first determined location and the second determined location. That is, system 100 may estimate that the highest ranked route is the most likely route taken by object 102 between the first determined location and the second determined location. In embodiments, system 100 may perform the estimation while object 102 is in motion. In other embodiments, system 100 may perform the estimation after object 102 becomes stationary.

[0043] Reference now Figure 6 , illustrates an illustration of a method 600 consistent with the disclosed embodiments that may be performed by the system 100. The method 600 is directed to estimating a corrected route of the object 102. At step 610, the method 600 includes tracking the travel history of the object 102. That is, the system 100 may track and store past routes taken by the object 102 in the same area as the location of the object 102.

[0044] At step 620, method 600 includes tracking the route of object 102 along the mapped path. That is, position-determining device 120 may track object 102 along the mapped path to determine the route taken by object 102 along the mapped path.

[0045] At step 630, method 600 includes determining a difference between the tracked route and the mapped path. That is, system 100 may identify that the tracked route of object 102 is not along the mapped path (such as a tracked route in a field between paths of the mapped path).

[0046] At step 640 , method 600 includes determining a dynamic characteristic of object 102 . That is, dynamic sensor 130 may determine a velocity and / or an acceleration of object 102 .

[0047] At step 650, method 600 includes simulating a plurality of possible corrected routes between the tracked route and the mapped path. That is, the system can simulate a plurality of possible routes from the point where the tracked route deviates from the mapped path.

[0048] At step 660, method 600 includes ranking a plurality of possible corrected routes between the tracked route and mapped path 146. That is, system 100 may rank the plurality of possible routes based on the travel history of object 102, dynamic characteristics of object 102, or other possible criteria.

[0049] At step 670, method 600 includes estimating the most likely corrected route between the tracked route and the mapped path. That is, system 100 may estimate that the highest ranked corrected route is the most likely corrected route taken by object 102. In an embodiment, system 100 may perform the estimation while object 102 is in motion. In other embodiments, system 100 may perform the estimation after object 102 becomes stationary.

[0050] Thus, embodiments of the present disclosure provide a method for estimating the route of an object that can more efficiently estimate the route taken by the object. In particular, the system can use the object's travel history, the object's dynamic characteristics, or various other criteria to rank multiple different simulated routes. In embodiments, the system can operate in real time to determine the route taken by the object. In other embodiments, the system can operate after the journey is completed to estimate the route taken by the object. Compared with conventional route estimation methods, the system can simulate multiple possible routes for longer durations.

[0051] It may be noted that one or more of the following claims utilize the terms "where," "wherein," or "in which" as transitional phrases. For purposes of defining the present technology, it may be noted that these terms are introduced in the claims as open transitional phrases used to introduce a recitation of a series of features of a structure, and should be interpreted in the same manner as the more commonly used open introductory term "comprising."

[0052] It should be understood that any two quantitative values ​​assigned to a certain property may form a range for that property, and that all combinations of ranges formed by all of the stated quantitative values ​​for a given property are contemplated in the present disclosure.

[0053] Having described the subject matter of the present disclosure in detail and with reference to specific embodiments, it is noted that the various details described in the present disclosure should not be considered to imply that these details are related to elements that are essential components of the various embodiments described in the present disclosure, even in the case where specific elements may be shown in each of the drawings accompanying this description. Rather, the appended claims should be regarded as the only indication of the breadth of the present disclosure and the corresponding scope of the various embodiments described in the present disclosure. In addition, it is apparent that modifications and variations are possible without departing from the scope of the appended claims.

Claims

1. A method comprising: determining a first position of the object at a first time; determining a second position of the object at a second time after the first time; automatically simulating a plurality of possible routes between a first location and a second location; ranking the plurality of possible routes between the first location and the second location; as well as A most likely route is estimated from among the plurality of possible routes between the first location and the second location.

2. The method of claim 1, wherein the object comprises a vehicle.

3. The method of claim 1, wherein the step of ranking the plurality of possible routes between the first location and the second location further comprises: determining an object velocity of the object at a first location; as well as The plurality of possible routes between the first location and the second location are ranked based at least in part on an object velocity of the object at the first location.

4. The method of claim 1, wherein the step of ranking the plurality of possible routes between the first location and the second location further comprises: determining an object acceleration of the object at a first location; as well as The plurality of possible routes between the first location and the second location are ranked based at least in part on an object acceleration of the object at the first location.

5. The method of claim 1, wherein the step of estimating a most likely object path from among the plurality of possible object paths is based at least in part on an object travel history. The method of claim 1 , further comprising displaying the most likely route on a display. The method of claim 1 , wherein the position of the object is unknown between the first position of the object and the second position of the object.

8. The method of claim 1, wherein the step of determining the first location of the object further comprises determining the first location of the object using GPS, and the step of determining the second location of the object further comprises determining the second location of the object using GPS.

9. The method of claim 1, wherein the estimated route follows a mapped road network.

10. The method of claim 9, wherein the estimated route is aligned with a mapped road network.

11. The method of claim 1, wherein the step of estimating a most likely route from among the plurality of possible routes between the first location and the second location further comprises estimating while the object is in motion.

12. The method of claim 1, wherein the step of estimating a most likely route from among the plurality of possible routes between the first location and the second location further comprises estimating after the object becomes stationary.

13. A method comprising: tracking the path of the object along the drawn path to determine a tracked path of the object; determining the difference between the drawn path and the tracked route of the object; simulating a plurality of possible corrected routes from the tracked route to the drawn path; ranking the plurality of possible corrected routes between the tracked route and the mapped path; as well as A most likely corrected route is estimated from among the plurality of possible corrected routes between the tracked route and the mapped path.

14. The method of claim 13, wherein the object comprises a vehicle.

15. The method of claim 13, wherein the step of ranking the plurality of possible routes between the tracked route and the mapped path further comprises: determining a velocity of the object along a tracked path of the object; as well as The plurality of possible routes between the tracked route and the mapped path are ranked based at least in part on a speed of the object along the route.

16. The method of claim 13, wherein the step of estimating a most likely route from among the plurality of possible routes between the tracked route and the mapped path is based at least in part on an object travel history.

17. The method of claim 13, further comprising: determining the acceleration of the object along the path of the object; as well as The plurality of corrected routes between the tracked route and the mapped path are ranked based at least in part on an acceleration of the object along the route of the object.

18. The method of claim 13, wherein the step of tracking the path of the object further comprises tracking the path of the object using GPS.

19. The method of claim 13, wherein the step of estimating the most likely route from among the plurality of possible routes between the tracked route and the mapped path is performed while the object is in motion.

20. The method of claim 13, further comprising displaying the detected and / or corrected route on a display.

Images